AIR QUALITY MANAGEMENT PLANNING FOR LAGOS STATE Joseph Akpokodje; Christopher Weaver; Mofoluso Fagbeja; Francesco Forastiere; Joseph V. Spadaro; Todd M. Johnson; Obi Ugochuku; Oluwakemi Osunderu and Sarath Guttikunda. AUGUST 2022 TASK TEAM LEADER: JOSEPH AKPOKODJE AIR QUALITY MANAGEMENT PLANNING FOR LAGOS STATE Joseph Akpokodje; Christopher Weaver; Mofoluso Fagbeja; Francesco Forastiere; Joseph V. Spadaro; Todd M. Johnson; Obi Ugochuku; Oluwakemi Osunderu and Sarath Guttikunda © 2022 World Bank Group 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org Email: feedback@worldbank.org All rights reserved. This volume is a product of the staff of the World Bank Group. The findings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of World Bank Group or the governments they represent. The World Bank Group does not guarantee the accuracy of the data included in this work. 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Cover photos credit: Elohor Egbane / SmartEdge. ii Air Quality Management Planning for Lagos State CONTENTS ACKNOWLEDGMENTS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix LIST OF ABBREVIATIONS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi EXECUTIVE SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv CHAPTER 1: INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.1. Lagos: population, economy, and environment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2. Need for an integrated air quality strategy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 CHAPTER 2: AIR QUALITY CONDITIONS IN LAGOS. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1. Particulate matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.2. Lead aerosol. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3. Gaseous pollutants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.4. Organic compounds and toxic air contaminants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.5. Greenhouse gases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.6. Pollutant emission inventory. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 2.7. Pollutant dispersion modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 CHAPTER 3: HEALTH AND ECONOMIC IMPACTS OF AIR POLLUTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.1. Methodology and exposure-response functions (ERFs) for air pollutants of concern. . . . . . . . . . . . . . . . . . . . . . . . . . 39 3.2. impacts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Quantification of health ­ 3.3. Valuation of health impacts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 CHAPTER 4: POTENTIAL EMISSION CONTROL MEASURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.1. Pollution control strategies by sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.2. National Action Plan to Reduce Short-Lived Climate Pollutants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.3. Policies and investments to improve air quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.4. Financing air quality management. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 CHAPTER 5: LAWS, REGULATIONS, AND INSTITUTIONAL CAPACITY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 5.1. Nigerian legal and regulatory framework. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 5.2. Lagos State’s legal and regulatory framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 5.3. Organizations involved in Lagos State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 5.4. Existing regulations in Lagos State. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.5. Strengthening the scientific base for AQM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 5.6. New regulatory and enforcement structures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 5.7. The health system should be an active actor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90 Air Quality Management Planning for Lagos State iii CHAPTER 6: RECOMMENDED AIR QUALITY MANAGEMENT STRATEGY FOR LAGOS STATE . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 6.1. Institutional development. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 6.2. Public involvement – AQI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95 6.3. Recommended AQM actions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 ANNEX 1: ESTIMATING THE HEALTH AND MORTALITY EFFECTS OF AIR POLLUTION IN LAGOS . . . . . . . . . . . . . . . . . . . . 101 A1.1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 A1.2. Definition and applications of HIA of air pollution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 A1.3. Available ERF models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 A1.4. Methods and input data for the HIA in Lagos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 A1.5. Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 A1.6. Discussion and conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 ANNEX 2: SUPPLEMENTARY MATERIAL . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 A2.1. Mortality and morbidity data at the local level. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 A2.2. Sensitivity calculations using an alternative assessment of the PWE. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 ANNEX 3: ECONOMIC AND FINANCIAL ASSESSMENT: POLICY, INVESTMENT, AND COST ASSUMPTIONS. . . . . . . . . . 147 A3.1. AQM control strategies by sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 A3.2. Financing AQM. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 A3.3. Control cost assumptions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 A3.4. Co-benefits of climate change mitigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 ANNEX 4: METHODOLOGY FOR DEVELOPING AN AQI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 A4.1. What is an AQI?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 A4.2. How is AQI calculated? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 END NOTES. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169 BIBLIOGRAPHY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 iv Air Quality Management Planning for Lagos State FIGURES Figure 1.1. PMEH institutional arrangements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Figure 2.1. Satellite view of Lagos showing the six monitoring sites, main roads, and the US Consulate (Source of satellite data – Google Earth) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Figure 2.2. PM2.5 measurements at each monitoring site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Figure 2.3. PM10 measurements at each monitoring site. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Figure 2.4. Correlation between PM filter data and 24-hour average optical sensor PM estimates. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Figure 2.5. Corrected optical sensor PM2.5 readings versus 24-hour filter measurements – Jankara site. . . . . . . . . . . . . . . . . . . . . . . . 10 Figure 2.6. Corrected optical sensor PM10 readings versus 24-hour filter measurements – Jankara site. . . . . . . . . . . . . . . . . . . . . . . . 10 Figure 2.7. Summary of the chemical composition of PM2.5 collected at the six monitoring sites. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Figure 2.8. PM2.5 source apportionment by PMF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Figure 2.9. PM2.5 source apportionment by CMB. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Figure 2.10. PM10 source apportionment of PM10 by PMF. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Figure 2.11. PM concentration versus wind direction for Ikorodu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Figure 2.12. Quarterly average lead aerosol concentrations measured at each site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Figure 2.13. Eight-hour average CO concentrations at each monitoring site (green lines, Nigerian/WHO standard; red lines US NAAQS). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Figure 2.14. Twenty-four-hour average NO2 concentrations at each monitoring site (red lines Nigerian standard, green lines WHO guideline) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Figure 2.15. Eight-hour average O3 concentrations at each monitoring site (green lines, Nigerian/WHO standard; red lines US NAAQS). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Figure 2.16. SO2 concentrations at LASEPA and UNILAG sites (green lines, Nigerian/WHO standard, red lines US NAAQS) . . . . . . . . 24 Figure 2.17. Average GHG concentrations measured at each monitoring site. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Figure 2.18. Average concentrations of CFCs, HCFCs, and HFCs measured at each monitoring site. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Figure 2.19. Breakdown of estimated criteria pollutant emissions by type of source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Figure 2.20. CO2 equivalent emissions by source type. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 Figure 2.21. Episodes selected for air quality modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Figure 2.22. Comparison of FARM model output with in situ measurement for O3, NO2, PM2.5, and PM10 at UNILAG station for episode period of September 10–20, 2020 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Figure 2.23. Comparison of FARM model output with in situ measurement for O3, NO2, PM2.5, and PM10 at UNILAG station for episode period of December 10–20, 2020 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Figure 2.24. Comparison of FARM model output with in situ measurement for O3, NO2, PM2.5, and PM10 at UNILAG station for episode period of March 5–16, 2021. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Figure 2.25. Comparison of FARM model output with in situ measurement for O3, NO2, PM2.5, and PM10 at UNILAG station for episode period of April 25–May 5, 2021 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Figure 2.26. Comparison of FARM model output with in situ measurement for O3, NO2, PM2.5, and PM10 at UNILAG station for episode period of June 27–July 7, 2021 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Figure 3.1. Schematic presentation of the main steps in the air pollution HIA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Figure 3.2. Size of the Lagos population by LGA according to the base and sensitive case populations. . . . . . . . . . . . . . . . . . . . . . . . . 41 Figure 3.3. Lagos State and LGA ambient air quality data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 Figure 3.4. PM2.5 attributable morbidity and mortality in Lagos State for PWE data and GHE (WHO 2021) baseline mortality rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Figure 3.5. Health benefits for a reduction in ambient air pollution across Lagos State. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Figure 4.1. Lagos Light Rail: Blue and Red Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Figure 4.2. LASG sector budget compared to air pollution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Air Quality Management Planning for Lagos State v Figure 4.3. Global green bond market. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Figure 5.1. Organization chart for Lagos State EPA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Figure 6.1. Comparisons of the variations in breakpoints and index nomenclature across specific countries . . . . . . . . . . . . . . . . . . . 95 Figure 6.2. Seasonal cycle of PM2.5 monitored from six stations in Lagos, August 2020 to July 2021. . . . . . . . . . . . . . . . . . . . . . . . . . . 96 Figure 6.3. AQI calculator page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Figure 6.4. Recommended AQM actions for Lagos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Figure A1.1. ERFs of the GBD 2000 study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 Figure A1.2. Schematic presentation of the main steps of the HIA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 Figure A1.3. Map of Lagos State Showing LGAs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Figure A1.4. Lagos State Population in 2006 and 2018. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Figure A1.5. Nigeria population long-term growth rate by age group, 2006–2018. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110 Figure A1.6. Lagos State mortality (both sexes) by cause of death and age, base case 2018. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Figure A1.7. ERFs for the Lagos HIA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Figure A1.8. Ambient air quality for Lagos State and LGAs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 Figure A1.9. PM2.5 attributable mortality by LGA and morbidity for Lagos State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124 Figure A1.10. PM2.5 attributable cause-specific mortality for Lagos State. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 Figure A1.11. PM2.5 attributable mortality by age group for Lagos State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Figure A1.12. Health benefits for a reduction in PM2.5 air pollution across Lagos State. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130 Figure A2.1. Ambient air quality in Lagos State and LGAs for PWE sensitivity analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142 Figure A2.2. PM2.5 attributable mortality by LGA and morbidity for Lagos State, PWE sensitivity analysis. . . . . . . . . . . . . . . . . . . . 145 Figure A3.1. Climate finance commitments by MDBs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Figure A3.2. Funding sources for climate financing (including private sector). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Figure A4.1. Schematic diagram of an air quality index. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 Figure A4.2. Colour coding of air quality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Figure A4.3 AQI breakpoints and nomenclature for different countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162 Figure A4.4 Pollutant predefined breakpoint and AQI ranges for India. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Figure A4.5 Summary of parameters for estimating an AQI for countries under review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Figure A4.6 Summary of breakpoints and nomenclature for seven countries under review. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 Figure A4.7 Steps for calculating AQI. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 vi Air Quality Management Planning for Lagos State TABLES Table 1.1. Recommended air quality strategy for Lagos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xviii Table 2.1. Annual average PM concentrations compared to WHO guidelines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Table 2.2. Ambient air quality standards and WHO guidelines for gaseous pollutants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Table 2.3. Estimated inventory of criteria pollutants and precursors for Lagos State. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Table 2.4. Estimated inventory of global-warming pollutants for Lagos State—calculated with 20-year GWPs. . . . . . . . . . . . . . . . 28 Table 2.5. Estimated inventory of global-warming pollutants for Lagos State—calculated with 100-year GWPs. . . . . . . . . . . . . . . 29 Table 3.1. Value of morbidity (sensitivity case population). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Table 3.2. Valuation of mortality due to air pollution in Lagos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Table 3.3. Value of lowering air pollution to WHO interim targets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 Table 3.4. Comparison of current estimates of PM2.5 mortality rates in Lagos State and previous work by Croitoru, Chang and Kelly (2020). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 Table 4.1. European diesel and gasoline standards and emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Table 4.2. BRT corridors in Lagos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 Table 4.3. Abatement measures in the National Action Plan (NAP) to Reduce Short-Lived Climate Pollutants. . . . . . . . . . . . . . . . . 69 Table 4.4. Clean air policies for Lagos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 Table 4.5. Indicative costs and benefits of reducing air pollution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Table 4.6. Possible funding sources for AQM in Lagos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Table 4.7. “Air quality” projects in the LASG 2021 budget. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Table 4.8. Five-year AQM financing scenarios. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .76 Table 4.9. Summary of possible funding instruments to support air quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Table 5.1. AQM laws, regulations, policies, and institutions at Lagos State and federal levels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 Table 6.1. Comparison of AQI results derived for Lagos. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Table A1.1. Estimates of Lagos State population by age group, 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Table A1.2. Estimates of Lagos State Population by LGA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Table A1.3. Lagos State mortality (both sexes) by cause of death and age, base case 2018. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111 Table A1.4. Lagos State mortality (both sexes) by cause of death and age, sensitivity case 2018. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112 Table A1.5. Lagos State mortality (both sexes) by cause of death and age, base case 2018. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114 Table A1.6. Lagos State mortality (both sexes) by cause of death and age, sensitivity case 2018. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115 Table A1.7. Nigeria mortality rates (per 100,000, both sexes) by cause of death and age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Table A1.8. Lagos State mortality (GHDx hazard rates, both sexes) by LGA, 2018. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Table A1.9. Lagos State mortality (GHE hazard rates, both sexes) by LGA, 2018 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 Table A1.10. Annual PM PWE by LGA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 Table A1.11. PM2.5 attributable health burdens for the base case population. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Table A1.12. PM2.5 attributable health burdens for the sensitivity case population . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Table A1.13. PM10 attributable short-term mortality due to the Harmattan season . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 Table A1.14. Impact assessment of air lead contamination in Ikorodu. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Table A1.15. Comparison of current estimates of PM2.5 mortality rates in Lagos State to estimates from previous work by Croitoru, Chang and Kelly (2020) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Table A2.1. Inpatient hospital admissions, 2017. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139 Table A2.2. Share of total inpatient hospital admissions by disease. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 Table A2.3. Outpatient hospital admissions, 2017. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 Table A2.4. Share of outpatient hospital admissions by disease. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 Table A2.5. Annual PM PWE by LGA for the sensitivity analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Air Quality Management Planning for Lagos State vii Table A2.6. PM2.5 attributable health burdens for PWE sensitivity analysis, base case population . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Table A2.7. PM2.5 attributable health burdens for PWE sensitivity analysis, sensitivity population. . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Table A3.1. Alternative vehicle technologies for large buses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Table A3.2. World Bank Africa Climate Business Plan (ACBP) Funding Windows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 Table A3.3. Action areas in the ACBP. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Table A3.4. Apportionment of PM2.5 emissions and ambient concentrations by sector. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156 Table A3.5. Cost-effectiveness of selected air quality measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 Table A3.6. Climate Co-benefits of selected air quality measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 BOXES Box 4.1. Measures to ensure fuel quality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 Box 4.2. From combis to minibuses in Mexico City. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 Box 4.3. Lagos Climate Action Plan, 2020–2025. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Box 4.4. Nigeria NDC targets and air quality. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 Box A3.1. Air pollution versus climate change costs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160 viii Air Quality Management Planning for Lagos State ACKNOWLEDGMENTS (REVISED OCTOBER 2022) This report was prepared by a team led by Joseph Akpokodje and comprising Christopher Weaver (Air Resources Engineer, California Air Resources Board), Mofoluso A. Fagbeja (Space Applications and Environmental Scientist, Centre for Space Science and Technology Education, Ile-Ife, Nigeria), Francesco Forastiere (Environmental Epidemiologist, National Research Council, Italy), Joseph V. Spadaro (Senior Environmental Research Scientist, Spadaro Environmental Research Consultants, USA and WHO Consultant, Bonn, Germany), Todd M. Johnson (Environmental Economist, former World Bank Group staff), Obi Ugochuku (Climate Finance Expert, former World Bank Group staff), Oluwakemi Osunderu (Principal Research Fellow, Forestry Research Institute of Nigeria), and Sarath Guttikunda (Director, Urban Emissions, India).The opinion expressed in this report are those of the authors and should not be attributed to their respective employer or affiliated organizations. The team would like to acknowledge, with thanks, the valuable support and advice from Jostein Nygard, Yewande Awe, Steve Baillie, Max Klotz, Urvashi Narain, Özgül Calicioglu, Oznur Oguz Kuntasal, Iguniwari Thomas Ekeu-Wei, Omezikam Onuoha, Jayne Kwengwere, Rohan Selvaratnam, and Abiodun Elufioye. This report benefited from contributions and inputs provided by the following colleagues: Silvia Calderon, Felix Ukeh, and Andrew Kelly. The team would like to acknowledge comments provided by the peer reviewers: Sameer Akbar – Senior Environmental Specialist (SCAEN); Craig Meisner – Senior Economist (SCCDR); Roger Gorham - Senior Transport Economist (ILCT1); Jian Xie – Senior Environmental Specialist (SAEE2); and Gary Kleiman – Senior Environ- mental Specialist Consultant (SCAEN). Editorial support was provided by Akashee Mehdi. The team would like to acknowledge the valuable support of His Excellency, Babajide Sanwo-Olu, Executive Governor of Lagos State and the following Mr. ­ Lagos State Government officials: Mr. Tunji Bello, Honorable Commissioner for Environment and Water Resources; Prof Akin Abayomi, Honorable Commissioner for Health, Lagos State Ministry of Health; Mr. Sam Egube, Honorable Commissioner, Lagos State Ministry of Economic Planning and Budget.; Dr. Frederic Abimbola Oladeinde, Honorable Commissioner, Lagos State Ministry of Transportation; Engr. Olalere Odusote, Honorable Commissioner for Energy and Mineral Resources; Mrs. Abisola Olusanya, Honorable Commissioner for Agriculture; Dr. Dolapo Fasawe, General Manager, Lagos State Environmental Protection Agency (LASEPA); Mr. Air Quality Management Planning for Lagos State ix Olajide Oduyoye, General Manager, Lagos State Department) at the Federal Ministry of ­Environment. Metropolitan Transport Agency (LAMATA); Mr. Ibrahim Prof. Oluwatoyin Ogundipe, Vice Chancellor of the Adejuwon Odumboni, General Manager, Lagos Waste University of Lagos. Dr Rose Alani, Lead, Air Quality Management Agency (LAWMA); Mr.  Tayo Oseni-Ope Monitoring Research Group of the Department of (Director), Mr. Peter Kehinde Olowu (Deputy Director), Chemistry, University of Lagos. Professor Wellington and Mrs. Bolanle Pemede (Assistant Director) at the Oyibo, Director of Research and Innovation Unit, Lagos State Ministry of Economic Planning and Budget/ University of Lagos Lagos Bureau of Statistics; Dr. Idowu Abiola (Director, Lagos Health Management Information System) and Dr. The report is a product of the Environment, Natural Kuburat Enitan Layeni-Adeyemo (Director, Occupational Resources and Blue Economy Global Practice of the Health Services) at Lagos State Ministry of Health; Mr. World Bank. This work was conducted under the Ayodipupo Quadri (Environment and Safety Specialist) supervision of Ernesto Sanchez-Triana (PMEH Program at Lagos Metropolitan Area Transport Authority; Mr. Manager), Sanjay Srivastava (Practice Manager, SAWE4), Lewis Gregory Adeyemi (Chief Scientific Officer) at and Christian Albert Peter (Practice Manager, SENGL). the Lagos State Ministry of Environment/Lagos State Environmental Protection Agency; Mr. Adedotun The financial support of the World Bank’s Pollution Atobasire (Deputy Director, Census) at the National Management and Environmental Health (PMEH) Population Commission; Mr. Charles Ikeah, Director Multi-Donor Trust Fund in the preparation of this Pollution Control and Environmental Management; and report is gratefully acknowledged. PMEH is supported Mr. ­Emmanuel Ojo (Former Focal Point and Deputy by the ­ governments of Germany, Norway, and the Director, Pollution Control and ­Environmental Health United ­Kingdom. x Air Quality Management Planning for Lagos State LIST OF ABBREVIATIONS ACBP Africa Climate Business Plan ACRIF African Climate Resilience Infrastructure AFC Africa Finance Corporation AfDB African Development Bank AFOLU Agriculture, Forestry and Other Land Use ALRI Acute Lower Respiratory Infections AQI Air Quality Index AQM Air Quality Management BEV Battery Electric Vehicle Bpd Barrels per Day BRT Bus Rapid Transport CBA Cost-Benefit Analysis CFC Chlorofluorocarbon CH4 Methane CHA Cardiovascular Hospital Admission CI Confidence Interval Cl Chloride Ion CMB Chemical Mass Balance CNG Compressed Natural Gas CO Carbon Monoxide CO2 Carbon Dioxide COPD Chronic Obstructive Pulmonary Disease CSO Civil Society Organization DPR Department of Petroleum Resources ECOWAS Economic Community of West African States EGASPIN Environmental Guidelines and Standards for the Petroleum Industry in Nigeria EIB European Investment Bank EPA Environmental Protection Agency ERF Exposure-Response Function EU European Union FFMM Fact-Finding Air Quality Monitoring Mission FMEnv Federal Ministry of Environment FMPR Federal Ministry of Petroleum Resources GBD Global Burden of Disease GCF Green Climate Fund GDP Gross Domestic Product GEF Global Environment Facility GEMM Global Exposure Mortality Model GHDx Global Health Data Exchange Air Quality Management Planning for Lagos State xi GHE Global Health Estimates GHG Greenhouse Gas GWP Global-Warming Potential HCA Human Capital Approach HCFC Hydrochlorofluorocarbon HFC Hydrofluorocarbon HFO Heavy Fuel Oil HIA Health Impact Assessment HRAPIE Health Risk of Air Pollution in Europe IEA International Energy Agency IER Integrated Exposure-Response IFC International Finance Corporation IHD Ischemic Heart Disease IHME Institute for Health Metrics and Evaluation I&M Inspection and Maintenance IQ Intelligence Quotient IPCC Intergovernmental Panel on Climate Change ISDB Islamic Development Bank IT Interim Target kW Kilowatt(s) LACVIS Lagos Computerized Vehicle Inspection Service LAGFERRY Lagos State Ferry LAMATA Lagos State Metropolitan Transport Agency LASEPA Lagos State Environmental Protection Agency LASG Lagos State Government LASWMO Lagos State Wastewater Management Office LAWMA Lagos Waste Management Agency LBS Lagos Bureau of Statistics LGA Local Government Area LMoE Lagos State Ministry of Environment and Water Resources LMoEMR Lagos State Ministry of Energy and Mineral Resources LMEPB Lagos State Ministry of Economic Planning and Budget LMoH Lagos State Ministry of Health LMICs Low- and Middle-Income Countries LMoT Lagos State Ministry of Transport LPG Liquefied Petroleum Gas LUTP Lagos Urban Transport Project MDAs Ministries, Departments, and Agencies MDB Multilateral Development Bank MSW Municipal Solid Waste NAAQS National Ambient Air Quality Standards NAP National Action Plan NAPEP National Poverty Eradication Programme NCD Noncommunicable Disease NCF Nigerian Conservation Foundation xii Air Quality Management Planning for Lagos State NDC Nationally Determined Contribution NEP National Environmental Policy NESREA  National Environmental Standards and Regulations Enforcement Agency NH3 Ammonia NILU Norwegian Institute for Air Research NIMET Nigerian Meteorological Agency NIS Nigerian Industrial Standards NNPC Nigerian National Petroleum Corporation N2O Nitrous Oxide NO Nitric Oxides NO2 Nitrogen Dioxide NOx Nitrogen Oxides NOSDRA National Oil Spill Detection and Regulatory Agency NSE Nigerian Stock Exchange NUPRC Nigerian Upstream Petroleum Regulatory Commission O3 Ozone OECD Organisation of Economic Co-operation and Development PAF Population Attributable Fraction PforR Program-for-Results PCEH Pollution Control and Environmental Health PM Particulate Matter PM1 Particulate Matter with Diameter Less than 1 µm PM2.5 Particulate Matter with Diameter Less than 2.5 µm PM10 Particulate Matter with Diameter Less than 10 µm PMEH Pollution Management and Environmental Health PMEH-MDTF  Pollution Management and Environmental Health Multi-Donor Trust Fund PMF Positive Matrix Factorization ppb Parts per Billion ppm Parts per Million PPMC Pipelines and Product Marketing Company ppv Parts per Volume PWE Population-Weighted Exposure REVIHAAP Review of Evidence on Health Aspects of Air Pollution RHA Respiratory Hospital Admission RR Relative Risk SAWE4  Environment, Natural Resources and Blue Economy West and Central Africa SCC Social Cost of Carbon SENGL Environment, Natural Resources and Blue Economy, Global team  SIP State Implementation Plan SO2 Sulfur Dioxide SOx Sulfur Oxides SON Standards Organization of Nigeria SPO Second-Party Opinion TSC Technical Service Contractor TSP Total Suspended Particulate Matter Air Quality Management Planning for Lagos State xiii UK United Kingdom UNFCCC United Nations Framework Convention on Climate Change UNILAG University of Lagos US United States US EPA United States Environmental Protection Agency VOC Volatile Organic Compound VSL Value of Statistical Life WBG The World Bank Group WHO The World Health Organization µg/m3 micrograms per cubic meter xiv Air Quality Management Planning for Lagos State EXECUTIVE SUMMARY INTRODUCTION Ambient air pollution is a major contributor to illness and premature deaths in much of the developing world, including Lagos. The World Bank is committed to supporting countries severely affected by pollution through its advisory service, tech- nical assistance, and lending. With funding from the Pollution Management and Environmental Health Multi-Donor Trust Fund (PMEH-MDTF), the World Bank, ­ collaboration with the Lagos State Government (LASG), and specifically the Lagos in ­ Environmental ­ State ­ Protection Agency (LASEPA), contracted consultants to establish the scientific basis for air quality management (AQM) and to develop an AQM plan for Lagos State. The effort included the following: » Establishment of a network of six air-quality-monitoring stations to collect 12 months of air quality data on PM2.5, PM10, other criteria pollutants (sulfur ­dioxide [SO2], nitrogen dioxide [NO2], carbon monoxide [CO], ozone [O3]), greenhouse gases – GHGs (carbon dioxide [CO2], methane [CH4], nitrous ­ oxide [N2O], black carbon [BC], chlorofluorocarbons [CFCs], ­ hydrofluorocarbons [HFCs]), and meteorological data » Chemical analysis and source apportionment analysis of collected aerosol par- ticulate matter (PM) to determine the composition and likely sources of PM emissions » Development of an inventory of air pollutant emissions » Photochemical dispersion modeling to reconcile the inventory with observed pollutant concentrations and to estimate the exposure in each local government area (LGA) » Assessment of the health impacts of air pollution in Lagos by estimating the effects of air pollution on the incidence of premature mortality and illness in each LGA » Economic and financial analysis of the costs of premature mortality and illness due to air pollution, and the costs and benefits of measures to control pollutant emissions » Assessment of existing institutional and governance structures for successful AQM in Lagos and Nigeria » Recommendation of an integrated AQM plan and establishment of an air quality index (AQI) for the State of Lagos. Air Quality Management Planning for Lagos State xv estimated to cause 180,000 to 350,000 acute lower respira- AIR QUALITY CONDITIONS tory infections (ALRI) per year, primarily cases of pneu- IN LAGOS monia in children under 5. Another 250 to 500 deaths are estimated to be due to PM10 exposure during the Harmattan season. Exposure to lead aerosol in Ikorodu is estimated to The World Health Organization (WHO) guideline for have cost the LGA’s children an average of 6.2 intelligence annual average PM2.5 concentrations is 5 µg/m3 (micro- quotient (IQ) points and to be causing another 300 to 400 grams—or one-millionth of a gram—per cubic meter) of deaths from cardiovascular disease per year. Mortality and air. This project found annual average PM2.5 concentra- morbidity due to gaseous pollutants were not estimated but tions at the six monitoring sites ranging from 30 to 97 would likely increase these numbers by about 10 percent. µg/m3, with a population-weighted average of 47 µg/m3. The highest average PM2.5 was found in the industrial/ Using the human capital method, which essentially val- residential area of Ikorodu, an industrialized LGA in ues a life at the time of death equal to the amount that Lagos. Concentrations of lead aerosol in Ikorodu were a person could earn over his or her remaining life, the also dangerously high—more than 10 times the US EPA economic costs of PM2.5 air pollution in Lagos State are standard of 0.15 µg/m3 for lead aerosol. Measurements estimated at US$1.2–2.3 billion per year—1.6 to 3.2 per- of gaseous pollutants also showed concentrations of CO cent of Lagos’ gross domestic product (GDP). Using the and NO2 in excess both of Nigerian air quality standards value of a statistical life (VSL) approach, which considers and of WHO guidelines. how much society is willing to pay to reduce a small risk of death, the costs are estimated at US$3.1–5.8 billion The PM source apportionment conducted for this project (4.2 to 8.1 percent of Lagos’ GDP). The economic costs found that open burning of biomass and solid waste accounts of exposure to lead aerosol in Ikorodu are estimated at for about 30 percent of the annual ambient PM2.5; gasoline an additional US$300–600 million per year, or US$400– and diesel engines combined account for about 16 percent; 600 for every resident of that LGA. and industrial emissions account for about 18 percent on average (ranging from 48 percent at Ikorodu to less than 9 percent at other sites). Ammonium nitrate and ammonium POTENTIAL EMISSION sulfate—produced by chemical reactions between gaseous sulfur oxides (SOx), nitrogen oxides (NOx), and ammonia CONTROL MEASURES (NH3)—make up 10 percent of the PM2.5. Dust, including dust from roads, construction sites, and agricultural fields as well as the seasonal Harmattan, makes up about 26 percent Given the range of human-made air pollution sources of ambient PM2.5 and 50 percent of PM10. that have been identified in Lagos, a multi-sectoral approach is needed to improve air quality. The following are key air-quality policies recommended for near-term HEALTH AND ECONOMIC implementation in Lagos, based on measured pollution levels, assessed health impacts, readiness for implemen- IMPACTS OF AIR POLLUTION tation, and consistency with the National Action Plan (NAP) to Reduce Short-Lived Climate Pollutants. Exposure to PM2.5 pollution is a serious, but preventable, Solid waste. While the per capita generation of munici- public health hazard, especially in children under 5 years. pal solid waste (MSW) in Lagos is still low by international In Lagos, PM2.5 exposure is estimated to cause between standards, based on air pollution modeling and source 16,000 and 30,000 premature deaths per year, with about apportionment, a large fraction of MSW appears to be half of these being infants under 1 year. Air pollution is also openly burned. For air pollution control, open burning of xvi Air Quality Management Planning for Lagos State waste should be banned, along with a public information stricter fuel quality standards than their respective coun- program to explain the health impacts of open burning. tries. In the face of numerous incentives to adulterate Lagos should also strive to collect as much MSW as possible fuel, it is necessary for fuel quality to be regulated and and ensure that open burning is not taking place at landfills enforced at retail outlets. or transfer stations. Recycling and composting can reduce the amount of MSW destined for landfills by as much as Industry. Industrial emissions account for a sizable share two-thirds while also generating revenue from the sale of of PM2.5 emissions in Lagos, principally in Ikorodu, but products such as fertilizer and cardboard to offset the costs. also throughout the state. Continuous-emissions-moni- toring equipment should be employed to regulate emis- Power. Small, engine-driven generating sets (gensets) are sions from large industrial sources, with fines imposed estimated to account for nearly half of the total electricity for noncompliance. LASEPA staff have legal authority produced in Lagos and are responsible for a much larger to carry out emissions source tests to enforce emission share of air pollution from power generation. Gensets are standards; they should be trained and equipped to do so. one of the least regulated sources of air pollution in Lagos. There is an urgent need to reduce emissions from gensets Financing for air quality. An AQM program in by substituting electricity from the grid or from distributed Lagos could build on existing public support for the power generation (such as from solar photovoltaic) and by transport and solid waste sectors, and for industrial relo- setting and enforcing genset emission standards. cation through environmental financing. Green bonds, supplemental finance from multilateral organizations, Transport. Over the long term, public transport (buses, and climate finance can be used to support the intersec- light rail, ferries) can reduce air pollution from the transport tion between air quality and climate change, such as for sector in Lagos by lessening road congestion and the number solid waste management, electric power reform, public of private passenger vehicles. At the same time, it is essential transport, and alternative fuels. to control emissions from vehicles through a systematic pro- cess of improving vehicle emission standards and the qual- ity of transport fuels. Achieving Euro 3 and Euro 4 vehicle LAWS, REGULATIONS, AND standards could reduce PM emissions from transport in Lagos by an estimated 65–83 percent, compared to Euro INSTITUTIONAL CAPACITY 1 vehicles. Economic Commission of West African States (ECOWAS) directive C/Dir.2/09/20 requires imported light-duty vehicles to meet Euro 4 standards from January Under the Lagos Environmental Management Protec- 2021, and requires vehicles in circulation to meet them from tion Law of 2017, LASEPA has the legal authority to January 2025. Heavy-duty trucks and buses are required to enforce emission standards on industrial, agricultural, meet Euro 6 standards. Given that Euro 4 vehicles have and government sources, as well as generating plants been manufactured globally since 2006, it is well within in residential and commercial areas; to set and enforce the capacity of Lagos State to achieve a high share of such vehicle emission standards; and to set up an air quality vehicles in its total vehicle population through a program of monitoring network. However, it mostly lacks the techni- emissions testing and vehicle retrofits. cal capacity and staff to do so effectively. Training and capacity building, together with additional staff and Fuel quality. One of the key constraints on reducing equipment investments, are needed for LASEPA to effec- emissions from transport vehicles (and stationary engines tively fulfill its statutory role in AQM. This will require for industry or power generation) has been the lack of an increase in budget. As a parastatal, the agency has the clean gasoline and diesel fuel. To reduce air pollution, capacity to be self-funding and already derives a large many megacities around the world, including in Mexico fraction of its budget from fees, fines, and the Environ- established City, Delhi, Santiago, and Rio de Janeiro, have ­ mental Development Charge. Air Quality Management Planning for Lagos State xvii Table 1.1.  RECOMMENDED AIR QUALITY STRATEGY FOR LAGOS S/No Short-term recommendation – 1 year Medium-term recommendation – 3 years Responsible authority Air quality monitoring 1 Resume air quality monitoring at the six sites Establish 8–12 additional air quality monitoring LASEPA, Lagos State for which a monitoring record already exists, sites, including upwind and downwind Ministry of Economic and begin planning an expanded network. locations as well as sites influenced by the ports, Planning and Budget traffic, and industrial areas, to better monitor (LMEPB) population-based exposure and to strengthen the basis for air quality modeling. 2 Train and equip LASEPA staff to carry out Strengthen the scientific basis for AQM by LASEPA, Lagos emission measurements on industrial sources continuing to develop the emissions inventory, State Ministry of and begin such testing with the largest and strengthening oversight of the emissions Environment and worst emitters. auditing process, and strengthening the Water Resources reporting of health and economic statistics. (LMoE), Lagos Bureau of Statistics (LBS) Health 3 Provide education, training, and lifelong Strengthen the scientific basis for health LASEPA, Lagos State learning to health personnel on the health impact assessment, expand the system of Ministry of Health effects of air pollution. health information collection, and initiate (LMoH) epidemiological research on air pollution. 4 Engage public opinion by adopting an AQI LASEPA, LMoH and routinely providing air quality data and forecasts to the media and on LASEPA’s website. Regulation and enforcement Solid waste management 5 Redouble efforts to collect and dispose of solid LAWMA waste by landfill, recycling, composting, and/or incineration with emission controls, and enforce prohibitions on the open burning of waste and biomass. Industries 6 Locate and shut down any lead-smelting or LASEPA battery-recycling operations in Ikorodu, measure lead levels in soil and in the blood of the potentially affected population, and take remedial action as necessary. Transport 7 Implement ECOWAS Directive C/ Nigerian Upstream Dir.1/09/20, limiting sulfur in gasoline and Petroleum Regulatory diesel fuel to 50 ppm by weight; enforce this Commission by collecting and analyzing fuel samples (NUPRC), Standards at the port and at retail stations, with Organization of fines and/or the loss of retail licenses for Nigeria (SON) noncompliance. xviii Air Quality Management Planning for Lagos State S/No Short-term recommendation – 1 year Medium-term recommendation – 3 years Responsible authority 8 Begin execution of ECOWAS Directive C/ Strengthen the existing vehicle inspection and National Environmental Dir.2/09/20 by notifying vehicle importers maintenance system to enforce the requirement Standards and and implementing inspections and testing of ECOWAS Directive C/Dir.2/09/20 that Regulations to confirm that newly imported, light-duty vehicles in circulation meet Euro 4 emission Enforcement Agency vehicles (whether new or used) meet Euro standards from January 2025. (NESREA), Lagos 4 emission standards and that heavy-duty State Metropolitan vehicles meet Euro 6 standards. Transport Agency (LAMATA), Lagos State Ministry of Transport (LMoT) 9 Replace the existing danfo (microbus) fleet with LAMATA larger minibuses, preferably plug-in hybrid electric vehicles with advanced emission controls, and restructure the routes to coordinate with the bus rapid transit (BRT) system. By charging from the power grid when it is available and from their onboard engine when not, plug-in hybrids could provide reliable service in the near term while retaining the ability to switch to all-electric operation in the future. 10 Consider measures to phase out engine-driven LAMATA taxicabs, okada motorcycle taxis, and keke NAPEP tricycle taxis in favor of battery electric vehicles (BEVs). Energy 11 Set and enforce emission standards for backup Increase the capacity and reliability of the LASEPA, Federal generators. electric-generating system to reduce the need Ministry of Power for backup generators and consider retrofitting (FMP) the Egbin power plant for combined-cycle operation with low-NOx gas turbines. 12 Consider grouping small power users into “mini Federal Ministry of grids” of a few hundred kW incorporating Power, Lagos State solar photovoltaic panels and diesel-generating Ministry of Energy sets with advanced emission controls. and Mineral Resources (LMoEMR), LASEPA Air quality financing 13 Consider a percentage of existing or new LMEPB, LASEPA emission fees and other charges as line charge to sustainably support increased staffing and equipment for LASEPA. 14 Consider multilateral financing and/or an LMEPB, LASEPA air quality green bond to support needed investments in emission controls, air quality monitoring infrastructure, emissions measurement capabilities, and capacity building for air quality enforcement and management. Air Quality Management Planning for Lagos State xix CHAPTER 1 INTRODUCTION Air pollution is a major contributor to illness and premature death in much of the developing world, including Lagos. The World Bank is committed to supporting coun- tries severely affected by pollution through its advisory service, technical assistance, and lending. The World Bank’s Environment, Natural Resources and Blue Economy Global Practice has set pollution management and environmental health (PMEH) as one of its five core business lines to increase support in this area. Consequently, the Pollution Management and Environmental Health Multi-Donor Trust Fund (PMEH- MDTF) was established in 2015 to drive actions to address air and land pollution issues in low- and middle-income countries (LMICs). With funding from the PMEH, the World Bank contracted with Technical Service Contractors (TSCs) to carry out the preliminary work to establish a scientific basis for air quality management (AQM) and to develop an AQM plan for the State of Lagos. This document is the final report of that effort. The effort included the following: » Establishment of a network of six air quality monitoring stations, which represent six of the land use classes, to monitor and collect 12 months of air quality data on PM2.5, PM10, other criteria pollutants (sulfur dioxide [SO2], nitrogen dioxide [NO2], carbon monoxide [CO], ozone [O3]), greenhouse gases – GHGs (carbon dioxide [CO2], black carbon [BC], methane ([CH4], nitrous oxide [N2O], chlorofluorocarbons [CFC] and hydrofluorocarbons [HFC]), as well as meteorological parameters » Chemical analysis and source apportionment analysis of collected aerosol par- ticulate matter (PM) to determine the composition and likely sources of PM emissions » Development of an inventory of air pollutant emissions, together with potential measures to reduce those emissions » Photochemical dispersion modeling to reconcile the emission inventory with observed pollutant concentrations and to estimate the severity of exposure in each local government area (LGA) Air Quality Management Planning for Lagos State 1 » Assessment of the health impacts of air pollution only about 40 percent of the waste generated is collected in Lagos by estimating its effects on the incidence and transported to dumpsites. The remaining 60 percent of premature mortality and illness in each LGA is mostly burned. The dumpsites themselves are in poor » Economic and financial analysis of the costs of condition. Compounding that, Olusosun dumpsite—the premature mortality and illness due to air pollu- largest of three major dumpsites and second largest in tion and of the costs and benefits of measures to Africa—is located within the city. These dumpsites are control pollutant emissions sources of biomass burning, fugitive dust, and various » Assessment of the existing institutional and gover- gaseous emissions such as methane (CH4). nance structure for successful AQM in Lagos and, more broadly, in Nigeria Lagos bears the additional burden of a coastal city with » Recommendation of an integrated AQM plan two busy seaports. Most of Nigeria’s maritime trade and establishment of an air quality index (AQI) passes through Lagos’ ports of Apapa and Tin Can for the State of Lagos. Island, the largest and busiest in West Africa. The ports are constantly overwhelmed with hundreds of old, die- sel-engined tractor-trailers conveying containers from 1.1. LAGOS: POPULATION, the seaports to other parts of the country and contrib- uting to the traffic congestion and vehicular emissions. ECONOMY, AND Ship traffic is equally congested, with ships often having ENVIRONMENT to wait offshore for weeks to unload. Downwind of the seaports is the Okobaba sawmill, with emissions from the constant burning of sawdust. The Ikorodu indus- Lagos is the largest city in Sub-Saharan Africa and one of trial zone—one of several in the city—is a major source the world’s fastest-growing megacities. Although Lagos is of the unregulated discharge of industrial emissions. the smallest state in the Federal Republic of Nigeria by area, it is among the highest in population. From 7.5 mil- Physically, most of Lagos is built on a low-lying, wooded lion in 2006 (the most recent census), the population in coastal plain and adjacent barrier islands surround- 2019 was estimated at about 13.5 million by the National ing a large lagoon. The climate is warm and humid, Bureau of Statistics, and at 23 million by the Lagos State with a pronounced wet season from May to Septem- Bureau of Statistics (LBS). This rapid growth has pro- ber and a dry season the remaining months. During the duced urban sprawl and severely strained the infrastruc- dry season, occasional strong northeasterly Harmattan ture and the provision of basic services. More than half winds carry dust from the Sahara Desert, resulting in the population live in informal settlements. low humidity and extremely high concentrations of air- borne PM. Lagos State has the highest gross domestic product (GDP) of any Nigerian state, accounting for about 25 percent of national GDP. It is a primary center for the transport and 1.2. NEED FOR AN manufacturing industries. INTEGRATED AIR As the economic hub of Nigeria, Lagos experiences QUALITY STRATEGY significant vehicle traffic, resulting in severe traffic con- gestion, vehicular emissions, and suspended road dust. Businesses and residences rely on diesel and gasoline Lagos currently lacks a standardized AQM system generators as a backup to compensate for virtually daily despite the growing evidence of unhealthily high levels of power interruptions. Waste disposal is a critical problem; PM and other pollutants and high emissions of  GHGs. 2 Air Quality Management Planning for Lagos State A fact-finding air quality monitoring mission (FFMM) PM levels at industrial, commercial, traffic, dumpsites, was ­conducted by the World Bank and uMoya-NILU mixed-residential areas, signifying that substantial and ­ (Norwegian Institute for Air Research)1 in Lagos between PM emissions are being g ­ enerated from diverse sources December 11 and 18, 2015 to inform the Lagos AQM such as motor vehicles, domestic power plants, and plan proposal. Air sampling data collected at eight loca- improper management of wastes. tions with diverse source characteristics (industrial, commercial, residential, dumpsite, heavy traffic, high Both the Nigerian Federal Government and the State of population density, conservation, and mixed land use) Lagos have developed plans to address emissions that indicated several cases of extremely high mean PM contribute to climate change but, compared to other concentrations.2 Across locations, the results indicated megacities in the developing world, much less attention mean PM2.5 levels ranging from 116 µg/m3 to 483 µg/ has been given to ambient air pollution in the major m3—up to 19 times higher than WHO’s 24-hour mean ­ cities. The major exception was the Federal Govern- guideline3 of 25 µg/m3—and PM10 levels ranging from ment’s 2018 plan for managing short-lived GHGs (Gov- 55 µg/m3 to 442 µg/m3, up to nine times higher than ernment of Nigeria 2018), which explicitly considered the 24-hour mean WHO guideline of 50 µg/m3. The the benefits of reducing PM2.5 pollution in concert with results of the FFMM showed remarkably high ambient reductions in black carbon and CH4 emissions. FIGURE 1.1.  PMEH INSTITUTIONAL ARRANGEMENTS PMEH Institutional arrangements Federal Ministry of Finance (FMF) World Bank Department of Pollution Control and Environmental Health (PC&EH) Lagos State PMEH Steering Committee Federal Ministry of (LSMEPB Chair) Environment (FME) Department of Climate Change (DCC) PMEH Technical committe (LSME Chair) Lagos State Lagos State Lagos State Lagos State Ministry of Lagos State Lagos State Lagos State Ministry of Ministry of Ministry of Lagos State Physical Ministry of Ministry of Ministry of Energy and Commerce, Economic Ministry of Planning and Environment Health Transport Mineral Industry and Planning and Agriculture Urban (LSME) (LSMH) (LSMT) Resources Cooperatives Budget (LMA) Development (LMEMR) (LSMCIC) (LSMEPB) (LSMPPUD) Lagos State Lagos State Lagos Lagos State Vehicle Development Lagos Environmental Waste Metropolitan Urban Inspection Partnership Bureau of Protection Management Area Transport Renewal Office Department Statistics Agency Agency Authority Agency (VIO) (DPD) (LSB) (LASEPA) (LAWMA) (LAWATA) (LSURA) Reports Air Quality Management Planning for Lagos State 3 An integrated approach to pollution management, tar- » The low level of public awareness of sources and geting global warming, air pollution, solid waste, and impacts of pollution. wastewater management is increasingly important in order to manage the interrelated and complex pollu- For Lagos State, the major obstacle to an integrated tion issues and maximize the benefits of environmental approach to addressing air pollution and GHG e ­ missions regulation. Some of the impediments to an integrated in a cost-effective, cohesive manner is the ­ complexity approach in Lagos are: in interinstitutional coordination between different sectors to ensure synergy among the different institutions ­ » The lack of an air quality monitoring network, indicated in figure 1.1). (­ ­ resulting in the unavailability of good-quality data that would help identify the sources, extent, and impacts of pollution REFERENCE » Limited institutional and human resource capac- ity in pollution monitoring and management Government of Nigeria. 2018. “Nigeria’s National Action » Poor interinstitutional coordination between state Plan to Reduce Short-lived Climate ­ Pollutants.” and federal government agencies h t t p s : / / c l i m a t e ch a n g e. g ov. n g / w p - c o n t e n t​ » The lack of detail and enforcement provisions in /uploads/2020/09/nigeria-s-national-action-plan​ air quality standards and regulations -nap-to-reduce-short-lived-climate-pollutants-slcps​ » Limited capacity to monitor and enforce compli- -.pdf. ance with standards 4 Air Quality Management Planning for Lagos State CHAPTER 2 AIR QUALITY CONDITIONS IN LAGOS AQM planning must start with knowledge of the existing conditions. Until August 2020, only limited and discontinuous measurements of air quality had been carried out in Lagos. The PMEH therefore funded a TSC to carry out 12 continuous months of air quality monitoring at six monitoring sites. Monitoring began in August 2020 and concluded at the end of July 2021. Details of the monitoring are given in the TSC’s report (EnvironQuest 2021a). The main air quality measurements at each monitoring site were PM2.5 and PM10. These were collected on filters for 24-hour periods every three days. The filter collection followed US EPA reference methods, and the samplers used were con- sidered “near-reference” quality. Each monitoring site was also equipped with a weather station, equipment to collect ambient air samples in a vacuum canister over a 24-hour period, and a low-cost, continuous air quality monitoring system. The latter system was included for evaluation. It used an optical sensor to estimate concentrations of PM10, PM2.5, and PM1 and electrochemical sensors to measure gaseous pollutants. As further discussed in section 2.2, the results from this system were of limited value. From January 1, 2021, the US Consulate in Lagos also began reporting hourly PM2.5 concentrations measured by a US EPA reference-grade instrument. Those data are also summarized in this report. Figure 2.1 shows a satellite view of the Lagos metro- politan area, with markers showing the locations of the US Consulate and the six air quality monitoring sites. Air Quality Management Planning for Lagos State 5 FIGURE 2.1.  SATELLITE VIEW OF LAGOS SHOWING THE SIX MONITORING SITES, MAIN ROADS, AND THE US CONSULATE Legend Site US Consulate Source: Satellite data—Google Earth. ­ easurements Figure 2.2 is a chart showing the individual m 2.1. PARTICULATE MATTER taken at each site over the year of monitoring. These are 24-hour averages collected every three days, except for the US Consulate data, which are hourly. Figure 2.3 is a Table 2.1 shows the average of the PM2.5 and PM10 filter similar chart of PM10 measurements over the year. As measurements taken every third day at each monitoring these figures show, the WHO guidelines for 24-hour aver- site as well as the year-to-date measurements by the US age PM2.5 and PM10 concentrations are exceeded nearly Consulate. The Abesan, Jankara, Lagos State Environ- every day of the year. mental Protection Agency (LASEPA), and University of Lagos (UNILAG) sites are all typical urban locations, with average PM2.5 concentrations ranging from 40.3 to As Figure 2.2 and Figure 2.3 show, the PM concentra- 46.5 µg/m3. This range is probably representative of most tions at Ikorodu are systematically much higher than of the urban areas. The Nigerian Conservation ­Foundation at the remaining sites, which tend to bunch closely (NCF) site is in a protected and undisturbed natural eco- together. The hourly PM2.5 data from the US Consu- system near the coast, which is considered to represent late also agree well with the PM filter measurements. regional background concentrations. The Ikorodu site Both PM2.5 and PM10 concentrations are noticeably shows extremely high PM concentrations. It is located at a higher during the dry season. Finally, the effects of the school in a residential area near a concentration of heavy Harmattan winds in January 21–26 and February 19–24 ­ industry. Finally, the US Consulate site is located across can be seen in the extremely high concentrations of the ship channel from Apapa and Tin Can Island ports, so both PM2.5 and PM10 across all of the monitoring sites it may be affected by the emissions there. during those periods. 6 Air Quality Management Planning for Lagos State TABLE 2.1.  ANNUAL AVERAGE PM In addition to the PM filter measurements, the low-cost CONCENTRATIONS COMPARED TO WHO Earthsense Zephyr monitoring systems estimated PM2.5 and PM10 concentrations using an optical sensor. Unfortu- GUIDELINES nately, these estimates were not very accurate. Figure 2.4 compares the PM concentrations determined by the filter Concentration (µg/m3) samplers with the average of the optical sensor concentra- Location PM2.5 PM10 tion estimates over the same sampling period. The correla- tion coefficient is only moderate, with R2 about 0.62. The Abesan 46.5 119.4 slope of the best-fit line for PM2.5 is 2.94 and that for PM10 Jankara 41.5 104.9 is 4.3. Thus, the optical sensor greatly underestimated the LASEPA 40.3 103.3 actual PM concentrations as measured by the filters. UNILAG 41.7 96.2 While far from perfect, the inexpensive optical sensor in the Ikorodu 96.8 170.5 Earthsense Zephyr correlates well enough to give a reason- NCF 29.5 73.6 able indicator of PM levels in real time. Figure 2.5 plots the optical sensor reading for PM2.5 for one of the sites—­ US Consulate 49.2a Figure 2.4— corrected using the best-fit equation shown in ­ WHO guidelines (µg/m3) with the corresponding results from the 24-hour PM filter Annual average 5 15 measurements. Figure 2.6 shows a similar plot for PM10. The two sets of data agree well, except for the month of 24-hour average 15 45 October. The same is true for the remaining sites, except Note: a. January 1 to October 15, 2021 for Ikorodu. The anomalously high readings from the optical sensor during October occurred in the early- to ­ mid-morning hours and may have been due to fog. FIGURE 2.2. PM2.5 MEASUREMENTS AT EACH MONITORING SITE PM2.5 Measurements - Every 3 Days 400 350 300 250 PM2.5 ug/m3 200 150 100 50 0 0 0 0 0 0 1 1 1 1 1 21 1 0 -2 -2 -2 -2 -2 -2 -2 -2 -2 l-2 -2 -2 n- ar pr g ug ct ov ec n eb ay ep -Ju Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 Abesan Ikorodu Jankara LASEPA NCF UNILAG US Consulate Air Quality Management Planning for Lagos State 7 FIGURE 2.3. PM10 MEASUREMENTS AT EACH MONITORING SITE PM10 Measurements - Every 3 Days 700 600 500 PM2.5 ug/m3 400 300 200 100 0 0 0 0 0 21 1 0 21 1 1 1 1 0 -2 -2 -2 -2 -2 -2 l-2 -2 r-2 -2 -2 n- n- ar ug ct g ec ov eb ay ep -Ju p Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 Abesan Ikorodu Jankara LASEPA NCF UNILAG 2.1.1.  PM COMPOSITION of the total. Fine soil made up between 25 percent and 36 percent, while ammonium nitrate and ammonium In addition to measuring the amount of PM mass col- sulfate made up about 10 percent. Other trace elements lected, the TSC carried out chemical analysis of a sub- such as zinc and unidentified material made up about set of the PM filters. Generally, the filters analyzed were 15 percent, except at Ikorodu, where they accounted those from the three monitoring days at each site that for about 33 percent. Much of the unidentified material showed the highest PM2.5 concentrations. For each set was likely made up of oxygen combined with the metal- of filters, the measurements included concentrations lic trace elements or water adsorbed by the particulate of 41 chemical elements (from sodium to uranium), as matter. well as elemental carbon, organic carbon, and six water- soluble ionic species. The concentrations of 225 organic Ammonium nitrate, ammonium bisulfate, and other sul- marker species were also measured. These data were fates are typically secondary pollutants, meaning that analyzed to apportion the PM present among different they are not emitted directly but are formed in the atmos- source categories. Details of the chemical analysis can be phere through chemical reactions among gaseous pollut- found in the TSC’s final report (EnvironQuest 2021a). ants: NH3, SO2, and NO2. Some of the particulate organic matter is also formed by secondary reactions The results of the chemical analysis are summarized in involving gaseous hydrocarbons in the atmosphere. The Figure 2.7. For the PM2.5 samples analyzed, elemental remaining pollutants and the bulk of the organic matter carbon (EC) made up about 10 percent and a mix of are primary pollutants, meaning that they are directly organic compounds (OM) made up about 30 percent emitted into the atmosphere by various sources. 8 Air Quality Management Planning for Lagos State FIGURE 2.4.  CORRELATION BETWEEN PM FILTER DATA AND 24-HOUR AVERAGE OPTICAL SENSOR PM ESTIMATES PM2.5 - Filter vs Zephyr Continuous - All stations 400 350 y = 2.9433x–16.057 R² = 0.6146 300 Filter PM2.5 (µg m–3) 250 200 150 100 50 0 20 40 60 80 100 Zephyr PM2.5 24 hr Average (µg m–3) PM10 - Filter vs Zephyr Continuous - All stations 700 y = 4.2973x–16.057 R² = 0.6294 600 500 Filter PM10 (µg m–3) 400 300 200 100 0 20 40 60 80 100 120 140 160 Zephyr PM10 24 hr Average (µg m–3) Air Quality Management Planning for Lagos State 9 FIGURE 2.5.  CORRECTED OPTICAL SENSOR PM2.5 READINGS VERSUS 24-HOUR FILTER MEASUREMENTS—JANKARA SITE JANKARA - 24-hour PM2.5 filter vs. continuous Zephyr PM2.5 600 500 400 PM2.5 (ug m–3) 300 200 100 0 –100 4-Aug-20 3-Sep-20 3-Oct-20 2-Nov-20 2-Dec-20 1-Jan-21 31-Jan-21 2-Mar-21 1-Apr-21 1-May-21 31-May-21 30-Jun-21 30-Jul-21 Zephyr (corrected - 1 hr avg) 24-hour filter FIGURE 2.6.  CORRECTED OPTICAL SENSOR PM10 READINGS VERSUS 24-HOUR FILTER MEASUREMENTS – JANKARA SITE JANKARA - 24-hour PM10 filter vs. continuous Zephyr PM10 1000 800 600 PM10 ug/m3 400 200 0 –200 4-Aug-20 3-Sep-20 3-Oct-20 2-Nov-20 2-Dec-20 1-Jan-21 31-Jan-21 2-Mar-21 1-Apr-21 1-May-2131-May-2130-Jun-21 30-Jul-21 Zephyr (corrected - 1 hr avg) 24-hour filter 10 Air Quality Management Planning for Lagos State FIGURE 2.7.  SUMMARY OF THE CHEMICAL COMPOSITION OF PM2.5 COLLECTED AT THE SIX MONITORING SITES Abesan PM mass: 64.8 µg m–3 Ikorodu PM mass: 123.6 µg m–3 Jankara PM mass: 58.7 µg m–3 3.2% 3.6% 10% 5.2% 11.3% 4.1% 10.5% 5.6% 4.4% 4.7% 6.6% 1.5% 25.2% 1.8% 21.7% 10.2% 25.9% 13.1% 36.3% 6.1% 27.6% 19.5% 8.9% 32.9% Lasepa PM mass: 57.6 µg m–3 NCF PM mass: 43.1 µg m–3 Unilag PM mass: 62.0 µg m–3 7.8% 4.0% 5.5% 9.1% 5.5% 6.0% 15.6% 5.4% 3.9% 6.4% 6.2% 1.5% 10.1% 6.0% 12.3% 1.9% 31.3% 24.7% 11.8% 36.1 28.8% 31.5% 28.6% Ammon nitrate Ammon sulphate Fine soil OM EC Sea salt Trace elements Unidentified 2.1.2.  PM SOURCE APPORTIONMENT 2021b). The results of the source apportionment of PM2.5 by PMF are summarized in Figure 2.8, while the results To better determine the sources of ambient PM concen- of the CMB analysis are summarized in Figure 2.9. trations in Lagos, the TSC carried out a source appor- The two techniques gave similar results for PM source tionment analysis using the PM compositions. Two apportionment in Lagos during the monitoring period. different source apportionment techniques were applied: positive matrix factorization (PMF) and chemical mass The PMF analysis showed nine source types: dust, balance (CMB). Both analyses used techniques and soft- biomass burning, solid waste burning, diesel combus- ware developed for this purpose by the US EPA. Fur- tion, gasoline engine combustion, industrial emissions, ther details are given in the TSC’s report (EnvironQuest ammonium nitrate, sulfate, and a fraction that was rich Air Quality Management Planning for Lagos State 11 FIGURE 2.8. PM2.5 SOURCE APPORTIONMENT BY PMF Jankara Unilag Lasepa 0% 1% 0% 1% 0% 1% 11% 13% 18% 32% 37% 36% 25% 29% 22% 5% 7% 8% 2% 4% 4% 5% 5% 6% 8% 7% 13% NCF Abesan Ikorodu 0% 3% 5% 3% 1% 8% 2% 5% 11% 3% 8% 3% 37% 33% 32% 21% 41% 4% 50% 0% 0% 6% 9% 7% 0% 1% 7% Average of 6 sites 1% 2% 11% 27% 28% 5% 5% 3% 18% BB Cl Diesel Dust Gasoline Industrial NH4NO3 SO4 Waste combustion 12 Air Quality Management Planning for Lagos State FIGURE 2.9. PM2.5 SOURCE APPORTIONMENT BY CMB Jankara Unilag Lasepa 22% 22% 24% 36% 43% 44% 16% 18% 5% 27% 4% 7% 4% 4% 6% 6% 5% 7% NCF Abesan Ikorodu 22% 20% 28% 28% 31% 34% 5% 3% 4% 5% 4% 5% 6% 2% 9% 18% 30% 46% Average of 6 sites 24% 32% 17% 4% 5% 18% Dust Industrial NH4NO3 NH4HSO4 MV BBFW Air Quality Management Planning for Lagos State 13 in chloride ion (Cl-). The CMB analysis identified only six source types: dust, a combination of biomass with 2.2. LEAD AEROSOL solid waste burning and cooking, motor (gasoline and diesel engines combined), industrial emissions, ammo- nium nitrate, and ammonium sulfate. Dust makes up Lead aerosol is a highly toxic component of airborne 28 percent of the average source composition in PMF PM. Because of its former widespread use in gasoline and 24 percent in CMB. Open burning of biomass and paints, the US EPA has established a separate ambi- and solid waste makes up 28 percent in PMF; that plus ent air standard of 0.15 µg/m3 for lead, measured as a cooking make up 32 percent in CMB. Gasoline and quarterly average of total suspended particulate matter diesel engines combined make up 14 percent in PMF (TSP). With the worldwide elimination of leaded gasoline and 17 percent in CMB. Secondary ammonium nitrate and paints, this limit has largely become irrelevant except and ammonium sulfate make up 10 percent in PMF in the vicinity of poorly controlled lead-smelting activi- and 9 percent in CMB. Both techniques show indus- ties such as battery recycling. However, Figure 2.12 shows trial emissions at 18 percent of the average over the six that the airborne lead concentrations measured at the sites. Industrial emissions at Ikorodu are 50 percent in Ikorodu site are more than 10 times the level of the EPA PMF and 46 percent in CMB, less than 1–2 percent at standard, indicating a grave threat to public health. Four Abesan, and 5–9 percent at the other sites monitored. ­ of the other five monitoring sites marginally exceeded the standard during at least one quarter. Only the Abesan site did not. Abesan is also the site furthest from Ikorodu. The results of PMF source apportionment of the PM10 This could indicate that a major source of lead emissions composition data are summarized in Figure 2.10 (no near the Ikorodu site may be causing exceedance of the CMB analysis was done for PM10). These results show lead standard throughout much of the city. that the percentage of the PM10 due to dust is about twice as high as for PM2.5, while the percentage due to the chlo- ride-rich fraction is five times as high. This suggests that the chloride-rich fraction may be due to sea salt particles 2.3. GASEOUS POLLUTANTS since these occur primarily in the coarse mode. The con- tributions of the other sources are reduced more or less proportionally. Common gaseous pollutants for which the Federal ­ Ministry of Environment (FMEnv) has established ambient air quality standards include O3, NO2, CO, and ­ SO2. Table 2.2 shows the air quality standards in effect 2.1.3.  SOURCE OF HIGH PM in Nigeria and the US, along with the recently updated CONCENTRATIONS AT IKORODU guidelines of the WHO. Average PM concentrations at the Ikorodu site were con- Details of the gaseous pollutant measurements and sistently higher than for any of the other monitoring sites. ­ quality assurance are given in the TSC’s report (Environ- Although the site itself is at a secondary school, it is close Quest 2021a). In this monitoring campaign, the gaseous to a number of factories that were hypothesized to be pollutants were measured using low-cost electrochemical the source of the excess PM. To test this hypothesis, the sensors. Because of this, the data are not completely reli- TSC plotted the average PM2.5 and PM10 concentrations able. In particular, the measurements of O3, CO, and as functions of wind direction and speed, as shown in SO2 tend to show spuriously high “spikes” for an hour or Figure 2.11. Winds from the directions corresponding to two after the monitoring system starts up, while the NO2 the nearby industrial establishments consistently showed measurements tend to show spuriously low values. Dur- much higher PM concentrations than from any other ing some periods, battery problems with the solar power direction. systems at the LASEPA and Ikorodu sites caused the 14 Air Quality Management Planning for Lagos State FIGURE 2.10. PM10 SOURCE APPORTIONMENT OF PM10 BY PMF Jankara Unilag Lasepa 7% 2% 14% 1% 13% 10% 0% 12% 15% 9% 9% 5% 1% 3% 9% 0% 10% 2% 3% 0% 15% 3% 2% 11% 51% 45% 48% NCF Abesan Ikorodu 3% 1% 11% 11% 6% 10% 12% 11% 6% 5% 4% 0% 1% 0% 0% %4 0% 10% %0 1% 16% 5% 27% 46% 0% 53% 57 Average of 6 sites 8% 5% 10% 8% 1% 7% 8% 3% 50% BB Cl Diesel Dust Gasoline Industrial NH4NO3 SO4 Waste combustion Air Quality Management Planning for Lagos State 15 FIGURE 2.11.  PM CONCENTRATION VERSUS WIND DIRECTION FOR IKORODU a. b. Zephyr Ikorodu, Lagos N Mean 14 12 350 10 8 300 6 ws 4 250 W 2 E 200 150 100 50 S Zephyr Ikorodu, Lagos N Mean 14 12 10 8 400 6 ws 4 300 W 2 E 200 100 S FIGURE 2.12.  QUARTERLY AVERAGE LEAD AEROSOL CONCENTRATIONS MEASURED AT EACH SITE PM2.5 PM10 1.8 2.5 1.6 1.4 2.0 Concentration, µg m–3 Concentration, µg m–3 1.2 1.5 1.0 0.8 1.0 0.6 0.4 0.15 µg m–3 0.5 0.15 µg m–3 0.2 0 0 Qtr 1 Qtr 2 Qtr 3 Qtr 4 Qtr 1 Qtr 2 Qtr 3 Qtr 4 Abesan Ikorodu Jankara Lasepa NCF Unilag Limit 16 Air Quality Management Planning for Lagos State TABLE 2.2.  AMBIENT AIR QUALITY STANDARDS AND WHO GUIDELINES FOR GASEOUS POLLUTANTS WHO Air Quality Pollutant (units) Averaging period US EPA NAAQS Nigeria AAQS Standard O3 (μg/m3) 6 monthsa — — 60 8 hours 137 (0.07 ppm) 100 100 1 hour — 180 — NO2 (μg/m3) Annual 100 (53 ppb) — 10 24 hours — 120 25 1 hour 188 (100 ppb) 200 200 SO2 (μg/m3) 24 hours — 120 40 1 hour 196.5 350 — CO (mg/m3) 24 hours — — 4 8 hours 10 (9 ppm) 5 5 1 hour 40 (35 ppm) 10 10 Note: US EPA National Ambient Air Quality Standards (NAAQS) values in parenthesis are µg/m3 equivalent at 1 atmosphere and 25oC. a. Average of daily 8-hour peaks. monitors to shut down every night and start up the fol- Figure 2.14 shows the 24-hour average NO2 concentra- lowing morning. Data from those periods, as well as other tions measured at each monitoring site. These rarely spurious data (to the extent that these could be identi- exceeded the Nigerian air quality standard of 120 µg/m3 fied), have been redacted from the database. but exceeded the new WHO guideline of 25 µg/m3 almost all the time. Annual average concentrations ranged from After removing the spurious values, the results of the 48 µg/m3 at NCF to 76 µg/m3 at Jankara—far exceeding gaseous pollutant monitoring show that concentrations the WHO guideline of 10 µg/m3. of CO exceeded the Nigerian air quality standards and WHO health guidelines at all six sites. Figure 2.13 shows Figure 2.15 shows the 8-hour average O3 concentra- the 8-hour average CO concentrations measured at each tions measured at each of the six sites. The concentra- site. All six sites exceeded the Nigerian CO standard of tions at these sites exceeded the Nigerian air quality 5 µg/m3. The Abesan, Jankara, and UNILAG sites show standard of 100 µg/m3 twice, while the 1-hour aver- the highest and most frequent exceedances, sometimes age concentrations exceeded the 180 µg/m3 Nigerian exceeding the less stringent US standard of 10 µg/m3. standard once. The 6-month average peak concen- One-hour average concentrations (not shown) often tration at Abesan likely exceeded the WHO guide- exceeded the Nigerian standard of 10 µg/m3 but not the line of 100 µg/m3 as well. However, all of these sites US 40 µg/m3 standard. except NCF were situated close to significant sources Air Quality Management Planning for Lagos State 17 18 1- CO (mg/m3) 1- CO (mg/m3) 1- CO (mg/m3) 1- CO (mg/m3) Au Au Au Au g 0 2 4 6 8 10 12 0 12 0 2 4 6 8 10 12 14 16 18 20 2 4 6 8 10 0 2 4 6 8 10 12 14 16 18 20 g- g- g- -2 20 20 20 0 31 31 31 31 -A -A -A -A u g- u g- ug ug 20 20 -2 -2 0 0 30 30 30 30 -se -se -se -se p- p- p- p- 20 20 20 20 30 30 30 30 -O -O -O -O ct ct ct ct -2 -2 -2 -2 0 0 0 0 29 29 29 29 -N -N -N -N ov ov ov ov -2 -2 -2 -2 0 0 0 0 29 29 29 29 -D -D -D -D ec ec ec ec -2 -2 -2 -2 0 0 0 0 Green lines, Nigerian/WHO standard, red lines US NAAQS 28 28 28 28 -Ja -Ja -Ja -Ja n- n- n- n- 21 21 21 21 LASEPA 27 27 27 27 IKORODU JANKARA ABESAN -Ja -Ja -Ja -Ja n- n- n- n- 21 21 21 21 29 29 29 29 -M -M -M -M ar ar ar ar -2 -2 -2 -2 1 1 1 1 28 28 28 28 -A -A -A -A pr pr pr pr -2 -2 -2 -2 1 1 1 1 28 28 28 28 -M -M -M -M ay ay ay ay -2 -2 -2 -2 1 1 1 1 27 27 27 27 -Ju -Ju -Ju -Ju n- n- n- n- 21 21 21 21 27 27 27 27 -Ju -Ju -Ju -Ju l-2 l-2 l-2 l-2 1 1 1 1 FIGURE 2.13.  EIGHT-HOUR AVERAGE CO CONCENTRATIONS AT EACH MONITORING SITE Air Quality Management Planning for Lagos State FIGURE 2.13. (Continued ) NCF 12 10 8 CO (mg/m3) 6 4 2 0 0 0 20 0 0 0 21 21 1 1 1 21 1 -2 -2 -2 -2 -2 -2 -2 -2 l-2 n- n- p- n- ug ct g ov ar ay ec pr -Ju Au -se -Ja -Ju -Ja -O -M -D -A -M -N -A 27 30 1- 28 27 27 30 28 29 31 29 29 28 UNILAG 12 10 8 CO (mg/m3) 6 4 2 0 20 0 20 0 21 0 0 1 1 21 21 1 1 -2 -2 -2 -2 -2 l-2 -2 -2 g- n- n- p- n- ug ct ov ar ay ec pr -Ju Au -se -Ja -Ju -Ja -O -M -D -A -M -N -A 27 30 1- 27 28 27 30 28 29 31 29 29 28 of n­ itrogen oxides (NOx). The air quality modeling 1-hour standard and WHO guideline of 200 µg/m3. confirmed that much higher O3 concentrations are to The ­ missing data during the peak may indicate times be expected in the region downwind of the city. This when the ambient concentration was above the range is because nitric oxide (NO), the major constituent of of the sensor. Several other smaller events are also vis- NOx, reacts with O3 to form NO2 and O2, thus sup- ible in the UNILAG data. pressing O3 levels close to the emission source. In the presence of sunlight, NO2 reacts over time with volatile organic compounds (VOCs) in a complex process that produces O3 and other photochemical oxidants. Thus, 2.4. ORGANIC as distance from the source of NOx emissions increases, so usually does the O3 concentration. COMPOUNDS AND TOXIC AIR CONTAMINANTS The monitoring data for SO2 show levels generally well below the applicable standards, except for a single event with multiple spikes that was observed by both At each of the six sites, the air monitoring TSC collected the UNILAG and LASEPA sites from about 22:00 on a total of 22 air samples in evacuated canisters for chemi- October 6 to 06:00 on October 8 (Figure 2.16). At the cal analysis. Each sample was collected at a uniform UNILAG site, this event slightly exceeded the Nigerian rate over 24 hours. The resulting canister samples were Air Quality Management Planning for Lagos State 19 20 Nitrogen dioxide (ug/m3) Nitrogen dioxide (ug/m3) Nitrogen dioxide (ug/m3) Nitrogen dioxide (ug/m3) 1- 1- 1- 1- Au Au Au Au 0 20 40 60 80 100 120 140 0 50 100 150 200 250 300 0 20 40 60 80 100 120 140 0 20 40 60 80 100 120 140 g- 20 g- 20 g- 20 g -2 0 31 31 31 31 -A -A -A -A ug u g- ug ug -2 20 -2 -2 MONITORING SITE 0 0 0 30 30 30 30 -S -S -S -S e p- ep ep ep -2 -2 -2 20 0 0 0 30 30 30 30 -O -O -O -O ct ct ct ct -2 -2 -2 -2 0 0 0 0 29 29 29 29 -N -N -N -N ov ov ov ov -2 -2 -2 -2 0 0 0 0 29 29 29 29 -D -D -D -D ec Red lines Nigerian standard, green lines WHO guideline ec -2 ec ec -2 0 -2 -2 0 0 0 28 28 28 28 -Ja -Ja -Ja -Ja n- n- n- n- 21 21 21 21 ABESAN LASEPA JANKARA IKORODU 27 27 27 27 -Ja -Ja -Ja -Ja n- n- n- n- 21 21 21 21 29 29 29 29 -M -M -M -M ar ar ar ar -2 -2 -2 -2 1 1 1 1 28 28 28 28 -A -A -A -A pr pr pr pr -2 -2 -2 -2 1 1 1 1 28 28 28 28 -M -M -M -M ay ay ay ay -2 -2 -2 -2 1 1 1 1 27 27 27 27 -Ju -Ju -Ju -Ju n- n- n- n- 21 21 21 21 FIGURE 2.14.  TWENTY-FOUR-HOUR AVERAGE NO2 CONCENTRATIONS AT EACH 27 27 27 27 -Ju -Ju -Ju -Ju l-2 l-2 l-2 l-2 1 1 1 1 Air Quality Management Planning for Lagos State FIGURE 2.14. (Continued ) UNILAG 180 160 Nitrogen dioxide (ug/m3) 140 120 100 80 60 40 20 0 0 0 0 0 0 21 21 1 1 1 21 1 0 -2 -2 -2 -2 -2 -2 l-2 -2 -2 -2 n- n- n- ug ep ov ec ar pr ct ay g -Ju Au -Ja -Ja -Ju -O -M -D -A -M -S -N -A 27 28 27 1- 27 30 30 28 29 31 29 29 28 NCF 160 Nitrogen dioxide (ug/m3) 140 120 100 80 60 40 20 0 0 0 0 0 0 21 21 1 1 1 21 1 20 -2 -2 -2 -2 -2 -2 -2 l-2 -2 n- n- n- g- ug ep ct ov ec ar pr ay -Ju Au -Ja -Ja -Ju -O -M -D -A -M -S -N -A 27 28 27 1- 27 30 30 28 29 31 29 29 28 a ­ nalyzed for their content of 106 organic compounds large industrial user of dichloromethane solvents with and other toxic air contaminants, as well as chlorofluoro- little or no emission control. carbons (CFCs), HFCs, and GHGs. The results of the organic analysis showed that most 2.5. GREENHOUSE GASES compounds are present in less than parts per billion (ppb) concentrations. However, some are at concentrations of ppb or tens of ppb, among them ethane (a minor constit- The TSC analyzed the canister air samples for the main uent of natural gas), propane and butanes (from liquefied GHGs, as well as for common halocarbons (CFCs, hydro- petroleum gas, or LPG), and products of p ­ artial gasoline chlorofluorocarbons [HCFCs], and HFCs) with high combustion such as ethylene and propylene. Also pre- global-warming potential (GWP). The average GHG sent in significant amounts were common solvents such concentrations at each site are shown in Figure 2.17, as toluene, naphthalene, acetone, chloromethane, and while the average concentrations of halocarbons are dichloromethane—all of which are considered hazard- shown in Figure 2.18. ous air pollutants. From February, high concentrations of dichloromethane were seen at the Ikorodu and LASEPA CO2 concentrations at all sites were above the global sites (67 and 74 parts ppb initially, tapering to about 33 background level, reflecting the substantial CO2 emis- ppb over months). This likely indicates the startup of a sions in the metropolitan area. The same is true of CH4 Air Quality Management Planning for Lagos State 21 and nitrous oxide (N2O) concentrations. The significance as at any other site, while CFC 114 was similarly high of the variation in average concentrations among the six at UNILAG. This suggests possible emission sources of sites is not clear. these CFCs in the surrounding area. HCFCs 141b and 142b at all sites were significantly higher than the global Among the halocarbons measured, concentrations of background concentrations, suggesting that emission CFC 11 and CFC 12 were highest at Ikorodu, followed sources for these chemicals may be widespread through- by Jankara. CFC 113 was three times as high at Abesan out the metropolitan area. FIGURE 2.15.  EIGHT-HOUR AVERAGE O3 CONCENTRATIONS AT EACH MONITORING SITE Green lines, Nigerian/WHO standard, red lines US NAAQS Abesan 160 140 120 Ozone (ug/m3) 100 80 60 40 20 0 0 0 0 0 0 21 1 1 1 1 21 1 0 -2 -2 -2 -2 -2 -2 r-2 l-2 -2 -2 -2 n- n- ar g ug ct ov eb ec ay ep -Ju p Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 Jankara 120 100 80 Ozone (ug/m3) 60 40 20 0 –20 0 0 0 0 0 0 21 1 1 1 1 21 1 -2 -2 -2 -2 -2 -2 r-2 l-2 -2 -2 -2 n- n- ar g ep ug ov eb ct ec ay -Ju p Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 Ikorodu 120 100 Ozone (ug/m3) 80 60 40 20 0 0 0 0 0 0 21 1 1 21 1 1 1 0 -2 -2 -2 -2 -2 r-2 l-2 -2 -2 -2 -2 n- n- ar g ug ov eb ct ec ay ep -Ju p Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 22 Air Quality Management Planning for Lagos State FIGURE 2.15. (Continued ) Lasepa 160 140 120 Ozone (ug/m3) 100 80 60 40 20 0 0 0 0 0 0 21 1 1 1 1 21 1 0 -2 -2 r-2 -2 -2 -2 l-2 -2 -2 -2 -2 n- n- ar g ug ov eb ct ec ay ep -Ju p Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 NCF 120 100 Ozone (ug/m3) 80 60 40 20 0 20 0 0 0 0 21 1 21 1 1 1 1 0 -2 -2 -2 -2 -2 r-2 l-2 -2 -2 -2 g- n- n- ar ug ct ov eb ec ay ep -Ju p Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 Unilag 120 100 Ozone (ug/m3) 80 60 40 20 0 0 0 0 1 0 0 21 1 1 1 21 1 0 -2 -2 -2 -2 -2 r-2 -2 l-2 -2 -2 -2 n- n- ar g ug ov ec eb ct ay ep -Ju p Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 emissions inventory for Lagos State (ARIA 2021). 2.6. POLLUTANT EMISSION The preliminary inventory was then validated against the INVENTORY air quality monitoring data. An emissions inventory is an estimate of the emissions 2.6.1. CRITERIA POLLUTANTS of each type of pollutant in a given area, broken down by the type of source. Using PMEH funds, the World Table 2.3 shows the inventory estimates of criteria Bank contracted with a TSC to develop a preliminary pollutant4 emissions and their precursors. For discussion Air Quality Management Planning for Lagos State 23 24 Sulfur dioxide (ug/m3) Sulfur dioxide (ug/m3) Sulfur dioxide (ug/m3) Sulfur dioxide (ug/m3) 1- 1- 1- 30 Au Au Au -S –50 0 50 100 150 200 250 300 350 400 –50 0 50 100 150 200 250 300 350 400 –50 0 50 100 150 200 250 300 350 400 –50 0 50 100 150 200 250 300 350 400 g -2 g -2 g -2 ep -2 0 0 0 0 31 31 -A -A ug ug -2 -2 0 0 30 30 -S -S ep ep -2 -2 0 0 30 30 -O -O 7- ct ct 7- O -2 0 -2 0 O ct ct -2 -2 0 29 29 0 -N -N ov ov - 20 -20 29 29 -D -D ec ec -2 -2 Green lines, Nigerian/WHO standard, red lines US NAAQS 0 0 28 28 -Ja -Ja n- n -2 21 1 LASEPA 14 UNILAG UNILAG UNILAG 14 -O -O ct ct -2 27 27 -2 0 -F -F 0 eb eb -2 -2 1 1 29 29 -M -M ar ar -2 -2 1 1 28 28 -A -A p r-2 p r-2 1 1 21 21 FIGURE 2.16. SO2 CONCENTRATIONS AT LASEPA AND UNILAG SITES -O 28 28 -O ct -M -M ct -2 -2 0 ay -2 ay -2 0 1 1 27 27 -Ju -Ju n- n- 21 21 27 27 -Ju -Ju l-2 l-2 1 1 Air Quality Management Planning for Lagos State FIGURE 2.17.  AVERAGE GHG CONCENTRATIONS MEASURED AT EACH MONITORING SITE GHG Concentrations by Site 600 2,400 500 2,200 CO2 (ppm) and N2O (ppb) 400 2,000 Methane (ppb) 300 1,800 200 1,400 100 1,200 0 1,000 Abesan Ikorodu Jankara LASEPA UNILAG NCF Global Bkgnd CO2 (ppm) Methane (ppb) N2O (ppb) FIGURE 2.18.  AVERAGE CONCENTRATIONS OF CFCs, HCFCs, AND HFCs MEASURED AT EACH MONITORING SITE Halocarbon Concentrations by Site 0.5 0.4 Mixing ration (ppbv) 0.3 0.2 0.1 0 CFC11 CFC12 CFC113 CFC114 HCFC-22 HCFC-141b HCFC-142b HFC-134a Abesan Ikorodu Jankara LASEPA UNILAG NCF Global Bkgnd Air Quality Management Planning for Lagos State 25 TABLE 2.3.  ESTIMATED INVENTORY OF CRITERIA POLLUTANTS AND PRECURSORS FOR LAGOS STATE Pollutant emissions (tons/year) Source type PM10 PM2.5 NOx VOC SOx CO NH3 Trash burning 11,345 9,351 3,557 7,162 461 36,272 1,058 Biomass burning 274 159 103 406 10 1,677 21 Generators 1,021 1,021 21,528 27,054 3,542 10,77,489   Road traffic 1,820 1,470 38,388 38,275 6,529 2,36,771 723 Industry 3,072 2,837 2,915 19,955 1,662 16,612 1,013 Power plants 49 49 5,639 143 15 2,142 0 Seaport 243 243 4,280 197 3,283 607 0 Airport 2 0 726 71 41 587 0 Cooking 185 180 694 168 168 1,536   Waste disposala 0 0   2,585     58,100 Agriculture 166 7 722 104 0 0 681 TOTAL 18,177 15,317 78,552 96,120 15,711 13,73,693 61,596 Note: a. Other than open burning. Includes emissions from dumpsites and wastewater. purposes, the 11 source categories listed can be condensed Thus, the primary PM sources listed in Table 2.3 are to 7 by lumping together open burning of trash and responsible for about 60 percent of the ambient mass of biomass, as well as seaports and airports, and combining PM2.5 but only about 30 percent of ambient PM10. the minor categories of cooking, waste disposal, and agriculture as “other.” Figure 2.19 shows how the Of the roughly 60 percent of ambient PM2.5 attributable emission inventory for each primary pollutant breaks to primary emissions, the majority is estimated to be due down among these 7 categories. to open burning of solid waste and other biomass. Most of the rest is attributed to industry, road traffic (mostly The PM emission estimates shown in Table 2.3 include diesel vehicles and two-stroke motorcycles), and backup only primary emissions of PM and not secondary parti- generators. Diesel and gasoline engines used in road cles (sulfates, nitrates, and some organic compounds) vehicles and generators account for 76 percent of the formed by the chemical reactions of other pollutants in NOx, 68 percent of the VOC, 96 percent of the CO, the atmosphere. They also exclude resuspended dust as and 64 percent of the sulfur oxides (SOx) emissions (the the emission numbers are not directly comparable to latter due to average fuel sulfur concentrations of 0.24 those for the other categories. Dust particles—even in the percent in diesel fuel and 0.14 percent in gasoline). PM2.5 size range—are larger and settle out of the atmos- Nearly 80 percent of the CO emissions are attributed to phere much faster than particles from other sources, generators—mostly small, inefficient, portable generators which are usually less than 1 µm. Based on the source burning gasoline. The ports account for another 6 percent apportionment analysis, dust averages about 25 percent of NOx and 21 percent of SOx emissions—the latter due of atmospheric PM2.5 and 50 percent of PM10, while sec- mostly to ships burning heavy fuel oil (HFO) containing ondary material averages about 15 percent of PM2.5. up to 2 percent sulfur. 26 Air Quality Management Planning for Lagos State FIGURE 2.19.  BREAKDOWN OF ESTIMATED CRITERIA POLLUTANT EMISSIONS BY TYPE OF SOURCE PM2.5 NOx VOC 2% 1% 8% 6% 2% 5% 0% 7% 22% 18% 4% 27% 29% 10% 7% 62% 41% 49% SOx CO 1% 3% 1% 3% 21% 22% 17% 11% 42% 79% Open burning Generators Road traffic Industry Power plants Sea & Airports Other Although not itself a criteria pollutant, NH3 combines VOCs, and CO. Table 2.4 shows the inventory with with NOx and SOx to form secondary PM2.5. Improper CO2-equivalent values calculated using the estimated disposal of human and animal waste is estimated to 20-year GWP of each pollutant, while Table 2.5 is account for about 94 percent of NH3 emissions. calculated using the 100-year GWP estimates. In both cases, the N2O and CH4 GWPs are those determined by the Intergovernmental Panel on Climate Change (IPCC) 2.6.2. GREENHOUSE EMISSIONS AR6 Working Group 1 (IPCC 2021), while those for black carbon, VOC, and CO were selected from among Estimated GHG emissions are summarized in Table 2.4 the lower values listed in appendix 8 of the IPCC AR5 and Table 2.5. Estimated CO2 emissions in Lagos total Working Group 1 report (Myhre et al. 2013). 16.3 million tons per year, but in the near term their warming effect is outweighed by the effects of short- It is conventional to calculate GHG inventories and lived greenhouse pollutants such as CH4, black carbon, Nationally Determined Contributions (NDCs) using Air Quality Management Planning for Lagos State 27 TABLE 2.4.  ESTIMATED INVENTORY OF GLOBAL-WARMING POLLUTANTS FOR LAGOS STATE—CALCULATED WITH 20-YEAR GWPS GHG Emissions (tonnes /yr) Black Total CO2 Source Type CO2 Carbon CH4 N2O VOC CO Equivalent Global Warming 1 2,900 81.2 273 14 7.8   Potential (20 yr) Waste burning 13,80,000 607 3,521 0 7,162 36,272 38,09,395 Biomass burning 36,700 10 82 0 406 1,677 91,123 Generators 36,52,686 464 0 0 27,054 10,77,489 1,37,81,456 Road traffic 59,52,524 504 1,971 209 38,275 2,36,771 1,00,13,890 Industry 7,30,000 724 0 0 19,955 16,612 32,38,544 Power plants 29,50,926 1 53 5 143 2,142 29,78,784 Seaport 2,62,349 43 4 12 197 607 3,98,142 Airport 1,57,965 2 11 4 71 587 1,71,323 Waste disposala 0 0 66,593 0 2,585 0 54,43,542 Cooking 11,00,000 18 420 37 168 1,536 12,10,738 Agriculture 0 0 93 2,904 104 0 8,01,800 TOTAL 1,62,23,150 2,373 72,748 3,171 96,120 13,73,693 4,19,38,736 TOTAL CO2-eq. 1,62,23,150 68,82,280 59,07,138 8,65,683 13,45,680 1,07,14,805 4,19,38,736 Note: a. Other than open burning. Includes emissions from dumpsites and wastewater. the 100-year rather than the 20-year GWPs, which are Figure 2.20 shows the breakdown of GHG emissions by higher. We emphasize the 20-year GWPs here because source. Generators and road traffic are the sources with of the urgency of reducing near-term warming to stay the largest GHG impact, largely due to the high CO within the 1.5oC target and because the air quality emissions from gasoline engines. measures considered in this report would all take effect in the relatively near term (that is, the next 5 to 10 years). 2.6.3. LIMITATIONS OF THE INVENTORY For Lagos, using either the 20-year or 100-year GWPs, the An emission inventory can be only as accurate as the short-lived pollutants with the greatest global-warming data used to calculate it. Emissions from each type of effect are CO, black carbon, and CH4. Using the 20-year source are calculated by multiplying an estimate of the GWPs, these three pollutants are the CO2 equivalent of activity attributable to that type of source by an estimate about 11, 7, and 6 million tons per year, respectively. of the corresponding emission factor. Activity is typically 28 Air Quality Management Planning for Lagos State TABLE 2.5.  ESTIMATED INVENTORY OF GLOBAL-WARMING POLLUTANTS FOR LAGOS STATE—CALCULATED WITH 100-YEAR GWPS GHG emissions (tons /year) Black Total CO2 Source type CO2 carbon CH4 N2O VOC CO equivalent Global warming 1 830 27.9 273 5 2.2   potential (100 year) Waste burning 13,80,000 607 3,521 0 7,162 36,272 20,94,073 Biomass burning 36,700 10 82 0 406 1,677 52,804 Generators 36,52,686 464 0 0 27,054 10,77,489 65,30,025 Road traffic 59,52,524 504 1,971 209 38,275 2,36,771 71,76,026 Industry 7,30,000 724 0 0 19,955 16,612 14,57,264 Power plants 29,50,926 1 53 5 143 2,142 29,60,122 Seaport 2,62,349 43 4 12 197 607 3,03,649 Airport 1,57,965 2 11 4 71 587 1,62,635 Waste disposala 0 0 66,593 0 2,585 0 18,69,577 Cooking 11,00,000 18 420 37 168 1,536 11,40,894 Agriculture 0 0 93 2,904 104 0 7,95,855 TOTAL 1,62,23,150 2,373 72,748 3,171 96,120 13,73,693 2,45,42,923 TOTAL CO2-eq 1,62,23,150 19,69,756 20,29,669 8,65,683 4,32,540 30,22,125 2,45,42,923 Note: a. Other than open burning. Includes emissions from dumpsites and wastewater. expressed in terms of outputs such as vehicle-kilometers The applicability of the emission factors used is also sub- traveled or inputs such as tons of fuel consumed or tons ject to question. Few emission measurements have been of trash burned. For many of the source types considered conducted in Nigeria, so the emission factors had to be in this inventory, reliable data for estimating the output based on measurements in other countries, typically in values were not available for Lagos State, so crude esti- the Organisation for Economic Co-operation and Devel- mates or national-level statistics had to be applied. The opment (OECD). The degree to which emissions from, missing data included information on amounts of trash for example, small generators measured by the US EPA and biomass burned, industrial production and energy are representative of small generators used in Lagos is consumption, and the numbers and utilization of small unknown. The same is true of vehicle emission factors, generators for electricity. Details of these estimates are which were estimated by a model based on European given in the TSC’s report (ARIA 2021). Better statistics emission standards. These factors were adjusted to try to are needed, especially for critical activities such as trash account for the widespread Nigerian practice of remov- burning and backup generators. ing catalytic converters from imported vehicles, but the Air Quality Management Planning for Lagos State 29 FIGURE 2.20. CO2 EQUIVALENT EMISSIONS BY SOURCE TYPE 20-year GWP 100-year GWP 9% 11% 9% 15% 3% 5% 1% 2% 26% 7% 33% 12% 8% 6% 24% 29% Open burning Generators Road traffic Industry Power plants Sea & Airports Waste disposal Cooking & Ag adequacy of this adjustment is unknown. There is also validate the emissions inventory by comparing the model reason to think that the vehicle emission factor model results to measured pollutant concentrations. Another may underestimate PM2.5, black carbon, and VOC from goal was to extend the geographic range of the air quality diesel vehicles in Lagos because the model assumes Euro- data from the six monitoring sites to all 19 of the LGAs pean vehicle maintenance practices and lifetimes. defined in the State of Lagos. This inventory should thus be considered as a first—and very rough—approximation, and plans for AQM should 2.7.1.  MODELS AND METHODS include research to improve the estimates of both activi- ties and emission factors under Nigerian conditions. The modeling approach is described in the TSC’s report (ARIA 2021). Modeling was performed on several differ- ent scales. The largest scale encompassed much of Africa 2.7. POLLUTANT DISPERSION and used a global emissions database. This was done using CHIMERE software to establish the boundary MODELING conditions for the more detailed modeling. The detailed model covered a rectangle, a little bigger than the State of Lagos, and used FARM software. Both the FARM and The TSC responsible for the emissions inventory also CHIMERE models are three-dimensional Eulerian pho- conducted air quality modeling using the emissions tochemical models capable of modeling the dispersion, inventory and the weather conditions recorded during chemical transformation, and deposition of pollutants the year of air quality monitoring to simulate pollutant from both anthropogenic and biogenic sources over a concentrations. One goal of this modeling activity was to given area. 30 Air Quality Management Planning for Lagos State 2.7.2.  EPISODES MODELED 2.7.3.  MODEL RESULTS Modeling was conducted for the five selected episodes Initial simulations were conducted on the earliest two indicated by the brown horizontal bars in Figure 2.21. episodes in Figure 2.21. Those simulations showed NO2 These are September 10–20, December 10–20, March concentrations much higher than observed during the air 5–16, April 25–May 5, and June 27–July 7, 2021. quality modeling, and O3 concentrations much lower. These five periods were selected after consultation This suggested that the estimated NOx inventory was between the World Bank team and the TSC project probably too high. A review of the emission inventory team. The first three correspond to observed positive found that NOx emissions from generators had been sig- peaks or “spikes” in several air quality variables, nificantly overestimated. Several other errors in the notably PM2.5 and PM10. The final two periods are inventory were also found and corrected. Figure 2.22 to considered more representative of “background” Figure 2.26 show the correspondence between the moni- conditions, during which the air quality variables toring data at the UNILAG station and the model results O3, NO2, PM2.5, and PM10 varied only subtly above using the revised emissions inventory. These show rea- baseline concentrations. sonable agreement with the monitoring results. FIGURE 2.21.  EPISODES SELECTED FOR AIR QUALITY MODELING PM2.5 Measurements - Every 3 Days 350 300 250 PM2.5 ug/m3 200 150 100 50 0 1 20 20 20 1 0 0 0 21 1 1 1 1 -2 -2 -2 l-2 -2 r-2 -2 -2 -2 g- - - n- ar ay ug ep eb n ov ct ec -Ju p Au -Ja -Ju -O -M -D -F -A -M -N -S -A 27 28 1- 27 27 30 30 28 29 31 29 29 28 Abesan Ikorodu Jankara LASEPA NCF UNILAG Episodes to be Modeled Air Quality Management Planning for Lagos State 31 FIGURE 2.22.  COMPARISON OF FARM MODEL OUTPUT WITH IN SITU MEASUREMENT FOR O3, NO2, PM2.5, AND PM10 AT UNILAG STATION FOR EPISODE PERIOD OF SEPTEMBER 10–20, 2020 Unilag - air quality 150 150 NO2 (µg/m3) 100 O3 (µg/m3) 100 50 50 0 0 11 21 13 15 19 11 21 17 13 15 19 17 p p p p p p p p p p p p Se Se Se Se Se Se Se Se Se Se Se Se 200 300 150 PM2.5 (µg/m3) PM10 (µg/m3) 200 100 100 50 0 0 11 13 19 21 11 13 19 21 17 17 15 15 p p p p p p p p p p p p Se Se Se Se Se Se Se Se Se Se Se Se Farm Station data 32 Air Quality Management Planning for Lagos State FIGURE 2.23.  COMPARISON OF FARM MODEL OUTPUT WITH IN SITU MEASUREMENT FOR O3, NO2, PM2.5, AND PM10 AT UNILAG STATION FOR EPISODE PERIOD OF DECEMBER 10–20, 2020 Unilag - air quality 150 100 75 100 NO2 (µg/m3) O3 (µg/m3) 50 50 25 0 0 11 13 15 17 19 21 11 13 15 17 19 21 ec ec ec ec ec ec ec ec ec ec ec ec D D D D D D D D D D D D 500 200 400 PM2.5 (µg/m3) PM10 (µg/m3) 300 150 200 100 100 50 0 0 11 13 15 17 19 21 11 13 15 17 19 21 ec ec ec ec ec ec ec ec ec ec ec ec D D D D D D D D D D D D Farm Station data Air Quality Management Planning for Lagos State 33 FIGURE 2.24.  COMPARISON OF FARM MODEL OUTPUT WITH IN SITU MEASUREMENT FOR O3, NO2, PM2.5, AND PM10 AT UNILAG STATION FOR EPISODE PERIOD OF MARCH 5–16, 2021 Unilag - air quality 125 90 100 NO2 (µg/m3) O3 (µg/m3) 60 75 50 30 25 0 0 08 10 12 06 14 16 06 08 10 12 14 16 ar ar ar ar ar ar ar ar ar ar ar ar M M M M M M M M M M M M 300 150 PM2.5 (µg/m3) PM10 (µg/m3) 200 100 100 50 0 0 08 10 12 06 14 16 06 08 10 12 14 16 ar ar ar ar ar ar ar ar ar ar ar ar M M M M M M M M M M M M Farm Station data 34 Air Quality Management Planning for Lagos State FIGURE 2.25.  COMPARISON OF FARM MODEL OUTPUT WITH IN SITU MEASUREMENT FOR O3, NO2, PM2.5, AND PM10 AT UNILAG STATION FOR EPISODE PERIOD OF APRIL 25–MAY 5, 2021 Unilag - air quality 150 100 NO2 (µg/m3) O3 (µg/m3) 100 50 50 0 0 8 0 02 04 6 8 0 02 04 6 06 06 r2 r3 r2 r2 r3 r2 ay ay ay ay ay ay Ap Ap Ap Ap Ap Ap M M M M M M 250 200 150 PM2.5 (µg/m3) PM10 (µg/m3) 150 100 100 50 50 0 0 0 02 0 02 6 8 04 06 6 8 04 06 r3 r3 r2 r2 r2 r2 ay ay ay ay ay ay Ap Ap Ap Ap Ap Ap M M M M M M Farm Station data Air Quality Management Planning for Lagos State 35 FIGURE 2.26.  COMPARISON OF FARM MODEL OUTPUT WITH IN SITU MEASUREMENT FOR O3, NO2, PM2.5, AND PM10 AT UNILAG STATION FOR EPISODE PERIOD OF JUNE 27–JULY 7, 2021 Unilag - air quality 100 150 75 NO2 (µg/m3) O3 (µg/m3) 100 50 25 50 0 0 28 30 2 4 28 30 6 2 4 6 l0 l0 l0 l0 l0 l0 n n n n Ju Ju Ju Ju Ju Ju Ju Ju Ju Ju 300 400 PM2.5 (µg/m3) PM10 (µg/m3) 200 200 100 0 0 28 30 2 4 28 30 4 6 2 6 l0 l0 l0 l0 l0 l0 n n n n Ju Ju Ju Ju Ju Ju Ju Ju Ju Ju Farm Station data 36 Air Quality Management Planning for Lagos State IPCC. 2021. “Summary for Policymakers.” In Climate REFERENCES Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergov- ARIA. 2021. Air Pollutant Emission Inventory Development, ernmental Panel on Climate Change, edited by V . Masson- Modeling and Potential Emission Control Measures for Lagos. Delmotte, P. Zhai, A. Pirani, S. L. ­ Connors, C. Péan, Final report under World Bank Technical Services S. Berger, N. Caud, et al. Cambridge U ­ niversity Press. Contract.7199005. Myhre, G., D. Shindell, F.-M. Bréon, W. Collins, EnvironQuest Limited. 2021a. Lagos Air Quality and PM J. Fuglestvedt, J. Huang, D. Koch, et al. 2013: Source Apportionment Study Final 12 Months Summary “Anthropogenic and Natural Radiative Forcing.” In Report. Final report under World Bank Technical Climate Change 2013: The Physical Science Basis. Contri- ­ Services Contract 7195720. bution of Working Group I to the Fifth Assessment Report EnvironQuest Limited. 2021b. Lagos Air Quality and PM of the Intergovernmental Panel on Climate Change, edited Source Apportionment Study Final Source Apportionment by T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, Report. Report under World Bank Technical Services S. K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex, Contract 7195720. and P.M. Midgley. Cambridge, United Kingdom: Cambridge University Press and New York: IPCC. Air Quality Management Planning for Lagos State 37 CHAPTER 3 HEALTH AND ECONOMIC IMPACTS OF AIR POLLUTION PM air pollution (PM2.5 and PM10) is the leading environmental risk factor for poor health. Globally, ambient and household air pollution together currently rank 4th for attributable disease and mortality among 20 major risk factors evaluated in the Global Burden of Disease study (GBD), following hypertension, smoking, and dietary fac- tors (GBD 2020). The estimates indicate that around 7 million deaths,5 mainly from noncommunicable diseases (NCDs), are attributable annually to the joint effects of ambient and household air pollution, with the greatest attributable disease burden seen in low- and middle-income countries (LMICs)—89 percent of the global total, with low- and lower-middle-income countries alone contributing around 40 percent of the total burden. Higher estimates have been published (Burnett et al. 2018). A recent report indicated 10.2 million premature deaths annually from fossil fuel use (Vohra et al. 2021). Regions with large anthropogenic contributions had the highest attribut- able deaths, suggesting substantial health benefits from replacing traditional fossil fuel- based energy sources (McDuffie et al. 2021). 3.1. METHODOLOGY AND EXPOSURE- RESPONSE FUNCTIONS (ERFS) FOR AIR POLLUTANTS OF CONCERN Traditionally, PM2.5 mass has been used as the index pollutant for quantifying the impact of outdoor air pollution. First, previous studies have demonstrated that mortality from long-term exposure to PM2.5 dominates the overall health impact of air pollution. Air Quality Management Planning for Lagos State 39 ­ econd, there is a vast set of published in epidemiological S 3.1.1.  METHODS: INPUT DATA FOR THE studies from around the world linking PM2.5 to mortality HIA IN LAGOS (Chen and Hoek 2020). Third, the PM2.5 effects observed in epidemiological studies are supported by toxicological Figure 3.1 illustrates the key steps in the burden calculation and human clinical studies (US EPA 2019). Fourth, PM2.5 of mortality and morbidity in Lagos due to air pollution. concentrations can be obtained from monitors and/or satellite data, while chemical transport models can gen- erate modeled data that can be used to assess the impact of emission-reduction strategies on health. Finally, PM2.5 3.1.1.1.  AIR POLLUTION DATA is ubiquitous and is generated by many fuel combustion sources in Lagos, including mobile sources (cars, buses, We have used the PM2.5 and PM10 concentrations trucks and motorcycles), stationary sources (power plants, measured during the period of the project. The con- port emissions, diesel or gasoline electrical generators, tinuous and filter-based monitored data were limited industrial boilers), biomass use, open waste burning, and to six sites in the city of Lagos for the 1-year period suspended dust. This set of factors sets PM2.5 apart from from August 2020 to July 2021. The measurements all other air pollutants. from the six monitors were used to assign an annual exposure for the population of each LGA (local gov- The health impact assessment (HIA) methodology for air ernment area) in Lagos State, where the monitors pollution is well documented. A WHO publication (WHO were located. For the LGAs without monitors, we have Regional Office for Europe 2016) provides the basic con- used the results of the dispersion modeling described cepts and general principles. Estimations of the burden of in section 2.7 to derive adjustment factors between diseases linked either to air pollution or to evaluation of the LGAs with and without monitors. These models policy scenarios and cost-benefit analyses (CBAs) are both covered five distinct episodes distributed throughout possible. Annex 1 details the methods and input data for the monitoring period. For this exercise, data from the the HIA applied in Lagos for 2020–2021. recent emission inventory were used as inputs to the FIGURE 3.1.  SCHEMATIC PRESENTATION OF THE MAIN STEPS IN THE AIR POLLUTION HIA Air pollution data modelled levelsa Population risk overall (or monitored) susceptible groups Exposure estimate Concentration-response function(s) Background data mortality rates morbidity rates Impact estimate a If modelled data are used, the approach can be used to assess the impact of emission reduction strategies on different health outcomes. 40 Air Quality Management Planning for Lagos State dispersion analysis. We first estimated a provisional are calculated assuming the same age composition in population-weighted exposure (PWE) for each LGA each LGA. Figure 3.2 illustrates the population by LGA using the results of the dispersion analysis, coupled according to the base and sensitivity case populations. with a high-resolution map of the population density distribution within each LGA, to calculate the grid- level representation of the LGA-specific PWE. We 3.1.1.3.  MORTALITY AND MORBIDITY DATA then derived the PWE for the entire Lagos State by weighting each LGA by its population size. Average ­ nternational For the estimation of the mortality data, two i annual exposures for Lagos State and each LGA were sources were consulted to derive the required informa- used in the impact assessment (Figure 3.2). tion for the base case and sensitivity case populations: the Global Health Data Exchange (GHDx) database of the GBD (IHME 2021), and the Global Health Estimates 3.1.1.2.  POPULATION DATA (GHE) database (WHO 2021). The number of deaths for each age group is calculated as the product of the Two alternative population compositions (base and sen- national hazard rate (number of deaths of a particular sitivity case population) by quinquennial age group for outcome per 100,000 population from either the GHDx Lagos State in 2018 have been used with further details or GHE database) and the age-specific population size in specified by LGA. The base case reflects the population Lagos. as estimated by the National Bureau of Statistics, and the sensitivity case reflects that estimated by the Lagos For PM2.5 (long-term exposure), the following health end- Bureau of Statistics (LBS). Estimates at the LGA level points were considered: FIGURE 3.2.  SIZE OF THE LAGOS POPULATION BY LGA ACCORDING TO THE BASE AND SENSITIVE CASE POPULATIONS 3.0 2.5 Millions of persons 2.0 1.5 1.0 0.5 0 e od o Sh olo Su lu Am Ali un Ba pa y E e eju sa ko i e Ik ja u La gos ofe ai d M d n fe e o- ho fin Ifa ekk ler Ep ay eg gr sh Oj od s M lan an hi e o Ib ti-O a uw os d do Ik La os s om da us Ag -Ij Ap ru nl or i-I lo /L go Is m K O i-I om O er Aj Sensitivity Case Base Case Air Quality Management Planning for Lagos State 41 » Mortality due to NCDs and specific GBD Desert, and it involves a large increase of particles in the ­ categories, including acute lower respiratory air, especially the coarse fraction of PM (between 2.5 and ­ infections (ALRI), ischemic heart disease (IHD), 10 µm in diameter). stroke, chronic obstructive pulmonary disease (COPD), lung cancer, and type 2 diabetes » Infant (<1 year) mortality. According to the GHDx 3.1.1.4.  EXPOSURE-RESPONSE FUNCTIONS and GHE databases, the infant mortality rate stands at 6.7 percent and 7.5 percent, respectively The ERFs from the epidemiological literature, which » Lower respiratory tract infections in children un- quantitatively relate the health risk to a PM2.5 exposure der age 5 (mainly pneumonia). The number of in- level, have been reviewed in annex 1. The epidemio- cidences per 1,000 children is 302 (95 percent con- logical studies provide an estimate of the percent change fidence interval [CI]: 160–538) and was obtained in risk that might be expected per unit change in air from the study by McAllister et al. (2019) pollution. The best approach has been to use the inte- » Chronic bronchitis incidences in adults over grated exposure-response (IER) functions developed by 27 years (3.9 cases per 1,000 individuals). These GBD (2020) for cause-specific mortality, and the expo- data were taken from Health Risk of Air Pollution sure response function (ERF) of the Global Exposure in Europe [HRAPIE] (WHO 2013) Mortality Model (GEMM) (Burnett et al. 2018) for the » Restricted activity days (19 days per year per per- noncommunicable plus ALRI diseases. For infant mor- ­ son of all ages). These data are from HRAPIE tality, we used the ERF for Africa derived by Heft-Neal (WHO 2013). Hospital admissions were subtract- et al. (2018). For the assessment of the short-term bur- ed to calculate net PM-related cases den on mortality due to the Harmattan season, we applied » Respiratory hospital admissions (RHAs) and the short-term ERF for PM10 from Orellano et al. (2020). emergency room visits, which include pneumonia, Graphical representations of the ERFs used in this work bronchitis, and asthma. The baseline statistics for are presented in annex 1. the entire Lagos State were estimated based on public hospital data, assuming that private hospi- Finally, the concentration of lead in PM2.5 and PM10 tals had a similar caseload of patients (2017 data) observed at Ikorodu LGA (1.35 μg/m3) has been found » Cardiovascular hospital admissions (CHAs) and to be particularly elevated when compared to the US emergency room visits, which consist of IHD EPA standard (0.15 μg/m3). Following the methodology including heart attacks), heart failure, and stroke. (­ in the US EPA report (1999), the air lead concentration The baseline statistics for the entire Lagos State has been converted into blood lead levels, using a conver- were estimated based on public hospital data, sion factor of 4 for children (0–6 years) and 2 for adults ­ assuming that the private hospitals had a similar (over 40 years). Based on the estimated blood lead lev- case load of patients (2017 data). els, the impact of lead exposure on children’s IQ (intel- ligence quotient) has been estimated (change in IQ equal We also estimated the impact of short-term exposure to 1.15 points per 1 µg/dl (microgram per deciliter) blood to PM10 on daily mortality during the Harmattan season. lead change; Pew Charitable Trusts, 2017, 104) as well In the specific situation of Lagos, daily population expo- as the impact of lead on adult cardiovascular mortality sure to PM10 has importance and, in some instances, it (Brown et al. 2020). Lead exposure is also implicated in does not correlate well with that of PM2.5. This happens adverse behavioral outcomes (for example, learning dis- on days when the Harmattan wind is prevalent (between abilities and disorderly conduct), but lack of local data in the end of November and mid-March). It is a dry, dusty Lagos prevented a quantitative estimation of these health wind from the North-East originating from the Sahara ­burdens. 42 Air Quality Management Planning for Lagos State 3.1.2. COUNTERFACTUAL to 5 years were estimated, together with 14,700 new cases of chronic bronchitis in adults, 46 million restricted activity CONCENTRATIONS (AND AIR days, and 1,490 hospital admissions for cardiovascular and QUALITY TARGETS) respiratory diseases. Alimosho, Ikorodu, and Oshodi are the LGAs with the greatest impact. In the HIA, a PM2.5 counterfactual concentration (the lowest level of PM below which no health effects are The estimates are double when considering the sensitiv- calculated) has been used to estimate the burden of dis- ­ ity case population: Annual mortality is 30,350 deaths ease. For the IER assessment, the counterfactual is a uni- (14,890 infant deaths), 349,000 annual cases of lower res- form distribution over the interval 2.4–5.9 μg/m3 PM2.5 piratory infections in children up to 5 years, 28,300 new used in the GBD (2020) study. A single value (2.4 µg/m3 cases of chronic bronchitis in adults, 88 million restricted PM2.5.) is applied in the case of GEMM and for infant days, and 2,840 hospital admissions. In this sensitiv- mortality. Multiple annual air quality targets have been ity calculation, the LGAs with the greatest impact were examined, such as the new WHO air quality guideline of ­ Alimosho, Mushin, Shomolo, and Oshodi. 5 µg/m3 and the WHO four interim targets (35, 25, 15, 10 µg/m3 PM2.5) to quantify the health benefits achieved Additional results are reported in annex 1, including from exposure reductions. attributable cases of premature mortality by cause of death, applying the GBD 2020 IER functions. The age- specific mortality results using baseline mortality data 3.2.  QUANTIFICATION OF from GHDx and GHE for the base case population and sensitivity case population are also reported. HEALTH ­IMPACTS 3.2.1. PM2.5 RELATED PREMATURE 3.2.2.  HARMATTAN HEALTH BURDEN  MORTALITY AND MORBIDITY Attributable mortality due to short-term exposure to Figure 3.3 shows the estimates of PM2.5 PWE by LGA. PM10 during January and February has been estimated. The overall concentration for Lagos State is 47 µg/m3 We have assumed an excess PM10 exposure equal to the and 114 µg/m3 for PM2.5 and PM10, respectively, for the difference of the average concentration for the months base case. Only a small difference has been estimated January and February and the average of the shoulder when using the sensitivity case population (46 µg/m3 and months December and March. In January and February, 116 µg/m3 for PM2.5 and PM10, respectively). The popu- the excess PM10 concentration was 88 µg/m3 PM10 for the lation living in Ikorodu, Shomolu, Mushin, and Oshodi base case population and 90 µg/m3 for the sensitivity case are exposed to particularly high values of PM2.5 ambient population, contributing a total of 250 and 500 prema- pollution (97, 85, 71, and 60 µg/m3, respectively). ture deaths, respectively. These deaths are in addition to the long-term PM2.5 -related mortality.  Figure 3.4 summarizes the results of the calculation of the PM2.5 attributable burden of mortality and morbidity in Lagos for both the base and sensitivity case populations. For 3.2.3.  HEALTH BENEFIT ANALYSIS FROM the base case, the estimated annual mortality attributable to IMPROVEMENTS IN AIR QUALITY  PM2.5 is 15,850 deaths, of which 7,790 are infant deaths, or around 50 percent of the total mortality. In total, 182,400 Figure 3.5 indicates the health benefits that could be annual cases of lower respiratory infections in children up achieved if PM2.5 concentrations across Lagos State Air Quality Management Planning for Lagos State 43 FIGURE 3.3.  LAGOS STATE AND LGA AMBIENT AIR QUALITY DATA Agege Ajeromi-Ifelodun Alimosho (ABESAN) 46 124 Amuwo-Odofin Apapa Badagry Epe Eti-Osa (NCF) 29 74 Ibeju/Lekki Ifako-Ijaye Ikeja (LASEPA) 41 106 Ikorodu (IKORODU) 97 171 Kosofe Lagos Island (JANKARA) 42 105 Lagos Mainland (UNILAG) 42 97 Mushin Ojo Oshodi-Isolo Shomolu Surulere Lagos State 47 114 0 30 60 90 120 150 180 210 PM10 PM2.5 Note: The names of the six LGAs where daily ambient concentrations were monitored during the 1-year campaign between August 2020 and July 2021 are highlighted by the gray boxes along the y-axis on the left. ­ were reduced compared to present values. Progres- 3.2.4.  IMPACT OF LEAD EXPOSURE ON sively attaining the different 2021 WHO-recom- CHILDREN’S IQ AND CARDIOVASCULAR mended interim targets for PM2.5—IT 1 (35 μg/m3), IT 2 (25 μg/m3), IT 3 (15 μg/m3), IT 4 (10 μg/m3) MORTALITY  and the WHO air quality guideline (5 μg/m3)—would The results of the impact assessment of lead contamination avert 29 percent, 46 percent, 66 percent, 77 percent, in Ikorodu based on measured air contamination (1.35 and 90 percent, respectively, of the current attribut- µg/m3 air lead) indicate that every child in Ikorodu (125,500 able premature deaths.  according to the base case and 163,800 according to the 44 Air Quality Management Planning for Lagos State FIGURE 3.4.  PM2.5 ATTRIBUTABLE MORBIDITY AND MORTALITY IN LAGOS STATE FOR PWE DATA AND GHE (WHO 2021) BASELINE MORTALITY RATES Base Case 2018 Population 4,000 3,500 Number of premature deaths 3,000 2,500 2,000 1,500 1,000 500 0 fe e Am Ali un o- sho Ap n Ba pa y E e eju sa ko ki e Ik ja u La go ofe ai d M d n od jo e Sh olo Su olu i-I geg Ep ay ler gr od s M lan an fi hi Ifa Lek e sh O Ib ti-O a d do Ik s s om da us uw o -Ij ru nl or La o lo i-I go s Is A m K O / om O er Aj Total Mortality (15,850 deaths) Infant Mortality (7,790 deaths) Lagos State Base Case 2018 Population 400,000 360,000 320,000 280,000 Number of episodes 240,000 200,000 182,400 160,000 120,000 80,000 46,000 40,000 14,700 1,250 240 0 Childhood Incidences of Restricted Respiratory Cardiovascular Pneumonia COPD in Adults Activity Days Hospital Hospital (< 5 years) (in thousands) Admissions Admissions Air Quality Management Planning for Lagos State 45 FIGURE 3.4. (Continued ) Sensitivity Case 2018 Population 4,000 3,500 Number of premature deaths 3,000 2,500 2,000 1,500 1,000 500 0 fe e Am Ali un o- sho Ap n Ba pa y E e eju sa ko ki e eja u La go ofe ai d M d e n od jo Sh olo Su olu Ep ay ler i-I geg gr od s M lan an fi hi Ifa Lek sh O Ib ti-O a d do Ik s s om da us uw o -Ij ru nl or La o lo i-I go s Is A m K O / Ik om O er Aj Total Mortality (30,350 deaths) Infant Mortality (14,890 deaths) Lagos State Sensitivity Case 2018 Population 400,000 360,000 349,000 320,000 280,000 Number of episodes 240,000 200,000 160,000 120,000 88,000 80,000 40,000 28,300 2,380 460 0 Childhood Incidences of Restricted Respiratory Cardiovascular Pneumonia COPD in Adults Activity Days Hospital Hospital (< 5 years) (in thousands) Admissions Admissions 46 Air Quality Management Planning for Lagos State FIGURE 3.5.  HEALTH BENEFITS FOR A REDUCTION IN AMBIENT AIR POLLUTION ACROSS LAGOS STATE 0 –10 % change compared to current burden –20 –23% –30 –38% –36% (IT#1) –40 –50 –55% (IT#2) –57% –60 –69% –70 –75% (IT#3) –80 –84% –86% (IT#4) –90 –95% (WHO AQG 2021) –100% –100 0 5 10 15 20 25 30 35 40 45 50 Rollback (Reduction) in ambient air PM2.5 concentration, µg/m3 18,000 15,852 (–100%) 16,000 14,000 IT #4 12,239 (–77%) WHO AQG Averted Premature Deaths 12,000 2021 14,279 (–90%) 10,000 IT #2 IT #3 8,000 7,307 (–46%) 10,477 (–66%) IT #1 6,000 4,533 (–29%) 4,000 2,000 0 5 10 15 20 25 30 35 40 45 50 Rollback (Reduction) in ambient air PM2.5 concentration, µg/m3 Infant mortality Adult mortality (25+) Mortality (all ages) Morbidity episodes (all ages) Note: The top figure shows the relative mortality and morbidity reduction compared to the current state, while the figure below shows the averted deaths for the base case population and applying the WHO GHE baseline mortality rates. Air Quality Management Planning for Lagos State 47 TABLE 3.1.  VALUE OF MORBIDITY (SENSITIVITY CASE POPULATION) Childhood Onset chronic Restricted activity Hospital admissions pneumonia (Under 5) bronchitis (adult 27+) days (all ages) (all ages) Total Number of incidences 348,900 28,280 87.61 million 2,840 Value (US$, millions) 87.2 109.0 674.6 0.4 871 Share of GDP (2018) - % 0.121 0.151 0.94 0.001 1.2 Note: Childhood pneumonia is valued at five times the daily wage assuming the illness lasts for one week, during which time a parent or guardian remains home. Onset chronic bronchitis assumes EUR 68,000 per case transferred to Lagos using the benefit-transfer method of US$3,855 per incident. Restricted activity days are valued at an average cost of $7.7 per day. Hospital admissions are valued at between N30,000 and N100,000, or an average of US$158 per hospital admission. sensitivity population) is significantly affected by lead expo- cost. In this study, mortality values accounted for more sure. The calculated loss of intelligence by each child is 6.21 than 85 percent of the total health impacts using the VSL IQ points, which represents a huge physical burden on the (value of a statistical life) method for valuing the loss of current generation and potentially a significant loss of future human life. income. The total loss in IQ points is 780,000 and 1,017,000 for the base case and sensitivity case population, respectively. Additionally, the impact of lead on cardiovascular mortality 3.3.1.  LEAD IMPACTS in adults is remarkably high; the attributable premature mortality is 285 and 373 deaths for the base case and sensi- Lead exposure in children has been found to be associ- tivity case populations, respectively. ated with additional medical costs as well as impacts on cognitive development, which in turn can affect earn- ings later in life. Recent studies in the US have estimated 3.3. VALUATION OF HEALTH that the value of a reduction in IQ on earnings can IMPACTS amount to US$12,000–17,500 per IQ point lost (Zhou and Grosse 2019). Based on the measurements of lead exposure in Ikorodu, the impacts amount to US$318 million–464 ­ million in the base case (780,000 IQ points The financial value of the air pollution health impacts lost) and US$416 million–606 million in the sensitivity has been estimated to be between 1.0 and 6.9 percent of case (1,017,000 IQ points lost). Additionally, adult deaths the GDP of Lagos State (Table 3.2). The wide range in associated with lead exposure are valued at US$47 mil- value is due to (a) the difference in the total population lion–61 million using the VSL method. exposed to air pollution, reflected in the base case and sensitivity case population estimates for Lagos State, and (b) different methodologies for valuing loss of human life. 3.3.2.  VALUE OF STATISTICAL LIFE (VSL) Health impacts include both morbidity and mortality due to air pollution. The value of morbidity includes things Valuing the loss of human life, not surprisingly, can be a such as hospital costs, medications, and lost wages from controversial topic. Here, two methods have been used. patients or caregivers during the illness. As in other stud- The first, the VSL method, attempts to provide a value by ies, the estimated cost of mortality dwarfs the morbidity society of preventing a fatality of an anonymous  ­person. 48 Air Quality Management Planning for Lagos State The VSL is society’s willingness to pay to reduce the mar- of Lagos’ 2018 GDP. The value of reducing air pollu- ginal risk of mortality. This can be observed in the mar- tion from current levels of average of 45 μg/m3 to ket, for example, through wage-risk studies or contingent 10 μg/m3 is estimated to be between US$0.55 billion valuation studies. For this study, the value of a statistical and US$3.8 billion, or between 0.76 and 5.3 percent life has been estimated as US$164,000 (2018) per prema- of GDP (Table 3.3). ture mortality.6 3.4.  DISCUSSION AND 3.3.3.  HUMAN CAPITAL CONCLUSIONS APPROACH (HCA) The HCA values life as the productivity or lifetime These health impact estimates show that air pollution income that is lost due to premature mortality. Because from PM2.5 poses a serious public health hazard, espe- lost productivity is age-specific, the HCA value will be cially among children younger than 5. The PWE is high, different depending on the age when the life was lost. reaching 47 µg/m3, a value nearly 10 times higher than The average wage used for the HCA calculations was the new recommended WHO air quality guideline of 5 US$10,000 per year (2018), multiplied by the aver- µg/m3 (WHO 2021). Urgent action to reach at least the age years lost, with the total discounted over time at WHO IT 1 (35 µg/m3) is therefore recommended. The 3 ­percent. overall impact of the present PM2.5 levels on mortality across all the age groups is responsible for between 15,850 Using the same VSL and HCA methodologies, it is and 30,350 premature deaths per year, with the largest possible to estimate the benefits of lowering ambient contribution related to infant mortality (between 7,790 air pollution levels to the WHO interim targets. and 14,890 infant deaths). For adult mortality, the impact Table 3.2 shows the reductions in mortality (both total is largest for cardiovascular diseases. The impact on mor- and infant), along with the value, expressed as a share bidity, especially pneumonia and other acute respiratory TABLE 3.2.  VALUATION OF MORTALITY DUE TO AIR POLLUTION IN LAGOS Air Pollution Mortality Value of Statistical Life Human Capital Lagos Total Attributable Mortality Value of Share of Human Capital Share of Population (all ages) Mortality (VSL= GDP (%) Approach (annual GDP (%) Scenarios USD 164,000) wage = USD10,000) (b (b USD) USD) Base Case 15,850 $2.6 b 3.6% $0.7 b 1.0% Population (13.3 m) Sensitivity 30,350 $5.0 b 6.9% $1.4 b 1.9% Case (25.6m) Air Quality Management Planning for Lagos State 49 TABLE 3.3.  VALUE OF LOWERING AIR POLLUTION TO WHO INTERIM TARGETS Air Pollution Reduction Scenarios Air Quality Target*0 35 ug/m3 25 ug/m3 15 ug/m3 10 ug/m3 Reduction in PM2.5 –10.0 –20.0 –30.0 –35.0 Reduction in Total Mortality 4,533–8,316 7,307–13,747 10,477–19,969 12,239–23,370 Benefit of Reduced Mortality (VSL) mUS$ $734–$1,364 $1,198–$2,255 $1,718–$3,275 $2,007–$3,833 Share of GDP (2018) 1.03–1.89% 1.66–3.13% 2.39–4.55% 2.79–5.32% Benefit of Reduced Mortality – Human $202–$371 $326–$613 $467–$890 $546–$1,042 Capital Approach (HCA) mUS$ Share of GDP (2018) 0.28–0.51% 0.45–0.85% 0.65–1.24% 0.76–1.45% conditions in children 0–5 years (between 182,400 and The exposure assessment is one of the most important 349,000 incidences), is particularly worrisome. Other aspects of the study; it is based on an extensive monitoring outcomes were also estimated and they contribute to program of ambient air pollution that has been set up in increasing the overall burden. several locations with standardized procedures and qual- ity controls. The results of the monitoring program have Two additional critical contributions should be added been coupled with the results of a dispersion model and to the estimated loss of life from long-term exposure to with population data to estimate ­ population-weighted PM2.5: (a) the impact of the daily high levels of PM10 dur- exposures (PWEs) at the LGA level. In this way, the con- ing the Harmattan period and (b) industrial air pollution centration values are referred to the population, which is in Ikorodu with the relevant lead contamination, which the target of the HIA. We have considered a variety of accounts for a sizable loss of intellectual capabilities in possible outcomes, encompassing both mortality (natural children (a total of 780,000 to 1 million IQ points lost mortality, which excludes accidental deaths, and cause- at the population level), and a high attributable cardio- specific mortality) and several morbidity outcomes. We vascular mortality in that particular LGA (285 to 373 have addressed not only PM2.5 but also the complemen- premature cardiovascular deaths). The quantified health tary contributions of daily levels of PM10, mainly attrib- burdens should be interpreted as conservative estimates utable to episodes of Harmattan desert dust, and the lead because the additional impact from direct exposure to contamination in Ikorodu. Children are the segment of other critical pollutants (for example, gaseous air pollut- the population most affected by air pollution: they suf- ants such as NO2 and SO2) has not been quantified in fer from extraordinarily high infant mortality, experience this work. A preliminary estimate of the potential burden frequent episodes of pneumonia and other respiratory on mortality from direct exposure to NO2, for example, disorders, and have to cope with a large limitation of could add another 10 percent to the PM2.5 total mortal- their intellectual capability. It is irreversible damage to ity. However, the adverse health effects from exposure to the next generation. Finally, we have considered several secondary inorganic aerosols (a component of PM) cre- methodological aspects in our assessment (exposure esti- ated through chemical transformation of NO2 and SO2 mation, choice of the ERFs, alternative demographic precursor emissions are already incorporated in the main assumptions) to overcome the main limitations described PM2.5 impact assessment. below. 50 Air Quality Management Planning for Lagos State The HIA for Lagos refers to the most recent period of tions (the public sector) register mortality and morbidity ambient air pollution monitoring—August 2020 to July statistics, and a large fraction of health care providers do 2021. This is the period with the most accurate measure- not release regular information. This difficulty is coupled ment of air pollution. The other data for the HIA refer with the traditional lack of medical certification for per- to a preceding period (that is, 2018 population data and sons dying at home. We have used two sources of mor- available health statistics for 2017 and 2018). We believe tality information related to Nigeria (GBD and WHO) that the error induced by this choice is minimal because and have scaled down to Lagos, accounting for the dif- the recent mortality rate has trended lower over the past ferences between national and local age distribution. For decade, although population growth has been observed hospitalizations, we have used the registrations of the at the same time. The net effect is that our estimates events in the public sector with the strong assumption are on the conservative side. In addition, it should be that the ­ private sector has a proportionally similar load noted that the measurement period occurred during the of patients. Finally, it is clear that a source-specific HIA COVID-19 pandemic. The pandemic has affected Africa was not performed because a clear partition of PM2.5 including Nigeria, with a decrease in economic activity exposure data was not available. as reflected by the change in the internal gross product, a 3.5 percent drop in 2020 at the national level compared Presently, there is still limited experience with HIAs of to the previous year when there was no COVID-19. air pollution in Africa. Among the few extant studies, This aspect makes our assessment for 2020–2021 some- we cite the HIA study in Cairo, Egypt (Wheida et al. how conservative in comparison to the air pollution data 2018); in Addis Ababa, Ethiopia (Kumie et al. 2021); probably experienced in past years. and in Accra (Garcia et al. 2021; Kanhai et al. 2021). In 2020, Croitoru, Chang, and Akpokodje published The most relevant uncertainty regarding our work stems the first HIA of the burden of fine particulate matter from the difficulty of estimating the population at risk. Two in Lagos State. According to this study, in 2018, there different sources have been considered in this work because were 11,200 premature deaths attributed to exposure to they provide potential extremes of the population size esti- PM2.5 air pollution. The mortality was quantified using mate. Assumptions about age distribution across different the 2017 version of the cause-specific IER functions LGAs, often driven by operational choices, are another developed by GBD (2018). In Table 3.4, we compare source of uncertainty. The difficulties in such estimations the mortality rates (annual deaths per 100,000 popula- stem from the large size of slum settlements that are a tion) calculated in this work against the estimates pub- prominent feature of the urban landscape of Sub-Saharan lished by Croitoru, Chang, and Akpokodje (2020). Our Africa, and from the dynamic nature of this population cause-specific mortality results are based on the 2019 (Amegah 2021; Thomson et al. 2021). We are confident that IER functions (GBD 2020). our sensitivity choices, though imperfect and leading to a wide spread in the estimates, are the best approach to char- We also provide results based on the relationships of acterizing the size of the Lagos population. Heft-Neal et al. (2018) for infant mortality and GEMM (Burnett et al. 2018) for deaths in the broader category of Another concern about the estimates relates to the NCDs. The baseline mortality was estimated using the absence of reliable baseline health data for the entire WHO GHE hazard rates. As can be seen, our mortality population. The value of good-quality mortality data rates are consistent with the results of Croitoru, Chang, for public health is widely acknowledged. While effective and Akpokodje, when assuming the same PM2.5 exposure civil registration systems remain the gold-standard source (68 μg/m3) and using the same impact risk model (GBD for continuous mortality measurement, in most African IER), but our mortality estimates increase by a factor of countries fewer than 25 percent of deaths are registered, 2.5 when switching from the IER model to the GEMM and it appears to be the same in Lagos (Joubert et al. and Heft-Neal et al. relationships. The higher premature 2012). In addition, only a fraction of the hospital institu- mortality estimate can be explained in part due to the size Air Quality Management Planning for Lagos State 51 TABLE 3.4.  COMPARISON OF CURRENT ESTIMATES OF PM2.5 MORTALITY RATES IN LAGOS STATE AND PREVIOUS WORK BY CROITORU, CHANG AND KELLY (2020) Risk model Croitoru, Chang, and Akpokodje (2020) This study IER functions for deaths due to PM2.5 concentration: 47 μg/m3 based on cardiovascular and respiratory plus 1-year, 2020–21, measuring campaign 2019 lung cancer and diabetes IER functions (GBD 2020) Base case population: 13.3 million Mortality rate (per 105): 38.5 Sensitivity population: 25.6 million Mortality rate (per 105): 37.0 IER functions for deaths due to PM2.5 concentration: 68 μg/m3 Population PM2.5 concentration: 68 μg/m3, same as cardiovascular and respiratory plus size: 24.4 million Croitoru, Chang, and Akpokodje (2020) lung cancer and diabetes 2017 IER functions (GBD 2018) Mortality 2019 IER functions (GBD 2020) rate (per 105): 45.9 Base case population: 13.3 million Mortality rate (per 105): 47.0 Sensitivity population: 25.6 million Mortality rate (per 105): 45.5 GEMM for NCD and lower respiratory PM2.5 concentration: 47 μg/m3 based on illnesses plus Heft-Neal et al. 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Hoek. 2020. “Long-Term Exposure to Kumie, A., A. Worku, Z. Tazu, W. Tefera, A. Asfaw, PM and All-Cause and Cause-Specific Mortality: G. Boja, M. Mekashu, et al. 2021. “Fine Particulate A Systematic Review and Meta-Analysis.” Environ Int Pollution Concentration in Addis Ababa Exceeds the 143:105974. doi:10.1016/j.envint.2020.105974. WHO Guideline Value: Results of 3 Years of Con- Croitoru, L., J. C. Chang, and J. Akpokodje. 2020. “The tinuous Monitoring and Health Impact ­ Assessment.” Health Cost of Ambient Air Pollution in Lagos.” Environ Epidemiol 5 (3): e155. doi:10.1097/EE9​ Journal of Environmental Protection 11:753–765. https:// .0000000000000155. doi.org/10.4236/jep.2020.119046. McAllister, D. A., L. Liu, T. Shi, Y. Chu, C. Reed, Garcia, L., R. Johnson, A. Johnson, A. Abbas, R. Goel, Burrows, D. Adeloye, and Rudan, I. 2019. “Global, J. ­ L. Tatah, J. Damsere-Derry, et al. 2021. “Health Regional, and National Estimates of Pneumo- Impacts of Changes in Travel Patterns in Greater nia Morbidity and Mortality in Children Younger Accra Metropolitan Area, Ghana.” Environ Int than 5 Years between 2000 and 2015: A System- 155:106680. doi:10.1016/j.envint.2021.106680. atic ­Analysis.” Lancet Global Health 7:e47–57. http:// GBD 2019 Risk Factors Collaborators. 2020. “Global dx.doi​.org/10.1016/S2214-109X(18)30408-X. Burden of 87 Risk Factors in 204 Countries and McDuffie, E. E., R. V. Martin, J. V. Spadaro, R. ­Burnett, Territories, 1990–2019: A Systematic Analysis S. J. Smith, P. O’Rourke, M. S. Hammer, et al. 2021. for the Global Burden of Disease Study 2019.” “Source Sector and Fuel Contributions to Ambient Lancet 396(10258): 1223–49. doi:10.1016/s0140​ PM(2.5) and Attributable Mortality Across Multiple -6736(20)30752-2. Spatial Scales.” Nat Commun 12(1): 3594. doi:10.1038​ GBD 2017 Risk Factor Collaborators. 2018. “Global, /s41467-021-23853-y. Regional, and National Comparative Risk Assess- Orellano P, Reynoso J, Quaranta N, Bardach A, ment of 84 Behavioural, Environmental and Occu- ­ Ciapponi A. 2020. “Short-term exposure to par- pational, and Metabolic Risks or Clusters of Risks ticulate ­matter (PM10 and PM2.5), nitrogen dioxide for 195 Countries and Territories, 1990-2017: A Sys- (NO2), and ozone (O3) and all-cause and cause- tematic Analysis for the Global Burden of Disease specific ­mortality: ­ Systematic review and meta- Study.” Lancet 392: 1923–1994. analysis.” Environ Int. 142: 105876. doi: 10.1016/j​ IHME. 2021. Global Health Data Exchange (GHDx, .envint.2020.105876. IHME). http://ghdx.healthdata.org/gbd-results-tool. Thomson, D. R., A. E. Gaughan, F. R. Stevens, Heft-Neal, S., J. Burney, E. Bendavid, and M. Burke. G. ­ Yetman, P. Elias, and R. Chen. 2021. “Evaluat- 2018. “Robust Relationship between Air Quality Accuracy of Gridded Population Estimates in ing the ­ and Infant Mortality in Africa.” Nature 559 (7713): Slums: A Case Study in Nigeria and Kenya.” Urban Sci. 254–258. doi:10.1038/s41586-018-0263-3. 5:48. https://doi.org/10.3390/urbansci5020048. Joubert, J., C. Rao, D. Bradshaw, R. E. Dorrington, US EPA. 1999. “Implementer’s Guide to Phasing Out T. Vos, and A. D. Lopez. 2012. “Characteristics, Lead in Gasoline.” Availability and Uses of Vital Registration and Other US EPA. 2019. “Integrated Science Assessment for Mortality Data Sources in Post-Democracy South Particulate Matter.” EPA/600/R-19/188. U.S. ­ Africa.” Glob Health Action 5: 1–19. doi:10.3402/gha. ­ Environment Protection Agency, Research Triangle v5i0.19263. Park 2019. Air Quality Management Planning for Lagos State 53 Vohra, K., A. Vodonos, J. Schwartz, E. A. Marais, M. P. Sul- WHO. 2021. Global Health Estimates (GHE, WHO). prizio, and L. J. Mickley. 2021. “Global Mortality from https://www.who.int/data/gho/data/themes​ /­m Outdoor Fine Particle Pollution Generated by Fossil ortality-and-global-health-estimates/ghe-leading​ Fuel Combustion: Results from GEOS-Chem.” Environ -causes-of-death. Res 195: 110754. doi:10.1016/j​ .envres.2021.110754. WHO Regional Office for Europe. 2016. Health Risk Wheida, A., A. Nasser, M. El Nazer, A. Borbon, G. A. Assessment of Air Pollution – General Principles. Copenha- Abo El Ata, M. Abdel Wahab, and S. C. Alfaro. 2018. gen: WHO Regional Office for Europe. “Tackling the Mortality from Long-Term Exposure World Bank and Institute for Health Metrics and Evalu- to Outdoor Air Pollution in Megacities: Lessons ation (2016). The Cost of Air Pollution. World Bank, from the Greater Cairo Case Study.” Environ Res Washington DC. 160: 223–231. doi:10.1016/j​ .envres.2017.09.028. Zhou, Y., and S. D. Grosse. 2019. “Valuing the Benefits ­ RAPIE WHO. 2013. Health Risks of Air Pollution in Europe — H of Reducing Childhood Lead Exposure – Human Project. Recommendations for Concentration–Response Func- Capital, Parental Preferences, or Both? Centers for tions for Cost–Benefit Analysis of Particulate Matter, Ozone Disease Control and Prevention (CDC).” Prepared and Nitrogen Dioxide. Copenhagen, Denmark: WHO. for workshop at Harvard Center for Risk Analysis, WHO. 2021. WHO Global Air Quality Guidelines. Particulate September 26–27, 2019. https://cdn1.sph.harvard. matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur edu/wp-content/uploads/sites/1273/2019/09​ Dioxide and Carbon Monoxide.” https://apps.who.int​ /­Zhou-Grosse-2019.pdf. /­iris/handle/10665/345329. 54 Air Quality Management Planning for Lagos State CHAPTER 4 POTENTIAL EMISSION CONTROL MEASURES In considering potential air pollution control measures, policy makers should consider both the cost to the Government and the overall economic costs and benefits, as well as the implications for other social goals. At COP26, Nigeria committed to achieving net-zero GHG emissions by 2060, and the Climate Action Plan of the Lagos State Government (LASG) calls for net zero by 2050. Thus, any pollution control measures adopted should be consistent with a transition away from fossil fuels. Other social goals to consider include reducing road transport and traffic congestion, with its wastage of time and resources, and reducing pollution of land and water as well as the air. 4.1. POLLUTION CONTROL STRATEGIES BY SECTOR As explained in chapter 2, the PMEH source apportionment study showed that about 28 to 32 percent of ambient PM2.5 is due to open burning, mostly burning of solid waste. Industrial emissions account for about 18 percent on average, though this var- ies greatly from one location to another. Diesel and gasoline engines used in transport and backup generators account for another 14 to 17 percent. Together, these readily controllable sources of primary PM emissions account for 60 to 67 percent of the PM2.5 in the air. Another 28 to 32 percent of PM2.5 and 48 to 50 percent of PM10 is suspended dust, some of which has natural causes such as the Harmattan but much of which is human-generated and therefore controllable. The remaining 15 percent or so comprises sulfates, nitrates, and organic aerosol formed from SOx, NOx, and VOC, respectively, through chemical reactions in the atmosphere. This secondary PM2.5 can be controlled by reducing emissions of the reactant species. Air Quality Management Planning for Lagos State 55 4.1.1.  SOLID WASTE Another potential destination for solid waste is incin- eration and the production of energy. While generally Open burning of municipal solid waste (MSW) is esti- the costliest method of disposing solid waste, incinera- mated to account for as much as 30 percent of the PM2.5 tors can reduce the overall volume of solid waste and present in the air. Present solid waste production in Lagos produce electricity, which can be sold or used by waste is estimated at 4.2 million tons per year, of which only management facilities. A project currently under discus- about 1.8 million is collected and disposed at one of sion in Lagos is the establishment of a waste-to-energy four active dumpsites. Waste pickers scavenge for usable plant that would convert MSW to electricity (Omorogbe items, mainly metal and plastics, and the remainder of 2021).8 Aside from investment costs, the main drawback the waste, much of it organic, is left to decompose. There of incineration is that most of the combustible solid is a well-developed market for recycled materials (Salau waste in Lagos is potentially recyclable—such as paper et al. 2017). Most of the waste that is not collected is and plastics—or is organic matter that is not returned believed to be burned, and some burning also goes on at to the soil. dumpsites. Organic matter, which is estimated to be about half of To eliminate the open burning of solid waste would the total MSW in Lagos (LAWMA 2014), has the poten- require a substantial improvement in collection efficiency, tial to be composted and turned into fertilizer or a soil together with improved enforcement of regulations on additive. Because the separation of organic wastes can be waste disposal and open burning. The LASG is already costly, some municipalities have begun their composting taking steps in this direction, with the planned acquisition programs by targeting large sources of organic wastes, of another 100 collection trucks in 2021 and the planned such as produce markets, grocery stores, and restaurants. establishment of 20 transfer-loading stations and several Compost can also be an important product for urban material recovery facilities by 2030. gardens and municipal landscaping. Cities around the world are increasingly providing collection services for Plans are also being developed to replace the existing organic waste, such as bins for households, buildings, or dumpsites with modern landfills. Modern landfills are neighborhoods, as well as trucks and infrastructure for built to capture CH4 produced from decomposing organic transport and processing in large-scale compost facili- matter. CH4 captured can be used to generate electricity ties. Because organic waste is the raw material for CH4 or supplied to other energy users as fuel. Because CH4 is production in a landfill, reducing the amount of organic a powerful GHG,7 landfills can earn carbon credits by matter through composting can limit the amount of mitigating the release of CH4. CH4 released into the atmosphere. Composting pro- grams can thus earn carbon credits by diverting organic Government policies can help minimize the amount matter that would otherwise have resulted in the produc- of waste to be landfilled by encouraging the separation tion of CH4. The EarthCare program in Lagos had an of solid waste to facilitate recycling and composting. estimated CO2 reduction of 253,000 tons per year over Organic waste, for instance, needs to be separated so a 10-year period, for which it could earn carbon credits that it does not contaminate recyclables such as paper (World Bank 2010). and cardboard. Neighborhood collection sites that allow plastics, metals, and glass to be separated could enhance the feasibility of recycling by reducing the cost 4.1.2.  FUEL QUALITY of collection and ensuring a higher-quality recycled product. Collection fees for solid waste, if built into the Fuel “quality” is best understood as compliance with fee structure of essential urban services such as water, the specifications for that type of fuel. From the stand- could help cover the costs of collecting and disposing of point of air quality, the most important specification for solid waste. both diesel and gasoline is the allowable sulfur content. 56 Air Quality Management Planning for Lagos State Most of the sulfur present in motor fuel burns to form vehicles imported from developed countries to retain the SO2 in the exhaust; this is the main source of SO2 emis- particle filters with which they come equipped, as well sion in Lagos. A few percent of the sulfur is emitted in as allow the operation of new vehicles meeting Euro 4 the form of sulfate particles, and these can increase die- or better emission standards (Table 4.1).9 This would sel PM emissions significantly. Some of the SO2 emitted also permit the use of particle filters and other advanced to the atmosphere reacts to form sulfate particles as well. emission controls on backup generators. SO2 in the exhaust also binds to the catalyst materials Nigeria presently has no operational petroleum refiner- used in catalytic converters and diesel particulate filters, ies, except for some small illegal operations in the Niger reducing their efficiency. Diesel oxidation catalysts can delta. The Nigerian National Petroleum Corporation also oxidize SO2 to SO3, which combines with water (NNPC) is the only legal importer of refined products, vapor in the exhaust to form sulfuric acid. Operating but smuggling is thought to be widespread. The new an engine on high-sulfur fuel can clog diesel particulate Dangote refinery10 now under construction will have filters; for this reason, fuel sulfur limits are needed for more than enough capacity to supply Nigeria’s needs adequate emissions control for diesel engines. The US, and has been designed to produce ultra-low sulfur diesel European Union (EU), and many other countries have and gasoline (Euro 5–6 specifications). Until that refinery set ultra-low fuel sulfur limits of 10 to 15 ppm (by weight) comes online, all legal refined petroleum products used for distillate fuels. in Lagos will continue to be purchased on the world mar- ket and imported by ship. Gasoline and diesel fuel meet- Diesel fuel samples collected at Lagos retail stations in 2020 ing low or ultra-low sulfur specifications are available on averaged 2,389 ppm sulfur: for gasoline, 1,424 ppm. New the world market. Thus, to begin enforcing the 2017 or fuel standards allowing 150 ppm sulfur for gasoline and ECOWAS fuel sulfur limits would be relatively simple— 50 ppm for diesel were set to be introduced in N ­ igeria in NNPC would need to change its purchase specifications 2017 but have not yet been implemented. Nigeria is also and contract to buy fuel meeting the sulfur standards. signatory to the agreement of the E ­ conomic ­ Commission of West African States (ECOWAS) to limit sulfur to The new fuel standards would need to be enforced 50 ppm in both diesel and gasoline. By implement- through collection and analysis of fuel samples both at ing and enforcing these standards, the Nigerian and/or dockside and in the retail stations. Sulfur removal adds to Lagos State Government would make it feasible for used the fuel cost, so shippers would be tempted to s ­ ubstitute TABLE 4.1.  EUROPEAN DIESEL AND GASOLINE STANDARDS AND EMISSIONS European diesel (AGO) and gasoline (PMS) standards and emissions Implementation Sulfur limit Sulfur limit Standard date (Europe) AGO (ppm) Emissions (g/km) PMS (ppm) Emissions (g/km) Euro 1 1994 2,000 0.14 2,000 0.09 Euro 2 1996 500 0.08 500 0.01 Euro 3 2000 350 0.05 150 0.01 Euro 4 2005 50 0.025 50 0.01 Euro 5 2009 10 0.005 10 0.005 Source: Transportpolicy.net. https://www.sciencedirect.com/science/article/pii/S259019822030083X Air Quality Management Planning for Lagos State 57 high-sulfur for low-sulfur products if there were no dan- fuels but not for industrial fuels, there could be leakage ger of being detected. Similarly, the higher cost of low- or cases of misfueling where vehicle owners end up put- sulfur fuel would increase the incentives for smuggling ting cheaper and dirtier fuels in their vehicles. Requiring and adulteration at the retail level. that all petroleum products in Lagos meet higher qual- ity standards will reduce misfueling and thus contribute Improved fuel quality would help lower PM2.5 emissions, to lowering emissions from the transport sector, industry, primarily through the introduction of more sophisti- and backup electricity generators used throughout Lagos cated emissions control systems on vehicles, especially State and Nigeria. advanced catalytic converters and diesel particulate filters. The current fuel quality in Nigeria does not allow the effective operation of vehicle catalysts beyond 4.1.3.  ROAD TRANSPORT Euro 1, standards that were implemented in Europe in the early 1990s. Properly functioning Euro 5 vehicles The road transport sector accounts for about 10 per- can lower emissions of PM2.5 by 28 times compared to cent of primary PM2.5 emissions in Lagos and is also Euro 1. To guard against fuel adulteration and protect a main source of NOx and SO2, which react to form the emissions control equipment on vehicles, it is nec- secondary PM2.5. It is also the second-largest source of essary to ensure that fuel quality at fueling stations is GHG emissions. Given its importance to the economy—­ maintained (box 4.1). moving people and goods—and the fact that it will cer- tainly grow, effective air pollution control measures To the extent that the same quality of petroleum products for this sector will be essential to sustainable growth. is available to all consumers in Lagos, requiring that they Equally, appropriate technology choices will be needed all meet higher fuel specifications will reduce emissions. for the government to meet its target of net-zero GHG Conversely, if fuel standards are tightened for transport emissions by 2050. BOX 4.1.  MEASURES TO ENSURE FUEL QUALITY Tamper-proof locks. Products are supplied to retail outlets in modified tank lorries fitted with tamper-proof locks. Comprehensive sealing. Dispensing units are sealed in a comprehensive manner, which makes meter tampering impossible. Periodic and surprise checks by staff. Stringent, periodic, surprise checks are carried out to ascertain correct delivery and the sealing of the pumps. Testing of product samples. Regular comprehensive testing of samples is done without prior warning. Certification of retail outlets. Periodic audits and recertification of retail outlets are carried out by a reputable certification agency. Source: Rogers 2002 as quoted in Gwilliam, Kojima, and Johnson 2004. Note: Based on practices of Bharat Petroleum, India. 58 Air Quality Management Planning for Lagos State 4.1.3.1.  GLOBAL WARMING substantial benefits for the sake of both air quality and climate change priorities. The Nigerian Government has committed to achieving net-zero GHG emissions by 2060. Achieving net-zero emissions in the road transport sector will require a mas- 4.1.3.2.  VEHICLE EMISSION STANDARDS sive shift away from fossil fuels and toward more sustain- able technologies. Planning to accommodate this shift The most effective and least costly way to reduce ­ vehicle is needed now, as infrastructure commissioned today is emissions is to require new vehicles to comply with emis- quite likely to be in use in 2060. Thus, shifting to another sions standards. Incorporating emission ­ controls into the fossil fuel, even a “clean” fuel such as natural gas, would vehicle design from the beginning is much less costly than be contraindicated. to retrofit them. The main drawback is that the vehicle fleet turns over slowly, so the full benefit of new emission Througout most of the world, battery electric vehicles standards is not seen for more than a decade. In specific (BEVs) are now the clear favorites to replace internal cases such as drayage trucks and public transport vehi- combustion engines that burn fossil fuels. BEVs make up cles, it may be cost-effective to accelerate fleet turnover a significant and increasing fraction of the new vehicle by mandating s ­ pecific emission standards. fleet in Europe, China, and North America. BEVs are most effective where vehicle range requirements are fairly Most vehicles in Nigeria were originally sold in Europe short, such as private automobiles, city buses, drayage or North America and are imported into Nigeria as used and delivery trucks, and taxicabs. Where long range is upon reaching the end of their economic life in their important, as in long-haul trucking and air travel, liquid country of origin. This has the advantage that the vehi- fuels such as biodiesel and renewable (synthetic) diesel cles are likely equipped with advanced emission control and jet fuel may continue to have a role. systems, but the disadvantage that those systems may be in poor condition. At present, the importers typically To be practical in Nigeria, BEVs will require a reliable, remove the catalytic converters and/or particulate filters low-cost source of electricity for charging, which cur- before reselling the vehicles. rently excludes Nigeria’s electric grid. Substantial invest- ment will be required in electric generation and charging Nigeria has joined in the decision of the ECOWAS11 to infrastructure. This is discussed in the section on electric- require all newly registered vehicles, both new and used, ity generation, below. In the meantime, hybrid vehicles— to meet Euro 4 emission standards and for the sulfur especially plug-in hybrids—have much to recommend content of vehicle fuels to be limited to 50 ppm (UNEP them. This is especially true in stop-and-go traffic, where 2020). Imported vehicles are also subject to age limits of the use of regenerative braking both saves energy and 5 years for light-duty vehicles and 10 years for heavy- reduces brake wear. By charging from the power grid duty vehicles. Meeting the Euro 4 standards requires that when it is available and from their onboard engine when diesel engines be equipped with a particulate filter, and not, plug-in hybrids could provide reliable service in the gasoline engines with a three-way catalytic converter and near term while retaining the ability to switch to all-­ electronic engine controls. These standards would not be electric operation in the future. feasible without the fuel sulfur limit because sulfur poi- sons the catalysts used, reducing their effectiveness. So Of course, for BEVs to reach net-zero GHG emissions, far, the 50 ppm sulfur limit has not been implemented in the charging electricity will need to come from renew- Nigeria, and it does not appear that the Euro 4 require- able sources such as solar photovoltaics and wind. Until ment is being enforced. those renewable electricity sources are available, how- ever, a plug-in hybrid or BEV charged by (for example) a The requirement that a vehicle meets Euro 4 or equiv- combined cycle natural gas power plant would still have alent North American emission standards should be Air Quality Management Planning for Lagos State 59 implemented as soon as possible. For new vehicles, the being able to monitor and enforce vehicle emission regu- manufacturer’s certificate of compliance can generally lations. Currently, the program requires private vehicles be relied on, though occasional spot-checks are recom- to be inspected for emissions and roadworthiness once a mended to keep the manufacturers honest. For used year, and commercial vehicles every 6 months. Vehicles vehicles, the vehicle should at least be inspected to ensure are required to display their roadworthiness certificates that it retains all its emission control equipment and on the vehicle or face a fine. should preferably be subjected to emission measurements under load to verify that the system remains functional. As vehicle emission controls are phased in, LACVIS will This would require test facilities equipped with chassis need to be strengthened to maintain its effectiveness. This dynamometers and appropriate emission analyzers. This should include upgraded testing equipment to measure testing could potentially be carried out by the Lagos particulate emissions and to allow vehicles to be tested Computerized Vehicle Inspection Service (LACVIS) or under load using a chassis dynamometer. This is ­ especially another independent testing service but should not be left important for diesel vehicles. ECOWAS d ­ irective to the importers themselves. C/Dir.2/09/20 requires that all vehicles in ­circulation meet Euro 4 emission standards by January 1, 2025. Confirming compliance with the Euro 4 standard would require testing 4.1.3.3.  VEHICLE INSPECTION AND under load in a transient driving cycle. MAINTENANCE (I&M) Even in the absence of emission control systems, a poorly 4.1.3.4.  UPGRADING VEHICLE FLEETS adjusted or worn-out engine will produce much higher emissions than if it were well maintained. Where vehi- The most effective and least costly way to control vehicle cles are equipped with emission controls, this difference emissions is to replace the existing fleet as they retire with is much greater, and it has been commonly observed that new vehicles that have emission controls designed in from most of the emissions from the vehicle fleet are concen- the beginning (Faiz, Walsh, and Weaver 1996). In some trated in a small percentage of “gross emitters” (Krzyz- cases, it may be cost-effective to retrofit existing vehicles anowski et al. 2014).12 These gross emitters include or to accelerate the replacement of the existing fleet with vehicles where the emission control system is malfunc- emission-controlled replacements. Public transport and tioning and those where it has been removed or tampered delivery fleets are especially suitable due to their high with. Inspection and maintenance (I&M) programs are mileage in urban areas. designed to identify those gross emitters and require their repair. They can also perform related tasks such as Focusing on fleet vehicles such as taxis, buses, or delivery checking that all required emission control systems are trucks has been a proven approach to introducing alter- present, functional and interrogating engine electronic native fuel vehicles since this requires the establishment control systems for malfunction codes. An effective I&M and maintenance of fewer refueling facilities, and con- program is a prerequisite for implementing almost any version and maintenance can be handled by dedicated vehicle improvement program. service personnel (Faiz Walsh, and Weaver 1996). It also allows the refueling facilities to maintain their own fuel Experience has shown that the most effective I&M pro- quality, such as ultra-low sulfur diesel that is required grams are based in a relatively small number of high- for advanced catalysts and particulate filters. Given the volume stations that do not perform repairs, so that the global trend and falling costs of hybrid and electric vehi- inspectors have no vested interest in passing or failing cles, an evaluation of the costs of such vehicles should be a vehicle. LACVIS appears to be of this form, and its undertaken, particularly for fleet vehicles such as buses, establishment in 2016 was an important development in taxis, and delivery trucks (Mufson and Kaplan 2021).13 60 Air Quality Management Planning for Lagos State 4.1.3.4.1 Minibuses/danfos especially suitable targets for emission control efforts. Many cities around the world have switched their bus According to Lagos State Metropolitan Transport fleets to CNG, and an increasing number of BEV buses Agency (LAMATA), as recently as 2015, the small pas- are also being produced. Many cities have also purchased senger vans known as danfos accounted for about 45 per- “clean” diesel buses that are equipped with particulate fil- cent of all motorized passenger trips in Lagos. Given the ters and burn ultra-low sulfur fuel. Some, such as Mexico high mileage of danfos—reportedly as much as 80,000 km City, have successfully retrofitted older-model buses with per year—and the relatively old average age of the fleet diesel oxidation catalysts and particulate filters (Schipper (two-thirds may be over 17 years old), they would be logi- et al. 2006) (See Box 4.2). cal targets for replacement. The government’s 2018 plan for reducing short-lived GHGs (Government of Nigeria Nigeria has abundant natural gas, so a transition 2018) calls for phasing out the danfos in favor of 5,000 to CNG fuel would be a feasible strategy for buses new full-size buses. However, this is likely to face resist- in Lagos. The government’s plan (Government of ance from the danfo owners and operators. Nigeria 2018) for reducing short-lived GHGs includes a shift to CNG in buses nationally. This may not be the The danfos are mostly equipped with gasoline engines, best course, however, as it would require substantial which emit little PM2.5 unless the engines are worn out investment in new fueling infrastructure, which would and leaking oil into the exhaust. However, these engines have limited useful life as Nigeria transitions away are inefficient in urban traffic and emit large quantities from fossil fuels. CH4 emissions from CNG vehicles of CO and VOC as well as NOx and CO2. The danfos’ and infrastructure are also a concern. Biogas from small passenger capacity of 14 to 18 (crowded) people digesters and sewage treatment plants could be requires a large number of vehicles to meet passenger upgraded to “renewable natural gas” for vehicular use demand, so that they are major contributors to traffic but at considerable cost. congestion. Replacing the danfos with a smaller number of 35-passenger minibuses, as in Mexico City, would Clean diesel technology using particulate filters and help reduce congestion, improve passenger comfort and ultra-low sulfur diesel can achieve emission levels simi- safety, and reduce emissions and fuel consumption. The lar to CNG and would pose less risk of stranded invest- replacements should preferably be plug-in hybrids to ment. Hybrid buses using clean diesel technology offer allow for the possibility of electrification later, but even the potential for even lower emissions as well as fuel sav- conventional engines meeting Euro 4 emission stand- ings and savings on brake maintenance. Pure BEV buses ards would greatly reduce pollutant and GHG emis- would be the most practical either on short feeder routes sions. Such a replacement might logically be combined or in BRT service, where wireless charging systems could with improved safety standards and a reorientation of be installed in the stations. the danfo routes to better coordinate with the bus rapid transit (BRT) system. 4.1.3.4.3.  Motorcycle and tricycle taxis (okada and keke NAPEP) 4.1.3.4.2. Buses In Nigeria, motorcycle taxis, both two- and three-­ Diesel buses can be significant sources of PM2.5 emis- wheelers, play an important role in urban transport sions. They tend to operate in crowded areas where by providing short-distance mobility and a link for the many people are exposed to those emissions, are usually “first and last mile” of daily commutes. In Lagos, the centrally fueled (meaning that the buses are all fueled by two-wheel okada and three-wheel keke NAPEP taxis14 are one particular fleet operator), and are usually either oper- also an important source of employment. The 2,000 ated or supervised by public agencies. This makes them small buses approved for “first and last mile” trips in Air Quality Management Planning for Lagos State 61 BOX 4.2.  FROM COMBIS TO MINIBUSES IN MEXICO CITY In the early 1990s, public transit in Mexico City was dominated by large number of “combis”—11-seat ­Volkswagen microbuses with air-cooled gasoline engines that were extremely polluting. These vehicles were privately owned and operated and organized themselves into cooperatives to provide service on defined routes. Their large num- bers and lack of regulation led to traffic congestion, competition for passengers, haphazard stops outside of bus zones and in the middle of traffic, and other safety hazards. As part of its air pollution control program, the Mexico City Government, in 1993, established a maximum age limit of 8 years for combis and required that the replacement vehicles be minibuses. The minibuses are special- ized vehicles built on extended van chassis, with seats for 23 passengers and a maximum capacity of about 32. They were equipped with catalytic converters and used unleaded gasoline or in some cases LPG or compressed natural gas (CNG) fuel. Similar minibuses are still in widespread use today. Combi owners were provided with financing assistance to purchase the new minibuses through credit lines funded in part by the World Bank Transport Air Quality Project. Many combi owners also chose to lease their vehicles through specialized financing companies. 2021 demonstrate the importance of this segment of would need to be supplied but could be provided by the commute for getting passengers from their homes solar photovoltaic panels. to their jobs. Lagos restricted the import of two-stroke motorcycles 4.1.3.5.  PUBLIC TRANSPORT in 2014, but it is not clear if that has limited their cir- culation. Two-stroke motorcycles have been a major The expansion of public transport is considered an contributor to transport-related air pollution in cit- important way of improving the efficiency of transport in ies all over the world where motorcycles are numer- Lagos and of reducing both air pollution and GHG emis- ous, such as in South and Southeast Asia. Measures sions. With support from international donors, Lagos has to phase out two-stroke engines in favor of four-stroke invested in both the infrastructure and the institutions to have been one of the air quality successes in cities such improve public transport, including BRT, light rail, and as ­Bangkok, Dhaka, and Jakarta (Shah 2003).15 Like ferries. other public transport vehicles, motorcycle taxis should be required to meet emission standards as a condition The upgrading and expansion of public transport in for their operation. Lagos could have a large positive impact on air quality. Public transport investments are large and multi-year and Given their typically short trip distances, okada and must be justified largely on their transportation benefits keke NAPEP taxis in Lagos that presently use gaso- rather than on their contribution to improving air quality. line engines could potentially be replaced with BEVs. Although the air quality benefits of public transport can ­ Battery-electric motorcycles and three-wheelers are be large, public transport investments need to be evalu- already commercially available in some Asian countries. ated on their long-term contribution to air quality rather This would eliminate the engine noise and odor as well than on their capacity to make an immediate positive as pollutant emissions. Reliable charging arrangements impact on air quality. 62 Air Quality Management Planning for Lagos State 4.1.3.5.1.  Bus rapid transit (BRT) TABLE 4.2.  BRT CORRIDORS IN LAGOS In 2008, Lagos opened the first BRT corridor in Africa. Cost/ Total Distance km (US$, cost (US$, Before the BRT line, passengers in Lagos mostly used (km) millions) millions) “small commuter buses, known as danfos (85 percent), large commercial buses (8 percent), and cars (4 percent), and the Phase 1: Pilot 22.0 1.7 37.4 Corridor (2008) remaining 3 percent taxis, motorcycle taxis (okada) and shared taxis (kabu kabu)” (World Bank 2013). Among its Phase 2: Ikorodu 13.5 7.4 99.9 Extension benefits, the BRT system in Lagos has been successful in reducing travel times, public transport expenditures by Phase 3: Oshodi to 27.0 4.4 118.8 Abule-Egba low-income households, and road accidents. The BRT system has also proven to be profitable, with the opera- tor of the first BRT corridor recouping the entire capital 4.1.3.5.2.  Light rail investment of the bus fleet within 18 months and without attempting to bar competitor services (Gorham et al. 2017). The construction of light rail in Lagos is meant to augment the public transit system, resulting in less private vehicle By using larger buses traveling in dedicated bus lanes, the traffic and lower emissions per passenger-­ kilometer. The efficiency of transportation can improve and PM2.5 emis- fact that Lagos has a relatively low amount of rail-based sions can be reduced. BRT systems can lower air pollution public transit compared to other global megacities implies through several means: (a) BRT buses can displace smaller that there is significant potential for expanding light rail buses (such as danfos) and automobiles, which in turn would in Lagos. For instance, Lagos has about 2 km of light result in less pollution per passenger-kilometer; (b) dedi- rail per million residents compared to Beijing which has cated BRT lanes allow buses to run unhindered at higher 29 km and London which has 49 km (Croitoru, Chang, speeds than traffic on congested roadways—vehicles pro- and Kelly 2020). Two light-rail corridors (Figure 4.1) are duce the least amount of air pollution when they are cruis- to be the first lines in a passenger rail system in Lagos ing at an even speed rather than stopping and starting; and planned to ultimately include seven lines: blue, red, (c) BRT buses can employ newer bus technologies—clean green, yellow, purple, brown, and orange.16 diesel, CNG, electric—that are able to reduce air pollution emissions better than current vehicle technologies. 4.1.3.5.3.  Public ferries The BRT program that has been under development in Lagos since 2008 has resulted in faster commutes, lower Given the proximity of Lagos to large inland waterways, fares, and reduced fuel consumption per passenger-kilo- ferries could provide an additional source of transport meter. Under the first phase of the Lagos Urban Trans- for commuters. Ferry service currently operates on Lagos port Project (LUTP), a 22 km BRT corridor was Lagoon, connecting multiple locations with the commer- constructed, ultimately transporting around 200,000 pas- cial center on Lagos Island. Like the investments made sengers per day or 37 percent of all public transport trips for BRT and light rail, it is assumed that ferry service in in the corridor, while accounting for only 4 percent of Lagos could be expanded to help relieve road traffic. vehicles in 2008 (Mobereola, 2009). Several additional BRT corridors have been constructed over the past dec- It has recently been reported by Lagos State Ferry (LAG- ade (see Table 4.2). Lower fuel consumption results in FERRY) that it has a mandate to move 30 percent of reductions in PM2.5 as well as CO2. Based on assessments commuters. Currently, LAGFERRY operates 12-seater, from phase 1, the original BRT line resulted in 13 percent 30-seater, and 50-seater boats. In its first year (begin- lower overall fuel consumption as well as lower CO2 ning February 2020), LAGFERRY carried 524,000 pas- emissions in the corridor. sengers (or 1,435 trips per day) (The Guardian 2021). Air Quality Management Planning for Lagos State 63 FIGURE 4.1.  LAGOS LIGHT RAIL: BLUE AND RED LINES17 Lagos Agbado Metro Blue Line (under construction) Metro Red Line (under construction) Iju Agege Domestic Ikeja Terminal MMIA International Terminal MMIA Oshodi Mushin Yaba Ebute Okokomaiko Metta Iganmu National Iddo Alaba Theatre LASU Trade Fair Festac Volkswagen Alakija Ebute Ero Mile 2 Marina Source: https://www.railway-technology.com/projects/lagosrailmasstransit/. 64 Air Quality Management Planning for Lagos State ­ Private f erries carry considerably more passengers, Measures to reduce emissions from other freight trucks with 67 private ferries carrying 6.5 million passengers must also be part of the solution to air pollution in Lagos. in 2012, and 165 private ferry operators with a com- In parallel with measures to upgrade light-duty vehicles bined public and private tally of 18.8 million passengers and buses, there needs to be an expanded program com- (51,507 passengers per day) in 2016 (Lagos State Water- bining vehicle inspections, emissions certificates, fines Authority 2017). ways ­ and removal from service for noncompliance, and a guar- anteed supply of clean diesel for heavy-duty trucks. This will require investments in newer trucks and in some cases 4.1.3.6.  FREIGHT TRANSPORT the retrofitting of existing trucks with pollution controls such as catalysts and diesel particulate filters. California Much of the container freight traffic for all of Nigeria has had considerable success in mandating the retrofit- flows through Apapa and Tin Can Island ports. The ting or replacement of older vehicles in diesel truck fleets. resulting diesel truck traffic is probably a major source While costly for truck owners, the gains are also likely to of PM2.5 and other emissions. The new Lagos-Ibadan be large given the high share of PM2.5 emissions from die- railway began service in June 2021 and reportedly offers sel combustion. Although diesel fuel accounted for about intermodal service from dockside in Apapa to the Inland 30 percent of petroleum product consumption in Lagos Container Depot in Ibadan. The line will eventually (IEA 2021) in 2020, compared to 65 percent for gasoline, extend to Kano in northern Nigeria. By diverting large PM2.5 emissions from diesel fuel have been found to be numbers of heavy trucks from Lagos, this intermodal ser- 3–4 times higher than from gasoline (see Figure 2.8). vice could save greatly on fuel consumption and travel time while reducing GHG emissions and air pollution. 4.1.4.  ELECTRICITY GENERATION Further developments could be made by improving the management of local truck traffic to the ports. As Lagos The electric power sector in Nigeria is expected to grow is the economic and manufacturing hub of the country, rapidly over the next 15 years to meet power demand, a significant part of the container flow must be to and which has far outgrown the country’s existing capacity. from locations in Lagos itself. This will continue to go by Current electricity consumption per capita in the coun- truck. In most ports, short-haul container delivery is the try is extremely low by international standards. Cur- last resort for truck-tractors that are too old and unreli- rently, per capita electricity consumption in Nigeria is able for long-haul service. These trucks are often in poor only 147 kWh, compared to the average for LMICs of condition, with high emissions. However, in California, 736 kWh and a global average of 3,298 (World Bank the ports of Los Angeles and Long Beach have had suc- 2020). Nigeria’s power sector is characterized by high cess in limiting access to trucks that meet emission stand- technical and financial losses, and the current system ards. Owner-operators of trucks that do not meet the cannot provide adequate electricity to the economy. As standards have been provided with financial assistance such, Nigeria has among the highest share of electricity to replace their old tractors. Apapa and Tin Can Island provided by backup generators (“gensets”) in the world. ports may wish to consider similar actions. Among other These generators are expensive to operate, noisy, and advantages, limiting access to only those trucks and driv- highly polluting. Long-term investment in power grid ers that meet standards could well improve safety and expansion and reliability will eventually reduce genset efficiency and reduce the need for congestion-causing usage. Improvements to Nigeria’s power sector are criti- checkpoints. cal for the sustainability of the system and the economy. Air Quality Management Planning for Lagos State 65 By increasing the supply of electricity, economic losses Currently there are no emissions standards for electric- would be reduced, while tariff revenues would increase, ity gensets in Nigeria. As in other countries, the emis- generating considerable income to pay for the reforms. sions from such generators should be regulated, requiring (a) improvements in fuel and (b) the installation of pollu- With the growth of the power sector, baseline emissions tion-control equipment. of both CO2 and NOx might be expected to rise (World Bank 2014). (Since the power plants almost exclusively While improving the generating capacity and reliability use natural gas fuel, their PM2.5 emission are negligible). of the electric grid would reduce the need for backup However, meeting the commitment to achieving “net generators, this is at best a long-term goal. One approach zero” emissions by 2050 (Lagos) and by 2060 (Nigeria) in the short run could be to encourage the formation of will require that most of the new power generation “mini grids” based on standardized generating sets of a capacity be renewable—for example, wind and solar. few hundred kW, each equipped with advanced emission Fortunately, the costs of wind and solar power generation controls (for example, US Tier 4 final or EU Stage V). have decreased considerably, to the point that they can Thus, instead of each family or business having its own be cost-competitive with thermal power plants in many 2 kW generator, a 100 such might be connected to a sin- locations. In the 2014 low-carbon study for Nigeria, the gle 200 kW generator. This mini-grid would connect to power sector was estimated to have the largest potential the main grid through a single transfer switch. A single (48 percent of total reduction) among four large sectors medium-size generator would be far more efficient than (agriculture, forestry and other land use [AFOLU], Oil many small ones and would have much lower emissions. and Gas, and Transport) for the reduction of GHG emis- Such mini-grids could then be augmented by renew- sions over the next 15 years (Cervigni et al. 2013).18 able sources such as solar photovoltaics, with the genset retained as backup. One step that could both reduce emissions and increase power output would be to retrofit the Egbin power plant for combined cycle operation. Presently, the plant uses 4.1.5. INDUSTRY natural gas-fired boilers to generate steam. Adding a gas turbine topping cycle could increase the overall plant effi- Industry is one of the major contributors to air pollu- ciency, producing more power from nearly the same fuel tion in Lagos. While a large share of industry is located input. By fitting these gas turbines with low NOx burners, near Ikorodu, surveys of industry activity confirm that the NOx output from the plant could also be reduced by industries are located throughout the metropolitan area, 75 percent or more. including in the industrial zones of Apapa, Idumota, Ikeja, and Odogunyan. At the Odogunyan site, iron smelting is responsible for extremely high PM2.5 concen- 4.1.4.1.  CONTROLLING EMISSIONS trations as well as lead emissions (Kemper and Chaud- FROM BACKUP GENERATORS huri 2020). Industries located in densely populated parts of Lagos need to either control their emissions or Backup generators (gensets) may account for as much relocate. Several such industries have moved in recent as 40 percent or 1,940 GWh of electricity generation in years, and the government has assisted in the relocation. Lagos and a much greater share of pollutant emissions The government’s main role, however, is the monitoring from power generation.19 While total PM emissions from and enforcement of air pollution standards, which may gensets are difficult to calculate, gensets represent one of require automatic pollution-monitoring equipment at least regulated sources of air pollution in Lagos. As noted major industrial plants. Augmenting LASEPA’s ability to earlier, improving the quality of diesel and gasoline sup- perform such monitoring of industrial emissions is criti- pled to Lagos would help reduce emissions from gensets. cal for their effective control. In general, if an industry 66 Air Quality Management Planning for Lagos State is exceeding the emissions standard, it is up to LASEPA ­ ystematic program of cleaner fuels, which for petroleum s to enforce the standard and for the industry to remedy products such as diesel and fuel oil could correspondingly the situation through investments in cleaner fuel and/or lower genset and industrial emissions, and pollution from pollution control equipment. ships. Improving fuel quality is one of the most effective ways of reducing air pollution from industrial facilities. Espe- 4.1.6.1.  CROP RESIDUE BURNING cially for small industries, for which baghouses or other expensive emissions control equipment is not feasible, Recent studies using satellite imagery indicate severe air upgrading fuel quality is the most cost-effective way to pollution (PM2.5) associated with the burning of agri- reduce air pollution. To the extent that firms can convert cultural crop residues in Sub-Saharan Africa, including from polluting fuels such as fuel oil, diesel, and biomass to Nigeria (Hickman et al. 2021).20 Given the high popu- cleaner fuels such as electricity and natural gas, it may be lation density in Nigeria and Lagos State, air pollution possible for industries to remain in urban areas and not from agricultural fires is a risk for human health. Field contribute significantly to air pollution. The conversion burning is most severe in Nigeria during the dry season to cleaner fuels can greatly reduce industrial air pollution (November–February), and preliminary air-quality moni- emissions and often allow industries to meet minimum toring data confirm significantly higher PM2.5 levels dur- pollution standards. Industry-wide investments in cleaner ing this period in Lagos. This is an area where pollution energy sources, such as solar photovoltaic on factory roof- sources outside of Lagos State could be having a signifi- tops, could be an option for some types of industries that cant impact on air pollution, and thus measures to reduce have modest energy requirements and are currently rely- field burning in surrounding areas, especially during the ing on dirty fuels. dry season, could be an important air quality measure. The monitoring and enforcement of industrial emis- sion standards, particularly for large and polluting 4.1.6.2.  COOKING FUELS industries such as metallurgy, chemicals, and cement, is important for ensuring that industries control their Another source of biomass burning in Lagos State is air pollution. At the same time, helping industries con- the combustion of charcoal and fuelwood for cooking vert to cleaner technologies or fuels, through training (residential and commercial). Among low- to medium- and technical assistance, can be an important way for income residential areas in Lagos, the use of LPG for them to remain competitive and improve their produc- cooking is not widespread, unlike kerosene and charcoal tivity and profitability. Cleaner production is critical for (Ozoh 2018).21 LPG is preferred by most consumers in the survival of many industries such as food process- Lagos but is more costly than other fuels, including for ing or the information technology sector, which is why the upfront purchase of the gas cylinder and the fuel so many countries have established cleaner production (Emagbetere, Odia, and Oreko 2016). A consistent sup- programs for industry. ply of LPG, along with subsidies for low-income consum- ers, could be effective in reducing PM emissions from solid fuels used for residential and commercial cooking. 4.1.6.  OTHER SOURCES While the above analysis has focused on the four main 4.1.6.3.  PORT EMISSIONS sectors identified as responsible for air pollution (PM2.5), there are other pollution sources in Lagos that can be Lagos is home to some of the busiest ports in Africa, reduced. Some sources can be reduced through a Apapa and Tin Can Island being the two largest. Air Quality Management Planning for Lagos State 67 ­ necdotal evidence suggests that pollution from ships in A dust may be due to traffic traveling on unpaved roads. Lagos is severe. Measures to reduce the fuel consump- While such dust could be assigned to the transport sec- tion and air pollution emissions associated with ships at tor, the remedy involves paving roads, watering roads, or port, such as through shore-based electrification, fuel simply reducing the amount of traffic or enforcing speed standards, or alternative fuels, may be an effective way to limits on unpaved roads. Sustainable agricultural prac- reduce air pollution in Lagos (Sofiev et al. 2018; Winkel tices such as those that reduce deforestation or do not et al. 2016). The port authorities should also consider the leave fields barren between crop seasons can help reduce feasibility of enforcing the limit of 0.5 percent sulfur in the amount of windblown soil from agricultural land, marine bunker fuel. Since Nigeria has no refineries, sales while industrial practices that reduce overall pollution of marine HFO are probably limited but the port could will also limit the amount of dust from industry. take and analyze samples of the fuel on board. A second source of emissions at the ports relates to the 4.2. NATIONAL ACTION PLAN diesel trucks that pick up or drop off loads. Reportedly, as many as 5,000 high-polluting diesel trucks seek access TO REDUCE SHORT-LIVED to the ports every day, resulting in congestion and air pol- CLIMATE POLLUTANTS lution (Kemper and Chaudhuri 2020). Measures to deal with emissions from the thousands of diesel trucks could include investments in traffic management or systems for Many of the pollutants that contribute to urban air pol- better loading and unloading. lution are also short-lived GHGs. The progress in the implementation of the Federal Government’s plan to reduce short-lived climate pollutants (Government of 4.1.6.4. ABATTOIRS Nigeria 2018) forms part of Nigeria’s NDC. Table 4.3 lists the 22 abatement measures included in that plan. There are a reported 16 abattoirs (slaughterhouses) in Lagos that generate air and other pollutants associated While the NAP applies to the rest of Nigeria as well as with the processing of meat and hides and the disposal of Lagos, there is considerable overlap between the planned animal wastes. Improving the management of abattoirs, abatement measures and those discussed in section 4.1. as has been done at several state-run facilities, can reduce In the transport section, common measures include the air pollution emissions. Investment in biogas production renewal of the urban bus fleet in Lagos, introduction of from animal wastes is one method that has been used to low-sulfur diesel and petrol, elimination of high-emitting both reduce air pollution and generate energy for sale or vehicles by means of I&M, and reduction of car-based self-use. vehicle trips through public transport. The measures pro- posed for the residential sector in the NAP are of little relevance to Lagos, as they have already been surpassed. 4.1.6.5. DUST Likewise, there is little oil and gas activity and relatively little agriculture in Lagos State so the NAP measures for One of the major sources of air pollution identified those sectors have little relevance. Waste management through air quality monitoring—as much as 28 percent and electric generation, however, are key sectors both of total PM2.5—is “dust.” The sources of dust include for Lagos and the country at large, and the measures resuspended particulates from unpaved roads, industrial included in the NAP are consistent with those recom- pollution, and windblown soil and sand. Much of this mended here. 68 Air Quality Management Planning for Lagos State TABLE 4.3.  ABATEMENT MEASURES IN THE NATIONAL ACTION PLAN (NAP) TO REDUCE SHORT-LIVED CLIMATE POLLUTANTS Source Sector SLCP Abatement Measures Target Transport 1. Renewal of urban bus fleet in Lagos 5000 new buses in Lagos complete and Danfo buses fully replaced by 2021 2. Adoption of CNG Buses in Nigeria 25% all Buses converted to CNG by 2030 3. Introduction of low sulphur Diesel and Petrol 50 ppm diesel fuel introduced in 2019; 150 ppm petrol 4. Elimination of high emitting vehicles that do not meet introduced in 2021 vehicle emission standards Euro IV limits met by all vehicles by 2030 5. Reduction of vehicle journey’s by car through transport modal shifts 500, 000 daily journeys shifted from road to rail & waterways Residential 6. Increase in population using modern fuels for cooking 80% ofH/H using modern fuels for cooking in 2030 (LPG, electricity, kerosene, biogas, solar cookers) 20%> H/H using improved biomass stoves for cooking in 7. Replacement of traditional biomass cookstoves with 2030 more efficient improved biomass stoves All kerosene lighting replaced by solar lamps by 2022 8. Elimination of kerosene lamps Oil & Gas 9. Elimination of gas faring 100%) of gas faring eliminated by 2020 10. Fugitive emissions/lecikages Control 50% Methane Reduction by 2030 11. Methane Leakage Reduction 50% Methane Reduction by 2030 Industry 12. Improved Energy’ Efficiency in industrial Sector 50% improvement in energy’ efficiency by 2050 Waste 13. Reduction of methane emissions and open burning of 50% methane recovered from landfills by 2030; 50% Management waste at open dumpsites through adoption of digesters reduction in open burning of waste by 2030 at dump sites Promote Septic sludge collection, treatment and recycling 14. Septic sludge collection in 37 municipalities 15. Sewerage Systems and Municipal wastewater Establish, expand Sewerage Systems and municipal treatment plants wastewater treatment plants in Lagos, Kami and Port Harcourt Agriculture 16. Increased adoption of intermittent aeration of rice 50% cultivated land adopt ABD management system by paddy fields (A WD) 2030 17. Reduce open-field burning of crop residues. 50% reduction in the fraction of crop residue burned infields by 2030 18. Anaerobic Digestion (AD) 50% reduction by 2030 19. Reduce methane emissions from enteric fermentation 30% reduction in emission intensity bv 2030 Power 20. Expansion of National Electricity Coverage 90% of the Population have access to electricity grid by [Energy] 2030 21. Increase share of electricity generated in Nigeria from renewables 30% electricity generated using renewable energy in 2030 HFCs 22. Elimination of HFC Consumption. 10% of HFCs phased out by 2030, 50% by 2040 and 80% by 2045 Source: Government of Nigeria 2018 Air Quality Management Planning for Lagos State 69 readiness for implementation, and consistency with 4.3. POLICIES AND the NAP to Reduce Short-Lived Climate Pollutants. INVESTMENTS TO IMPROVE AIR QUALITY 4.3.1.  COSTS OF AIR POLLUTION CONTROL From the sectoral air quality interventions outlined earlier, it is possible to sketch out potential AQM To assess the cost of potential air pollution control meas- scenarios for Lagos to progressively reduce ambient ures in Lagos, the financial and economic costs of selected air pollution. Different combinations of policies and interventions have been estimated, along with their actions can be used to reduce PM2.5 emissions. Table potential to reduce air pollution (measured as avoided 4.4 contains a list of key air quality policies recom- tons of PM2.5 per year). While it has not been possible to mended for near-term implementation in Lagos based undertake field visits and conduct detailed CBAs for all on measured pollution levels, assessed health impacts, potential air quality projects in Lagos, a preliminary desk TABLE 4.4.  CLEAN AIR POLICIES FOR LAGOS Sector Policies and Actions Solid Waste • Solid waste collection strategy to raise the share collected • Recycling, composting, and WTE to reduce MSW landfilled • Ban on open burning of solid waste Industry • Monitoring and enforcement of industrial emissions • Clean fuel and “cleaner production” incentives Transport • Vehicle emissions testing and display of inspection certificates • Fines and cancellation of certificates of violators • Transition to Euro 3 and 4 vehicle standards Fuel quality • Clean fuel import strategy for both diesel and gasoline (Euro 4) • Guaranteed fuel quality among fuel distributors and retailers Power • Power sector reform • Genset emissions standards Other • LPG for residential and commercial cooking • Ban on field burning during the dry season • Paving, watering, and speed limits on unpaved roads Administrative • Installation of air quality monitoring stations • Creation of an air quality monitoring index and information system to alert vulnerable groups to hazardous air days • Installation of automatic pollution-monitoring equipment at major pollution sources (e.g., large industries). Source: Author’s own elaboration 70 Air Quality Management Planning for Lagos State exercise was undertaken to estimate indicative costs for » Solid waste burning. Control costs include several high-priority interventions, using data from exist- the increased cost of collecting a growing share ing projects in Lagos and elsewhere. of MSW, based on private concessionaire costs for Lagos (Aliu et al. 2014). To accommodate the Two sets of costs for reducing air pollution have been increased amount of MSW, the costs of addi- evaluated. Public costs include the building of public tional landfills and recycling and composting are infrastructure such as landfills and roads, as well as public included. administrative costs such as pollution monitoring, regula- » Road transport. Control costs include the costs tion, and licensing. The costs of reducing emissions from to upgrade vehicle fleets to Euro 3 and Euro 4 vehicles, factories, or electric generators to comply with standards, plus the additional costs of cleaner emission standards lie with the owners and are referred to gasoline and diesel. ­ as private compliance costs. Where possible, the net cost » Industry. Control costs include the installa- (investment minus revenue) of public investments, regula- tion of emission-monitoring equipment on large tory costs, and compliance costs have been estimated for ­ industrial enterprises and the enforcement of selected air quality measures. emissions standards. The compliance costs for industrial enterprises have not been estimated. ­ The indicative costs of lowering PM2.5 concentrations to » Electricity generation. Control costs include (a) reach WHO air quality targets have been estimated based the estimated costs needed to increase the ­ supply on public and private costs. Although on-the-ground analy- and reliability of power from the grid to offset pow- sis of specific air pollution control measures in Lagos for this er supplied by backup generators or (b) the costs of study was not carried out, available costs of similar interven- emissions control for backup generators in Lagos. tions from Nigeria and elsewhere have been used. The fol- lowing control measures account for around three-quarters Using the cost estimates and the health benefits outlined of potential PM2.5 emission reduction measures in Lagos. in chapter 3 (Table 3.3), it is possible to create scenarios The cost assumptions for these measures are provided in for lowering air pollution in Lagos to meet WHO interim annex 2.3. targets. The results are presented in Table 4.5. TABLE 4.5.  INDICATIVE COSTS AND BENEFITS OF REDUCING AIR POLLUTION Air pollution reduction scenarios Air quality target 35 ug/m3 25 ug/m3 15 ug/m3 10 ug/m3 Reduction in PM2.5 −10.0 −20.0 −30.0 −35.0 Cost (public and private) – US$, millions 200–300 350–500 450–600 500–700 Reduction in total mortality 3,598–6,840 7,196–13,680 10,793–20,521 12,592–23,941 Reduction in infant mortality 1,829–3,468 3,657–6,936 5,486–10,404 6,400–12,138 Benefit of reduced mortality (VSL) – US$, millions 890–1,691 1,780–3,381 2,670–5,072 3,115–5,917 Benefit (VSL)/Cost ratio 3.0–8.4 3.6–9.7 4.5–11.3 4.5–11.8 Benefit of reduced mortality – HCA (US$, millions) 235–446 469–891 704–1,337 821–1,559 Benefit (HCA)/Cost ratio 0.8–2.2 0.9–2.5 1.2–3.0 1.2–2.3 Source: Author’s own elaboration. See section A4 for cost assumptions. Air Quality Management Planning for Lagos State 71 where, in addition to the financial analysis, investors 4.4. FINANCING AIR QUALITY will require a technical plan for meeting the environ- MANAGEMENT mental objectives of the project, in this case the lower- ing of air pollution. The current LASG budget is not well aligned with the priority areas for reducing PM2.5 An essential element for improving air quality in Lagos is air pollution (Figure 4.2), which is understandable to identify viable financing resources to support air pollu- given that Lagos has many important economic and tion interventions. Based on discussions with both public social issues to address. Based on “air quality” projects and private officials in Lagos, an explicit AQM program and activities in the current LASG budget (Table 4.7), in Lagos could be funded through a variety of financing a strategic program of policy and regulatory initiatives sources, including the state capital budget, private ­sector focused on a broader set of air pollution sources could interventions, multilateral support, and climate funds be developed. (Table 4.6). To better align the budget with air quality concerns, the Using internal and external resources, Lagos could mobilize LASG budget should focus on those policies most impor- and redirect resources between FY21 and FY26 to finance tant to reduce air pollution, expanding beyond public an air quality improvement plan. The LASG has announced transport to other priority sectors, such as solid waste and plans to issue a green bond of N25 billion (US$60 million), power. Priority areas for AQM have been identified in which could be the centerpiece of a broader funding pack- THEMES, an acronym for Lagos’ current administra- age for air quality that includes private investment, multilat- tion’s development agenda that includes projects in trans- eral credit lines, and grant financing. port, health, and the environment. 4.4.1.  LASG BUDGET 4.4.2.  PRIVATE FUNDING The LASG has an active debt issuance program, with The global market for issuance of green bonds continues N100 billion (US$243 million) included in its 2021 to expand (Figure 4.3) and country commitments from appropriations budget. The issuance of a green bond COP26 will likely expand those related to climate and air is significantly different from issuing plain vanilla quality. As of 2020, domestic financial institutions had a bonds. A key requirement for the issuance of a green total of N16 trillion (US$39 billion) in short-term instru- bond is the provision of a second-party opinion (SPO), ments. The local pension funds had over N12 trillion TABLE 4.6.  POSSIBLE FUNDING SOURCES FOR AQM IN LAGOS Lagos State Budget The LASG budget is currently financing projects that address air pollution and could be strategically realigned to make a larger contribution to both climate and air quality goals. Green Bonds Worldwide, the issuance of environmental finance products continues to grow annually. Lagos’ recent announcement of plans to issue a green bond is evidence of the trend. See Figure 4. Multilateral Lines Bilateral and Multilateral Development Banks (MDBs) have supported projects that address air pollution, including in areas such as solid waste management, power, and transport. Climate Funds Climate funds are available that can support air quality interventions. For example, the World Bank Group’s Climate Business Plan has targets and funding commitments within the sectors identified as principal contributors to air pollution in Lagos. 72 Air Quality Management Planning for Lagos State FIGURE 4.2.  LASG SECTOR BUDGET (US$29 billion), with a significant share of those resources COMPARED TO AIR POLLUTION invested in green bonds. By being able to develop and design green projects and interventions, the LASG can LASG 2021 budget PM 2.5 emissions put itself in a position to access some of these resources through dialogue with the private sector. 4.4.3.  MULTILATERAL SUPPORT Multilateral development banks (MDBs) have provided financing for interventions to address air pollution from all the key contributing sectors, including solid waste, trans- Solid Waste Industry Transport Power Other port, and power. Although air quality has not been the primary motivation for such projects in Africa, this study Source: Own elaboration. demonstrates the seriousness of the problem and could be TABLE 4.7.  “AIR QUALITY” PROJECTS IN THE LASG 2021 BUDGET WASTE Lagos Waste Management Reconstruction and upgrading of three solid waste transfer stations. Authority (LAWMA) Construction of new landfill. INDUSTRY Ministry of Agriculture Relocation of sawmill from Oko baba to Agbowa timber village. TRANSPORT Lagos Metropolitan Area Transit Bus Rapid Transit. High-speed buses operating in segregated lanes. Authority (LAMATA) 2,000 buses to transport passengers from Oshodi to Abuie Egba. Completion of 27 km blue line from Okoko to Marina. Phase 1 construction of 27 km red line from Agbado to Marina. Bike share program. LAGFERRY Passenger transport by ferries displacing private road vehicles. POWER Ministry of Energy and Mineral Light-Up Lagos Resources Expansion of LPG in two government estates. High-tension power lines, including pilot solar project for hospitals. Installation of electricity meters. OTHER LASEPA Installation of 8 air quality monitoring stations across Lagos State. Source: Lagos State Ministry of Economic Planning and Budget Air Quality Management Planning for Lagos State 73 FIGURE 4.3.  GLOBAL GREEN BOND MARKET $400 $300 $200 $100 $0 2013 2014 2015 2016 2017 2018 2019 2020 Corporate and government green bond issuance $700 $600 Annual issuance ($ billion) $500 $400 $300 $200 $100 $0 2013 2014 2015 2016 2017 2018 2019 2020 2021F Green bond Social bonds Sustainability bonds Source: Bloomberg. the basis of developing an air quality program. Projects PforR was developed specifically to address air pollution specifically related to air quality improvement have been control in the northern Jing-Jin-Ji Region. Lagos would developed by MDBs, and have included sector financing be an excellent candidate to develop an AQM program as well as pollution-monitoring equipment and technical with multilateral and bilateral support. assistance for effective AQM (Croitoru, Chang and Kelly 2020). The World Bank has financed numerous air qual- ity improvement projects, including a recent project in 4.4.4.  CLIMATE FUNDS Cairo. The financing of environmental improvement has sometimes been through performance-based programs, A future AQM plan for Lagos should link with its where financing is provided as pollution-reduction tar- Climate Action Plan (Lagos State Government 2021) gets are met (World Bank 2016a). The World Bank’s and Nigeria’s NDC to mobilize resources. COP26 “Program-for-Results (PforR)” instrument has been used has created a renewed interest in mobilizing private for social, health, and environment projects. In China, a sector resources toward the US$100 billion per year 74 Air Quality Management Planning for Lagos State commitment by developed countries to address cli- 4.4.5.  SUMMARY OF FUNDING FOR AQM mate-related issues. The amount of funding that is available to address Leveraging the Lagos Climate Action Plan. The Lagos air quality appears well within the reach of Lagos. Climate Action Plan targets interventions in sectors Table 4.8 provides a 5-year perspective on such a plan that are major contributors to air pollution (Box 4.3). that includes green bonds, plain vanilla bonds, multi- Additional data on baseline numbers and reductions in lateral credit lines, and access to grants through cli- PM2.5 emissions would be needed to list the actions in mate funds. the financing plan. Table 4.9 provides a summary of the potential size of Leveraging Nigeria’s NDCs. Under the United Nations such a 5-year program. It could mobilize resources of Framework Convention on Climate Change (UNFCCC), up to US$1.29 billion (N537 billion) for the state with Nigeria has set targets that align with the sectors responsi- an increase in the green component of its financial mix. ble for air pollution in Lagos. Most of the priority actions Being able to achieve this mix could likely incentivize for air quality outlined in this chapter are included in access to multilateral lines of US$299 million as well as Nigeria’s NDC (Box 4.4). climate funds of US$190 million. BOX 4.3.  LAGOS CLIMATE ACTION PLAN, 2020–2025 The five-year plan aims to put Lagos on a pathway to zero carbon by 2050, enhance the climate resilience of the city and its population and to maximize the co-benefits of climate action, such as greener and healthier lifestyles. It was developed through a stakeholder engagement process, that allowed the plan to gain broad buy-in from business, civil society and the wider public. The plan envisages a range of actions to reduce GHG emissions in each section, including: Transport » Expansion of the BRT network in Lagos. » Spatial planning to promote transit-oriented development. » Encourage the uptake of low-emission vehicles. » Encourage the shift of freight from road to rail. Energy » Installing solar PV systems on all schools, hospitals and municipal buildings. » Reduce emissions in the residential sector by promoting the development of energy storage tech- nologies and incentivizing the deployment of micro-grids in off-grid urban communities. Waste » Divert organic waste from landfill by encouraging separation at source and introducing composting technologies. » Implement composting, waste-to-energy and other waste recovery initiatives in underserved communities. Air Quality Management Planning for Lagos State 75 BOX 4.4.  NIGERIA NDC TARGETS AND AIR QUALITY Sector Measure Residential 48 % of population (26.8 million households) using LPG and 13 % (7.3 million households) using improved cookstoves by 2030 Elimination of kerosene lighting by 2030 Energy efficiency 2.5% per year reduction in energy intensity across all sectors Transport 100,000 extra buses by 2030 Bus Rapid Transport (BRT) will account for 22.1 % of passenger-km by 2035 25 % of trucks and buses using CNG by 2030 All vehicles meet EURO lllemission limits by 2023 and EURO IV by 2030 Electricity generation 30 % of on-grid electricity from renewables (12 GW additional large hydro, 3.5 GW small hydro, 6.5 GW Solar PV, 3.2 GW wind) 13 GW off grid renewable energy (i.e., mini-grids 5.3 GW, Solar Home Systems and street lights 2.7 GW, self-generation 5 GW) Reduce grid transmission and distribution losses to 8% of final consumption of electricity in 2030, down from 15% in 2018. 100% of diesel and single cycle steam turbines replaced with combined cycle Elimination of diesel and gasoline generators for electricity generation by 2030 Oil and gas Zero gas flaring by 2030 60% reduction in fugitive methane emissions by 2031 TABLE 4.8.  FIVE-YEAR AQM FINANCING SCENARIOS Program Funding Components 2021 2022 2023 2024 2025 Allocation Allocation Allocation Allocation Allocation (°/o) N’B (°/o) N’B (°/o) N’B (°/o) N’B (°/o) N’B Borrowing Plan 100.0 125.0 125.0 130.0 140.0 Multilateral Lines 0.0% – 25.0% 31.3 30.0% 37.5 30.0% 37.5 30.0% 37.5 Green Bond 25.0% 25.0 30.0% 30.0 30.0% 30.0 30.0% 30.0 30.0% 30.0 Issuance Grant Funding 0.0% – 0.0% 18.8 0.0% 17.5 0.0% 22.5 0.0% 32.5 (climate funds) LASG Vanilla 75.0% 75.0 45.0% 45.0 40.0% 40.0 40.0% 40.0 40.0% 40.0 Bonds 76 Air Quality Management Planning for Lagos State TABLE 4.9.  SUMMARY OF POSSIBLE ESMAP​/­World Bank. https://esmap.org​ FUNDING INSTRUMENTS TO SUPPORT /­node/1145. 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Corbett. 2018. “Cleaner Fuels for -Recovery-Operation. 78 Air Quality Management Planning for Lagos State CHAPTER 5 LAWS, REGULATIONS, AND INSTITUTIONAL CAPACITY A study has been conducted as part of the Lagos PMEH to describe and analyze the regulatory and institutional arrangements for air quality and pollution control objec- tives in Lagos State in relation to Nigeria’s national framework. The outcome of this study, as presented in this chapter, reveals the deficiencies in the legal, regulatory, and institutional frameworks for air quality that currently exist at both the federal and Lagos State levels. Having adopted the national regulations operated by National Environ- mental Standards and Regulations Enforcement Agency (NESREA), the Lagos State framework operated by LASEPA inherits the federal-level regulatory deficiencies. Key challenges to air quality governance in Nigeria and Lagos State include the lack of a unified regulatory framework, inadequate and ineffective regulations, deficiencies in the technical and enforcement capacity of regulatory bodies, and budgetary con- straints. We therefore make recommendations to strengthen existing legislation and regulations, establish a scientific basis for deriving air quality and emission standards, strengthen the technical capacity of relevant institutions to undertake air quality mon- itoring and health impact assessments, strengthen the enforcement capacity of regula- tory institutions, and ensure adequate funding for the relevant institutions to establish monitoring stations and build other necessary capacity. 5.1. NIGERIAN LEGAL AND REGULATORY FRAMEWORK The Federal Constitution of Nigeria allows the federal, state, and local governments to legislate with respect to pollution (Suleiman et al. 2017). At the federal level, the key leg- islation is the 2007 NESREA Act, which established NESREA as the agency under the FMEnv responsible for setting and enforcing environmental regulations,1 except for the Air Quality Management Planning for Lagos State 79 petroleum industry. Another important law is the 1996 such as paint manufacturing, textile, quarries—lack Petroleum Act,2 which assigned responsibility to the Fed- clarity, and there is no guidance on the methodolo- eral Ministry of Petroleum Resources (FMPR) for setting gies and protocols to calculate emissions from various and enforcing the Environmental Guidelines and Stand- sources, such as emissions factors for different emission ards for the Petroleum Industry in Nigeria (EGASPIN). sources (Ukeh 2021). Also significant is the Environmental Impact Assessment Act of 1992, the scope of which covers any project under- The 2011 National Environment Control of Vehicular taken by the government (at any level), or which requires Emissions from Petrol and Diesel Engines Regulations a government license or permit, and which could have a (Vehicle Emissions Regulations) are aimed at reducing significant impact on the environment. and preventing air pollution from automobiles. The reg- ulations also make provision for citizens’ right to clean Of potential significance for air quality are directives air and for the improvement of the health of Nigerians, C/Dir.1/09/20 and C/Dir.2/09/20, of the Commission especially in urban settings with high incidences of air of the ECOWAS, to set a common fuel sulfur standard pollution caused by the increased number of automo- for ECOWAS of 50 ppm by weight for both diesel and biles. The regulations set standards for specific pollutants gasoline fuels, and to establish Euro 4 and Euro 6 emission for different on-road vehicles manufactured after certain standards for light-duty vehicles and Euro 6 standards for years. However, the implementation of this regulation has heavy-duty vehicles, respectively. The directives lay down run into multiple obstacles, including enforcement of the more stringent standards for motorcycles and tricycles and ban placed on importing two-stroke engines, ­ prohibition call for the emission standards to apply to newly imported of vehicles that do not comply with emissions-­ reduction vehicles—whether new or used—from January 1, 2021. technologies, and conducting of annual testing of v ­ ehicles Euro 4 emission standards would apply to both light- and for gas emissions (Center for Science and Environment heavy-duty vehicles that are in the existing vehicle fleet from 2013; Ukeh 2021). January 1, 2025. To date, it does not appear that either directive has been implemented in Nigeria. The 2009 Permitting and Licensing System Regulations set provisions for the issuance of environmental permits to operators of stationary sources. However, the regulation is not specific on the nature or type of permit, lacks clarity 5.1.1.  EXISTING NATIONAL REGULATIONS about which phase of the construction or operation of a ON AIR QUALITY facility a permit is required, and offers no guidance to prepare and submit an application. Additionally, the few 5.1.1.1.  NON-OIL AND GAS permit requirements in the regulations—such as how REGULATIONS—NESREA ACT to quantify a facility’s emissions footprint to determine the type and nature of air permit required, protocols The 2014 Air Quality Control Regulations (Air Reg- to adopt in determining a facility’s emissions footprint, ulations) set provisions for the maximum permissible and emissions stack requirements—are not ­ science- limit values for six criteria pollutants, excluding PM2.5. based. Moreover, the terms of the permit are vague Standards for some pollutants exceed the WHO guide- and unrealistic. Most regulated entities are therefore lines threefold. Moreover, the standards do not set lim- not motivated or incentivized to prepare and submit air its for population exposure, and it is unclear if their pollution permits. NESREA does not currently implement definition was based on scientific country-level studies. auditing, monitoring, and evaluation of performance Under the Air Regulations, stationary sources and to ensure compliance with permits. Unfortunately, the facilities must submit annual emissions reports. How- regulators lack the financial, technical, and human ever, the emission limits for different source catego- resource capacities to effectively enforce compliance with ries—combustion of fossil fuel, industrial operations the permit conditions (Ukeh 2021). 80 Air Quality Management Planning for Lagos State Other regulations under the NESREA Act that have decommissioning phases (Olawuyi and Tubodenyefa implications for air quality and emissions produced by 2018). In relation to air emissions, the EGASPIN other mobile and stationary sources are the Pollution sets requirements regarding gaseous point-source Abatement in Industries and Facilities producing Waste emissions, which include their estimation, registration, Regulations, the Ozone Layer Protection Regulations, inventories, the installation of equipment to reduce or and Regulations for Sanitation and Waste Control, and prevent them, the implementation of air quality and for Energy and Industry. The 2011 Control of Bush or emissions-monitoring programs, and the installation Forest Fire and Open Burning Regulations were enacted of appropriate sampling points. to minimize and prevent the destruction of the natu- ral ecosystem owing to fire outbreaks and uncontrolled Fuel standards are established through the Nigerian burning of materials that may affect human health and Industrial Standards (NIS) issued by the Standards the environment because of emissions of hazardous and Organization of Nigeria (SON). In 2003, Nigeria criteria air pollutants. phased out leaded gasoline. In 2017, the Nigerian Industrial Standard for Petroleum Products established Despite the existing legal framework, there are increasing a low-sulfur policy through NIS No. 116 and 949. The environmental problems and air pollution in Nigeria, maximum permissible sulfur content in diesel was set which are largely due to the lack of compliance with at 50 ppm, 150 ppm for gasoline, and 150 ppm for environmental laws. NESREA currently does not kerosene. Currently, these standards lack government have the capacity to monitor pollution or engage in approval and implementation (Croitoru, Chang and technical discussions with regulated entities to gather Kelly 2020). In 2020 as part of a high-level meeting the information needed to establish adequate standards, of the ECOWAS, Nigeria agreed to set regulations which compels the agency to adopt regulations without for cleaner fuels and vehicles to permit a maximum of knowing emissions levels or existing technologies 50 ppm sulfur content for gasoline and diesel by 2021, (Suleiman et al. 2017). The compliance requirements a minimum of Euro 4 vehicle emissions standard for set by the legal and regulatory framework are emphatic all vehicles imported, and a plan to improve vehicle about enforcement for noncompliance but not clear efficiency for all vehicles imported (UNEP 2020). The about how regulated entities should realistically go about government had committed to adopting such standards demonstrating compliance, nor about the pathway by 2020, but the deadline, which was extended to 2021, or timeline to demonstrate compliance. In addition, was not met (SDN 2022). Currently, no specific date has penalties are rarely calculated and imposed on violators been set. In summary, despite the existence of official because the regulators lack the resources. In general, standards and formal commitments, fuel quality in enforcement actions are often implemented without Nigeria continues to be poor compared to other African proof of violation (Ukeh 2021). countries, even as the importation of dirty fuels continues (Croitoru, Chang and Kelly 2020). 5.1.1.2.  OIL AND GAS REGULATIONS—PETROLEUM ACT 5.1.1.3.  ADDITIONAL ACTS Under the 1969 Petroleum Act, the FMPR issued There are additional acts that also aim at controlling the EGASPIN in 1991, which was revised in 2002, atmospheric and other types of pollution in Nigeria. The 2016, and 2018. The EGASPIN is operated by Harmful Waste Act prohibits, without lawful authority, the Department of Petroleum Resources (DPR).3 the carrying, dumping, or depositing of harmful waste The EGASPIN establishes robust environmental in the air. The Environment Impact Assessment Act standards and requirements to be met by operators details the procedures and sectors required to perform during project approval, operations, closure, or environment impact assessments of potential negative ­ Air Quality Management Planning for Lagos State 81 impacts to the environment, including air resources. funding sources. No information was found on the level of The Environmental Impact Assessment Act is relevant to implementation of NEP’s policy statement. assessing the environmental impacts of the oil and gas sector and controls its air emissions. Nigeria has a comprehensive NAP to Reduce Short-Lived Climate Pollutants covering important air criteria pol- lutants. In 2019, after a 2-year consultation process, the 5.1.1.4.  INTERNATIONAL AGREEMENTS country’s National Council of Ministers approved a cross- sector action plan to reduce short-lived climate pollut- Nigeria is a signatory of multilateral agreements for ants (NAP-SLP). The plan identifies emissions levels and environmental protection and pollution control. Nigeria sources for PM2.5, SO2, NOx, and CO and other air and ratified the Vienna Convention (1987)4 and the Montreal climate pollutants, and prioritizes 22 abatement measures Protocol (1988)5 to protect the O3 layer, and the Stock- based on economic and engineering modeling. The plan holm Convention (2003)6 that regulates persistent organic introduces specific emissions reductions and sector policy pollutants (POPs). Regarding GHGs, Nigeria ratified the targets and is associated with achieving emissions reduc- Kyoto Protocol (2000) and the Paris Agreement (2016). tions of between 58 and 78 percent for PM2.5, SO2, NOx, In 2015, Nigeria submitted an NDC in the form of an and CO by 2030, if the plan were implemented (Federal unconditional contribution of 20 percent below business- Government of Nigeria 2018). The adoption of this action as-usual levels, and a 45 percent contribution conditional plan elevated the importance of tackling air pollution at on international support by 2030. The government sub- the national level. The implementation of the NAP-SLP mitted an updated NDC in June 2021 with unconditional is coordinated by FMEnv’s Climate Change Department. contribution still at 20 percent below business as usual, However, because the action plan includes targets and but a slightly more ambitious conditional contribution of sectoral actions for the reduction of atmospheric pollut- 47 percent, with the addition of two new sectors (waste ants, it is unclear if such policy actions should be headed and water) to the existing five: AFOLU, Energy, Oil and by the Climate Change unit or the Pollution Control and Gas, Industry, and Transport. The enhanced NDC will Environmental Health (PCEH) unit.7 cover short-lived pollutants, including black carbon, an air pollutant with a high incidence of morbidity and pre- mature mortality (Federal Government of Nigeria 2021). 5.1.3.  FEDERAL INSTITUTIONS 5.1.3.1.  FEDERAL MINISTRY OF 5.1.2.  NATIONAL STRATEGIC VISION ENVIRONMENT FOR AQM The FMEnv leads the governance architecture for the Nigeria does not have a stand-alone policy or strategy on protection of the environment in Nigeria. The ministry pollution control and AQM. However, it has the National administers environmental law and policy and shoulders Environmental Policy (NEP) of 2016, which sets out the a key responsibility—to ensure that environmental mat- Federal Government’s vision for AQM. The NEP con- ters are adequately mainstreamed into all developmen- tains several policy statements that express the intention of tal activities in the country. The ministry’s mandate was the Federal Government to improve air and atmospheric further strengthened by an NAP for the Promotion of resources institutional arrangements, strengthen guidelines Human Rights. NAP recognizes Nigerians’ collective and standards, enhance enforcement capacity, improve rights to a safe, healthy, and ecologically sustainable envi- monitoring of emissions, and promote efficient transport ronment for the present and future generations (Ukeh systems (Federal Ministry of Environment 2016). How- 2021). However, the ministry does not have a strate- ever, NEP policy statements lack specific targets, sector gic approach to the regulation-making process, or the abatement measures, responsible parties, timelines, and technical and financial capacity to adopt other policy 82 Air Quality Management Planning for Lagos State instruments to guide the country’s efforts to improve air to AQM in the oil and gas sector.10 In 2018, an amend- quality. In 2021, the FMEnv had allocations correspond- ment to the NOSDRA Act was passed by the Nigerian ing to 0.34 percent of the total budget appropriations Senate Committee on Environment. Based on a 2018 act.8 Air quality does not seem to be a priority within the report of the Senate Committee on Environment, FMEnv’s budget. For example, in 2021 only N33 million A Bill for an Act to Amend the National Oil Spill Detection and (approximately US$8,000) was allocated to air quality Response Agency, Act 2006 and for Other Matters Connected monitoring equipment and studies on air pollution.9 The Therewith (SB557),11 changes proposed to the functions FMEnv and other ministries, departments and agencies of NOSDRA which could potentially give the agency (MDAs) rely heavily on intervention funds from multilat- jurisdiction for AQM were excluded from the final eral and bilateral development institutions to battle both amended bill. The exclusion suggests that the functions short-lived and long-lived air pollutants (Ukeh 2021). of NOSDRA are intended to be limited to pollution from oil spillage, but not gaseous emissions. Based on The FMEnv leads a comprehensive set of departments, this, the roles NOSDRA will play in regulating air qual- institutions, and regional offices. The ministry is made up ity matters in the oil and gas industry remain unclear of six technical departments, which include PCEH and when the 2018 NOSDRA Amendment Bill is eventually Climate Change departments, and seven regulatory agen- signed into law. cies, which include NESREA and the National Oil Spill Detection and Response Agency (NOSDRA). The min- istry is structured into six zonal operational offices and 5.1.3.4. NIMET 36 state-level field offices. The state zonal offices work in partnership with and provide operational guidance to their The Nigeria Meteorological Agency (NIMET) is involved respective state ministries of environment (Ukeh 2021). in air pollution monitoring and currently pursues objec- tives related to air quality analysis and policy advising. NIMET is an agency under the Federal Ministry of Avia- 5.1.3.2. NESREA tion. Its statutory mandate is continuous observation of national weather and climate and generation of timely NESREA has a series of policy instruments to implement meteorological, hydrological, and oceanographic data environmental policy and air pollution control, composed to support national needs and in fulfilment of relevant mainly of enforcement instruments. The NESREA Act international obligations. NIMET maintains 60 weather empowers the agency with multiple instruments to enforce observation and air quality monitoring stations across the environmental law. The agency has the power to perform country. In relation to air quality, the agency has a Dob- inspections and searches, forbid polluting equipment, son O3 spectrophotometer at its Regional Meteorological issue enforcement notices, establish mobile courts, con- Training Center in Lagos. It has installed environmental duct public investigations, and prosecute and take legal safety monitoring instrument gas analyzers at its observa- action against citizens or companies violating the law. The tion centers in Abuja, Lagos, Enugu, Kano, and Maidu- NESREA Act has been discussed in Section 5.1.1.1. guri Airports to monitor CO, CO2, NOx, PM2.5, PM10, and O3. These gas analyzers are currently not collecting data. BAM gas analyzer was deployed at the National 5.1.3.3. NOSDRA Hospital, Abuja in January 2019 to measure the listed air pollutants. The agency also had a portable Technolo- NOSDRA is responsible for surveillance and compli- gies Ozone Monitor Model 202 installed at its headquar- ance assurance for all existing environmental legislation ters Abuja in 2018 to monitor for tropospheric O3. The and regulations in the oil and gas sector. The National agency has also adopted a comprehensive list of air qual- Oil Spill Detection and Response Agency Act of 2006 ity and GHG emissions objectives to be implemented did not give any specific role to the agency with respect across the country (Ukeh 2021). Air Quality Management Planning for Lagos State 83 5.1.3.5.  OTHER INSTITUTIONS and Water of the MoE; and the General Manager of LASEPA. pollution Other institutions with mandates related to air ­ are the FMPR, SON, National Automotive Design and The 2017 law gives LASEPA broad powers to, among Development Council (NADDC) under the Federal others, “monitor and control all forms of environ- Ministry of Industry, Trade and Development, and the ­ mental degradation from agricultural, industrial and Federal Ministry of Health. government operations; set, monitor and enforce stand- ards and guidelines on vehicular emissions; survey and monitor surface, underground and potable water, air, land and soil environments in the state to determine 5.2.  LAGOS STATE’S pollution levels in them and collect baseline data; and LEGAL AND REGULATORY prepare a periodic master plan to enhance capacity building for the Agency and for the environment and FRAMEWORK natural resources management.” The law also estab- lishes that “the funds of the Agency shall consist of: (a) such monies as may be appropriated to the Agency Lagos’ institutional air quality framework faces mul- by the state; and (b) all subscriptions from the charge, tiple development challenges. The existing legal and fees and charges for services rendered by the Agency.” regulatory framework lacks certain key elements that are Thus, the law specifically provides for the agency to required for adequate AQM. Most regulations in Lagos supplement its appropriated funding with (for example) depend on the national framework, which itself is inad- permit fees, emission fees, and other charges paid by the equate. AQM plans have not been developed, nor have organizations it regulates. jurisdictional monitoring and reporting requirements been implemented. Although the LASEPA under the Nigeria’s federal structure implies that state legislation Lagos State Ministry of Environment has the statutory may equip state agencies with powers and functions role of regulating air quality in the state, multiple institu- duplicative of the Federal Government. For example, tions have duplicative or overlapping functions related to both NESREA and LASEPA are empowered to moni- pollution control—which blurs the lines of accountabil- tor and control industrial pollution and to set standards ity—while coordination, enforcement, and implementa- on vehicular emissions. This creates the potential for tion capacities remain weak. duplication of effort and even conflicting standards. At present, coordination between NESREA and LASEPA Lagos has adopted environmental legislation and estab- appears satisfactory, possibly because both the Federal lished a Lagos State Ministry of Environment and Water President and the Governor of Lagos State are from the Resources (LMoE) as well as several parastatal agencies same political party. Lagos State has not yet established with environmental responsibilities. The key environ- its own standards and currently abides by federal air mental legislation in Lagos State is the Environmental quality and fuel standards. Management Protection Law of 201712, which consoli- dated and expanded the previous environmental laws. Another issue is the challenges that LASEPA encounters Part VI of that law establishes LASEPA as a parastatal in regulating the operations of federal establishments agency within LMoE, with a board comprising a chair- that operate within Lagos State. For instance, LASEPA man, three public members, and eight ex officio mem- is unable to regulate fuel quality within Lagos, which has bers: the permanent secretaries of the Ministries of impacts on vehicular emissions. This is due to the ina- Health, Agriculture, Works and Infrastructure, Transpor- bility of Lagos State to determine the quality of refined tation, Finance, and Local Government and Community petroleum product imports and the distribution of the Affairs; the Director of Environmental Services, Sewage imported products within the state. 84 Air Quality Management Planning for Lagos State Second, Lagos State’s existing legislation does not require with statutory responsibility for AQM in the state. The LASEPA to adopt specific plans to achieve air quality Lagos State Waste Management Agency (LAWMA) is standards and control pollution, a shortcoming of the fed- responsible for solid waste management, and the Lagos eral regulations adopted by LASEPA (Center for Science State Waste Water Management Office (LASWMO) is and Environment 2013). This further renders actions by responsible for sewage collection and treatment. LASEPA in air pollution control ineffective and results in the inefficient allocation of resources. An AQM plan is LASEPA was established in 1996 to enforce measures just being developed for Lagos State through the PMEH to combat environmental degradation on manufactur- intervention. ing premises. Figure 5.1 shows the present organization chart, which comprises seven scientific offices, eight zonal Third, the adopted legal and regulatory framework does offices, four scientific units, and seven non-scientific units. not have air quality and emissions monitoring require- In 2021, it was slated to receive only the equivalent of ments for specific jurisdictions, or requirements to report US$1.25 million from the state budget. That means that compliance with national air quality standards. Fourth, most of LASEPA’s funding has to come from fees and an airshed delineation or transboundary air management is annual Environmental Development Charge on industry. not mandated or incentivized by existing regulations. As a result, LASEPA does not have an understanding of the Under the Lagos Environmental Management Protec- airshed responsible for air pollution within Lagos. This tion Law of 2017, LASEPA has the legal authority to effectively limits any collaborative efforts among EPAs enforce emission standards on industrial, agricultural, across geographical boundaries to monitor and manage and government sources and on generating plants in transboundary air pollution. residential and commercial areas, to set and enforce vehicle emission standards, and to set up an air quality Finally, current legislation is heavy on enforcement monitoring network. However, it mostly lacks the techni- mechanisms but is less developed on other policy tools cal capacity and staff to do so effectively. Training and to incentivize compliance, tools such as market-based capacity building, as well as additional staff and equip- instruments like voluntary certification programs, pol- ment investments, are needed for LASEPA to effectively lution taxes and emissions trading systems, which when fulfill its statutory role in AQM. This will require an combined with enforcement tools would likely yield bet- increase in budget. As a parastatal, the agency has the ter policy results. capacity to be self-funding and already derives a large fraction of its budget from fees, fines, and the Environ- mental Development Charge. 5.3. ORGANIZATIONS In Lagos, the discharge of injurious gases that cause air INVOLVED IN LAGOS STATE pollution is an offence, and individuals and corporate bodies can be fined for causing pollution. Over time, LASEPA has demonstrated the capacity to enforce In Lagos State, LMoE is charged with securing a cleaner, regulations on noise pollution in Lagos. However, the healthier, and more sustainable environment conducive agency lacks the instruments and training to effectively to tourism, economic growth, and the wellbeing of all control emissions of air pollutants and GHGs. A key citizens. It serves as the coordinating ministry for all the objective of the PMEH program is to enhance the offices and parastatals under Environment. The key objec- capacity of LASEPA to effectively monitor and regulate tive of the ministry is to ensure that environmental mat- air pollution. To realize this objective, the PMEH has ters are adequately mainstreamed into all developmental engaged LASEPA personnel in on-field and classroom activities in the state. LMoE is made up of two offices capacity-building sessions on the various components and seven parastatal agencies. LASEPA is the ­ parastatal of AQM. Air Quality Management Planning for Lagos State 85 86 FIGURE 5.1.  ORGANIZATION CHART FOR LAGOS STATE EPA General Manager Zonal Office Directorate Chemical Water and Monitoring, Amuwo Agege Badagry Ikorodu Apapa Ojo Alimosho Lekki Noise and Research and Natural Finance Admin and Land Laboratory Compliance Zonal Zonal Zonal Zonal Zonal Zonal (Coming (Coming Emissions and Hazardous Resource and Human Pollution Services and Office Office Office Office Office Office Soon) Soon) Control Development Materials Protection Accounts Resources Control Department Enforcement Department Department Management Department Department Department Department Department Department Information Data Hydrocarbon Budget Communi- Internal E-Waste Public Management Billing and Legal Engineering and Procurement cation Audit Management Relations Enquries and Unit Gases Storage Unit Unit Planning Unit Technology Unit Unit Unit Complaints Unit Unit Unit Unit Scientific Departments Non-scientific Departments Scientific Units Non-Scientific Units Air Quality Management Planning for Lagos State Along with NESREA, several other federal MDAs are in chapter 2, the World Bank PMEH program has taken stakeholders with interest and influence in AQM in Lagos. the first steps to fill these gaps in Lagos by (a) sponsor- The Nigerian Ports Authority, which controls the two ing one year of continuous data collection at six selected ports of Apapa and Tin Can Island, the Airports Author- locations in Lagos State, (b) funding the development of ity, and the Nigerian Railway Corporation, reports to the an emissions inventory for the state, and (c) funding ini- Federal Ministry of Transportation. Under the FMPRs, tial efforts to model specific episodes during the year of the NNPC has exclusive authority to import refined petro- monitoring to compare those results with the measured leum products, which are distributed across the country by data. The LASG should build on these initial steps. its subsidiary, the Pipelines and Product Marketing Com- pany (PPMC) (Ehinomen and Adeleke 2012). Tertiary- Ground-based air quality information in Nigeria is level hospitals report to the Federal Ministry of Health. In sparse. The FMEnv and other MDAs own air quality the past, LASEPA has been limited in its ability to enforce monitoring stations, but there is little information on regulations at federal institutions located in Lagos due to their location, functionality, and datasets and whether jurisdictional conflicts with NESREA. the generated data are actually informing public deci- sions. Until this project, analyses of air quality had been based on irregular, short-term, sampling efforts. This pre- 5.4.  EXISTING REGULATIONS cluded the country and cities like Lagos from developing a longer-term understanding of the dynamics of air pol- IN LAGOS STATE lution. Due to the lack of consolidated information on air qual- LASEPA has largely adopted the NESREA standards ity, most national and international studies use satel- and regulations rather than establish its own. Table 5.1 lite observations, aircraft observations, and simulation looks at the Lagos State and national AQM policies, reg- models to understand pollution sources and the concen- ulations, and standards from the perspective of recom- trations. Robust studies of other pollutants, such as par- mended international AQM systems aimed at realizing ticulate matter, require near-source measurements, which the five strategic AQM goals.13 are limited in the country. 5.5.  STRENGTHENING THE LASEPA still needs to work on the following priority areas to enhance its AQM information system: conduct SCIENTIFIC BASE FOR AQM long-term monitoring of pollutants, including PM2.5 in several representative locations, collaborate with the LSMoH to centralize city health data, extend and To effectively manage air quality requires systematic, improve the present emissions inventory, conduct refined ongoing measurements of ambient air pollution levels source apportionment studies, and establish a platform (air quality monitoring), a detailed understanding of for public dissemination of air quality information. This the sources of air pollution (emissions inventory), and will require funding for the procurement of new equip- the ability to predict the effects of changes in the emis- ment and the maintenance of existing infrastructure and sion inventory on ambient levels of pollution (air quality datasets, integration of new technologies such as satel- modeling). Until now, none of these three capabilities lite data and machine learning to augment ground-based have been in operation in Lagos and Nigeria. A previ- monitoring, establishment of standards for measuring ous effort at developing an emissions inventory in Nigeria pollutant emissions from sources and for monitoring air highlighted critical missing links in the development of quality, and improvement of the community’s accept- an emissions inventory infrastructure in a typical Nige- ance of public air monitoring infrastructure to decrease rian environment (Fagbeja et al. 2017). As documented vandalism of monitoring equipment. Air Quality Management Planning for Lagos State 87 TABLE 5.1.  AQM LAWS, REGULATIONS, POLICIES, AND INSTITUTIONS AT LAGOS STATE AND FEDERAL LEVELS Policy, regulation, standard Lagos State level National level 1. Ambient Air Quality a. Part VI of Lagos State Environmental Part VI of National Air Quality Control Standards (AAQS) Regulations, 2017 (LMoE – LASEPA) Regulations, 2014 (FMEnv – NESREA), references and recognizes the NAAQS established the NAAQS. consistent with the federal regulations. b. Lagos environmental regulations adopts the languages of the federal (NESREA) air quality regulations. 2. Ambient Air Quality a. Part VI of Lagos State Environmental a. National Air Quality Control Monitoring and Modeling Regulations, 2017 (LMoE – LASEPA) Regulations, 2014 (FMEnv – NESREA). Program referenced air quality monitoring b. EGASPIN, 1991, Revised 2002, 2016, requirements. 2018 (FMPR – DPR). b. Lagos State adopts most of the federal (NESREA) air quality regulations. 3. Standards for Stationary a. Part VI of Lagos State Environmental a. Part II of National Air Quality Control Sources Regulations, 2017 (LMoE – LASEPA). Regulations, 2014 (FMEnv – NESREA). b. Lagos State adopts most of the federal b. National Environmental (Control of (NESREA) air quality regulations. Bush or Forest Fire and Open Burning) c. Industrial Guidelines – LASEPA. Regulations, 2011 (FMEnv – NESREA). 4. Standards for Mobile a. Part VI of Lagos State Environmental a. Part III of National Air Quality Control Sources Regulations, 2017 (LMoE – LASEPA). Regulations, 2014 (FMEnv – NESREA). b. Lagos State adopts most of the federal b. Control of Vehicular Emissions from (NESREA) air quality regulations. Petrol and Diesel Engines (2011). 5. Compliance Requirements a. Part VI of Lagos State Environmental Part VII and X of National Air Quality and Penalties Regulations, 2017 (LMoE – LASEPA). Control Regulations, 2014 (FMEnv – b. Lagos State adopts most of the federal NESREA). (NESREA) air quality regulations. 6. Operating Permit Program a. Part VI of Lagos State Environmental Part IX of National Air Quality Control Regulations, 2017 (LMoE – LASEPA). Regulations, 2014 (FMEnv – NESREA) b. Lagos State adopts most of the federal (NESREA) air quality regulations. 7. Continuous Emissions No emissions monitoring regulations exist. No emissions monitoring regulations exist. Monitoring 8. Area Designation for Air No related policies or legislation found. No related policies or legislation found. Quality Planning 9. Climate Change Program Lagos State adopts the National Policy on National Policy on Climate Change – 2012. Climate Change. Energy and Alternative 10.  No related policies or legislation found. Part IV of National Environmental (Energy Energy Sector) Regulations (2014). 11. Emissions Trading Policy No emission trading policy found. No emission trading policy found. 88 Air Quality Management Planning for Lagos State The amendment should have a requirement for the 5.6.  NEW REGULATORY Federal Government to lead a multi-stakeholder discus- AND ENFORCEMENT sion and adoption of a National Air Quality Strategy with clear emissions reductions targets, sectoral actions, STRUCTURES and budget allocations. The NESREA Act amendment should also mandate federal and state governments to work together to delineate regional airsheds. State gov- The current air quality regulatory framework in Lagos ernments should be required to establish air zones for air State and Nigeria is insufficient to tackle increasing pollu- quality monitoring and management purposes based on tion challenges. This is due to the identified institutional airshed dynamics. The NESREA Act amendment should and legislative deficiencies. Therefore, the Lagos State exhort the Federal Government to develop an AQI meth- and Federal Governments need to modify the existing odology to be adopted by state governments. Finally, the legal and regulatory framework to promote adequate proposed amendment should include demanding state governance structures and more effective enforcement of governments to comply with air monitoring and report- pollution control. The following four recommendations ing requirements, develop air pollutant emission inven- are aimed at establishing new regulatory and enforce- tories, and disclose information to the public on the ment structures. state of air quality. Lagos State must therefore amend its regulatory framework to also foster cooperation within Strengthen current ambient air quality standards estab- the state. LASEPA, through its regional offices, can then lished in the 2014 Federal Air Quality Control Regula- coordinate with the local government on the adoption tions. A standard for PM2.5 needs to be established based of  state implementation plans (SIPs) and air zone moni- on scientific studies, and other standards need to be toring and management plans incentivizing transbound- revised based on scientific knowledge. LASEPA should ary cooperation. create a schedule for the adoption of lower concentration limits to comply with the WHO’s recommendations, and Strengthen NESREA, LASEPA, and other state EPAs a national exposure reduction target for key pollutants enforcement capacities. With the support of interna- such as PM2.5. This will represent the realities in the state tional institutions, NESREA should work with LASEPA and provide a basis for improving the existing regulations. and other state EPAs to devise measures to enhance national and state institutional capacities to (a) develop Amend the NESREA Act to establish clear and differen- sound air quality regulations; (b) determine realistic emis- tiated institutional roles and responsibilities. Federal insti- sions standards across different emissions source catego- tutions and state institutions need to have differentiated ries; and (c) develop practical enforcement mechanisms, and complementary roles and responsibilities to enforce such as through the use of incentives and market-based air quality control measures with regulated entities and instruments, with adequate science-based infrastruc- to implement air quality policy in a way that avoids the ture, including research and development and meteoro- duplication of effort. Lagos State Management Protec- logical observation technologies. Regulated institutions, tion Law also needs to be revised accordingly and clarify including LASEPA, should implement a robust staff- roles and responsibilities. training program to promote professionalism, integrity, consistency, and transparency for AQM. LASEPA should Amend the NESREA Act, and by extension the Lagos explore collaboration with international donor agencies State Environmental Protection Laws, to require plan- to fund a technical service consultancy to equip and train ning and monitoring at the f ­ederal and state levels. LASEPA personnel on air quality enforcement strategies. Air Quality Management Planning for Lagos State 89 the civil society, and the public to take bold, evidence- 5.7.  THE HEALTH SYSTEM based actions to stop pollution at source as a key pub- SHOULD BE AN ACTIVE lic health measure for health prevention. It is essential to build multisectoral partnerships. Pollution prevention ACTOR strategies that hold great promise include a transition to less-polluting renewable energy sources, a reduction in the reliance on fossil fuels, promotion of less-polluting The health sector in Lagos should proactively tackle public transport, proper management of wastes, and the health impact of air pollution and act with a strong incorporation of pollution prevention into all forward advocacy voice to promote urgent intervention actions to planning. reduce air pollution emissions and population exposure, perform continuous health impact evaluation, improve HIA is a critical element of air quality assessment, and expand the system of health information collection, management, and planning. The institutional and and initiate epidemiologic research on air pollution. policy framework for HIA and health monitoring of air pollution needs to be improved. HIA provides a There is a major need for the health sector in Lagos to basis to draw policy recommendations that should be be better informed about the health hazards of air pol- considered in the AQM plan for Lagos. The Lagos lution. Air pollution is a powerful causative factor of health sector should be informed about the results of mortality and morbidity. This association is not widely air pollution monitoring and should be able to perform acknowledged within the Lagos health care community the necessary HIA to quantify the health benefits of and appropriate education on the scientific evidence for changes in air pollution levels. Appropriate education it should be pursued. There is a major need to educate of technical personnel should be undertaken to equip personnel on how pollution exposure is driving the rise them with the necessary professional skills, and the of NCD because air pollution impedes the formation health information system should be upgraded. of new human capital and undermines the prospects of future development by causing damage across the entire The health information system needs to be fundamen- population. This is particularly true in children. It has tally reshaped. There is a lack of knowledge of the most been shown that the two periods when pollution expo- important health events occurring in the Lagos popula- sure is the most critical to the health status of an individ- tion because the current health information system covers ual at later stages in life are during gestation and during only the public sector. The system should be redesigned the first few years after birth. As the WHO recommends, to enable it to acquire timely and reliable information member countries should “enable health systems, including on the most important health events taking place in the health protection authorities, to take a leading role in raising aware- entire population, including vital statistics such as births ness in the public and among all stakeholders of the impacts of air and deaths. pollution on health and of opportunities to reduce or avoid exposure” (WHO, 2015). Promote research and build research capacity on air pollution, human health, and the economy in Lagos/ Health systems have a key role in monitoring and Nigeria research institutions. Support for research will responding to air pollution health risks and should raise build long-term, local scientific and technical capacity their voice. The Lagos State Ministry of Health (LMoH), and strengthen the national economy. The creation of a together with other relevant health ­ institutions, should research infrastructure is an investment in the future, and recognize the growing danger of ambient air pollution it will be of particular value to start epidemiologic studies and engage health care personnel (doctors and nurses), and derive ERFs for the Lagos/Nigeria population. 90 Air Quality Management Planning for Lagos State Federal Ministry of Environment. 2016. “National Policy REFERENCES on the Environment.” Olawuyi, D. S., and Z. 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Ehinowen, C., and A. Adeleke. 2012. “An Assessment of 2017. “A Deep Dive into the Review of National the Distribution of Petroleum Products in ­ Nigeria.” E3 ­ Environmental Standards and Regulations Journal of Business Management Economics 3(6): 234–241. ­ Enforcement Agency (NESREA Act).” Fagbeja, M. A., J. L. Hill, T. L. Chatterton, J. W. S. Long- Ukeh, Felix. 2021. “Stakeholders and Institutional hurst, J. E. Akpokodje, G. I. Agbaje, and S. A. Halilu, ­Assessment Study, Air Quality Management ­Program 2017. Challenges and opportunities in the design in Lagos, Nigeria.” and construction of a GIS-based emissions inventory UNEP (UN Environment Programme). “West A ­ frican infrastructure for the Niger Delta region of ­ Nigeria. Ministers Adopt Cleaner Fuels and Vehicle Environmental Science and Pollution Research ­S tandards.” https://www.unep.org/news-and​ 24(8): 7788–7808. -­stories/story/west-african-ministers-adopt-cleaner​ Federal Government of Nigeria. 2018. “Nigeria’s -fuels-and-vehicles-standards. National Action Plan (NAP) to reduce Short-Lived World Health Assembly, 68. (2015). Health and the Climate Pollutants.” ­ environment: addressing the health impact of air Federal Government of Nigeria. 2021. “Nigeria’s Nationally pollution. World Health Organization. https://apps​ Determined Contribution.” https://www4​ .unfccc.int​ .who.int/iris/handle/10665/253237. /­sites/ndcstaging/PublishedDocuments/Nigeria%20 First/NDC%20INTERIM%20REPORT%20SUB​ MISSION%20-%20NIGERIA.pdf. Air Quality Management Planning for Lagos State 91 CHAPTER 6 RECOMMENDED AIR QUALITY MANAGEMENT STRATEGY FOR LAGOS STATE 6.1.  INSTITUTIONAL DEVELOPMENT The State of Lagos, and indeed Nigeria, needs a new policy vision for AQM that is supported by regulatory changes. The regulatory changes discussed in ­section 5.5 will provide a more stable basis for the implementation of Lagos State’s and Nige- ria’s new policy on air quality. The following seven recommendations, however, can be worked in parallel to the proposed regulatory modifications. LASEPA to undertake a holistic assessment of Lagos State’s AQM ­ challenges and opportunities as identified by the PMEH program and develop a policy strategy to engage stakeholders drawn from the ­ relevant MDAs, private sector, academia, and the civil society. The main purpose of this engagement is to chart the State Air Quality Strategy with air pollution reduction goals, specifically for the pollutants of concern. The strategy should also have an implementation plan with specific cross- sectoral actions, responsible actors, budget allocations, and a monitoring plan. The strategy will develop a principal framework for the state and local government efforts to protect air quality across the state, giving considerations to the existing national laws and regulations guiding air quality. It will focus on enhancing the capacity to respond to criteria and climate change air pollutants with adequate science-based infrastructure, including research and development initiatives and meteorological observation technologies. The strategy will also focus on strengthening the collection and reporting of data by the relevant public and private institutions, which will be useful for estimating and inventorying emissions of air pollutants and GHGs. The policy should have a broad communication strategy and its level of implementation be periodically reported to the State Executive Council. Ensure that the Lagos State air quality institutions work collaboratively with federal air quality institutions. The State Air Quality Strategy should devise mechanisms to Air Quality Management Planning for Lagos State 93 promote collaboration between the state and federal capacities, identifying the state, location, and integrity institutions to achieve their respective mandates with of air monitoring equipment, laboratories, and data. limited overlap and duplication of efforts. LASEPA Based on results, design and fund a plan to establish an should establish clear, measurable objectives with long- air quality information system based on a consolidated term roadmaps, including mechanisms for information air monitoring network, capable of reporting real-time dissemination, data sharing between agencies, and peri- data and responsive to state and federal assessment odic assessment of health and economic impacts. The and monitoring criteria. The Governments of Lagos process should consolidate and streamline air quality State and Nigeria should join efforts to build partner- regulatory, monitoring, and enforcement functions of ships with national and international research institu- various state agencies to minimize duplication and over- tions to plant the seed for the future development of lap and ensure better use of public resources, minimize air quality forecast systems. Lagos State should work burden on regulated entities, and maximize effective- on the following priority areas to enhance its AQM ness. The State Air Quality Plan should also leverage information system: conduct long-term monitoring Nigeria’s signatory status to multilateral agreements for of pollutants, including PM2.5, in several representa- environmental protection and pollution control—the tive locations, centralize city health data, implement Vienna Convention (1987),35 the Montreal Protocol an emissions inventory of air pollutants, and conduct (1988),36 and the Stockholm Convention (2003)37—to refined source apportionment studies. explore the co-benefits of air quality and GHG emis- sions monitoring to support Nigeria’s reporting on the Work with civil society organizations (CSOs) and the NDC. Nigeria’s updated NDC should cover short-lived media. By implementing training workshops for journal- pollutants including black carbon, an air pollutant with ists and public sensitization campaigns, the Lagos State high morbidity and premature mortality incidence (Fed- Ministry of Environment can collaborate to increase eral Government of Nigeria 2021). the general public’s knowledge about air pollution and its health effects. Working with CSOs to increase the Work toward establishing internationally standard- citizenry’s awareness of its rights to clean air, and the ized air quality research facilities in LASEPA and existing mechanisms to sanction violations, will improve other state-owned educational institutions to develop citizens’ accountability and engagement. an air pollutant database across sectors. The institu- tions should partner with NESREA to delineate the Strengthen courts to effectively rule against individuals air quality regions (airsheds) into which the state falls and corporations that violate air pollution control leg- within Nigeria for enhancing cross-boundary collabora- islation. This can be effectively achieved through train- tion with relevant states to improve air quality planning ing programs for judges, the sharing of case studies of within Lagos. The air pollutant database developed by effective rulings, and increasing LASEPA’s prosecution the institutions should support setting realistic targets capacities. for the state’s air pollution reduction strategies and pro- vide support for setting national air pollution ­ reduction Strengthen the financial capabilities of LASEPA by targets. An SIP designed by LASEPA should encour- enhancing funding through line charges, taxes, and age the establishment of policies, regulations, standards, levies, in addition to statutory budgetary allocations. research, technologies, and so on. This will position LASEPA to acquire the necessary equipment and build human and infrastructure capac- Assess current state monitoring capabilities, and ity to implement the State Air Quality Strategy with- develop and implement a strategy to establish air qual- out recourse to support from polluters. This will also ity information systems. The Lagos State Ministry of enhance LASEPA’s capacity to effectively enforce estab- Environment should assess actual air quality monitoring lished regulations. 94 Air Quality Management Planning for Lagos State it down into simple, color-coded bins that give peo- 6.2.  PUBLIC INVOLVEMENT— ple an instant visual grasp of pollution levels in their AQI surroundings, enabling them to develop the necessary alertness. The development of an Air Quality Index provides a While the methods to monitor air pollution and estimate platform for public awareness and information dissem- its health impacts are becoming standardized across the ination that essentially ensures that the public under- globe, this is not the case for methods used for calculat- stands the level of air quality within their vicinity and ing an AQI and the AQI nomenclature. These methods, participates in protecting public health. An AQI uni- and the degree of alertness disseminated by health alert fies the complicated science of pollution composition, systems, vary depending on different countries’ interpre- exposure rates-based health severity, ambient stand- tation of thresholds for regulatory purposes and back- ards, measurement and standard protocols and breaks ground conditions. FIGURE 6.1.  COMPARISONS OF THE VARIATIONS IN BREAKPOINTS AND INDEX NOMENCLATURE ACROSS SPECIFIC COUNTRIES Air Quality Management Planning for Lagos State 95 FIGURE 6.2.  SEASONAL CYCLE OF PM2.5 MONITORED FROM SIX STATIONS IN LAGOS, AUGUST 2020 TO JULY 2021 120 100 80 60 40 20 0 JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Abesan Ikorodu Jankara Lasepa NCF Unilag Based on a review of methodologies from seven respective country specifications. The general under- ­countries—the US, the EU, the UK, India, China, Repub- standing is that GREEN refers to good air quality and lic of Korea, and Singapore— to develop an AQI cen- BROWN and PURPLE indicate severe air quality. tered on air quality breakpoints and timescale variations, comparative AQIs for Lagos State have been developed. The most used/adapted methodology in the world is The AQI for Lagos used the 12-month air quality moni- from the US. According to this methodology, taking toring data from the six monitoring stations in the state. PM2.5 as the limiting pollutant, between August 2020 and The process relies on the average seasonal and diurnal July 2021, the City of Lagos experienced only 2 p ­ ercent cycles of the concentrations of PM2.5, PM10, and the other of days in category GOOD, 29 percent of days in cat- pollutants monitored from the sites (Figure 2). The data egory MODERATE, 45 percent of days in category were available at 5-minute intervals for 1 year, spanning UNHEALTHY FOR SENSITIVE PEOPLE, 23 ­percent August 2020 to July 2021. A summary of monthly PM2.5 of days in category UNHEALTHY, and 2 percent of concentrations is presented in Figure 2. Wintertime highs days in category VERY UNHEALTHY. There were no and rainy season lows are immediately evident in the data, SEVERE alert days. with highs around 120 µg/m3 and lows under 20 mg/m3. The presence of higher commercial and industrial activity There is no evidence that the current national air ­quality in the Abesan area is represented in its higher averages, standards operational in Lagos State, and in Nigeria, compared to the other five stations. have been developed based on extensive monitoring, emissions inventory development, and modeling. Con- Figure 6.3 shows a Microsoft Excel-based AQI calculator sequently, in developing the methodology for an AQI developed to explore the methodologies and their inter- in Lagos, there has to be a scientific basis to establish pretations for an application using the ambient-monitor- new standards. This will establish clearly defined break- ing data from the Lagos network. points and an AQI range for each pollutant, centered on evidence-based health and economic impacts of Table 6.1 presents a summary of an application of the local air quality. The recommendation is for LASEPA to seven methodologies for the City of Lagos, using the build on the outcomes of the PMEH study and ensure data collected from the six ambient-monitoring stations. expanded, continuous air-quality monitoring across The results are binned and colored according to the Lagos State. 96 Air Quality Management Planning for Lagos State FIGURE 6.3.  AQI CALCULATOR PAGE TABLE 6.1.  COMPARISON OF AQI RESULTS DERIVED FOR LAGOS PM2.5 % points in each bin USA EU UK India China S.Korea Singapore 2% 1% 1% 21% 30% 0% 2% 29% 6% 9% 63% 63% 0% 73% 45% 5% 20% 11% 4% 0% 23% 23% 54% 15% 3% 1% 0% 2% 2% 27% 14% 2% 2% 0% 0% 0% 7% 13% 0% 0% 0% 0% 10% 7% 4% 8% Air Quality Management Planning for Lagos State 97 TABLE 6.1.  (Continued ) PM10 % points in each bin USA EU UK India China S.Korea Singapore 10% 1% 0% 9% 9% 2% 9% 80% 4% 2% 40% 80% 29% 80% 7% 4% 6% 49% 10% 39% 10% 1% 40% 4% 1% 1% 25% 1% 1% 39% 5% 1% 1% 3% 1% 1% 12% 7% 1% 0% 2% 0% 7% 9% 7% 51% FIGURE 6.4.  RECOMMENDED AQM ACTIONS FOR LAGOS Air Quality AQM Investment Target Policies 35 ug/m3 • Increase MSW collection by 25% USDm (Reduction of • Euro 4 vehicles/fuels (13% of fleet) 200–300 10ug/m3) • Reduce industrial emissions by 25% • Reduce “other” emissions by 10% Outcomes Financing Reduction in USDm 200–300 mortality: (Green bonds, 3,598 (low) climate funds, 6,840 (high) multilateral) annual premature mortality by 3,598–6,840 deaths, over 6.3. RECOMMENDED half of which are infant deaths. Such premature mor- AQM ACTIONS tality is valued at US$235–1,691 million or between 0.33–2.35 percent of Lagos’ GDP. Given the large health impacts associated with air pol- Poor air quality is an urgent public health problem in lution that have been estimated for Lagos, immediate Lagos and requires an urgent response. Recommended action is needed. An initial goal would be to lower ambi- actions to address air pollution in Lagos include the ent PM2.5 air pollution by 10 µg/m3, which could reduce ­following: 98 Air Quality Management Planning for Lagos State Within 1 year Energy Air quality monitoring et and enforce emission standards for backup 8. S ­generators. 1. Resume air quality monitoring at the six sites for which a monitoring record already exists, and begin Air quality financing planning an expanded network. 2. Train and equip LASEPA staff to carry out emission 9. C onsider allocating a percentage of existing or new measurements on industrial sources, and begin such emission fees or other charges as line charges for testing with the largest and worst emitters. LASEPA to sustainably support increased staffing and equipment. Health Consider multilateral financing and/or an air quality 10.   green bond to support needed investments in emission 3. Start education, training, and lifelong learning of controls, air quality monitoring infrastructure, emis- health personnel on the health effects of air pollution. sions measurement capabilities, and capacity building for air quality enforcement and management. Regulation and enforcement Solid waste management Within 3 years Air quality monitoring 4. Redouble efforts to collect and dispose of solid waste by landfill, recycling, composting, and/or incinera- Establish 8 to 12 additional air quality monitoring sites, 11.   tion with emission controls, and enforce prohibitions including upwind and downwind locations as well as on open burning of waste and biomass. sites influenced by the ports, traffic, and industrial ar- eas, to better monitor population-based exposure and Industries to strengthen the basis for air quality modeling. Strengthen the scientific basis for AQM by continuing 12.   5. Locate and shut down any lead smelting or battery to develop the emissions inventory, strengthening over- recycling operations in Ikorodu, measure lead levels sight of the emissions auditing process, and strengthen- in soil and in the blood of the affected population, ing the reporting of health and economic statistics. and take remedial action as necessary. Health Transport Strengthen the scientific basis for health impact 13.   6. Implement ECOWAS Directive C/Dir.1/09/20, ­ assessment, expand the system of health informa- limiting sulfur in gasoline and diesel fuel to tion collection, and initiate epidemiological research 50 ppm by weight; enforce this by collecting and on air pollution. analyzing fuel samples at the ports and at retail Engage public opinion by adopting an AQI and rou- 14.   stations, with fines or the loss of retail licenses for tinely providing air quality data and forecasts to the ­noncompliance. media and on LASEPA’s website. 7. Begin implementation of ECOWAS Directive C/ Dir.2/09/20 by notifying vehicle importers and im- Regulation and enforcement plementing inspections and testing to confirm that Transport newly imported light-duty vehicle (whether new or used) meet Euro 4 emission standards and Euro Strengthen the existing vehicle inspection and 15.   6 standards for heavy-duty vehicles. maintenance system to enforce the requirement of Air Quality Management Planning for Lagos State 99 ECOWAS Directive C/Dir.2/09/20 that vehicles Energy in circulation meet Euro 4 emission standards from January 2025. Increase the capacity and reliability of the electric- 18.   Replace the existing danfo (microbus) fleet with larger 16.   generating system to reduce the need for backup minibuses, preferably plug-in hybrid-electric vehicles generators, and consider retrofitting the Egbin power with advanced emission control, and restructure the plant for combined cycle operation with low-NOx routes to coordinate with the BRT. By charging from gas turbines. the power grid when it is available and from their on- Consider grouping small power users into “mini 19.   board engine when not, plug-in hybrids could provide grids” of a few hundred kilowatts incorporating reliable service in the near term while retaining the solar photovoltaic panels and diesel-generating sets ability to switch to all-electric operation in the future. with advanced emission controls. Consider measures to phase out engine-driven taxi- 17.   cabs, okada motorcycle taxis, and keke NAPEP tricycle taxis in favor of BEVs. 100 Air Quality Management Planning for Lagos State ANNEX 1 ESTIMATING THE HEALTH AND MORTALITY EFFECTS OF AIR POLLUTION IN LAGOS KEY MESSAGES » Current levels of PM2.5 ambient air concentration (47 μg/m3 weighted by pop- ulation) pose a serious, but preventable, public health hazard, especially in chil- dren under 5 years. » The morbidity burden is especially high in children, including 180,000 to 350,000 ALRI (primarily cases of pneumonia) and infant mortality (8,000 to 15,000 deaths, or one-half of the total mortality burden). » Lead exposure contributes to a high loss of IQ in young children (especially those younger than 6 years), with a mean loss of 6.2 IQ points per child, and up to 1 million IQ points lost at the population level. » Current PM2.5 pollution is responsible for 16,000 to 30,000 premature deaths annually, or 18 percent of all natural deaths, in Lagos State. An additional 250 to 500 deaths are attributable to PM10 exposure during the Harmattan season and 300 to 400 excess cardiovascular deaths in adults from exposure to lead. » Reducing the PM2.5 concentration to the WHO-recommended IT 1 (35 μg/m3) would reduce premature mortality by 28 percent (4,300 deaths among infants and adults), and additionally prevent 64,000 lower respiratory infections in children under 5 years. ­ » Additional efforts to collect baseline health data, including mortality statistics and data on hospital admissions, are necessary to improve the HIA. Air Quality Management Planning for Lagos State 101 impact of air pollution. Second, there is a vast set of A1.1. INTRODUCTION published studies from around the world linking PM2.5 to mortality in humans (Chen and Hoek 2020). Third, the PM2.5 effects observed in epidemiologic studies are Air pollution, in particular particulate matter (PM2.5 supported by toxicological and human clinical studies and PM10), is the leading environmental risk factor (US EPA 2019). Fourth, concentrations of PM2.5 can worldwide. Globally, among 20 major risk factors eval- be obtained from monitors, chemical transport models, uated in the GBD study, ambient and household air and/or satellite data. Finally, PM2.5 is ubiquitous and is pollution together currently rank 4th for attributable generated from many different sources in Lagos, including disease and mortality—after hypertension, smoking, fuel combustion from mobile sources (cars, buses, trucks, and dietary factors (GBD 2020). The estimates indicate and motorcycles) and stationary sources (for example, that around 7 million deaths,1 mainly from NCDs, are gasoline-powered power plants, port emissions, diesel- or ­ attributable to the joint effects of ambient and house- electrical generators, industrial boilers, and factories), hold air pollution, with the greatest attributable dis- biomass burning, cooking, waste combustion, and road ease burden seen in LMICs (89 percent of the global dust. This set of factors sets PM2.5 apart from all other total, with low-income and lower-middle-income coun- air pollutants. tries alone contributing around 40 percent of the total impact). Higher estimates than these have been pub- lished (Burnett et al. 2018). A recent report indicated The approaches and the methods of HIA (health impact 10.2 million premature deaths from fossil fuels use assessment) of air pollution are well documented. A pub- (Vohra et al. 2021). Regions with large anthropogenic lication from WHO (WHO Regional Office for Europe contributions had the highest attributable deaths, sug- 2016) provides the basic concepts and general principles gesting substantial health benefits from replacing tradi- of air pollution health risk assessment for various scenar- tional, fossil fuel-based energy sources as well as taking ios and purposes. In fact, both estimation of the burden actions on the other different anthropogenic sources of diseases attributable to air pollution, and evaluation such as industry, transport, and agriculture practices of policy scenarios and CBAs, are possible. The present (McDuffie et al. 2021). report illustrates the methods and input data for the HIA of particulate-matter air pollution in Lagos, Nigeria, as The recent literature indicates there is strong evidence of 2020–2021. of a causal relationship between PM2.5 air pollution exposure and all-cause mortality as well as ALRI (acute lower respiratory infections), IHD (ischemic A1.2.  DEFINITION AND heart disease), stroke, COPD (chronic obstructive pulmonary disease), and lung cancer (GBD 2020). APPLICATIONS OF HIA A growing and suggestive body of evidence also OF AIR POLLUTION reports causal relationships between PM2.5 air pollu- tion and type II diabetes and its effects on neonatal mortality from low birth weight and short gestation as There are four main steps in the health impact assess- well as neurologic effects in both children and adults ment (HIA) that combine expertise in exposure science, (Thurston et al. 2017). epidemiology, and public health. They are: PM2.5 mass has been generally used as the index pollutant 1. Estimate the exposure of the population under con- for quantifying the impact of outdoor air pollution. sideration to specific air pollutants. Ground-level First, previous studies have demonstrated that mortality monitoring data, together with air quality model- from long-term exposure to PM2.5 dominates the overall ing and satellite data, are currently used to evaluate 102 Air Quality Management Planning for Lagos State ­ urrent (or past) exposure or to predict levels in future c FIGURE A1.1.  ERFS OF THE GBD 2000 scenarios, provided that future emission inventories STUDY are available. 2. Select the counterfactual (or cut-off value) of the spe- 1.4 cific pollutant above which the estimate of the health Linear 1.3 impact is actually performed. 3. Assess the health impact associated with the estimated Relative risk 1.2 exposure to air pollution in the specific population. Log-linear Both the appropriate exposure-response functions 1.1 (ERFs) from epidemiological studies and the baseline local health statistics are required. The results are re- 1.0 ported as numbers of premature deaths, cases of dis- ease, years of life lost, disability-adjusted life years, or 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 change in life expectancy attributable to exposure, or a change in exposure to air pollution. 4. Finally, a critical evaluation of the uncertainties and Source: Cohen et al. 2004. potential errors involved in the calculation is an es- sential step of the assessment, which is also carried conducted assuming a linear association from the same out through sensitivity analyses. counterfactual to 50 μg/m3, with no additional risk change above this value. A risk model based on the logarithm of There are historical landmarks in risk assessment of air concentration was also considered. These risk associations pollution. In 1998, Ostro and Chestnut were the first to are depicted in Figure A1.1. propose a methodology to quantify the health benefits of potential nationwide reductions in ambient PM10 in the US (Ostro and Chestnut 1998). Kunzli et al. (2000) evalu- ated the impact of outdoor and traffic-related air pollu- A1.3.  AVAILABLE ERF MODELS tion on public health in Austria, France, and Switzerland. In the same period, two WHO documents (WHO 2000, A1.3.1.  LINEAR (LOG-LINEAR) ERFS 2001) provided guidance on several aspects related to air pollution HIAs. In 2013, the WHO Regional Office for Europe coordi- nated two projects (REVIHAAP – Review of evidence Cohen et al. (2004) published the first GBD evaluation for on health aspects of air pollution, and HRAPIE – Health 2000. Population-weighted annual average concentrations risks of air pollution in Europe) to provide the European of PM2.5 and PM10 were estimated, and the two health Commission and its stakeholders with evidence-based outcomes for adults were mortality from cardiopulmonary advice on the adverse effects of ambient air pollution. In disease and mortality from lung cancer, using risk coef- particular, the documents provide the health outcomes ficients from the large American Cancer Society cohort and ERFs that could be used for risk assessment of short- study of adults in the US (Pope et al. 2002). Cohen and and long-term exposure on morbidity and mortality in colleagues assumed that the risk of death increased linearly the European context (WHO 2013a, 2013b). over a range of annual average concentrations of PM2.5, between a counterfactual concentration of 7.5 μg/m3 and HRAPIE experts recommended estimation of the impact a maximum of 30 μg/m3, the highest observed concen- of long-term (annual average) exposure to PM2.5 on natu- tration at the time of any cohort study of PM2.5, with no ral cause2 mortality in adult populations (age 30+ years) additional increase in the health risk assumed for con- for cost-effectiveness analysis. A linear ERF3, with a rel- centrations beyond 30 μg/m3. ­ Sensitivity  analyses were ative risk RR4 of 1.062 (95 percent CI = 1.040, 1.083) Air Quality Management Planning for Lagos State 103 per increment of 10 µg/m3, was recommended. The LIMITATIONS ­ recommended risk coefficient was based on a meta-­ analysis of all cohort studies published before January » All-cause or natural-cause mortality is influenced 2013 by Hoek et al. (2013) and included 11 different by other conditions than chronic diseases, and the studies conducted in adult populations of North America percentage of NCDs varies across countries. and Europe. The review conducted by Hoek et al. (2013) » The application is difficult outside the exposure also provided meta-analyses for cardiovascular mortality ranges of the original studies; in particular, the with a stronger and statistically significant effect (RR of use of the log-linear model poses a problem for as- 1.11, 95 percent CI = 1.05, 1.16 per 10 µg/m3, based sessments in any place with high levels of outdoor on 11 studies). The effect of PM2.5 on respiratory mor- PM2.5. Extrapolating log-linear model coefficients tality (excluding mortality from lung cancer) was weaker derived from studies in low-exposure, high-income and with a large uncertainty (RR of 1.029, 95 percent countries to much greater levels of outdoor PM2.5 CI = 0.94, 1.126 per 10 µg/m3, based on six studies). results in implausibly large estimates of relative risk and attributable deaths in LMICs. Following the review by Hoek et al. (2013), several additional cohort studies have been published on PM2.5 (or PM10) all-cause or cause-specific mortality. In particular, in the most recent update of the WHO Air Quality A1.3.2.  INTEGRATED EXPOSURE Guidelines (WHO 2021), three relevant systematic reviews RESPONSE (IER) FUNCTIONS OF THE GBD on short- and long-term exposure to air pollutants and mortality have been conducted (Chen and Hoek 2020 on Pope et al. (2009) assessed the shape of the exposure- long-term effects of PM; Huangfu and Atkinson (2020) response relationship between cardiovascular mortality on long-term effects of NO2; and Orellano et al. (2020) on and fine particulates from cigarette smoke and ambient air short-term effects of several pollutants). pollution in the American Cancer Society cohort. They found that there were substantially increased cardiovascu- Below is a short list of the strengths and limitations of the lar mortality risks at low levels of active cigarette smoking, application of a linear (or log-linear) function to estimate and smaller but nevertheless significant excess risks even the all-cause mortality attributable to air pollution. at the much lower exposure levels associated with second- hand cigarette smoke and ambient air pollution. Based on these findings, Burnett et al. (2014) suggested a more com- STRENGTHS plex shape to describe the association between PM2.5 con- centrations and mortality, with no association below some » Applicability, because mortality statistics on all-cause concentration (counterfactual), a near-linear association for mortality are generally available worldwide with a low to moderate concentrations, and a diminishing change greater accuracy than cause-specific mortality. in risk as concentration increases over the global range » Effect estimates are robust as they are based on of PM2.5. Burnett et al. incorporated information on risk several studies. from other sources of PM2.5 such as secondhand and active » Effects estimates are all based on studies involving smoking and exposure to indoor sources of PM2.5 from the mean PM2.5 outdoor air pollution in the range of burning of biomass for cooking and heating (Pope et al. 2 to 30–40 µg/m3. 2009). Concentrations from these sources are much larger » The mathematical modeling is relatively simple: than those observed in cohort studies of ambient air pol- lution that have been conducted largely in North America  xposed population × Background rate of Health Impact = E and Western Europe (Hoek et al. 2013). The Burnett et al. mortality or morbidity × Concentration- ­ (2014) approach provided a method to estimate risk over Response function,CRF  × Change in pollution the global range of ambient concentrations. 104 Air Quality Management Planning for Lagos State The GBD project has included ambient air pollution in such that the change in relative risk at higher concentra- its evaluation since its 2010 release. For the project, IER tions declines as concentration increases, thus limiting the functions for fine particulate matter were derived from magnitude of the relative risk for the most polluted parts the pivotal study of Burnett et al. (2014) that considered of the world where few studies have been conducted. evidence from different combustion sources. To apply The attributable number of deaths due to PM2.5 exposure the GBD framework, IER functions were developed that worldwide was about twice that predicted by the IER, estimate the impact of ambient fine particulate matter in part because the GEMM considers natural causes of on mortality and morbidity within selected disease cat- mortality, specifically, NCDs plus adult lower respira- egories (including cardiovascular and respiratory mortal- tory infections, and in part because the IER incorporates ity and lung cancer) prespecified as part of the overall additional types of exposure, such as active smoking, that GBD comparative risk assessment project. have lower relative risks per unit PM2.5 than ambient air pollution (Burnett and Cohen 2020). The GBD project has released several updates since 2010. The underlying assumptions and the methodology In summary, there are three types of relative risk models are described in a paper by Burnett et al. (2014) and have proposed for assessing the population mortality burden been applied in subsequent years by the GBD collabora- due to outdoor PM2.5 exposure: linear (or log-linear), the tors. The last report in the GBD series was published in IER approach in GBD, and the GEMM approach. Each 2020 (GBD 2020). of these model specifications has strengths and limitations that have implications depending on the specific analytic Since its introduction, the IERs have been accepted as the objectives and the study area. The work by Burnett and state-of-the art model, now used by various organizations, Cohen (2020) provides an illustration of the differences including WHO, to estimate the burden of disease and among these models for areas that are at lower outdoor examine strategies to improve air quality at global, national, concentrations, and over the global range. and subnational scales for outdoor-air, fine-particulate pollu- tion and household pollution from the use of solid fuels for heating and cooking. The estimates of the IERs continue A1.4.  METHODS AND INPUT to evolve, changing with the incorporation of new data and fitting methods. Due to recent studies providing estimates of DATA FOR THE HIA IN LAGOS high levels of fine particulate pollution in China, new esti- mators based solely on outdoor, fine-particulate air pollution evidence have been proposed which require fewer assump- Figure A1.2 illustrates the main steps for calculating the tions than the IER, and yield larger relative risk estimates burden of mortality and morbidity in Lagos. (Burnett and Cohen 2020; Burnett et al. 2018). A1.4.1.  AIR POLLUTION DATA A1.3.3.  GLOBAL EXPOSURE In estimating the burden of disease, it is desirable to MORTALITY MODEL (GEMM) assess the current exposure of the population to an index pollutant, traditionally PM2.5 and PM10, based on either The most recent innovation in the GBD approach was ground-level monitors, remote-sensing satellites, land- the introduction of a new model known as the GEMM use regression models, chemical transport models, or (Burnett et al. 2018), based on 41 cohort studies of expo- some combination of the above. Ideally, these concentra- sure to only ambient air PM2.5 concentrations in popula- tions are based on several recent years of complete data tions predominantly in Europe and North America, but (to reduce the influence of an atypical year or season) also in Asia. The approach has more flexible parameters from monitors that are reasonably representative of local Air Quality Management Planning for Lagos State 105 FIGURE A1.2.  SCHEMATIC PRESENTATION OF THE MAIN STEPS OF THE HIA Air pollution data modelled levelsa Population risk overall (or monitored) susceptible groups Exposure estimate Concentration-response function(s) Background data mortality rates morbidity rates Impact estimate If modelled data are used, the approach can be used to assess the impact of emission reduction strategies on a different health outcomes. population exposure. At a minimum, 1 year of data are inputs to the dispersion analysis. We first estimated a provi- necessary for the HIA to make sure that seasonal pat- sional PWE (population-weighted exposure) for each LGA terns are incorporated into the annual average (this is (Lagos government area) using the results of the dispersion the case for the Lagos study). The monitors should not analysis coupled with a high-resolution map of the popu- be unduly influenced by local sources such as a nearby lation density distribution within each LGA to calculate highway, factory, or power plant but should rather reflect an accurate representation of the LGA-specific PWE. We average exposures over a wide impact area. Typically, then derived the PWE for the entire Lagos State, weighing ground-based, population-oriented monitors have been each LGA by its population size. Average annual exposure averaged across a metropolitan area to characterize air for Lagos State and each LGA was used in the assessment. quality in epidemiological studies. These concentrations This calculation was repeated for both PM2.5 and PM10 are then combined with population data to obtain PWEs. exposures, with the latter index being more appropriate to estimate the impact of the Harmattan season. We have used the 1-year concentration data of PM2.5 and PM10 measured during the period of the project. The con- The adjustment factor and LGA PWE estimates were tinuous and filter-based monitoring of air pollutants was calculated using the following equations: limited to six sites located across the City of Lagos between August 2020 and July 2021, giving one full year of moni- tored data. The annual data from the six monitors were PWE dispersion result for LGA interst used to assign an annual exposure value for the popula- LGA Adjustment factor = tion of each LGA in Lagos State where the monitor was PWE dispersion result for LGA with monitor located. For the LGAs without monitors, we have used the results of a dispersion model covering five distinct episodes distributed throughout the monitoring period to derive Cloest Non- LGA adjustment factors between the LGAs served with the mon- monitoring monitored = × Adjustment itors and those not served with the monitors. For this exer- station to LGA LGA exposure factor of int erst cise, data from the recent emission inventory were used as 106 Air Quality Management Planning for Lagos State In a sensitivity analysis, we used the simplest solution, compositions by quinquennial age group for Lagos State that is, to assign to the LGA without a monitor the aver- in 2018, while Table A1.2 presents the population distribu- age concentration of the closest LGA (see results in the tion by LGA. Figure A1.3 shows a map of LGA districts. Supplementary Material). Figure A1.4 depicts the two population distributions and their temporal evolution between 2006, the year of the A1.4.2.  POPULATION DATA last national census, and 2018. For the base case, the total population is projected out to 2018, assuming a As illustrated in Figure A1.2, the HIA requires input data 3.2 ­percent mean annual growth (LBS 2019). For each age on demographics and baseline rates for mortality and group, a differential growth is applied. This ­age-adjusted morbidity. Table A1.1 shows two alternative population rate is computed from the national level all-age popu- lation growth using the following expression: All-age population growth × μ, where μ is a multiplier equal to the growth in a particular age group, divided by the all- TABLE A1.1.  ESTIMATES OF LAGOS STATE age population growth in Nigeria (Figure A1.5). As an POPULATION BY AGE GROUP, 2018 example, for ages 0–4 years, the multiplier is 2.3 percent/​ 2.7 percent = 0.85; for ages 75–79 years, the multiplier Age (years) Base case Sensitivity is 3 percent/2.7 percent = 1.11, and so on. The sensi- tivity case represents the population distribution in 2018 0–4 1,591,424 3,065,496 using the approach in LBS (2019)—multiplying each age 5–9 1,437,766 2,769,515 group in the 2006 census by 1.926 and then adjusting for 10–14 1,292,164 2,489,349 the annual population growth since 2006. The base case population is about half as large as that of the sensitiv- 15–19 1,269,198 2,445,056 ity case. Figure A1.4 also shows the LBS 2018 projected 20–24 1,492,935 2,875,657 population (dotted red line). Compared to the sensitiv- 25–29 1,529,662 2,946,225 ity case (dash gray curve), the Lagos Bureau of Statistics (LBS) curve is shifted to younger ages. 30–34 1,233,580 2,375,555 35–39 1,049,921 2,021,579 A1.4.3.  MORTALITY AND 40–44 761,198 1,465,616 MORBIDITY DATA 45–49 543,296 1,045,888 50–54 386,546 744,286 There is a paucity of local data on mortality (and mor- 55–59 232,479 447,515 bidity). Whatever information is currently available is incomplete at best and has not been fully vetted. Regard- 60–64 168,103 323,732 ing hospitalizations, we have evaluated the summary sta- 65–69 99,570 191,740 tistics of inpatient admissions (hospitalized patients and their mortality) and outpatient care (emergency room vis- 70–74 78,318 150,863 its and their mortality) for 2017 (see data in the Supple- 75–79 42,736 82,335 mental Material). These statistics are derived from 184 80–84 42,969 82,824 public health care facilities, but data for the remaining 1,927 care facilities across the state are not available. In 85+ 47,982 92,471 addition, for most of the deaths occurring at home, there Total 13,299,845 25,615,703 is no medical certification, and, therefore, the mortality Source: Author’s own elaboration. statistics could not be compiled. Air Quality Management Planning for Lagos State 107 TABLE A1.2.  ESTIMATES OF LAGOS STATE POPULATION BY LGA 2006 Population 2018 Projected populationa LGA Census† LBS‡ Base Case Sensitivity Agege 461,743 1,033,064 673,840 1,507,591 Ajeromi-Ifelodun 687,316 1,435,295 1,003,027 2,094,583 Alimosho 1,319,571 2,047,026 1,925,702 2,987,306 Amuwo-Odofin 328,975 524,971 480,086 766,111 Apapa 222,986 522,384 325,412 762,336 Badagry 237,731 380,420 346,930 555,162 Epe 181,734 323,634 265,212 472,292 Eti-Osa 283,791 983,515 414,147 1,435,282 Ibeju/Lekki 117,793 99,540 171,900 145,263 Ifako-Ijaye 427,737 744,323 624,214 1,086,220 Ikeja 317,614 648,720 463,507 946,703 Ikorodu 527,917 689,045 770,410 1,005,551 Kosofe 682,772 934,614 996,396 1,363,919 Lagos Island 212,700 859,849 310,402 1,254,812 Lagos Mainland 326,700 629,469 476,766 918,609 Mushin 631,857 1,321,517 922,094 1,928,542 Ojo 609,173 941,523 888,990 1,374,002 Oshodi-Isolo 629,061 1,134,548 918,014 1,655,691 Shomolu 403,569 1,025,123 588,944 1,496,003 Surulere 502,865 1,274,362 733,851 1,859,727 Lagos State 9,113,605 17,552,942 13,299,845 25,615,703 † National Population Commission, https://catalog.ihsn.org/index.php/catalog,/3340/download/48521| ‡ Lagos Bureau of Statistics population composition (LBS 2019) a Mean annual growth rate is 3.2% (Nigeria National Bureau of Statistics & LBS; the rate is 3.22% according to United Nations World Urbanization Prospects, https://population.un.org/wup/) Source: Author’s own elaboration. 108 Air Quality Management Planning for Lagos State FIGURE A1.3.  MAP OF LAGOS STATE SHOWING LGAS FIGURE A1.4.  LAGOS STATE POPULATION IN 2006 AND 2018 3.5 LBS (2018) 3.0 2.5 Millions of persons 2.0 Lagos Bureau of Statistics (2006) 1.5 1.0 National Bureau of 0.5 Statistics (Census 2006) 0 4 9 4 9 4 9 4 9 4 9 4 9 4 9 4 9 4 + 0– 5– –1 –1 –2 –2 –3 –3 –4 –4 –5 –5 –6 –6 –7 –7 –8 85 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 LBS data (2006; 17.55 million) Nigeria NBS (2006; 9.11 million) LBS data (2018; 25.62 million) Base case (2018; 13.30 million) Sensitivity (2018; 25.62 million) Source: Author’s own elaboration. Note: The LBS (2018) curve is biased to younger ages if compared to the sensitivity line composition. Moreover, the curve is shifted up by a fixed factor equal to 1.459, which represents the 12-year total population growth at 3.2 percent. Air Quality Management Planning for Lagos State 109 FIGURE A1.5.  NIGERIA POPULATION LONG-TERM GROWTH RATE BY AGE GROUP, 2006–2018 4.0 Growth faster than all ages 3.4 3.3 3.5 Mean % change per year (12-years) 3.0 3.0 2.9 2.9 2.8 3.0 2.8 2.8 2.7 2.5 2.5 2.2 2.2 All ages mean growth 2.3 2.3 Growth slower than 2.0 2.2 rate 2.7 1.5 all ages 1.0 0.5 0 9 9 9 4 9 4 4 4 4 9 4 9 4 4 9 9 –1 –2 –3 0– 5– –1 –2 –3 –4 –5 –7 –4 –5 –6 –6 –7 15 25 35 10 20 30 40 55 70 45 50 60 65 75 Source: Author’s own elaboration with data from the UN World Population Prospects 2019, https://population.un.org/wpp. For the estimation of the mortality data for the HIA, » Mortality due to NCDs and specific GBD catego- two international sources were consulted to derive the ries, including lower respiratory infections, stroke, required information for the base and sensitivity case COPD, lung cancer, diabetes, and IHD. scenarios: these are the GHDx database of the GBD » Infant mortality (age less than 1 year) from the database (IHME 2021), and the GHE database (WHO same sources (GBD and WHO). The infant mor- 2021). The all-cause and cause-specific deaths (both tality rate stands at 6.7 percent and 7.5 percent, sexes) are summarized in table A1.3 (base case) and respectively, for GBD and WHO databases. Table A1.4 (sensitivity case) for calculations based on » Lower respiratory tract infections for children the GHDx inputs. Figure A1.6 depicts the data shown ­ under age 5 (mainly pneumonia). The baseline in table A1.3. Values calculated based on data from rate (incidences per 1,000 children is 302, with a GHE are presented in Table A1.5 (base case) and Table 95 percent CI: 160–538) was obtained from the A1.6 (sensitivity case). The number of deaths for each study by McAllister et al. (2019). age group is calculated as the product of the Nigerian » Incidence of chronic bronchitis in adults 27 years hazard rate (number of deaths for a particular outcome and older (3.9 cases per 1,000 individuals, based per 100,000 population from the GHDx or GHE data- on the rate from HRAPIE, WHO 2013b). base; Table A1.7) and the age-specific population size » Incidence of restricted activity days in the popula- from Table A1.1. Estimates at the LGA level are calcu- tion of all ages (19 days per year) was taken from lated assuming the same age composition in each LGA. HRAPIE (WHO 2013b). Hospital admissions The results are shown in Table A1.8 for the base case were subtracted to calculate the net PM attribut- and Table A1.9 for the sensitivity case. For the long- able restricted activity days. term PM2.5 exposure, the following health endpoints » RHAs and emergency room visits (including were considered: pneumonia, bronchitis, and asthma). The baseline 110 Air Quality Management Planning for Lagos State TABLE A1.3.  LAGOS STATE MORTALITY (BOTH SEXES) BY CAUSE OF DEATH AND AGE, BASE CASE 2018 Age (years) Persons All causes NCD IHD Stroke COPD ALRI LC DM 0–4 1,591,424 36,702 3,642 0 64 3 6,145 0 0 5–9 1437,766 1,508 247 0 9 0 75 0 0 10–14 1,292,164 853 205 0 11 0 36 0 0 15–19 1,269,198 1,243 284 9 10 5 36 0 6 20–24 1,492,935 1,976 417 17 26 2 56 1 3 25–29 1,529,662 2,821 619 20 35 7 85 2 8 30–34 1,233,580 3,185 727 49 46 8 82 5 15 35–39 1,049,921 3,797 949 84 76 9 97 7 13 40–44 761,198 3,694 1,161 116 124 11 100 10 34 45–49 543,296 3,507 1,326 174 150 I8 112 18 63 50–54 386,546 3,425 1,601 238 226 36 136 29 95 55–59 232,479 2,866 1,520 220 214 34 129 28 90 60–64 168,103 3,178 1,875 305 302 59 160 39 122 65–69 99,570 2,824 1,776 337 295 75 160 41 127 70–74 78,318 3,616 2,270 482 407 117 233 53 145 75–79 42,736 3,025 2,129 440 400 101 221 39 144 80–84 42,969 4,630 3,348 713 618 148 392 42 215 85+ 47,982 8,453 6,167 1,395 1,047 280 857 43 349 Total 13,299,845 91,302 30,263 4,600 4,061 914 9,112 357 1,429 Source: Author’s own elaboration. Note: LC = Lung cancer; DM = Diabetes mellitus. Estimates derived from GHDx national hazard rates applied to the projected population based on 2006 census. estimated statistics for the entire Lagos State were ­ ­ equire hospitalization (McAllister et al. 2019). r based on public hospital data, assuming that the Further, this increases by 32 percent to include private hospitals had a similar load of patients other respiratory illnesses, such as COPD and (2017 data). For RHAs, the incidences in children asthma (according to inpatient statistics from the under 5, who account for 12 percent of the total LMoH inpatient records for 2017). population and contribute 85 percent of total » CHAs and emergency-room visits consist of cases (according to LMoH inpatient records for disease-specific categories such as IHD, which 2017), are 302 LRI cases per 1,000 children, of includes heart attacks, heart failure, and stroke. which 2.09 percent (range: 0.91–4.79 percent) The baseline statistics for the entire Lagos State Air Quality Management Planning for Lagos State 111 TABLE A1.4.  LAGOS STATE MORTALITY (BOTH SEXES) BY CAUSE OF DEATH AND AGE, SENSITIVITY CASE 2018 Age (years) Persons All causes NCD IHD Stroke COPD ALRI LC DM 0–4 3,065,496 70,698 7,015 0 124 7 11,837 0 0 5–9 2,769,515 2,905 476 0 17 0 145 0 0 10–14 2,489,349 1,643 395 0 22 0 70 1 0 15–19 2,445,056 2,394 548 17 19 9 69 1 11 20–24 2,875,657 3,807 804 33 50 3 108 1 6 25–29 2,946,225 5,433 1,192 39 67 13 163 3 16 30–34 2,375,555 6,133 1,401 94 88 16 159 9 28 35–39 2,021,579 7,312 1,827 162 146 17 187 14 26 40–44 1,465,616 7,112 2,235 223 238 21 192 20 66 45–49 1,045,888 6,752 2,552 335 288 35 216 34 122 50–54 744,286 6,595 3,083 458 436 69 262 55 184 55–59 447,515 5,517 2,926 424 412 66 248 54 172 60–64 323,732 6,120 3,611 588 582 114 307 76 235 65–69 191,740 5,438 3,421 649 568 144 308 79 244 70–74 150,863 6,965 4,372 928 784 225 449 102 279 75–79 82,335 5,828 4,102 848 771 194 425 76 277 80–84 82,824 8,924 6,453 1,375 1,191 286 755 80 415 85+ 92,471 16,291 11,885 2,688 2,018 540 1,651 82 672 Total 25,615,703 175,865 58,297 8,861 7,823 1,761 17,553 687 2,752 Source: Author’s own elaboration. Note: LC = Lung cancer; DM = Diabetes mellitus estimates derived from GHDx national hazard rates applied to the projected population based on LBS (2006). were estimated based on the available public hos- We also estimated the impact of short-term exposure pital data, assuming that the private hospitals had to PM10 on daily overall mortality due to the Harmattan a similar load of patients (2017 data). For CHAs, season. In the specific situation of Lagos, daily popula- we assumed most cases occur among adults, and tion exposure to PM10 has importance and, in some based on Sub-Saharan Africa data presented in instances, it does not correlate well with that of PM2.5. Etyang and Scott (2013) (table S2), the ­ baseline This happens on days when the Harmattan winds blow, rate is 2.6  times higher than the adult RHA between the end of November and mid-March. It is a ­ incidence rate (adults account for 15 percent of dry and dusty wind from the North-East originating the all-age RHA cases). from the Sahara Desert, and it involves a large size 112 Air Quality Management Planning for Lagos State FIGURE A1.6.  LAGOS STATE MORTALITY (BOTH SEXES) BY CAUSE OF DEATH AND AGE, BASE CASE 2018 20 36,700 deaths 16 Deaths in thousands 12 8 4 0 4 9 4 9 4 9 4 9 4 4 9 4 9 4 9 4 + 0– 5– –1 –1 –2 –2 –3 –3 –4 –5 –5 –6 –6 –7 –7 –8 85 10 15 20 25 30 35 40 50 55 60 65 70 75 80 IHD Stroke COPD LC DM Other NCD ALRI All causes Note: Estimates derived from GHDx national hazard rates (table A1.3). increase of particles in the air, especially the coarse A1.4.4. EXPOSURE-RESPONSE fraction (that is between 2.5 and 10 microns in diame- FUNCTIONS (ERF) ter). The health effects of this type of source have been suspected (De  Longueville et al. 2010) but never well ­ The ERFs from the epidemiological literature that studied. On the other hand, there is ample evidence of quantitatively relate exposure to PM2.5 to the risk of the acute health effects of Saharan dust from other the specific health effect have been reviewed in the first locations (Querol et al. 2019), although the overall part of the document. The epidemiological studies short-term effect of particles on mortality is much provide an estimate of the percent change in risk that lower in comparison to the overall effect of chronic might be expected per each unit change in air pollution. exposure. For the assessment of the short-term burden For example, for ambient air PM2.5 concentrations below on mortality due to the Harmattan season, we applied 30–40 µg/m3, current studies of long-term exposure the short-term ERF for PM10 from Orellano et  al. indicate that a 10  μg/m3 change is expected to result (2020). Air Quality Management Planning for Lagos State 113 TABLE A1.5.  LAGOS STATE MORTALITY (BOTH SEXES) BY CAUSE OF DEATH AND AGE, BASE CASE 2018 Age (years) Persons All causes NCD IHD Stroke COPD ALRI LC DM 0–4 1,591,424 38,158 3,237 0 62 3 7,936 0 9 5–9 1,437,766 3,137 519 0 24 1 216 0 6 10–14 1,292,164 1,715 402 0 31 1 101 0 8 15–19 1,269,198 1,174 190 7 7 4 26 0 6 20–24 1,492,935 1,888 301 13 20 1 42 0 6 25–29 1,529,662 2,710 449 14 23 4 53 1 10 30–34 1,233,580 3,044 645 37 34 6 62 2 19 35–39 1,049,921 3,647 946 64 56 6 73 4 19 40–44 761,198 3,542 1,107 88 92 8 75 6 36 45–49 543,296 3,345 1,231 134 118 14 86 13 52 50–54 386,546 3,282 1,434 199 194 30 116 14 85 55–59 232,479 2,720 1,562 238 231 37 139 12 103 60–64 168,103 3,003 1,911 338 335 66 177 9 142 65–69 99,570 2,668 1,888 403 353 89 191 6 157 70–74 78,318 3,397 2,391 591 499 139 286 5 184 75–79 42,736 2,843 2,048 497 453 112 248 3 166 80–84 42,969 4,320 3,075 772 674 154 425 3 234 85+ 47,982 8,131 5,771 1,528 1,166 298 883 3 382 Total 13,299,845 97,724 29,107 4,923 4,373 975 11,134 81 1,623 Note: Estimates derived from GHE national hazard rates applied to the projected population based on 2006 census. in an 8 ­percent increase in the risk of premature death plus lower respiratory illnesses. For infant mortality, we used from all natural causes of death (Chen and Hoek 2020). the novel paper by Heft-Neal et al. (2018). They found that However, for the high levels of PM2.5 pollution recorded in a 10 μg/m3 increase in PM2.5 concentration was associated Lagos—well above the range of the concentration levels with a 9.2 percent (95 percent CI: 4–14 percent) rise in observed in most of the studies—the best approach has infant mortality based on a large study carried out in been to apply the IER functions used by GBD to assess the Africa. Figure A1.7 is a graphical representation of the ambient air PM2.5 cause-specific mortality (for example, ERFs that have been used in this work. Croitoru, Chang, and Akpokodje 2020). In this study, we used the most recent IER functions (GBD 2020) as well as The concentration of lead in PM2.5 and PM10 observed the GEMM relationship (Burnett et al. 2018) for the NCDs section 2.2) in Ikorodu LGA is particularly elevated (see ­ 114 Air Quality Management Planning for Lagos State TABLE A1.6.  LAGOS STATE MORTALITY (BOTH SEXES) BY CAUSE OF DEATH AND AGE, SENSITIVITY CASE 2018 Age (years) Persons All causes NCD IHD Stroke COPD ALRI LC DM 0–4 3,065,496 73,502 6,235 0 120 6 15,287 0 18 5–9 2,769,515 6,043 1,001 0 46 1 417 0 12 10–14 2,489,349 3,305 775 0 60 1 194 0 15 15–19 2,445,056 2,261 366 13 14 7 51 0 11 20–24 2,875,657 3,637 580 25 38 2 81 1 11 25–29 2,946,225 5,219 865 28 45 8 101 2 20 30–34 2,375,555 5,861 1,243 72 66 12 119 5 36 35–39 2,021,579 7,021 1,822 124 107 12 140 8 37 40–44 1,465,616 6,821 2,131 169 178 16 143 12 70 45–49 1,045,888 6,440 2,369 258 227 28 166 25 100 50–54 744,286 6,320 2,761 383 374 58 224 28 163 55–59 447,515 5,237 3,006 457 444 71 267 22 198 60–64 323,732 5,784 3,679 651 644 126 340 18 274 65–69 191,740 5,137 3,636 777 680 172 369 11 303 70–74 150,863 6,544 4,606 1,138 961 268 550 9 353 75–79 82,335 5,478 3,947 957 872 216 479 5 319 80–84 82,824 8,326 5,927 1,489 1,300 298 819 5 452 85+ 92,471 15,669 11,122 2,945 2,247 574 1,701 7 736 Total 25,615,703 178,605 56,070 9,485 8,424 1,878 21,448 157 3,127 Source: Author’s own elaboration Note: LC = Lung cancer; DM = Diabetes mellitus. Estimates derived from GHE national hazard rates applied to the projected population based on LBS (2006). compared to the US EPA 2016 standard (0.15 μg/m3). consequently, increasing cardiovascular mortality (Brown Lead exposure in children has been linked to severe brain et al. 2020; US EPA 1999). To estimate the impact of lead damage, leading to loss of intelligence (IQ), and adverse exposure on the Ikorodu population—the LGA with the behavioral outcomes such as learning disabilities, school highest lead exposure exceedance (1.35 µg/m3 air lead) as failure, and conduct disorder (Lanphear et al. 2005; Pew compared to the US standard—the air concentration has Charitable Trusts 2017; Ruckart et al. 2021). In adults, been converted into blood levels using a conversion factor lead exposure can affect the cardiovascular system by of 4 for children 0–6 years and 2 for adults (US EPA 1999). increasing the likelihood of high blood pressure and, Based on the estimated blood lead levels, the impact Air Quality Management Planning for Lagos State 115 116 TABLE A1.7.  NIGERIA MORTALITY RATES (PER 100,000, BOTH SEXES) BY CAUSE OF DEATH AND AGE All causes NCD IHD Stroke COPD ALRI LC DM Age group GBD WHO GBD WHO GBD WHO GBD WHO GBD WHO GBD WHO GBD WHO GBD WHO 0–4 2,306 2,398 229 203 0 0 4 4 0 0 386 499 0 0 0 1 5–9 105 218 17 36 0 0 1 2 0 0 5 15 0 0 0 0 10–14 66 133 16 31 0 0 1 2 0 0 3 8 0 0 0 1 15–19 98 92 22 15 1 1 1 1 0 0 3 2 0 0 0 0 20–24 132 126 28 20 1 1 2 1 0 0 4 3 0 0 0 0 25–29 184 177 40 29 1 1 2 2 0 0 6 3 0 0 1 1 30–34 258 247 59 52 4 3 4 3 1 1 7 5 0 0 1 2 35–39 362 347 90 90 8 6 7 5 1 1 9 7 1 0 1 2 40–44 485 465 153 145 15 12 16 12 1 1 13 10 1 1 4 5 45–49 646 616 244 227 32 25 28 22 3 3 21 16 3 2 12 10 50–54 886 849 414 371 62 51 59 50 9 8 35 30 7 4 25 22 55–59 1,233 1,170 654 672 95 102 92 99 15 16 55 60 12 5 39 44 60–64 1,890 1,787 1,116 1,137 182 201 180 199 35 39 95 105 23 5 73 85 65–69 2,836 2,679 1,784 1,897 339 405 296 355 75 90 161 192 41 6 127 158 70–74 4,617 4,338 2,898 3,053 615 754 519 637 149 178 297 365 68 6 185 234 75–79 7,078 6,653 4,982 4,793 1,030 1,162 937 1,059 235 262 517 581 92 6 337 387 80–84 10,774 10,053 7,792 7,156 1,660 1,798 1,439 1,570 346 359 912 989 97 6 501 545 85+ 17,617 16,945 12,852 12,027 2,907 3,185 2,182 2,430 584 621 1,786 1,839 89 7 727 796 All ages 742 766 225 206 32 31 30 29 6.6 6.3 81 103 2.9 0.6 11 11 Sources: Author’s own compilation of mortality data from GHDx (IHME 2021) and GHE (WHO 2021). Note: Both databases provide similar mortality rates for the selected group of diseases. Lung cancer is a notable exception, for which the WHO estimate is much lower than the GBD value (up to a factor of 15 times smaller for ages 75 and older, and by a factor of 4.5 times smaller when considering all ages). Air Quality Management Planning for Lagos State TABLE A1.8.  LAGOS STATE MORTALITY (GHDX HAZARD RATES, BOTH SEXES) BY LGA, 2018 All causes NCD IHD Stroke COPD ALRI LC DM Local Government Base Base Base Base Base Base Base Base Area, LGA case Sensitivity case Sensitivity case Sensitivity case Sensitivity case Sensitivity case Sensitivity case Sensitivity case Sensitivity Agege 4,626 10,350 1,533 3,431 233 522 206 460 46 104 462 1,033 18 40 72 162 Ajeromi- 6,886 14,380 2,282 4,767 347 725 306 640 69 144 687 1,435 27 56 108 225 lfeiodun Alimosho 13,220 20,509 4,382 6,799 666 1,033 588 912 132 205 1,319 2,047 52 80 207 321 Amuwo- 3,296 5,260 1,092 1,744 166 265 147 234 33 53 329 525 13 21 52 82 Odofin Apapa 2,234 5,234 740 1,735 113 264 99 233 22 52 223 522 9 20 35 82 Air Quality Management Planning for Lagos State Badagry 2,382 3,811 789 1,263 120 192 106 170 24 38 238 380 9 15 37 60 Epe 1,821 3,243 603 1,075 92 163 81 144 18 32 182 324 7 13 28 51 Eti-Osa 2,843 9,854 942 3,266 143 497 126 438 28 99 284 983 11 38 44 154 Ibeju/Lekki 1,180 997 391 331 59 50 52 44 12 10 118 100 5 4 18 16 Ifako-ijaye 4,285 7,457 1,420 2,472 216 376 191 332 43 75 428 744 17 29 67 117 Ikeja 3,182 6,500 1,055 2,155 160 327 142 289 32 65 318 649 12 25 50 102 Ikorodu 5,289 6,904 1,753 2,288 266 348 235 307 53 69 528 689 21 27 83 108 Kosofe 6,840 9,364 2,267 3,104 345 472 304 417 68 94 683 935 27 37 107 147 Lagos island 2,131 8,615 706 2,856 107 434 95 383 21 86 213 860 8 34 33 135 Lagos 3,273 6,307 1,085 2,091 165 318 146 281 33 63 327 629 13 25 51 99 Mainland Mushin 6,330 13,240 2,098 4,389 319 667 282 589 63 133 632 1,321 25 52 99 207 Ojo 6,103 9,433 2,023 3,127 307 475 271 420 61 94 609 942 24 37 95 148 Oshodi-lsolo 6,302 11,367 2,089 3,768 317 573 280 506 63 114 629 1,135 25 44 99 178 Shomolu 4,043 10,271 1,340 3,405 204 518 180 457 40 103 403 1,025 16 40 63 161 Surulere 5,038 12,768 1,670 4,232 254 643 224 568 50 128 503 1,274 20 50 79 200 All LGA 91,302 175,865 30,263 58,297 4,600 8,861 4,061 7,823 914 1,761 9,112 17,553 357 687 1,429 2,752 Source: Author’s own elaboration. Note: LC = Lung cancer; DM = Diabetes mellitus. Estimates derived from GHDx national hazard rates assuming the same age profile in each LGA. Projected population based on 2006 census (base case) and LBS (2006) (sensitivity). 117 118 TABLE A1.9.  LAGOS STATE MORTALITY (GHE HAZARD RATES, BOTH SEXES) BY LGA, 2018 All causes NCD IHD Stroke COPD ALRI LC DM Local Government Base Base Base Base Base Base Base Base Area, LGA case Sensitivity case Sensitivity case Sensitivity case Sensitivity case Sensitivity case Sensitivity case Sensitivity case Sensitivity Agege 4,698 10,512 1,475 3,300 249 558 222 496 49 111 564 1,262 4 9 82 184 Ajeromi- 6,993 14,604 2,195 4,585 371 776 330 689 74 154 840 1,754 6 13 122 256 lfeiodun Alimosho 13,426 20,829 4,214 6,539 713 1,106 633 982 141 219 1,612 2,501 12 18 235 365 Amuwo- 3,347 5,342 1,051 1,677 178 284 158 252 35 56 402 641 3 5 59 94 Odofin Apapa 2,269 5,315 712 1,669 120 282 107 251 24 56 272 638 2 5 40 93 Badagry 2,419 3,871 759 1,215 128 206 114 183 25 41 290 465 2 3 42 68 Epe 1,849 3,293 580 1,034 98 175 87 155 19 35 222 395 2 3 32 58 Eti-Osa 2,887 10,007 906 3,142 153 531 136 472 30 105 347 1,202 3 9 51 175 Ibeju/Lekki 1,198 1,013 376 318 64 54 57 48 13 11 144 122 1 1 21 18 Ifako-ljaye 4,352 7,574 1,366 2,378 231 402 205 357 46 80 523 939 4 7 76 133 Ikeja 3,231 6,601 1,014 2,072 172 351 152 311 34 69 388 793 3 6 57 116 Ikorodu 5,371 7,011 1,686 2,201 285 372 253 331 56 74 645 842 5 6 94 123 Kosofe 6,947 9,510 2,181 2,985 369 505 328 449 73 100 834 1,142 6 8 122 167 Lagos island 2,164 8,749 679 2,747 115 465 102 413 23 92 260 1,051 2 8 38 153 Lagos 3,324 6,405 1,043 2,011 176 340 157 302 35 67 399 769 3 6 58 112 Mainland Mushin 6,429 13,447 2,018 4,221 341 714 303 634 68 141 772 1,615 6 12 113 235 Ojo 6,198 9,580 1,946 3,008 329 509 292 452 65 101 744 1,150 5 8 109 168 Oshodi-lsolo 6,400 11,544 2,009 3,624 340 613 302 545 67 121 769 1,386 6 10 112 202 Shomolu 4,106 10,431 1,289 3,275 218 554 194 492 43 110 493 1,253 4 9 72 183 Surulere 5,116 12,967 1,606 4,071 272 689 241 612 54 136 614 1,557 4 11 90 227 All LGA 92,724 178,605 29,107 56,070 4,923 9,485 4,373 8,424 975 1,878 11,134 21,448 81 157 1,623 3,127 Source: Author’s own elaboration. Note: LC = Lung cancer; DM = Diabetes mellitus. Estimates derived from GHE national hazard rates assuming the same age profile in each LGA. Projected population based on 2006 census (base case) and LBS (2006) (sensitivity). Air Quality Management Planning for Lagos State FIGURE A1.7.  ERFS FOR THE LAGOS HIA 2.2 2.0 GEMM RR and 95% CI 1.9 Chronic Obstructive Pulmonary 2.0 Population at risk: Adults 25+ Disease (COPO) RR and 95% CI Health outcome: NCD + LRI deaths 1.8 Population at risk: Adults 25+ 1.8 1.7 Relative risk 1.6 Relative risk 1.6 1.5 1.4 1.4 1.3 1.2 1.2 Lower Respirasory Infection (LRI) deaths 1.1 Population at risk: All ages 1.0 1.0 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100 2.0 2.0 1.9 Lung Cancers (LC) RR and 95% CI 1.9 Stroke death RR and 95% CI Population at risk: Adults 25+ Population at risk: Adults 25+ 1.8 1.8 RR by 5-yr age groups: 70–74 yr shown 1.7 1.7 Relative risk Relative risk 1.6 1.6 1.5 1.5 1.4 1.4 1.3 1.5 1.2 1.2 Ischemic Heart Disease (IHD) deaths Type 2 Diabetes Mellitius (DM) deaths 1.1 Population at risk: Adults 25+ 1.1 Population at risk: Adults 25+ RR by 5-yr age groups: 70–74 yr shown 1.0 1.0 0 10 20 30 40 50 60 70 80 90 100 0 10 20 30 40 50 60 70 80 90 100 3.0 2.8 Heft-Neal et al. RR and 95% CI Population at risk: Infants (< 1 year) 2.6 Health outcome: Natural deaths 2.4 Relative risk 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0 10 20 30 40 50 60 70 80 90 100 Note: Estimates derived from GHDx national hazard rates (table A1.3). Air Quality Management Planning for Lagos State 119 of lead exposure on children’s IQ has been estimated summarizes the findings for both the base and sensitivity (as a decrease in children’s IQ equal to 1.15 points per case populations. For the base case population, the esti- 1 µg/dl (microgram per deciliter) blood lead increase; mated annual mortality attributable to PM2.5 is 15,850 Pew Charitable Trusts 2017), as has the impact of lead deaths, of which 7,790 are infant deaths, or around 50 per- on cardiovascular mortality in adults (Brown et al. 2020). cent of the total mortality. In total, 182,400 annual cases of lower respiratory infections in children up to 5  years A PM2.5 counterfactual concentration has been used to were estimated, together with 14,700 new cases of chronic estimate the burden of disease. The GBD (2020) study bronchitis in adults, 46 million restricted activity days, and assumed a uniformly distributed value between 2.4 and 1,490 hospital admissions for cardiovascular and respira- 5.9 µg/m3 PM2.5, whereas GEMM assumes 2.4 μg/m3, tory diseases. The table provides 95 percent CIs around and the same counterfactual is applied for infant mortal- these estimates. Alimosho, Ikorodu, and Oshodi are the ity. Furthermore, multiple targets have been examined, LGAs with the greatest impact. The estimates are doubled such as the new WHO Air Quality guideline of 5 µg/m3 (Table A1.12 ) when considering the sensitivity population: or the WHO interim targets (35, 25, 15, 10 µg/m3 PM2.5) the annual mortality attributable to PM2.5 is 30,350 deaths to quantify the health benefits that could be achieved (14,890 infant deaths), 349,000 annual cases of lower res- from exposure reductions. piratory infections in children up to 5 years, 28,300 new cases of chronic bronchitis, 88 million restricted days, and 2,840 hospital admissions. In the sensitivity population A1.5. RESULTS calculation, the LGAs that had the greatest impact were Alimosho, Mushin, Shomolo, and Oshodi. A1.5.1.  PM2.5 PREMATURE MORTALITY Figure A1.10 shows the attributable cases of premature AND MORBIDITY (BASE AND mortality by cause of death applying the IER func- SENSITIVITY SCENARIOS) tions proposed by GBD in 2020. Mortality results have been adjusted for co-exposure to indoor air pollution, Table A1.10 and Figure A1.8 show the estimates of PM2.5 assuming that 40 percent of the population in the fol- PWE by LGAs in Lagos. The estimation is based on fixed lowing LGAs use solid fuel for cooking purposes: Amuwo- monitor data (for LGAs with such a monitoring station) Odofin, Badagry, Epe, Eti-Osa (NCF), Ibekju/Lekki, and and the results of the air dispersion analysis for five epi- Ojo (Croitoru, Chang and Kelly 2020). The adjustment sodes between August 2020 and July 2021. The overall for indoor air pollution follows the GBD 2020 recom- values for the entire Lagos are 47 µg/m3 and 114 µg/m3 mended proportional population attributable fraction for PM2.5 and PM10, respectively (base case). Only a small (PAF) approach (Source: GBD 2020, SI appendix 1, 11). difference has been estimated when using the sensitiv- The calculations were done on the base case population ity population (46 µg/m3 and 116 µg/m3 for PM2.5 and and using baseline mortality rates from GHDx-IHME PM10, respectively). The population living in Ikorodu, and GHE-WHO. The results were similar using the two Shomolu, Mushin, and Oshodi are exposed to particu- databases and indicated that mortality from lower respir- larly high values of ambient pollution (PM2.5 values of atory infections, IHD, and stroke had the greatest impact. 97, 85, 71, and 60 µg/m3, respectively). The alternative calculations, based on the closest monitors, provide simi- Figure A1.11 presents the age-specific mortality results lar estimates (see results in the Supplemental Material). for the base case population (top) and sensitivity case population (bottom). The total mortality is calculated Table A1.11 shows the results of the calculation of the as the sum of infant mortality (Heft-Neal et al. 2018), attributable burden in Lagos for mortality (calculated deaths from lower respiratory infections for ages 1–25 using GEMM for adults and Heft-Neal et al. for infants) (GBD 2020), and adult mortality (ages 25+) according and morbidity (calculated using HRAPIE). Figure A1.9 to GEMM. 120 Air Quality Management Planning for Lagos State TABLE A1.10.  ANNUAL PM PWE BY LGA PWE, μg/m3 Local Government Area (LGA) Closest monitoring station PM2.5 Adj factor PM10 Adj factor PM2.5 PM10 Agege Mean of Ikeja & Alimosho 0.84 0.85 36 97 Ajeromi-lfelodun Lagos Island 1.02 1.02 42 108 Alimosho* 46 124 Amuwo Odofin Eti-Osa 1.63 1.62 48 119 Apapa Lagos Island 0.94 0.95 39 100 Badagry Same as Epe 0.55 0.53 16 39 Epe Eti-Osa 0.55 0.53 16 39 Eti-Osa* 29 74 Ibeju-Lekki Same as Epe 0.55 0.53 16 39 Ifako-ljaye Mean of Ikeja & Alimosho 0.76 0.78 33 89 Ikeja* 41 106 Ikorodu* 97 171 Kosofe Ikeja 1.15 1.14 47 120 Lagos Island* 42 105 Lagos Mainland* 42 97 Mushin Lagos Mainland 1.70 1.73 71 168 Ojo Eti-Osa 0.83 0.86 25 64 Oshodi Lagos Mainland 1.43 1.45 60 141 Shomolu Lagos Mainland 2.03 2.05 85 199 Surulere Lagos Mainland 0.77 0.79 32 76 Lagos State (Base Case population) 47 114 Lagos State (Sensitivity population) 46 113 * LGAs where air monitors are located (mean monitored concentration over period Aug 2020 to Jul 2021). Source: Author’s own elaboration. Air Quality Management Planning for Lagos State 121 FIGURE A1.8.  AMBIENT AIR QUALITY FOR LAGOS STATE AND LGAS Agege Ajeromi-Ifelodun Alimosho (ABESAN) 46 124 Amuwo-Odofin Apapa Badagry Epe Eti-Osa (NCF) 29 74 Ibeju/Lekki Ifako-Ijaye Ikeja (LASEPA) 41 106 Ikorodu (IKORODU) 97 171 Kosofe Lagos Island (JANKARA) 42 105 Lagos Mainland (UNILAG) 42 97 Mushin Ojo Oshodi-Isolo Shomolu Surulere Lagos State 47 114 0 30 60 90 120 150 180 210 PM10 PM2.5 Source: Author’s own elaboration Note: The six LGAs where daily ambient concentrations were monitored during the monitoring campaign between August 2020 and July 2021 are highlighted by the gray boxes along the y-axis on the left. 122 Air Quality Management Planning for Lagos State TABLE A1.11. PM2.5 ATTRIBUTABLE HEALTH BURDENS FOR THE BASE CASE POPULATION Hospital Admissions Lower Respiratory Onset Chronic Restricted All ages, Infant Total Mortality* Infections Bronchitis Activity Days cardiovascular and Mortality (all ages) Children under 5-years Adults over 27-years All ages (in thousands) respiratory Local Government Area (LGA) Deaths Deaths 95%CI Cases 95%CI Cases 95%CI Cases 95%CI Cases 95%CI Agege 320 680 430–890 7,670 2,280–14,210 710 340–880 1,840 1,660–2,040 58 2–115 Ajeromi-lfelodun 550 1,140 720–1,490 13,080 3,970–23,380 1,120 550–1,370 3,190 2,880–3,550 102 3–201 Alimosho 1,130 2,320 1,470–3,020 26,730 8,220–46,890 2,320 1,180–2,760 6,580 5,950–7,310 211 6–415 Amuwo Odofin 300 600 380–780 6,950 2,160–12,040 570 290–680 1,720 1,560–1,910 55 2–109 Air Quality Management Planning for Lagos State Apapa 170 350 220–460 3,980 1,200–7,240 350 170–430 960 870–1,070 31 1–60 Badagry 70 180 120–250 1,810 500–3,810 180 70–250 410 370–460 13 0–25 Epe 60 140 90–190 1,390 380–2,910 140 50–190 310 280–350 10 0–19 Eti-Osa 160 350 220–470 3,920 1,130–7,560 360 160–470 920 830–1,030 29 1–57 Ibeju-Lekki 40 90 60–120 900 250–1,890 90 40–130 200 180–230 6 0–13 Ifako-ljaye 270 590 370–780 6,560 1,920–12,370 620 290–790 1,550 1,400–1,730 49 1–97 Ikeja 250 510 330–670 5,860 1,770–10,570 510 250–630 1,420 1,290–1,580 45 1–89 Ikorodu 810 1,520 1,000–1,860 18,210 6,710–25,370 1,060 610–1,190 5,170 4,730–5,670 177 6–334 Kosofe 600 1,220 780–1,590 14,120 4,360–24,620 1,180 600–1,410 3,490 3,160–3,880 112 3–220 Lagos Island 170 350 220–460 4,000 1,210–7,170 340 170–420 970 880–1,080 31 1–61 Lagos Mainland 260 540 340–700 6,160 1,870–11,030 500 240–630 1,500 1,350–1,670 48 1–94 Mushin 780 1,510 980–1,900 17,890 6,040–27,660 1,270 720–1,430 4,740 4,310–5,230 157 5–302 Ojo 290 670 420–890 7,080 2,010–14,080 700 300–930 1,630 1,470–1,830 51 2–102 Oshodi 680 1,340 860–1,710 15,740 5,100–25,650 1,170 620–1,370 4,040 3,660–4,470 132 4–256 Shomolu 570 1,070 700–1,330 12,810 4,530–18,700 860 520–930 3,520 3,210–3,870 119 4–226 Surulere 310 670 420–890 7,490 2,190–14,220 660 300–860 1,770 1,600–1,970 56 2–111 Lagos State 7,790 15,850 10,130–20,450 182,400 57,770–311,400 14,710 7,440–17,770 45,920 41,600–50,900 1,490 46–2,910 Note: * Baseline rates obtained from the WHO GHE database for 2018. 123 FIGURE A1.9. PM2.5 ATTRIBUTABLE MORTALITY BY LGA AND MORBIDITY FOR LAGOS STATE Base Case 2018 Population 4,000 3,500 Number of premature deaths 3,000 2,500 2,000 1,500 1,000 500 0 fe e Am Ali un o- sho Ap n Ba pa y E e eju sa ko ki e Ik ja u La go ofe ai d M d od jo e n Sh olo Su olu i-I geg Ep ay ler gr od s M lan an fi hi Ifa Lek e sh O Ib ti-O a d do Ik s s om da us uw o -Ij ru nl or La o lo i-I go s Is A m K O / om O er Aj Total Mortality (15,850 deaths) Infant Mortality (7,790 deaths) Lagos State Base Case 2018 Population 400,000 360,000 320,000 280,000 Number of episodes 240,000 200,000 182,400 160,000 120,000 80,000 46,000 40,000 14,700 1,250 240 0 Childhood Onset Adult Restricted Respiratory Cardiovascular Pneumonia Chronic Activity Days Hospital Hospital (< 5 years) Bronchitis (in thousands) Admissions Admissions 124 Air Quality Management Planning for Lagos State FIGURE A1.9. (Continued ) Sensitivity Case 2018 Population 4,000 3,500 Number of premature deaths 3,000 2,500 2,000 1,500 1,000 500 0 fe e Am Ali un o- sho Ap n Ba pa y E e eju sa ko ki e eja u La go ofe ai d M d e n od jo Sh olo Su olu Ep ay ler i-I geg gr od s M lan an fi hi Ifa Lek sh O Ib ti-O a d do Ik s s om da us uw o -Ij ru nl or La o lo i-I go s Is A m K O / Ik om O er Aj Total Mortality (30,350 deaths) Infant Mortality (14,890 deaths) Lagos State Sensitivity Case 2018 Population 400,000 360,000 349,000 320,000 280,000 Number of episodes 240,000 200,000 160,000 120,000 88,000 80,000 40,000 28,300 2,380 460 0 Childhood Onset Adult Restricted Respiratory Cardiovascular Pneumonia Chronic Activity Days Hospital Hospital (< 5 years) Bronchitis (in thousands) Admissions Admissions Source: Author’s own elaboration Note: Adult mortality quantified using GEMM and infant mortality using Heft-Neal et al. (2018). Baseline rates obtained from the WHO GHE database for 2018. Air Quality Management Planning for Lagos State 125 126 TABLE A1.12. PM2.5 ATTRIBUTABLE HEALTH BURDENS FOR THE SENSITIVITY CASE POPULATION Hospital Admissions Lower Respiratory Onset Chronic All ages, Infant Total Mortality* Infections Bronchitis Restricted Activity Days cardiovascular and Local Mortality (all ages) Children under 5-years Adults over 27-years All ages (in thousands) respiratory Government Area (LGA) Deaths Deaths 95%CI Cases 95%CI Cases 95%CI Cases 95%CI Cases 95%CI Agege 720 1,520 960–2,000 17,170 5,090–31,800 1,590 750–1,980 4,110 3,710–4,570 130 4–258 Ajeromi-lfelodun 1,150 2,370 1,500–3,110 27,330 8,300–48,830 2,340 1,140–2,860 6,660 6,020–7,410 212 6–419 Alimosho 1,760 3,610 2,290–4,680 41,470 12,750–72,750 3,590 1,830–4,280 10,200 9,230–11,340 327 10–644 Amuwo Odofin 470 960 610–1,240 11,090 3,440–19,210 900 460–1,090 2,750 2,490–3,050 88 3–174 Apapa 390 820 520–1,070 9,330 2,800–16,970 820 390–1,010 2,250 2,040–2,510 71 2–142 Badagry 120 290 190–400 2,900 800–6,090 290 110–410 650 590–730 20 1–41 Epe 100 250 160–340 2,470 680–5,180 240 100–340 550 500–620 17 1–34 Eti-Osa 570 1,230 770–1,630 13,590 3,930–26,200 1,260 560–1,640 3,180 2,870–3,550 100 3–199 Ibeju-Lekki 30 80 50–100 760 210–1,590 70 30–110 170 150–190 5 0–11 Ifako-ljaye 480 1,030 640–1,350 11,410 3,340–21,530 1,080 500–1,370 2,700 2,440–3,010 85 3–169 Ikeja 510 1,050 660–1,370 11,970 3,610–21,580 1,050 510–1,280 2,900 2,630–3,230 92 3–183 Ikorodu 1,060 1,980 1,310–2,420 23,770 8,760–33,120 1,390 790–1,560 6,740 6,170–7,400 231 7–435 Kosofe 820 1,670 1,060–2,170 19,340 5,970–33,700 1,610 810–1,940 4,780 4,320–5,300 153 5–301 Lagos Island 680 1,410 900–1,850 16,150 4,890–28,970 1,380 670–1,700 3,930 3,550–4,370 125 4–247 Lagos Mainland 500 1,040 660–1,360 11,860 3,590–21,260 970 460–1,200 2,890 2,610–3,210 92 3–182 Mushin 1,630 3,160 2,040–3,970 37,430 12,620–57,850 2,650 1,500–2,980 9,910 9,020–10,940 328 10–632 Ojo 450 1,030 650–1,380 10,950 3,100–21,770 1,080 470–1,440 2,530 2,270–2,820 79 2–158 Oshodi 1,220 2,420 1,550–3,090 28,390 9,200–46,270 2,120 1,130–2,460 7,280 6,610–8,060 238 7–462 Shomolu 1,430 2,720 1,790–3,380 32,540 11,500–47,520 2,170 1,310–2,370 8,930 8,150–9,830 301 10–574 Surulere 790 1,710 1,080–2,260 18,990 5,540–36,050 1,670 750–2,170 4,480 4,040–5,000 141 4–281 Lagos State 14,890 30,350 19,380–39,190 348,900 110,100–598,200 28,280 14.270–34,210 87,610 79,410–97,150 2,840 87–5,550 Source: Author’s own elaboration Note: *Baseline rates obtained from the WHO GHE database for 2018. Numbers may not add up due to rounding off errors. Air Quality Management Planning for Lagos State FIGURE A1.10. PM2.5 ATTRIBUTABLE CAUSE-SPECIFIC MORTALITY FOR LAGOS STATE GHDx-IHME baseline mortality rates WHO-GHE baseline mortality rates 7% 7% 22% 23% 41% 45% 21% 22% 5% Total: 4,610 Total: 5,120 2% 5% premature premature deaths deaths Acute lower respiratory infections Chronic obstructive pulmonary disease Lung cancers Ischemic heart disease Stroke Diabetes mellitus (type 2) Source: Author’s own elaboration. Note: Mortality quantified using the IER functions of the GBD (2020). Baseline rates obtained from the WHO GHE database for 2018. A1.5.2.  HARMATTAN HEALTH BURDEN A1.5.3.  HEALTH BENEFIT ANALYSIS FROM IMPROVEMENTS IN AIR QUALITY Table A1.13 presents the results of attributable mortality from short-term exposure to PM10 during the 2 months Figure A1.12 shows the benefits of reducing PM2.5 of January and February. We have assumed an excess ­ concentration in Lagos. Progressively reaching the PM10 exposure equal to the difference of the average different WHO PM2.5 interim targets, IT 1 (35 μg/m3), concentration for January–February and the average of IT 2 (25 μg/m3), IT 3 (15 μg/m3), IT 4 (10 μg/m3), and the shoulder months December and March. In ­ January the WHO air quality guideline (5 μg/m3) would avert and February, the excess PM10 concentration was 29 percent, 46 percent, 66 percent, 77 percent, and 88 µg/m3 PM10 for the base-case population and 90 µg/m3 90 percent of the estimated attributable premature deaths for the sensitivity-case population with a total of 250 and (green curve). 500 premature deaths, respectively. These numbers are not included in the overall impact assessment performed for PM2.5 long-term exposure. Air Quality Management Planning for Lagos State 127 FIGURE A1.11. PM2.5 ATTRIBUTABLE MORTALITY BY AGE GROUP FOR LAGOS STATE Lagos State Base case 2018 population 42,000 36,000 Number of premature deaths 30,000 24,000 18,000 95% CI 15,200 15,850 12,000 7,030 7,790 7,710 7,450 6,000 460 610 0 Infant Mortality Deaths in age group Adult mortality Total mortality 1 to 25 years (ages 25+) (all ages) Lagos State Sensitivity case 2018 population 42,000 36,000 Number of premature deaths 30,000 30,350 29,100 24,000 95% CI 18,000 14,890 14,780 14,280 13,440 12,000 6,000 880 1,180 0 Infant Mortality Deaths in age group Adult mortality Total mortality 1 to 25 years (ages 25+) (all ages) GHDx (IHME) mortality rates GHE (WHO) mortality rates Source: Author’s own elaboration. 128 Air Quality Management Planning for Lagos State TABLE A1.13. PM10 ATTRIBUTABLE SHORT-TERM MORTALITY DUE TO THE HARMATTAN SEASON Mortality† PM10 Sensitivity Case Population (aged 25+) excess Base Case population population Local Government exposure Area (LGA) Base Case Sensitivity μg/m3 Deaths 95%CI Deaths 95%CI Agege 314,953 704,522 70 10 9–12 23 19–27 Ajeromi-Ifelodun 468,816 978,832 91 20 16–24 41 34–49 Alimosho* 900,075 1,396,016 86 36 30–43 56 46–66 Amuwo Odofin 224,393 358,016 131 13 11–16 22 18–26 Apapa 152,098 356,252 85 6 5–7 14 12–17 Badagry 162,155 259,436 42 3 3–4 5 4–6 Epe 123,960 220,710 42 2 2–3 4 4–5 Eti-Osa* 193,573 670,731 81 7 6–9 25 21–30 Ibeju-Lekki 80,346 67,884 42 2 1–2 1 1–2 Ifako-Ijave 291,758 507,608 64 9 7–10 15 13–18 Ikeja* 216,643 442,409 79 8 7–10 16 14–19 Ikorodu* 360,090 469,910 37 6 5–7 8 7–10 Kosofe 465,716 637,381 90 19 16–23 27 22–32 Lagos Island* 145,082 586,394 89 6 5–7 24 20–29 Lagos Mainland* 222,841 429,281 82 8 7–10 16 14–19 Mushin 430,987 901,239 142 28 23–33 59 49–70 Ojo 415,515 642,093 70 13 11–16 21 17–25 Oshodi 429,080 773,731 119 23 20–28 42 35–50 Shomolu 275,273 699,106 168 21 18–25 54 45–64 Surulere 343,002 869,080 64 10 9–12 26 22–31 Lagos State (Base Case) 6,216,358 88 250 210–300 Lagos State (Sensitivity) 11,970,630 90 500 420–590 Source: Author’s own elaboration. Note: *LGAs where air monitors are located (mean monitored concentration over August 2020 to July 2021). † Short-term mortality (based on the ERF by Orellano et al. 2020) during the 2-month period of January and February, assuming an excess PM10 exposure equal to the difference of the average concentration for the months January and February and the average of the shoulder months December and March. Air Quality Management Planning for Lagos State 129 FIGURE A1.12.  HEALTH BENEFITS FOR A REDUCTION IN PM2.5 AIR POLLUTION ACROSS LAGOS STATE 0 –10 % change compared to current burden –20 –23% –30 –38% –36% (IT#1) –40 –50 –55% (IT#2) –57% –60 –69% –70 –75% (IT#3) –80 –84% –86% (IT#4) –90 –95% (WHO AQG 2021) –100% –100 0 5 10 15 20 25 30 35 40 45 50 Rollback (Reduction) in ambient air PM2.5 concentration, µg/m3 18,000 15,852 (–100%) 16,000 14,000 IT #4 12,239 (–77%) WHO AQG Averted Premature Deaths 12,000 2021 14,279 (–90%) 10,000 IT #2 IT #3 8,000 7,307 (–29%) 10,477 (–66%) IT #1 6,000 4,533 (–29%) 4,000 2,000 0 5 10 15 20 25 30 35 40 45 50 Rollback (Reduction) in ambient air PM2.5 concentration, µg/m3 Infant mortality Adult mortality (25+) Mortality (all ages) Morbidity episodes (all ages) Source: Author’s own elaboration Note: The top figure shows the relative mortality reduction compared to the current state, while the figure below shows the averted deaths for the base-case population and GHE baseline mortality rates. The absolute benefit is roughly doubled for the sensitivity-case population. 130 Air Quality Management Planning for Lagos State TABLE A1.14.  IMPACT ASSESSMENT OF AIR LEAD CONTAMINATION IN IKORODU Children (under 6 years old) Adults (over 40 years) Pb attributable Lead (Pb) air Pb blood IQ loss Pb blood mortality Population concentration Cardiovascular scenario μg/m3 Population μg Pb/dL Child Total deaths μgPb/dL Deaths 95%CI Base Case 1.35 125,499 5.4 6.21 779,349 475 2.7 285 191 346 Sensitivity 1.35 163,824 5.4 6.21 1,017,347 621 2.7 373 250 453 Case Source: Author’s own elaboration. A1.5.4.  IMPACT OF LEAD EXPOSURE ON recommended WHO air quality guideline of 5 µg/m3 (WHO 2021). Urgent action to reach the WHO IT 1 CHILDREN IQ AND CARDIOVASCULAR (35  µg/m3) is therefore recommended. The overall MORTALITY impact on mortality across the population of Lagos State is responsible for 15,850 to 30,350 premature Table A1.14 illustrates the results of the impact assessment deaths per year, with the largest contribution from infant of lead contamination in Ikorodu based on measured air mortality (between 7,800 and 14,900 infant deaths). For contamination (1.35 µg/m3 air lead). We estimated that adult mortality, the impact is larger for cardiovascular every child in Ikorodu (125,500 according to the base case diseases. The impact on morbidity, especially pneumo- and 163,800 according to the sensitivity population) is sig- nia and other acute respiratory conditions, in children nificantly affected by lead exposure. The calculated loss 0–5 years (between 182,000 and 349,000) is particularly of intelligence by each child is 6.21 IQ points, which rep- worrisome. Other outcomes were also estimated and resents a huge physical burden on the current generation they contribute to increasing the overall burden. and potentially a significant loss of future income. The total loss in IQ points for the two populations is 780,000 Two additional critical contributions should be added to and 1,017,000, respectively. Also, the impact of lead on the estimates’ loss of life from long-term exposure to PM2.5: cardiovascular mortality is remarkably high: the attribut- (a) the impact of the daily high levels of PM10 during the able premature mortality is 285 and 373 deaths, according Harmattan period, particularly during January and February to the base case and the sensitivity population, respectively. and (b) industrial air pollution in Ikorodu with the relevant lead contamination, which accounts for a sizable loss of intellectual capacity in children (a total of 780,000 to more A1.6. DISCUSSION than 1 million IQ points at the population level) and a high attributable cardiovascular mortality in that particular AND CONCLUSION LGA (285 to 373 premature cardiovascular deaths). The quantified health burdens should be interpreted as conservative estimates because the additional impact from The estimation of the health burden of disease in Lagos, direct exposure to other critical pollutants (for example, Nigeria, indicates that air pollution from PM2.5 poses a gaseous air pollutants such as NO2 and SO2) has not serious public health hazard, especially among ­children been quantified in this work. A preliminary estimate of younger than 5 years. The PWE is high, reaching the potential attributable burden on mortality from direct 47 µg/m3, a value nearly 10 times higher than the new NO2 exposure, for example, could add a further 10 percent Air Quality Management Planning for Lagos State 131 to the PM2.5 mortality. The adverse health effects from in economic activity as reflected by the change in the exposure to secondary inorganic aerosols (a component internal gross product, a 3.5 percent drop in 2020 at the of PM) created through chemical transformation of NO2 national level compared to the previous year when there and SO2 precursor emissions are already included in the was no COVID-19. This aspect makes our assessment for PM2.5 impact assessment. 2020–2021 somewhat conservative in comparison to the air pollution data probably experienced in past years. The exposure assessment, one of the most important con- tributions of this study, is based on an extensive monitoring The most relevant uncertainty regarding our work is program of air pollution that has been set up in several loca- due to the difficulty in the estimation of the population tions and with standardized procedures and quality controls. at risk. Two different sources have been considered in The results of the monitoring program have been coupled this work because they provide potential extremes of the with the results of a dispersion model and with population population size estimate. Assumptions about age distribu- data to estimate PWEs by LGA. In this way, the concen- tion across different LGAs, often driven by operational tration values are referred to the population, which is the choices, are another source of uncertainty. The difficul- target of the HIA. We have considered a variety of possible ties in such estimations stem from the large size of slum outcomes, encompassing both mortality (natural mortality, settlements that have become a prominent feature of cause-specific mortality) and several morbidity outcomes. the urban landscape of Sub-Saharan Africa, and from We have addressed not only PM2.5 but also the complemen- the dynamic nature of this population (Amegah 2021; tary contributions of daily levels of PM10, mainly attribut- Thomson et al. 2021). We are confident that our sensi- able to Sahara desert dust, and the lead contamination in tivity choices, though imperfect and leading to a broad Ikorodu. Children are the segment of the population most spread in the estimates, are the best approach to charac- affected by air pollution as they suffer from extraordinar- terizing the potential size range of the Lagos population. ily high infant mortality, experience frequent episodes of pneumonia and other respiratory disorders, and have to Another concern about the estimates is related to the cope with a large limitation of their intellectual capability. absence of reliable baseline health data for the entire It amounts to irreversible damage to the next generation. population. The value of good-quality mortality data for Finally, we have considered several methodological aspects public health is widely acknowledged. While effective civil in our assessment (exposure estimation, choice of the ERFs, registration systems remain the “gold standard” source alternative demographic assumptions) to overcome the for continuous mortality measurement, in most African main limitations described further below. countries fewer than 25 percent of deaths are registered, and it appears to be no different in Lagos (Joubert et al. The HIA for Lagos refers to the most recent period of 2012). In addition, only a fraction of the hospital institu- ambient air pollution monitoring—August 2020 to July tions (the public sector) register mortality and morbidity 2021. This is the period with the most accurate meas- statistics, and a large fraction of health care providers do urement of air pollution. On the other hand, the other not release regular information. This difficulty is coupled data for the HIA refer to a preceding period (that is, with the traditional lack of medical certification for per- 2018 population data and available health statistics for sons dying at home. We have used two sources of mortal- 2017 and 2018). We believe that the error induced by ity information related to Nigeria (GBD and WHO) and this choice is minimal because the recent mortality rate have scaled down to Lagos, accounting for the differences has trended lower over the past decade, although at the between national and local age distributions. For hospitali- same time population growth has been observed. The net zations, we have used the registrations of the events in the effect is that our estimates are on the conservative side. public sector with the strong assumption that the private In addition, it should be noted that the measurement sector has a proportionally similar load of patients. Finally, period occurred during the COVID-19 pandemic, which it is clear that a source-specific HIA was not performed as has affected Africa and Nigeria as well, with a decrease a clear partition of PM2.5 exposure data was not available. 132 Air Quality Management Planning for Lagos State Before comparing the present HIA with other evaluations health impact in Addis Ababa. After a continuous conducted worldwide and in Africa, it is worth noting measurement of 3  years, the annual average PM2.5 the strengths and limitations of the present work. There concentration was found to be 42.4 µg/m3. The PM2.5 are only a few examples of HIAs in Africa. Wheida related mortality was estimated at 2,043 premature et al. (2018) notably conducted an HIA to quantify the deaths, assuming a counterfactual equal to 10 μg/m3. mortality attributable to long-term exposure to PM2.5, Finally, in Ghana, a series of studies are ongoing in Accra NO2, and O3 in Greater Cairo (Egypt). As in Lagos, to address various sources of air ­ pollution such as waste PM2.5 concentrations vary from 50 to over 100 µg/m3 in management (Kanhai et al. 2021) and transportation the different sectors of the Egyptian megacity, with an (Garcia et al. 2021). average concentration of 75 µg/m3. In the population older than 30 years, 11 percent of the natural mortality These studies, however, rely on effect estimates from could be attributed to PM2.5. No assessment of infant other parts of the world because data from the African mortality and childhood morbidity was conducted. continent are largely deficient due to low access to good- In Ethiopia, Kumie et al. (2021) performed real-time quality health care, the high prevalence of infectious monitoring of PM2.5 concentrations and assessed the diseases, and different sources of air pollutants. As  a TABLE A1.15.  COMPARISON OF CURRENT ESTIMATES OF PM2.5 MORTALITY RATES IN LAGOS STATE TO ESTIMATES FROM PREVIOUS WORK BY CROITORU, CHANG AND KELLY (2020) Croitoru, Chang, and Risk model Akpokodje (2020) This study IER functions for deaths due to PM2.5 concentration: 47 μg/m3 based on 1-year, 2020–21, cardiovascular and respiratory measuring campaign plus lung cancer and diabetes 2019 IER functions (GBD 2020) Base case population: 13.3 million Mortality rate (per 105): 38.5 Sensitivity population: 25.6 million Mortality rate (per 105): 37.0 IER functions for deaths due to PM2.5 concentration: 68 μg/m3 PM2.5 concentration: 68 μg/m3, same as Croitoru, Chang, cardiovascular and respiratory and Akpokodje (2020) plus lung cancer and diabetes Population size: 24.4 million 2019 IER functions (GBD 2020) GBD 2018 IER function Base case population: 13.3 million Mortality rate (per 105): 45.9 Mortality rate (per 105): 47.0 Sensitivity population: 25.6 million Mortality rate (per 105): 45.5 GEMM for NCD and=d lower PM2.5 concentration: 47 μg/m3 based on 1-year, 2020–21, respiratory illnesses plus Heft- measuring campaign Neal et al. (2018) for infant mortality Base case population: 13.3 million Mortality rate (per 105): 119.2 Sensitivity population: 25.6 million Mortality rate (per 105): 118.6 Air Quality Management Planning for Lagos State 133 result, the health effects in Africa are likely underesti- switching from the IER model to the GEMM and Heft- mated (Abera et al. 2021). The paper by Heft-Neal et al. Neal et al. relationships. This difference is due in part (2018), for example, found that in the African context, a to the size of the baseline mortality used by the different 10 μg/m3 increase in PM2.5 concentration was associated models (Table A1.9), but, more importantly, the differ- with a 9.2 percent rise in infant mortality. PM2.5 concen- ence is related to the shape of the ERFs (Figure A1.7). trations were responsible for 22 percent of infant deaths For instance, the rate of decrease in the health risk at in the 30 countries of Africa considered in the study. higher exposures using the GEMM relationship is much This was equivalent to 449,000 additional infant deaths less than predicted by the IER model. in 2015, an estimate that was more than three times higher than previous estimates (Heft-Neal et al. 2018). In conclusion, the work illustrates a dramatic situation Finally, the recent work by Fisher et al. (2021) should in Lagos that highlights the large burden of PM air pol- be noted because they conducted an HIA for air pollu- lution on public health. A future analysis would benefit tion for the entire continent of Africa and indicated that from greater knowledge about exposure assessment, pos- ambient air pollution is increasing across the continent. sibly source-specific, and systematic collection of demo- In the absence of a deliberate intervention, it will likely graphic and health data. Further, it would be useful in increase morbidity and mortality, which will diminish follow-up analyses to undertake regional and/or local economic productivity, impair human capital formation, epidemiologic studies in Lagos so that ERFs would better and undercut development. reflect local conditions. Short of that, it would be ideal to develop disease-specific mortality risk estimates for Lagos In 2020, Croitoru, Chang and Kelly published the that could be utilized to enhance the accuracy of the first HIA of the burden of fine particulate matter in burden assessment from PM2.5 exposure. ­ Lagos State. 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TABLE A2.1.  INPATIENT HOSPITAL ADMISSIONS, 2017 Disease ICD-10 Cases Deaths Comment Ischemic heart disease (IHD) 120-25 5 0 Ages 15+: four cases Stroke 842 171 Listed as code 170 Chronic obstructive pulmonary J40-44 12 0 Asthma (J45): 159 cases (no deaths) disease (COPD) Lung cancer C30-39 31 1 Ages 15+: 28 cases; 1 infant death Diabetes E10-14 556 35 Ages 15+: 541 cases & 35 deaths Pneumonia J12-18 1,412 46 Under 5:1,221 cases & 41 deaths Other Acute lower respiratory J20-22 276 8 Under 5: 227 cases & 3 deaths infections (ALRI) Air Quality Management Planning for Lagos State 139 TABLE A2.2.  SHARE OF TOTAL INPATIENT HOSPITAL ADMISSIONS BY DISEASE Disease Incidences Deaths Circulatory 27.0% 65.5% IHD 0.2% – Stroke 26.9% 65.5% Respiratory 55.2% 21.1% COPD 0.4% – Lung cancer 1% 0.4% ALRI 53.9% 20.7% Diabetes 17.7% 13.4% TABLE A2.3.  OUTPATIENT HOSPITAL ADMISSIONS, 2017 Disease ICD-10 Cases Deaths Comment Ischemic heart disease (IHD) 120-25 729 0 Ages 15+: 729 cases Stroke 2,758 128 Listed as code 170 Chronic obstructive pulmonary J40-44 293 0 Asthma (J45): 4,413 cases (2 deaths) disease (COPD) Lung cancer C30-39 3 1 Ages 50+: 3 cases (1 death) Diabetes E10-14 8,203 24 Ages 15+: 8,202 cases & 24 deaths Pneumonia J12-18 6,338 37 Under 5: 3,964 cases & 30 deaths Other Acute lower respiratory J20-22 3,860 6 Under 5: 1,902 cases & 4 deaths infections (ALRI) TABLE A2.4.  SHARE OF OUTPATIENT HOSPITAL ADMISSIONS BY DISEASE Disease Incidences Deaths Circulatory 15.7% 65.3% IHD 3.3% – Stroke 12.4% 65.3% Respiratory 47.3% 22.4% COPD 1.3% – Lung cancer 0.01% 0.5% ALRI 46.0% 21.9% Diabetes 37.0% 12.2% 140 Air Quality Management Planning for Lagos State As a comparison to the Lagos data, the relative distribution of deaths for six GBD causes of death at the national level in 2019 (IHME 2021) is reported in the table below. IHD+Stroke LRI COPD LC DM 6-COD Total 38.1% 49.5% 4.0% 1.8% 6.5% 349,146 Note: The mortality ratio CVM (cardiovascular mortality) to LRI (lower respiratory infections) is about 3:1 in Lagos versus 0.77 at the national level. A2.2.  SENSITIVITY CALCULATIONS USING AN ALTERNATIVE ASSESSMENT OF THE PWE In the following tables and figures, results of a sensitivity assessment of the exposures are presented: for non-monitored LGA, PM2.5 concentration estimates have been assigned based on the LGA’s proximity to the nearest monitoring station. TABLE A2.5.  ANNUAL PM PWE BY LGA FOR THE SENSITIVITY ANALYSIS Population (all ages) PWE, mg/m3 Local Government Longitude Latitude Land Area Area (LGA) (deg) (deg) (km2) Base Case Sensitivity PM2.5 PM10 Agege 3.316 6.623 17.0 673,840 1,507,591 46 124 Ajeromi-Ifelodun 3.337 6.456 13.9 1,003,027 2,094,583 42 105 Alimosho* 3.255 6.576 137.8 1,925,702 2,987,306 46 124 Amuwo Odofin 3.279 6.439 179.1 480,086 766,111 29 74 Apapa 3.371 6.435 38.5 325,412 762,336 42 97 Badagry 2.914 6.442 443.0 346,930 555,162 29 74 Epe 3.973 6.553 965.0 265,212 472,292 29 74 Eti-Osa* 3.536 6.452 299.1 414,147 1,435,282 29 74 Ibeju-Lekki 3.911 6.454 653.0 171,900 145,263 29 74 Ifako-Ijaye 3.309 6.665 43.0 624,214 1,086,220 46 124 Ikeja* 3.350 6.604 49.9 463,507 946,703 41 106 Ikorodu* 3.566 6.612 345.0 770,410 1,005,551 97 171 Kosofe 3.399 6.600 84.4 996,396 1,363,919 41 106 Lagos Island* 3.392 6.454 9.3 310,402 1,254,812 42 105 Lagos Mainland* 3.383 6.499 19.6 476,766 918,609 42 97 Mushin 3.347 6.530 14.1 922,094 1,928,542 42 97 Ojo 3.153 6.454 182.0 888,990 1,374,002 29 74 Oshodi 3.314 6.542 42.0 918,014 1,655,691 42 97 Air Quality Management Planning for Lagos State 141 TABLE A2.5.  (Continued ) Population (all ages) PWE, mg/m3 Local Government Longitude Latitude Land Area Area (LGA) (deg) (deg) (km2) Base Case Sensitivity PM2.5 PM10 Shomolu 3.383 6.538 14.6 588,944 1,496,003 42 97 Sunilere 3.345 6.492 27.1 733,851 1,859,727 42 97 Lagos State (Base Case population) 3,577 13,299,845 43 105 Lagos State (Sensitivity population) 3,577 25,615,703 42 103 Source: Author’s own elaboration. FIGURE A2.1.  AMBIENT AIR QUALITY IN LAGOS STATE AND LGAS FOR PWE SENSITIVITY ANALYSIS Agege Ajeromi-Ifelodun Alimosho (ABESAN) 46 124 Amuwo-Odofin Apapa Badagry Epe Eti-Osa (NCF) 29 74 Ibeju/Lekki Ifako-Ijaye Ikeja (LASEPA) 41 106 Ikorodu (IKORODU) 97 171 Kosofe Lagos Island (JANKARA) 42 105 Lagos Mainland (UNILAG) 42 97 Mushin Ojo Oshodi-Isolo Shomolu Surulere Lagos State 43 105 0 30 60 90 120 150 180 210 240 270 300 PM10 PM2.5 Source: Author’s own elaboration. Note: The six LGAs where daily ambient concentrations were monitored during the monitoring campaign between August 2020 and July 2021 are highlighted by the gray boxes along the y-axis on the left. 142 Air Quality Management Planning for Lagos State TABLE A2.6. PM2.5 ATTRIBUTABLE HEALTH BURDENS FOR PWE SENSITIVITY ANALYSIS, BASE CASE POPULATION Hospital Admissions Local Lower Respiratory Onset Chronic All ages, Government Infant Total Mortality* Infections Bronchitis Restricted Activity Days cardiovascular and Area (LGA) Mortality (all ages) Children under 5-years Adults over 27-years All ages (in thousands) respiratory Deaths Deaths 95%CI Cases 95%CI Cases 95%CI Cases 95%CI Cases 95%CI Agege 400 820 520–1,060 9,350 2,870–16.410 810 410–970 2,300 2,080–2,560 2–145 Ajeromi-Ifelodun 550 1,140 720–1,480 12,910 3,910–23,160 1,110 540–1,360 3,140 2,840–3,490 100 3–198 Alimosho 1,130 2,320 1,470–3,020 26,730 8,220–46.890 2,320 1,180–2,760 6,580 5,950–7,310 211 6–415 Amuwo Odofin 190 410 260–550 4,550 1,310–8,760 420 190–550 1,060 960–1,190 33 1–67 Air Quality Management Planning for Lagos State Apapa 180 370 230–480 4,200 1,270–7.530 340 160–430 1,020 920–1,140 33 1–64 Badagrv 140 300 190–400 3,280 950–6,330 300 140–400 770 690–860 24 1–48 Epe 100 220 140–300 2,510 730–4,840 230 100–300 590 530–660 18 1–37 Eti-Osa 160 350 220–470 3,920 1,130–7,560 360 160–470 920 830–1,030 29 1–57 Ibeju-Lekki 70 150 90–200 1,630 470–3,140 150 70–200 380 340–430 12 0–24 Ifako-Ijaye 370 760 480–980 8,660 2,660–15,200 750 380–900 2,130 1,930–2,370 68 2–134 Ikeja 250 520 330–670 5,860 1,770–10,570 510 250–630 1,420 1,290–1,580 45 1–89 Ikorodu 810 1,510 1,000–1,860 18,210 6,710–25,370 1,060 610–1,190 5,170 4,730–5,670 177 6–334 Kosofe 530 1,100 700–1,450 12,600 3,800–22,710 1,100 530–1,350 3,060 2,760–3,400 97 3–192 Lagos Island 170 350 220–460 4,000 1,210–7,170 340 170–420 970 880–1,080 31 1–61 Lagos Mainland 260 540 340–700 6,160 1,870–11,030 500 240–630 1,500 1,350–1,670 48 1–94 Mushin 500 1,040 660–1,360 11,900 3,610–21,330 970 460–1,210 2,900 2,620–3,220 92 3–182 Ojo 350 760 480–1,010 8,420 2,430–16,230 780 350–1,020 1,970 1,780–2,200 62 2–123 Oshodi 500 1,040 660–1,350 11,850 3,590–21,240 970 460–1,200 2,880 2,610–3,210 92 3–182 Shomolu 320 660 420–870 7,600 2,300–13,630 620 290–770 1,850 1,670–2,060 59 2–116 Surulere 400 830 520–1,080 9,470 2,870–16,980 770 370–960 2,310 2,080–2,560 73 2–145 Lagos State 7,380 15,180 9,650–19,740 173,800 53,700–306,100 14,430 7,050–17,720 42,920 38,900–47,700 1,380 42–2,710 Note: *Baseline rates obtained from the WHO GHE database for 2018. 143 144 TABLE A2.7. PM2.5 ATTRIBUTABLE HEALTH BURDENS FOR PWE SENSITIVITY ANALYSIS, SENSITIVITY POPULATION Local Lower Respiratory Onset Chronic Restricted Hospital Admissions Government Infant Total Mortality* Infections Bronchitis Activity Days All ages, cardiovascular Area (LGA) Mortality (all ages) Children under 5-years Adults over 27-years All ages (in thousands) and respiratory Deaths Deaths 95%CI Cases 95%CI Cases 95%CI Cases 95%CI Cases 95%CI Agege 890 1,820 1,150–2,360 20,930 6,430–36,710 1,810 920–2,160 5,150 4,660–5,720 165 5–325 Ajeromi-Ifelodun 1,140 2,360 1,500–3,090 26,960 8,170–48,360 2,310 1,120–2,840 6,560 5,930–7,290 209 6–413 Alimosho 1,760 3,610 2,290–4,680 41,470 12,750–72,750 3,590 1,830–4,280 10,200 9,230–11,340 327 10–644 Amuwo Odofin 300 650 410–870 7,250 2,100–13,990 670 300–880 1,700 1,530–1,900 53 2–106 Apapa 420 870 540–1,120 9,840 2,980–17,640 800 380–1,000 2,400 2,170–2,660 76 2–151 Badagry 220 480 300–630 5,260 1,520–10,140 490 220–640 1,230 1,110–1,370 39 1–77 Epe 190 410 250–540 4,470 1,290–8,620 410 180–540 1,050 940–1,170 33 1–66 Eti-Osa 570 1,230 770–1,630 13,590 3,930–26,200 1,260 560–1,640 3,180 2,870–3,550 100 3–199 Ibeju-Lekki 60 130 80–170 1,380 400–2,650 130 60–170 320 290–360 10 0–20 Ifako-Ijaye 640 1,310 830–1,700 15,080 4,630–26,450 1,310 670–1,560 3,710 3,360–4,120 119 4–234 Ikeja 510 1,050 660–1,370 11,970 3,610–21,580 1,050 510–1,280 2,900 2,630–3,230 92 3–183 Ikorodu 1,060 1,980 1,310–2,420 23,770 8,760–33,120 1,390 790–1,560 6,740 6,170–7,400 231 7–435 Kosofe 730 1,520 960–1,980 17,250 5,210–31,090 1,510 730–1,850 4,180 3,780–4,660 133 4–263 Lagos Island 680 1,410 900–1,850 16,150 4,890–28,970 1,380 670–1,700 3,930 3,550–4,370 125 4–247 Lagos Mainland 500 1,040 660–1,360 11,860 3,590–21,260 970 460–1,200 2,890 2,610–3,210 92 3–182 Mushin 1,050 2,180 1,380–2,850 24,900 7,550–44,630 2,030 960–2,530 6,060 5,480–6,740 193 6–381 Ojo 540 1,180 740–1,570 13,010 3,760–25,080 1,200 530–1,570 3,050 2,750–3,400 95 3–191 Oshodi 900 1,870 1,180–2,440 21,380 6,480–38,310 1,740 830–2,170 5,200 4,700–5,790 166 5–327 Shomolu 820 1,690 1,070–2,210 19,320 5,850–34,620 1,570 750–1,960 4,700 4,250–5,230 150 5–296 Surulere 1,010 2,100 1,330–2,740 24,010 7,280–43,030 1,960 930–2,440 5,840 5,280–6,500 186 6–368 Lagos State 13,970 28,860 18,320–37,590 329,900 101,200–585,200 27,580 13,400–33,970 81,000 73,290–90,010 2,590 79–5,110 Source: Author’s own elaboration. Note: *Baseline rates obtained from the WHO GHE database for 2018. Numbers may not add up due to rounding off errors. Air Quality Management Planning for Lagos State FIGURE A2.2. PM2.5 ATTRIBUTABLE MORTALITY BY LGA AND MORBIDITY FOR LAGOS STATE, PWE SENSITIVITY ANALYSIS Base Case 2018 Population 4,000 3,500 Number of premature deaths 3,000 2,500 2,000 1,500 1,000 500 0 fe e Am Ali un o- sho Ap n Ba pa y E e eju sa ko ki e Ik ja u La go ofe ai d M d n od jo e Sh olo Su olu i-I geg Ep ay ler gr od s M lan an fi hi Ifa Lek e sh O Ib ti-O a d do Ik s s om da us uw o -Ij ru nl or La o lo i-I go s Is A m K O / om O er Aj Total Mortality (15,180 deaths) Infant Mortality (7,380 deaths) Lagos State Base Case 2018 Population 360,000 320,000 280,000 Number of episodes 240,000 200,000 174,000 160,000 120,000 80,000 43,000 40,000 14,400 1,160 220 0 Childhood Onset Adult Restricted Respiratory Cardiovascular Pneumonia Chronic Brochitis Activity Days Hospital Hospital (< 5 years) (thousands) Admissions Admissions Air Quality Management Planning for Lagos State 145 FIGURE A2.2. (Continued ) Sensitivity Case 2018 Population 4,000 3,500 Number of premature deaths 3,000 2,500 2,000 1,500 1,000 500 0 fe e Am Ali un o- sho Ap n Ba pa y E e eju sa ko ki e eja u La go ofe ai d M d e n od jo Sh olo Su olu Ep ay ler i-I geg gr od s M lan an fi hi Ifa Lek sh O Ib ti-O a d do Ik s s om da us uw o -Ij ru nl or La o lo i-I go s Is A m K O / Ik om O er Aj Total Mortality (28,860 deaths) Infant Mortality (13,970 deaths) Lagos State Sensitivity Case 2018 Population 360,000 330,000 320,000 280,000 Number of episodes 240,000 200,000 160,000 120,000 81,000 80,000 40,000 27,600 2,180 420 0 Childhood Onset Adult Restricted Respiratory Cardiovascular Pneumonia Chronic Brochitis Activity Days Hospital Hospital (< 5 years) (thousands) Admissions Admissions Source: Author’s own elaboration. Note: Adult mortality quantified using GEMM and infant mortality using Heft-Neal et al. (2018). Baseline rates obtained from the WHO GHE database for 2018. 146 Air Quality Management Planning for Lagos State ANNEX 3 ECONOMIC AND FINANCIAL ASSESSMENT: POLICY, INVESTMENT, AND COST ASSUMPTIONS The use of “economic” or social cost is a useful concept for assessing activities that have environmental externalities, such as air pollution, because it includes health and other kinds of damage that are not typically reflected in the market. Because con- sumer decisions typically rely on market prices, it is also important for policy makers to ensure that financial costs (reflected in “market prices”) are at appropriate levels to reduce air pollution, for example, by taxing air pollution or subsidizing clean fuels. Cost-effectiveness analysis allows different control measures to be compared based on their cost to reduce air pollution (Naira/US dollar per ton of PM2.5 reduced). The costs for implementing different interventions have been estimated using data from projects in Lagos and elsewhere. Where possible, the proposed interventions have been selected from projects already undertaken in Lagos or in Nigeria. Many potential air quality interventions, such as public transport or the power grid, require public investments while others, such as emissions testing for vehicles or enforcing emissions standards for industry, require regulatory costs. To comply with emissions standards, such as emissions control equipment or clean fuels, there needs to be private costs. These expenditures will be referred to as compliance costs. For some air quality interventions, such as electricity tariffs from additional power sold by the grid or fare revenue from public bus or rail service, there may be additional revenue from improved service. The main benefits of controlling air pollution are the expected reductions in health impacts. Premature mortality attributable to air pollution in Lagos has been estimated in this study at between 15,000 and 30,000 deaths per year, with infants under 1 year accounting for over half of the deaths. The value of premature mortality has been calculated between 1.9 and 3.6 percent of Lagos’ GDP based on lost productivity, Air Quality Management Planning for Lagos State 147 and between 3.7 and 7.2 percent using the VSL. By The remainder of the waste, much of it organic, is left to comparing the costs and benefits of reducing PM2.5 for decompose. Modern sanitary landfills are built to avoid each intervention, it is possible to (a) estimate how much contaminating groundwater and surface water and to it would cost to reduce emissions and (b) estimate and capture the CH4 produced from decomposing organic compare the cost-effectiveness of different air pollution matter. CH4 captured can be used to generate electricity control measures. or supplied to other energy users in the form of natu- ral gas. Because CH4 is a powerful GHG,43 landfills that For the economic and financial analysis, the share of air capture it can earn carbon credits through mitigating the pollution from the key sectors has relied on the estimates release of CH4. from the emissions inventory and source apportionment work from the study.42 The per capita generation of MSW in Lagos has been estimated at 0.75 kg per day, which translates to 15,000– 18,000 tons of MSW per day for a city of 20–25 million A3.1.  AQM CONTROL people. Open burning is used as a way for households and enterprises to dispose of uncollected MSW, and STRATEGIES BY SECTOR open burning occurs at landfills through intentional burning and the spontaneous combustion of waste. It is SOLID WASTE assumed that through additional investment in collection vehicles and landfills phased in over several years, waste Based on the air pollution monitoring and emissions collection could progressively increase from the cur- inventory conducted for the study, the burning of MSW, rent rate estimated at 54 percent (PwC 2021) to around both collected and uncollected, emerges as a major con- 80 percent of total MSW generated. Because available tributor to PM2.5 air pollution in Lagos. Because such a land for landfills is not limitless and the value of land in large share of air pollution in Lagos originates from the Lagos is continues to rise as the city grows, it is impor- open burning of solid waste, a critical policy for Lagos tant to reduce the overall amount of MSW that goes (and LAWMA) is to increase the amount of solid waste into landfills. Investments in recycling, composting, and that is collected and eliminate the open burning of solid incineration would reduce the amount of waste needed wastes at landfills. to be deposited in landfills. The analysis assumes that the organic fraction of MSW is 50 percent, the combusti- Government policies for waste management can help ble fraction is 75 percent (organic 50 percent + paper minimize the amount of waste that is generated by ensur- 15 percent + plastic 10 percent) and that 25 percent of ing that markets for recyclables and organic material are the collected and recyclable MSW (paper and plastic) is developed. Collection fees for solid waste could help recycled. cover the costs of collecting and disposing of solid waste. Regardless of collection fees, to reduce air pollution from In addition to special handling procedures for hazard- solid waste, it is essential that the municipality collect as ous wastes, it is important to encourage the separation much solid waste as possible and ensure that the MSW of solid waste to facilitate recycling and composting. collected is not burned. Organic waste, for instance, needs to be separated so that it does not contaminate recyclables such as paper and Based on estimates of per capita solid waste, the total cardboard. Neighborhood collection sites that allow plas- amount of MSW generated in Lagos is more than 15,000 tics, metals, and glass to be separated could enhance the tons per day, or more than 5 million tons per year. The feasibility of recycling by reducing the cost of collection majority of the share of Lagos’ MSW that is collected and ensuring a higher-quality recycled product. goes to one of four active dumpsites, where waste pick- ers scavenge for usable items, mainly metal and plastics. 148 Air Quality Management Planning for Lagos State TRANSPORT vehicle emissions. While improved vehicle standards cannot immediately replace Lagos’ old and high-­ The transport sector is one of several large contributors polluting fleet, requiring that new vehicles meet stricter to PM2.5 air pollution in Lagos. Given its importance to standards is an important start, including by providing the economy—moving people and goods—and the fact incentives and penalties. The fixed number of legal that it will undoubtedly grow, it is essential that air quality ports of entry, and the fact that most secondhand vehi- policy measures for the transport sector comprise a major cles originate from countries with well-established emis- part of Lagos’ AQM plan. Among the important meas- sion control regimes, imply that targeted efforts to verify ures to reduce PM2.5 emissions from the transport sector and improve the emissions performance of secondhand are (a) continued expansion and improvement of public vehicles are feasible. transport; (b) improvement in emissions control among vehicle fleets such as trucks, buses, passenger cars, and Although detailed information on the emissions stand- motorcycles; and (c) the increased supply and guarantee ards of the vehicle fleet in Lagos is not available, limited of clean transport fuels in conjunction with stricter emis- survey data suggest that most of the fleet is older than sions standards for vehicle fleets. 15 years. Although Nigeria agreed in 2018 to establish Euro 4 standards for new vehicle registrations along with 50 ppm fuel sulfur standards, this has not yet occurred. A new vehicle inspection program was established in INSPECTION AND MAINTENANCE Lagos in 2016,46 which is an important step to ensure that vehicles are safe and that emissions control equipment is I&M programs are a prerequisite for implementing maintained. Because high vehicle emissions often tend to vehicle improvement programs. The establishment of be concentrated in a small percentage of vehicles, vehi- LACVIS44 in 2016 was an important development in the cle inspection is important for removing “gross polluters” capability to monitor and enforce vehicle emission regu- from the road for repair or scrappage. I&M, combined lations, including the identification of gross polluters, with improving emission standards for new vehicles, is mandatory maintenance, vehicle retirement, and retrofit important for reducing emissions from the vehicle fleet. programs. Currently, the program requires vehicles to be inspected and that they display their emissions certificates on the vehicle or face a fine. MINIBUSES/DANFOS Based on experience elsewhere, a large share of vehicle Upgrading the vintage of vehicle fleet could significantly air pollution has been found to come from a small frac- reduce PM2.5 emissions. For example, if a Euro 1 vehicle tion of vehicles, so-called “gross polluters.” In practice, can be replaced by a Euro 4 vehicle,47 PM2.5 emissions this means that regulation and enforcement of ­ vehicle could be reduced ninefold (see Table A3.1). Requiring emissions will be effective if it can control the worst that danfos be less than 16 years old—Euro 4 equivalent ­ polluters (Krzyzanowski et al. 2005),45 which can be iden- vehicles were introduced in Europe and the US in 2005— tified through I&M or roadside inspection. would ensure that the emissions control equipment for new and most used vehicles in Nigeria would be at least Euro 4-spec. To achieve the lower emissions from newer IMPROVING VEHICLE TECHNOLOGY vehicles, it is necessary to improve fuel quality. Without lower sulfur fuels, the emissions control equipment (both Improving vehicle technology in line with cleaner fuel catalysts and filters) on newer vehicles could be perma- is the way many countries and cities have reduced nently destroyed. Air Quality Management Planning for Lagos State 149 TABLE A3.1.  ALTERNATIVE VEHICLE PUBLIC TRANSPORT TECHNOLOGIES FOR LARGE BUSES The expansion of public transport should be considered an Purchase PM2.5 emissions important way of improving the efficiency of transport in Technology cost (US$) (gPM2.5/km) Lagos and of reducing both air pollution and GHG emis- Baselinea 200,000 0.14 sions. With support from international donors, Lagos has invested in both infrastructure and institutions to improve Clean diesel 400,000 0.025 public transport, including BRT, light rail, and ferries. The CNG 450,000 0.009 upgrading and expansion of public transport in Lagos could Hybrid (diesel-electric) 500,000 0.012 have a large positive impact on air quality. Public transport investments are large and multi-year and must be justified Electric 750,000 0.003 largely on their transportation benefits rather than on their Note: a Baseline assumes Euro 1 diesel buses (properly tuned). https://www.catf​ contribution to improving air quality. Although the air qual- .us/wp-content/uploads/2019/02/CATF_Pub_Diesel_VS_CNG.pdf. ity benefits of public transport can be large, public transport investments need to be evaluated on their long-term contri- bution to air quality rather than on their capacity to make an immediate positive impact on air quality. BUSES Many countries and municipalities have attempted to reduce air pollution by converting vehicle fleets FREIGHT TRANSPORT to cleaner technologies such as “clean diesel,” natu- ral gas (CNG/LNG), diesel-electric hybrids, or fully Investments in alternatives to road transport for freight electric. The costs of establishing dedicated alterna- are under way in Lagos and should help relieve road traf- tive fuel systems for vehicles include new fuel or motor fic congestion and reduce air pollution. Major rail infra- systems as well as refueling stations. Because of the structure such as the Lagos-Ibadan portion of the larger difficulties of guaranteeing clean diesel fuel free from Lagos-Kano rail project will connect Apapa seaport and adulteration, some cities have used this as a reason for thus reduce the amount of truck traffic in central Lagos. moving to alternative fuels such as CNG or electric. As with BRT and light-rail projects, large investments in Focusing on fleet vehicles such as taxis, buses, or deliv- rail freight must be justified by their transportation ben- ery trucks has been a proven approach for alternative efits, such as reductions in shipping costs and delivery fuel vehicles, since this requires the establishment and times. Nonetheless, investment in rail freight from the maintenance of fewer refueling facilities, and conver- busy Apapa and Tin Can ports can reduce truck traffic sion and maintenance can be handled by dedicated and the air pollution they generate. service personnel. It also allows the refueling facilities to maintain their own fuel quality, such as the ultra- In addition to rail freight, measures to reduce emis- low sulfur diesel that is required for advanced catalysts sions from freight trucks must be part of the solution and particulate filters. Given the global trend and fall- to air pollution in Lagos. In parallel with measures to ing costs of hybrid and electric vehicles, an evaluation upgrade light-duty vehicles and buses, there needs to be of the costs of such vehicles should be undertaken an expanded program combining vehicle inspections, sooner rather than later, particularly for fleet vehicles emissions certificates, fines for noncompliance, and a such as buses, taxis, and delivery trucks (Mufson and guaranteed supply of clean diesel for heavy-duty trucks. Kaplan 2021).48 This will likely require investments in newer heavy-duty 150 Air Quality Management Planning for Lagos State trucks, or the retrofitting of existing trucks with pollution emissions from the transport sector. To guard against controls such as catalysts and diesel particulate filters. fuel adulteration and protect the emissions control Either option will likely be costly for truck owners, but equipment in vehicles, it is necessary to ensure that fuel the gains are also likely to be large, given the high share quality at fueling stations is maintained (Table A3.3). of PM2.5 that comes from diesel combustion. Requiring that petroleum products in Lagos meet higher-quality standards will reduce emissions not only from transport but also from other users of diesel fuel FUEL QUALITY such as industry and the backup electricity generators used throughout Lagos State. Improved fuel quality can lower PM2.5 emissions through the introduction of more sophisticated emissions con- trol systems on vehicles, such as catalysts and particu- INDUSTRY late filters that require the use of cleaner fuels. Many of the catalysts and particulate traps that are installed Industry is known to be a major contributor to air pol- in vehicles that are imported, either new or used, into lution in Lagos. Several high-polluting industries have Nigeria and other countries would quickly become inef- moved away from central Lagos in recent years, and the fective with Nigeria’s current fuel quality (assumed to government has sometimes assisted in their relocation. be 1,424 ppm sulfur for gasoline and 2,389 ppm sulfur The government’s main role, however, is the monitoring for diesel). Yet establishing stricter standards for trans- and enforcement of air pollution standards, which may port fuels—gasoline, diesel, and marine fuel oil—has require automatic pollution monitoring equipment at been hampered in Nigeria by fuel smuggling, includ- major industrial plants. At the same time, helping indus- ing from illegal refineries in the Niger delta, and by the tries convert to cleaner technologies or fuels, through delay in the construction of the Dangote refinery. At training and technical assistance, can be an important 650,000 bpd, the Dangote refinery would be the largest way for them to remain competitive and improve their in Nigeria and would meet the country’s refined petro- productivity and profitability. “Cleaner production” leum product needs of around 600,000 bpd. Nigeria emerged in the 1980s and 1990s as a strategy for both currently produces over 2.5 billion bpd of crude oil. reducing industrial pollution and facilitating the develop- In terms of fuel quality, the Dangote refinery is slated ment of many high-tech and high value-added industries to produce Euro 6 standard fuels, meaning ultra-low such as information and technology and food processing sulfur diesel and gasoline (10 ppm sulfur). New fuel (World Bank 1998). standards—150 ppm for gasoline and 50 ppm for diesel—were set to be introduced in Nigeria in 2017 but have not yet been implemented. ELECTRICITY GENERATION The current fuel quality in Nigeria does not allow the Nigeria’s power sector is characterized by high techni- effective operation of vehicle catalysts beyond Euro 1, cal and financial losses, and the current system cannot a standard that was implemented in Europe in the early provide adequate electricity to the economy. As such, 1990s. Properly functioning Euro 5 vehicles can lower Nigeria has among the highest share of electricity pro- emissions of PM2.5 by a factor of 28 compared to vided by backup generators (“gensets”) in the world. Euro 1 vehicles. Reducing the sulfur content of petro- These generators are expensive to operate, noisy, and leum fuels—gasoline, diesel, and fuel oil (marine)—can highly polluting. Gensets in Lagos may account for as lower the production of secondary aerosols such as much as 40 percent of electricity generation (1,940 GWh) SOx, which have been estimated at 10 percent of PM2.5 and as much as 90 ­ percent of air pollution from power Air Quality Management Planning for Lagos State 151 generation (chapter 2). Long-term investment in power PRIVATE FINANCING grid expansion and reliability would eventually reduce genset usage. Improvements to Nigeria’s power sector Access Bank. Access is a publicly listed commercial are critical for the sustainability of the system and the bank headquartered in Lagos. It has not only issued economy. By increasing the supply of electricity, eco- a green bond but equally invested in two green bonds nomic losses would be reduced while tariff revenues issued by the Federal Government. (It may also have would increase, generating considerable income to pay invested in the North South Power green bond in 2021.) for the reforms. Access Bank is well-positioned to take part in a subna- tional green bond, given its experience in the issuance Gensets represent one of the least regulated sources of and reporting obligations of its own green bond. air pollution in Lagos. As noted earlier, improving the quality of diesel and gasoline suppled to Lagos would Capital Assets. A privately held issuing house based help reduce emissions from gensets. Currently, there are in Lagos, Capital Assets acted as the financial adviser to no emissions standards for electricity gensets in Nigeria. the Federal Government in the issuance of the first and As in other countries, the emissions from such generators second green bonds in Nigeria, both of which were over- should be regulated, requiring (a) emission standards for subscribed. Issuing houses are a key part of the process electricity gensets, (b) improvements in fuel, and (c) the for issuance of capital market instruments. Capital Assets installation of pollution control equipment. has a ready pool of institutional and other investors inter- ested in green bonds. OTHER Nigerian Stock Exchange (NSE). The NSE is the There are many options for reducing emissions from premium exchange for trading of public instruments in other pollution sources. Policies to minimize the amount Nigeria, with a capitalization of N83 trillion (US$202 bil- of resuspended roads, such as paving, could reduce a lion). The NSE was a key player in the issuance of a green large fraction of dust emissions. Lower-cost options such bond by the Federal Government and currently lists four as watering or reducing speed limits on unpaved roads green bonds on its platform. NSE is concerned with the can also be effective in the short term and during the dry additional reporting obligations associated with green season. Likewise, policies to reduce crop residue burn- bonds but believes that local capacity can be developed ing, including bans, could be especially effective during to support issuers in meeting their reporting obligations. the dry season when emissions are at their peak. Sub- sidizing the use of LPG among low-income households could reduce the use of solid fuels for residential cooking. MULTILATERAL RESOURCES While a detailed assessment of the costs of reducing emissions from other sectors has not yet been carried Resources available through the multilaterals provide an out, it is reasonable to assume that selective policies and avenue to mobilize additional funds—Figure A3.1 lists investments could be effective in reducing the share of commitments by MDBs to climate finance. The MDBs PM2.5 emissions by a few percent. most relevant to the LASG are the African Development Bank (AfDB), the European Investment Bank (EIB), the World Bank Group (WBG), and the Islamic Develop- A3.2. FINANCING AQM ment Bank (ISDB). Others that are likely to have com- mitments not listed in figure A3.1 are Africa Finance Corporation (AFC) and International Finance Corpora- Among the potential sources of financing for air quality tion (IFC). These institutions typically have accreditation in Lagos are private financing, multilateral resources, and with climate funds such as the Global Environment Facil- climate funds. ity (GEF) and the Green Climate Fund (GCF) and have 152 Air Quality Management Planning for Lagos State internal programs designed to provide technical support LASG can access funding for technical support to in developing interventions to address climate issues. design relevant interventions or to create a blended approach to funding projects that can address air pollu- Figure A3.2 illustrates contributions to climate financing tion. Table A3.1 provides an overview of potential fund- as of 2019 and shows an increase since the signing of the ing from the World Bank Group that could be available Paris Agreement in 2015. to Lagos to address climate concerns, many of which would also improve air quality. Leveraging existing platforms for technical assistance—such as the Africa Climate Resil- The ACBP has several focal areas that overlap with the ient Infrastructure (ACRIF)—it is likely that the priorities of Lagos State that could address air pollution. FIGURE A3.1.  CLIMATE FINANCE COMMITMENTS BY MDBS CLIMATE FINANCE COMMITMENTS BY MDB African Development Bank Inter-American Development Bank Group Total US$ 3,600 million Total US$ 4,958 million For low- and middle-income economies US$ 3,600 million For low- and middle-income economies US$ 4,417 million African Development Bank Islamic Development Bank Total US$ 7,073 million Total US$ 466 million For low- and middle-income economies US$ 7,068 million For low- and middle-income economies US$ 464 million EUROPEAN Bank for Reconstruction and Development World Bank Group Total US$ 5,002 million Total US$ 18,806 million For low- and middle-income economies US$ 3,923 million For low- and middle-income economies US$ 18,437 million EUROPEAN Investment Bank Total US$ 21,658 million For low- and middle-income economies US$ 3,558 million FIGURE A3.2.  FUNDING SOURCES FOR CLIMATE FINANCING (INCLUDING PRIVATE SECTOR) USD 100 billion 78.3 79.6 80 71.7 70 14.6 14 61.8 58.5 14.5 2.1 2.6 60 52.4 16.7 10.1 2.1 50 Data gap 12.8 1.5 29.6 34.1 1.6 2.5 40 27.5 1.6 18.9 20.4 16.2 30 15.5 20 Not 28 32 28.8 25.9 27 available 10 22.5 23.1 yet 0 2013 2014 2015 2016 2017 2018 2019 2020 Bilateral public Multilateral public (attributed) Export credits Mobilised private (attributed) Air Quality Management Planning for Lagos State 153 TABLE A3.2.  WORLD BANK AFRICA CLIMATE BUSINESS PLAN (ACBP) FUNDING WINDOWS IDA/IBRD Indicator/commitment Time period Relevance to Africa IDA19 IDA’S climate co-benefits share of total commitments will increase FY21–23 Africa share of US$53 to at least 30 percent on average over FY21–23, with half billion, pro-rated, would supporting adaptation action. mean US$5.3 billion per year from portfolio (or total of US$15.9 billion) WBG The WBG is stepping up its climate support for Africa With FY21–25 Africa-focused; would be a continued strong support for IDA, our fund for the world’s summation of co­ -benefits poorest countries,a this will provideUS$22.5 billion for Africafor from IDA and IBRD climate adaptation and mitigation for the five years from portfolio 2021–25. WBG [...] in line with these new climate financing commitments and FY21–25 Africa focused; would be a future direction of our Africa Business Planb more than half summation of adaptation of the US$22.5 billion financing will be devoted to supporting co-benefits from IDA and adaptation and resilience in Africa. This will amount to about IBRD portfolio US$12 billion to US$12.5 billion over five years from 2021–25. IBRD Increasing the climate co-benefit target of 28 percent by FY20 to an FY20–23, and Bankwide target, no formal average of at least 30 percent over FY20–23, with this ambition through 2030 Africa target maintained or increasing to FY30.c Technical assistance or blended finance from the ACBP could help the LASG scale up its green bond program. A3.3. CONTROL COST In the energy sector, the ACBP has a focus on renewable ASSUMPTIONS energy generation and capacity as well battery storage. In transport, the plan has an objective to support five new BRT corridors in the region, which aligns with the LASG The first step in estimating the cost-effectiveness of 2021 budget. each sectoral intervention was to apportion total PM2.5 emissions across the sectors. A second simplifying Alignment with the ACBP. Lagos stands to benefit from assumption was that PM2.5 emissions are directly pro- support from the ACBP’s city interventions. Sectors such portional to ambient concentrations. Using the average as energy and transport also provide a rationale for Lagos of PM2.5 source apportionment monitoring data of six State to sieve its various plans to identify interventions sites (figure 10) and the baseline emissions inventory that are consistent with the pollution solution and that (Table A3.4), the following table apportions PM2.5 emis- could be funded through the commitments in the ACBP. sions (column 2) and ambient concentrations (column 3) The planned issuance of a green bond could benefit from to the five sectors (solid waste, industry, transport, power, technical support in the structuring or the provision of a and other). It is assumed that the cost of policies and blended financing approach to make the terms of issu- actions are perfectly divisible to achieve a given level of ance more sustainable. air pollution reduction. 154 Air Quality Management Planning for Lagos State TABLE A3.3.  ACTION AREAS IN THE ACBP Action area to support IDA-19 and Corporate climate actions and targets45 Business element World Bank instruments for delivery on climate action Timing Delivery of IDA ► Resilient Cities and Green Mobility FY21–23; and Corporate FY24–26 commitments ⊳ Cities ► Integrated planning: multisectoral climate-smart urban and transport plans prepared with up-to-date data for at least five African cities ► 30 cities with integrated, city-based resilience approach ► Target of US$2 billion in investment financing for urban resilience-building activities ⊳ Green mobility ► Support 5 new BRTs in fast-growing African cities (making at least 50% of jobs accessible within an hour of commute) ► Secure maintenance to make 100,000 km of climate-resilient African roads Special Areas of Emphasis ► Macroeconomic planning and policy FY21–23; FY24–26 ⊳ Increase engagement with ministries of finance and planning and other stakeholders on NDCs ⊳ Promote concrete and systematic policy actions (IDA19) ⊳ Analytics to inform policy action and design of prior actions in DPFs ► Green and Resilient Infrastructure FY21–23; Supports targets of Strategic Directions above, including FY24–26 ⊳ Energy ► renewable energy. ► battery storage. ► renewable energy generation capacity ⊳ Urban ► low carbon and compact urban planning ► integrated, city-based resilience approach PUBLIC REGULATION VERSUS PRIVATE emission standards lie with the owners and are referred COMPLIANCE COSTS to as private compliance costs. Where possible, the net cost (investment minus revenue) of public investments, Two sets of costs for reducing air pollution have been regulatory costs, and compliance costs have been esti- evaluated. Public costs include the building of public mated for each air quality measure. A notable exception infrastructure such as landfills and roads, as well as public is the cost required by industrial enterprises to reduce administrative costs such as pollution monitoring, regula- their air pollution. Aside from the lack of information tion, and licensing. The costs of reducing emissions from from industrial enterprises in Lagos, there is a wide range vehicles, factories, or electric generators to comply with of industrial processes that produce air pollution, making Air Quality Management Planning for Lagos State 155 TABLE A3.4.  APPORTIONMENT OF PM2.5 EMISSIONS AND AMBIENT CONCENTRATIONS BY SECTOR Air pollution reduction scenarios Share of PM2.5 Contribution to ambient Sectors emissions (t/yr) - % PM2.5 levels (ug/m3) 35 ug/m3 25 ug/m3 15 ug/m3 10 ug/m3 Solid Waste 26 11.7 –2.5 –4.9 –7.5 –9.0 Industry 20 9.0 –1.2 –4.0 –6.5 –8.0 Transport 20 9.0 –3.7 –5.0 –6.3 –7.6 Power 8 3.6 –1.6 –3.2 –3.2 –3.2 Other 26 11.7 –1.0 –2.8 –6.5 –7.2 Total 100 45 –10.0 –20.0 –30.0 –35.0 Source: Author’s own elaboration based on PM source apportionment. a cost assessment of private compliance costs for industry composting and recycling investments and operating prohibitive. It is also assumed that at least part of the expenses, it is assumed that 80 percent of the costs can be public regulation cost (such as vehicle emissions testing offset through income from the sale of products, such as or solid waste collection) can be paid through licensing fertilizer from composting, and paper and plastics from or user fees. recycling. SOLID WASTE INDUSTRY Collection and disposal costs for MSW are calculated The public costs associated with the control of industrial from waste collection fees charged by private concession- emissions are assumed to be the monitoring and enforce- aires. The cost of household waste collection services in ment costs for the regulator, while the private sector will Lagos was estimated at US$5.87 per ton in 2014. Assum- need to invest in pollution control measures to meet the ing this figure has increased to US$10 per ton today, the standard. The main regulatory expense is assumed to be cost of collecting and disposing of 18,750,000 tons per the monitoring and enforcement of industrial emission day (0.75 kg/cap/day times 25 million) is US$73 mil- standards, including through the installation of auto- lion per year (Aliu et al. 2014). Composting assumes that matic emissions monitoring systems on large industrial the organic fraction (50 percent) collected is composted, sources. Monitoring costs of US$100,000 are assumed with costs based on the EarthCare program in Lagos and for 1,000 enterprises, totaling US$100 million. Compli- the Terra Firma experience in Bangalore India (World ance costs have not been estimated but would include Bank 2016b). The assumed cost of building a new sani- pollution control equipment, cleaner fuels, or energy tary Olusosun-size (100 acres) landfill, at US$500,000 efficiency measures. Cleaner production—covering per acre, is US$50 million. If recycling and composting emissions control equipment and cleaner fuels—would are implemented, less landfill space (and the associated likely have a net benefit for industries such as food and cost) is needed. MSW that is not recycled or composted beverages, information and technology, and electronics. is assumed to be landfilled or incinerated. For both The payback for energy efficiency measures is typically 156 Air Quality Management Planning for Lagos State short for many industrial investments (pumps, motors, such fuels in sufficient quantity, it is assumed that fuel boilers, fans) and would lead to reductions in emissions is imported. The incremental cost for low-sulfur fuels is in proportion to reductions in fuel consumption. calculated at US$76 million per year (Miller et al. 2017) with the costs borne by consumers at around 5 percent increase in the cost, or US$0.02–0.03 per liter. Given TRANSPORT that all petroleum products are currently imported, the real challenge in obtaining clean fuel in Lagos (and Nige- Euro 3 and Euro 4 vehicle standards are assumed to be ria in general) is to prevent fuel adulteration. Additional achieved through testing, compliance, and enforcement, regulatory costs are assumed to ensure that fuel quality phased in over time. More than half of light-passenger is guaranteed, including fines and potential cancellation vehicles are less than 16 years old and likely therefore to of retail licenses for violations of fuel quality standards. have Euro 4 equipment already installed, both for new A program to guarantee fuel quality, as has been imple- and used vehicles. Modest costs are assumed for these mented in other countries, can help ensure the quality of vehicles to meet Euro 3 standards—for example, addition fuel in the face of numerous incentives to adulterate it of new catalytic converters—but many other vehicles (Gwilliam Kojima, and Johnson 2004). would need to either be retired or retrofitted to comply. Most used vehicles in Nigeria come from Europe, the US, and Japan, all of which have established emissions ELECTRICITY control standards of Euro 4 or higher. Regulation costs are assumed to include emissions testing for all vehi- It is assumed that the majority of emissions from the cles, ranging from US$4 (motorcycles) to heavy trucks power sector are from gensets in the residential, com- (US$30), and it is expected that the emissions testing will mercial, and industrial sectors rather than from the be done by the current testing service (LCVIS). Com- natural, gas-fired power plants on the electric grid. The pliance costs are assumed to be the expenditures vehi- cost of power sector reform in Lagos has been calcu- cle owners need to make in order to meet Euro 3 and 4 lated at around US$100 million, based on World Bank emissions standards. Compliance costs will be greatest for project costs for increasing power supply in the amount heavy trucks, which are assumed to be among the oldest currently provided by gensets. Several efforts are under fleets in Lagos. For passenger vehicles, minivans (includ- way to improve the efficiency of Nigeria’s power sector, ing danfos), and motorcycles, private compliance costs are including investment in transmission, distribution, and assumed to be the costs of catalytic converters, installa- metering (World Bank 2020).49 Such projects provide an tion costs, plus the costs of clean fuel. The incremental estimate of the costs of improving the supply and reli- cost of clean fuels (on average US$0.02–0.03 per liter) ability of the grid, measured as additional kWh that are would be paid by vehicle owners in the form of higher available to consumers, and thus generating additional diesel and gasoline prices. revenues from electricity sales. The increase in tariff rev- enue from increased power generation associated with the reforms is calculated at over US$200 million per year, CLEAN FUEL meaning that the reforms would pay for themselves in less than 2 years. Clean fuel is not assumed to be an independent reduc- tion action but is required for engines to achieve lower Alternatively, emissions from gensets could be regu- emission levels under Euro vehicle standards. Low-sulfur lated and emission controls enforced, requiring gen- diesel and gasoline (Euro 3 and 4 compliant) are assumed sets to install pollution control equipment. Although to be available (with guaranteed fuel quality) through- backup generators are not regulated in Nigeria, other out Lagos State. Until domestic refineries can produce jurisdictions around the world provide experience and Air Quality Management Planning for Lagos State 157 TABLE A3.5.  COST-EFFECTIVENESS OF SELECTED AIR QUALITY MEASURES Public Private PM2.5 Cost- “regulation” “compliance” reduction effectiveness cost cost potential (US$/t PM2.5 (US$, millions) (US$, millions) (t/year) reduced) Solid waste Enhanced MSW collection and new landfills 83 — 3,328 24,947 Enhanced MSW collection with recycling and 47 — 3,328 14,130 composting Industry Emissions monitoring and standard enforcement 95 ?? 3,000 31,605 Transport Vehicle regulation (Euro 3)a 12 149 1,200 133,725 Vehicle regulation (Euro 4)a 12 223 2,800 69,933 Power Power sector reform 110 — 1,152 95,833 Genset regulation and emissions control 5 246 1,152 218,229 Source: Author’s own elaboration. Note: a Requires fuel quality improvements. information on the costs of controlling genset emissions. The cost to reduce emissions from backup generators A3.4. CO-BENEFITS is estimated at one-quarter of the total capital costs of OF CLIMATE CHANGE gensets in Lagos (based on genset emissions control costs from the US) or US$280 million.50 While power sector MITIGATION reform would result in additional revenue from electricity sales that would offset the costs of reform measures, the genset emissions control expenditures would be a net cost Given the large costs of air pollution in Lagos, it is impor- to genset owners. tant that policies to address climate change also look for solutions to reduce ambient air pollution. Fortunately, the sectors targeted in Lagos’ Climate Action Plan— waste, COST-EFFECTIVENESS transport, industry, and energy—are precisely those con- tributing the most to PM2.5 emissions. That said, within Based on the costs of different measures to reduce each of these priority sectors, different measures to reduce PM2.5 emissions, it is possible to estimate the cost- GHG emissions will have varying degrees of success in effectiveness of different interventions. As seen in reducing air pollution. Several measures can reduce both Table A3.5, the measures to reduce solid waste burn- air pollution and GHG emissions (Table A3.6). It is also ing are among the lowest cost for air pollution control possible to compare the costs of air pollution to the costs in Lagos. of climate change (Box A3.1). 158 Air Quality Management Planning for Lagos State TABLE A3.6.  CLIMATE CO-BENEFITS OF SELECTED AIR QUALITY MEASURES Avoided CO2 Avoided CH4 Avoided black carbon Transport Public transport No Clean fuel No No Euro 3/4 vehicles No No Alternative vehicles (CNG, hybrid, electric) No Solid waste Enhanced collection Composting Industry Energy efficiency No Pollution controls No No Power Sector reform No Genset emissions control No No Other LPG for cooking No Paving roads No No Air Quality Management Planning for Lagos State 159 BOX A3.1.  AIR POLLUTION VERSUS CLIMATE CHANGE COSTS How do the costs of air pollution compare to the costs of climate change? The PMEH study has estimated the health costs of ambient air pollution based primarily on premature deaths attributable to high levels of ambient PM2.5 pollution. While it is difficult to measure the costs of climate change, a notional measure known as the “social cost of carbon” has been devised to reflect the costs of climate impacts such as droughts, floods, and sea level rise. The social cost of carbon (SCC) has been used by policy makers worldwide to attempt to internalize the negative externalities of climate change. In the US, a wide range of SCC values have been used, reflecting assumptions about the extent of climate change damage and the discount rate.52 Lagos CO2-equivalent emissions have been estimated at 2.64 million tons.51 If a mid-range global value of US$50/tCO2e is used for the SCC, the cost of climate change for Lagos amounts to US$1.3 billion. The health impact of PM2.5 emissions in Lagos has been estimated at US$2.6–5.0 billion, or more than twice the value of CO2 emissions. 160 Air Quality Management Planning for Lagos State ANNEX 4 METHODOLOGY FOR DEVELOPING AN AQI A4.1. WHAT IS AN AQI? Air pollution can be measured and presented in many forms. It includes all the aero- sols and gaseous components, each with its own way of affecting human health to various degrees depending on exposure rate. Some pollutants like CO and O3 can lead to an immediate response and require standard metrics presented on a shorter time scale (for example, 8 hourly) than other pollutants (24 hourly). Their presenta- ­ aries—for e tion also v ­ xample, aerosols are reported as mass fractions, and gases as volumetric fractions of air. An Air Quality Index (AQI) unifies the complicated science of pollution compo- sition, exposure rates-based health severity, ambient standards, measurement, and standard protocols and breaks it down into simple, color-coded bins that give people an instant visual grasp of pollution levels in their surroundings, enabling them to develop the necessary alertness. FIGURE A4.1.  SCHEMATIC DIAGRAM OF AN AIR QUALITY INDEX Air Quality Management Planning for Lagos State 161 FIGURE A4.2.  COLOUR CODING OF AIR across the globe, this is not the case for methods used QUALITY for calculating an AQI. These methods, and the degree of alertness disseminated by health alert systems, vary depending on different countries’ interpretation of thresholds for regulatory purposes and background conditions. This step is primarily driven by predeter- mined local standards and the feasibility of reaching the lowest possible pollution levels. For example, in a region where dust is naturally present and ubiquitous, A4.2. HOW IS AQI it is not possible to reach WHO guidelines for PM10 and PM2.5. The same principle also holds for the formula- CALCULATED? tion of an AQI by individual countries, which notion- ally mirrors that country’s standards. For example, for PM2.5 presented in the following figure, a concentration While the methods to monitor air pollution and esti- of 50 μg/m3 is considered borderline “unhealthy” in mate its health impacts are becoming standardized the US but “satisfactory” in India. FIGURE A4.3.  AQI BREAKPOINTS AND NOMENCLATURE FOR DIFFERENT COUNTRIES 162 Air Quality Management Planning for Lagos State Mathematically, an AQI is calculated using the following number ranges that are under each of the pollutants rep- equation: resent the breakpoints. In this table, all the breakpoints are in μg/m3, except for CO which is listed in mg/m3. AQI hi − AQI low AQI = * (CONC − BPlo ) + AQI low BPhi − BPlow The top of the AQI scale is 500, which means there will be point in the calculation when the AQI value itself will not change between absolute value of 1,000 and 2,000 where μg/m3 of PM2.5 or PM10. Once the color code reaches » CONC = concentration of the pollutant the severe category, there is no change in the AQI value » AQI = air quality index for the pollutant or the alert message. » BPhi = breakpoint that is greater than or equal to This report reviewed seven methodologies from the US, CONC the EU, the UK, India, China, the Republic of Korea, » BPlo = breakpoint that is less than or equal to and Singapore. A summary of parameters used to cal- CONC culate an AQI by each of these countries is presented » AQIhi = AQI value corresponding to BPhi below. Like the breakpoint variation in calculating AQI » AQIlo = AQI value corresponding to BPlo between countries, there is also a significant variation in the use of parameters and time scales. In the case of Every pollutant has a predefined breakpoint and AQI PM2.5 and PM10, all the countries use 24-hour average ranges for each of the color codes. An example for India concentrations to calculate the AQI. For SO2 and NO2, is presented below. the most-used time frame is the 24-hour average; and for CO and O3, the most-used time frame is the 8-hour aver- The numbers in the first column represent the AQI bins age. In the case of O3, when 8-hour averages reach a (high and low values to be used in the calculator). The certain threshold, the calculators switch to using 1-hour FIGURE A4.4.  POLLUTANT PREDEFINED BREAKPOINT AND AQI RANGES FOR INDIA AQI Category PM10 PM2.5 NO2 O3 CO SO2 NH3 Pb (Range) 24-hr 24-hr 24-hr 8-hr 8-hr 24-hr 24-hr 24-hr (mg/m3) Good (0–50) 0–50 0–30 0–40 0–50 0–1.0 0–40 0–200 0–0.5 Satisfactory 51–100 31–60 41–80 51–100 1.1–2.0 41–80 201–400 0.6–1.0 (51–100) Moderate 101–250 61–90 81–180 101–168 2.1–10 81–380 401–800 1.1– 2.0 (101–200) Poor 251–350 91–120 181–280 169–208 10.1–17 381–800 801–1200 2.1–3.0 (201–300) Very poor 351–430 121–250 281–400 209–748* 17.1–34 801–1600 1201–1800 3.1–3.5 (301–400) Severe 430+ 250+ 400+ 748+* 34+ 1600+ 1800+ 3.5+ (401–500) *One hourly monitoring (for mathematical calculation only) Air Quality Management Planning for Lagos State 163 averages—this happens in the methodologies employed The three steps in using the calculator are: (a) enter con- by the US, EU, China, and Singapore. centrations, preferably in μg/m3, but could be in other units; (b) from the seven countries, select a methodology A summary of all the breakpoints and nomenclature for to use; and (c) click to calculate the AQI. Another varia- these seven countries is presented below. All the concen- tion of the calculator is available in the resource material. trations are presented in μg/m3. That version can utilize larger datasets for multiple pol- lutants and build AQI trends. An Excel-based AQI calculator is included with this report that will allow for exploring the methodologies and their interpretations. FIGURE A4.5.  SUMMARY OF PARAMETERS FOR ESTIMATING AN AQI FOR COUNTRIES UNDER REVIEW 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 PM2.5 PM10 SO2 NO2 CO Ozone 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 1 USA x x x x x x x 2 EU x x x x x 3 UK x x x x x 4 India x x x x x x 5 China x x x x x x x 6 S.Korea x x x x x 7 Singapore x x x x x x x 8 9 10 164 Air Quality Management Planning for Lagos State FIGURE A4.6.  SUMMARY OF BREAKPOINTS AND NOMENCLATURE FOR SEVEN COUNTRIES UNDER REVIEW Number of bins Number of polls Break Points 6 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 PM2.5 PM2.5 PM2.5 PM10 PM10 PM10 SO2 SO2 SO2 NO2 NO2 NO2 CO CO CO Ozone Ozone Ozone 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr AQI ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 Low High col.code 0 0 0 0 0 0 0 1 Good 0 50 43 12 54 95 85 5210 110 0 2 Moderate 50 100 27 35 154 203 161 11131 142 254 3 Unhealthy for sensitive groups 100 150 45 55 254 501 579 14684 173 333 4 Unhealthy 150 200 3 150 354 823 1043 18237 213 414 5 Very Unhealthy 200 300 13 250 424 1635 2007 35999 406 820 6 Hazardous 300 500 9 500 604 2718 3293 59683 0 1226 European union Number of bins Number of polls Break Points 6 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 PM2.5 PM2.5 PM2.5 PM10 PM10 PM10 SO2 SO2 SO2 NO2 NO2 NO2 CO CO CO Ozone Ozone Ozone 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr AQI ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 Low High col.code 0 0 0 0 0 1 Very Good 0 50 10 10 20 100 40 50 2 Good 50 100 43 20 40 200 90 100 3 Medium 100 200 27 25 50 350 120 130 4 Poor 200 300 45 50 100 500 230 240 5 Very Poor 300 400 46 75 150 750 340 380 6 Extremely Poor 400 500 3 800 1200 1250 1000 800 United Kingdom Number of bins Number of polls Break Points 10 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 PM2.5 PM2.5 PM2.5 PM10 PM10 PM10 SO2 SO2 SO2 NO2 NO2 NO2 CO CO CO Ozone Ozone Ozone 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr AQI ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 Low High col.code 0 0 0 0 0 1 Low 0 1 43 11 16 88 67 33 2 Low 1 2 43 23 33 177 134 66 3 Low 2 3 43 35 50 266 200 100 4 Moderate 3 4 27 41 58 354 267 120 5 Moderate 4 5 44 47 66 443 334 140 6 Moderate 5 6 45 53 75 532 400 160 7 High 6 7 46 58 83 710 467 187 8 High 7 8 3 64 91 887 534 213 9 High 8 9 53 70 100 1064 600 240 10 Very High 9 10 13 100 150 1500 1000 300 India Number of bins Number of polls Break Points 6 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 PM2.5 PM2.5 PM2.5 PM10 PM10 PM10 SO2 SO2 SO2 NO2 NO2 NO2 CO CO CO Ozone Ozone Ozone 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr AQI ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 Low High col.code 0 0 0 0 0 0 1 Good 0 50 10 30 50 40 40 1000 50 2 Satisfactory 50 100 43 60 100 80 80 2000 100 3 Moderate 100 200 6 90 250 380 180 10000 168 4 Poor 200 300 45 120 350 800 280 17000 208 5 Very Poor 300 400 3 250 430 1600 400 34000 748 6 Severe 400 500 9 500 750 2500 800 50000 1000 Air Quality Management Planning for Lagos State 165 FIGURE A4.6. (Continued ) China Number of bins Number of polls Break Points 6 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 PM2.5 PM2.5 PM2.5 PM10 PM10 PM10 SO2 SO2 SO2 NO2 NO2 NO2 CO CO CO Ozone Ozone Ozone 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr AQI ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 Low High col.code 0 0 0 0 0 0 0 1 Optimal 0 50 4 35 50 50 40 2000 100 0 2 Good 50 100 6 75 150 150 80 4000 160 0 3 Light Pollution 100 200 22 115 350 800 280 24000 265 0 4 Moderate Pollution 200 300 3 150 420 1600 565 36000 800 800 5 High Pollution 300 400 21 250 500 2100 750 48000 0 1000 6 Severe Pollution 400 500 30 500 600 2620 940 60000 0 1200 Korea Number of bins Number of polls Break Points 6 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 PM2.5 PM2.5 PM2.5 PM10 PM10 PM10 SO2 SO2 SO2 NO2 NO2 NO2 CO CO CO Ozone Ozone Ozone 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr AQI ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 Low High col.code 0 0 0 0 0 1 Good 0 50 43 30 54 48 2368 81 2 Moderate 50 100 27 80 135 96 10658 162 3 Unhealthy for sensitive groups 100 150 45 120 271 241 14210 244 4 Unhealthy 150 250 3 200 406 321 17763 609 5 Very Unhealthy 250 350 13 300 1083 964 35526 1015 6 Hazardous 350 500 9 600 2707 3214 59210 1218 Singapore Number of bins Number of polls Break Points 6 18 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 PM2.5 PM2.5 PM2.5 PM10 PM10 PM10 SO2 SO2 SO2 NO2 NO2 NO2 CO CO CO Ozone Ozone Ozone 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr 24hr 8hr 1hr AQI ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 ug/m3 Low High col.code 0 0 0 0 0 0 0 1 Good 0 50 43 12 50 80 0 5000 118 0 2 Moderate 50 100 27 55 150 365 0 10000 157 0 3 Unhealthy 100 200 45 150 350 800 1130 17000 235 0 4 Very Unhealthy 200 300 3 250 420 1600 2260 34000 785 785 5 Hazardous 300 400 13 350 500 2100 3000 46000 0 980 6 Hazardous 400 500 9 500 600 2620 3750 57500 0 1180 166 Air Quality Management Planning for Lagos State FIGURE A4.7.  STEPS FOR CALCULATING AQI Select a nation for required India and click calculate AQI formate Reqd time. Conc Unit AQI Remarks avg 24hr 120.0 Micro-g/m3 300 Poor Conditional Pollutant PM2.5 - 24 hr 300 Poor PM2.5 8hr Micro-g/m3 NA Average of worst two 210 Poor 1hr Micro-g/m3 NA Average of all 118 Moderate 24hr 130.0 Micro-g/m3 120 Moderate PM10 8hr Micro-g/m3 NA 1hr Micro-g/m3 NA 24hr 54.0 Micro-g/m3 68 Satifactory SO2 8hr Micro-g/m3 NA 1hr Micro-g/m3 NA 24hr 34.0 Micro-g/m3 43 Good NO2 8hr Micro-g/m3 NA 1hr 80.0 Micro-g/m3 NA 24hr Micro-g/m3 NA CO 8hr 2000.0 Micro-g/m3 100 Satifactory 1hr 10000.0 Micro-g/m3 NA 24hr Micro-g/m3 NA Ozone 8hr 80.0 Micro-g/m3 80 Satifactory 1hr 200.0 Micro-g/m3 NA Air Quality Management Planning for Lagos State 167 END NOTES 1 uMoya-NILU, Who We Are, http://www.umoya​ 12 For example, in California, fewer than 15 percent of -nilu.co.za. vehicles are responsible for as much as half of total 2 6-hour mean at each sampling location. vehicle emissions. Similarly, in Europe, 3 percent of 3 World Health Organization. the fleet have been found to account for 27 percent 4 “Criteria pollutants” are those for which an ambient of emissions. air quality standard has been established. 13 It may also be possible to lease alternative-fuel 5 According to the GBD’s latest assessment, the PM vehicles as is being done with fleet vehicles in the attributable mortality is 6.455 million (plus 365,000 US and Europe. Several jurisdictions are currently for O3). This figure includes 373,000 neonatal procuring electric vehicle fleets through leasing disorders (including preterm birth and low-birth and service contracts with vehicle manufacturers weight). and third-party contractors. For example, a county 6 The study used a VSL value similar to that in in Maryland, US recently signed an agreement to Croitoru, Chang and Kelly (2020), which in turn convert its school bus fleet to electric vehicles over used a benefits transfer methodology and a base the next 15 years. value from a meta-analysis conducted in OECD 14 National Poverty Eradication Program. countries (World Bank 2016). 15 In Bangkok, two-stroke motorcycles and diesel 7 CH4 has a 100-year global warming potential 28 engines accounted for over 95 percent of motor times that of CO2. vehicle particulate matter in the early 2000s. 8 The investment by West Africa ENRG would 16 Railway Technology, “Lagos Rail Mass Transit amount to US$125–150 million for a 25 MW waste- System,” March 13, 2020, https://www.railway​ to-energy facility that would process 2.5 tons of -technology.com/projects/lagosrailmasstransit. MSW per day. 17 http://www.urbanrail.net/af/lagos/lagos.htm 9 Many of the catalysts and particulate traps that are 18 Power – 208 Mt CO2e; AFOLU – 136 Mt installed in vehicles that are imported either new or CO2e; Transport – 52 Mt CO2e; Oil and gas – used into Nigeria and other countries would quickly 40 Mt CO2e. be made ineffective with the current fuel quality 19 Estimates from the emissions inventory suggest that (assumed to be 1,424 ppm sulfur for gasoline and gensets may account for more than 95 percent of 2,389 ppm sulfur for diesel). power sector emissions of PM2.5. ARIA. 10 At 650,000 barrels per day (bpd), the Dangote 20 A recent study based on satellite measurements Refinery would be the largest in Nigeria and meet of PM2.5 shows that agricultural field burning is a the country’s refined petroleum product needs of significant source of PM2.5 in Sub-Saharan Africa, around 600,000 bpd. Nigeria currently produces including Nigeria, during the field burning season over 2.5 billion bpd of crude oil. In terms of fuel from November to February. Preliminary data from quality, the refinery is slated to produce Euro 6 air quality monitoring from six monitoring stations in standard fuels, meaning ultra-low sulfur diesel and Lagos show a dramatic increase in PM2.5 levels during gasoline (10 ppm sulfur). December 2020. To the extent that this increase is 11 ECOWAS directives C/Dir.2/09/20 and associated with seasonal field burning, measures to C/Dir.1/09/20, respectively. address biomass burning should be investigated. Air Quality Management Planning for Lagos State 169 21 In Ikeja, studies of household fuel used for cooking 32 https://placng.org/i/wp-content/uploads​/2019​/12​ show that kerosene (48.6 percent) and LPG /Report-of-the-Senate-Committee-on-Environment​ (36.3 percent) are the most common, with charcoal -on-National-Oil-Spill-Detection​-and​-Response​ (7.1 percent), fuelwood (5.7 percent), and electricity -Agency-Act-Amendment-Bill-2017.pdf. (2.4 percent) providing a minor share. 33 https://www.lasepa.gov.ng/wp-content​ 22 https:/www.nesrea.gov.ng/publications-downloads​ /­uploads/2020/01/Environmental-Management​ /­laws-regulations/. -Protection-Law-2017-1.pdf. 23 https://ngfcp.dpr.gov.ng/media/1070/petroleum​ 34 The five strategic goals of AQM are (a) develop -act.pdf. nationwide ambient air quality standards; 24 The DPR is currently transiting into the Nigerian (b) develop capacities to assess and determine Upstream Petroleum Regulatory Commission national, state, or city emissions reduction (NUPRC) as passed by the Nigerian Petroleum requirements; (c) establish strategies to Industry Act of 2021. achieve the desired emissions reduction; 25 The Vienna Convention addresses the loss of the O3 (d) develop strategies to implement and enforce layer as a global issue and establishes that all parties ambient air quality standard; and (e) develop should take appropriate measures to avoid impacts capacity to track and evaluate emissions on human health and the environment with the reduction results. modification of the O3 layer. 35 See endnote 25. 26 The Montreal Protocol, established in 1987, refers 36 See endnote 26. to the substances that deplete the O3 layer and 37 See endnote 27. seeks measures for their control for atmospheric 38 See endnote 5. protection. The protocol was amended in 1990 39 Natural cause mortality refers to deaths from all (London), 1992 (Copenhagen), 1995 (Vienna), 1997 causes except accidents, violence, and suicides. (Montreal), and 1999 (Beijing). 40 Exposure-response function is the mathematical 27 The Stockholm Convention, which entered in force relationship linking the size of a particular health in 2004, aims to protect human health and the effect to an exposure level of concern. environment from the effects of POPs. 41 A relative risk is the ratio of health effects 28 PCEH claimed that the Climate Change (incidence, mortality) between two groups of people Department’s mandate was limited to exposed to different levels of air pollution. inventorization and management of the impacts 42 The sectoral shares of PM2.5 emissions and of GHGs and does not permit them to formulate ambient concentrations that have been used for policies for other air pollutants such as CO, NOx, the economic and financial analysis are waste VOCs, and SO2. Climate Change claims that such (26 percent), industry (20 percent), transport mandate does indeed lie with them. (20 percent), power (8 percent), and other 29 According to the 2021 Appropriations Act, the (26 percent). As more detailed data and additional FMEnv had allocations for N46.17 billion, while the source assessment modeling work are completed, total budget was N13.59 trillion. the share of pollution from different sources and 30 The 2021 Appropriations Act identified three sectors can be adjusted. projects for air quality under the FMEnv’s budget 43 See endnote 7. allocation. These were related to the introduction 44 LACVIS currently has 20 inspection centers with an of smart air quality monitoring, the procurement intention to build a total of 50 centers throughout of analyzers for air monitoring stations, and the Lagos by 2024. See Lagos Computerized Vehicle implementation of pollution studies for cement. Inspection Service (LACVIS) http://lacvis.com.ng​ 31 NOSDRA Act 2006 is available at http:// /­about-us. extwprlegs1.fao.org/docs/pdf/nig124170.pdf. 45 See endnote 12. 170 Air Quality Management Planning for Lagos State 46 The Lagos Computerized Vehicle Inspection 50 Calculated as gensets producing 1,940 GWh per year Service (LACVIS). https://lacvis.com.ng. in Lagos, an installed capacity of 2,790 MVA, and a 47 Currently the majority of danfos are gasoline- total cost of US$1,116 million (US$400/kVA). powered, though a shift to diesel is likely to increase 51 For example, policy makers in the US have as gasoline subsidies are reduced. calculated the SCC between US$2 and $100 per 48 See endnote 13. ton of CO2, reflecting whether only American or 49 Based on costs from the recent PSRO project in total global damages are considered, and whether Nigeria, the investment cost to increase the amount high versus low discount rates are used. 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