Ghana’s climate vulnerability profile May 2024 Chloe Desjonqueres, Hongxi Zhao, Walker Kosmidou-Bradley, and Paul Corral Introduction Climate change is expected to exacerbate poverty across the globe, particularly for the poorest countries. Extreme weather events are expected to become more frequent and more harmful. There is limited evidence suggesting that richer countries cope or adapt to warming conditions (Burke, Hsiang, and Miguel 2015). Additionally, despite technological progress and increased exposure to warmer conditions the global response to climate change has not notably improved (ibid). Wealthier economies may be less vulnerable to the severe impacts of climate change, potentially impeding proactive adaptation efforts (ibid). As a result, projections indicate that rising temperatures will disproportionately affect the world's poorest countries, which coincidentally tend to be the warmest countries as well. This underscores the urgent need to address climate change impacts, particularly in regions with limited resources to cope with its effects. Ghana has experienced significant developmental progress in recent decades, as highlighted in the Country Climate Development Report. However, the COVID-19 pandemic has halted much of this progress, raising concerns about future growth prospects. The economy's increasing reliance on natural resource extraction has not effectively translated into essential infrastructure, human capital development, or institutional growth, leading to slower poverty reduction and job creation. Moreover, Ghana's economic and human development face threats from climate change and associated shocks, including rising temperatures and unpredictable rainfall patterns. Climate extremes such as floods, droughts, and heat waves have become more frequent and severe, posing risks to agriculture, infrastructure, and public health. These extremes are not evenly distributed across the country. Drawing on comprehensive census, poverty, and agriculture data from Ghana, alongside weather, climate, and hazard information, this descriptive work aims to enhance the Ghana CMU's understanding of vulnerability and exposure amid climate change. The work presented focuses on geospatial vulnerabilities, including exposure to observed weather and air pollution risks, climate risks using the latest projection data, and flood hazards affecting people and critical services. By combining these insights with census, poverty, and agriculture data, the most vulnerable population segments in Ghana are made salient. Our goal is to provide fresh understanding of how environmental conditions, climate change, and hazards intersect with poverty. The data generated and collected for this document is expected to feed into the Project Targeting Index for Ghana which allows project teams the possibility to consider climate related aspects in their decision of where projects could be most needed. The document presents a climate profile for the country, before discussing the country’s exposure to natural hazards. This is followed by a descriptive analysis of climate change and its potential impact in the country. The document closes providing a brief conclusion. 1 Climate Profile There are clear climate differences between the north and south of Ghana, with the south being cooler and more wet than the north’s hot and dry conditions (Figure 1). Southern regions experience cooler temperatures (panel A) and greater rainfall (panel B) compared to their northern counterparts. Low-precipitation zones coincide with the sparsely inhabited natural areas of the Savannah region, while the Northern and North East regions, which harbor the highest concentration of impoverished populations, experience the highest average temperatures and lowest levels of rainfall. Furthermore, within the southern regions, isolated pockets of elevated temperatures are observed, potentially attributable to the urban heat island effect.1 These areas, notably centered around urban hubs such as Accra and Kumasi, stand out amidst the broader climatic trends of the South. Air pollution is also unevenly distributed across the country, with Harmattan wreaking havoc between December and February (Figure 1-panel C & D). The prevalence of air pollution, as indicated by particulate matter 2.5 (PM2.5), is notably higher in densely populated regions of the South compared to the North. In 2019, Ghana recorded a national average PM2.5 level of 54 (IHME 2019), a staggering ten times higher than the WHO Air Quality Guideline (AQG) level (WHO 2021). The high concentration of particle air pollution in the northeast during December to February, exceeding WHO recommendations and interim targets, underscores the significant impact of the Harmattan. This dry and dusty trade wind originates from the Sahara and sweeps across West Africa into the Gulf of Guinea annually from late November to mid-March. The timing coincides with a pronounced surge in air pollution levels, highlighting the pervasive and severe consequences of this natural phenomenon. When isolating Harmattan from the rest of the year, Northern areas tend to exceed interim targets less than the rest of the country, except for densely populated metropolitan areas like Tamale and Wa. In contrast, the Southern regions bear the brunt of year-round air pollution, primarily within urban centers characterized by heavy traffic flow, regions hosting mining activities, as well as waste disposal relying on burning (Figure 2). Regions with moderate temperatures and abundant rainfall are also those that experience the most extreme weather variations. The Standardized Precipitation Evapotranspiration Index (SPEI) is a measure of drought risk that shows that in Ghana, drought conditions have been, at worst, moderate (the index goes down to -1 at most) in eastern parts of the country, with moderately to significantly wetter than average condition in the rest of the country, and particular in the agriculturally-intensive southwest, with the index reaching up to +2 on a scale of -3 to +3 (Figure 1 panel E). Values over 2 suggest areas that are extremely wet, and those below -2 suggest areas that are extremely dry. 1 “Urban heat islands (UHI) are urbanized areas where temperatures are higher than they otherwise would be if the areas were rural. The “UHI effect” is a local negative environmental externality that may expose urban residents to extreme heat events more often than their observationally equivalent rural counterparts by artificially elevating a city’s long-run average temperature (Houghton 2015).” Roberts et al. (2023) 2 Figure 1. Observed environmental and weather trends, 2018-2022 Each dot represents the centroid of a grid that contains residential settlements as of the population and housing census 2021. A. Annual temperature (mean) B. Monthly precipitation (mean) Source: Staff calculations using 2018-2022 NASA Source: Staff calculations using 2018-2022 CHIRPS data as data developed by Funk et. al. (2015) 3 C. Annual air pollution (mean) D. Monthly air pollution (mean) Jan 50 Dec 45 Feb 40 35 30 Nov 25 Mar 20 15 10 5 Oct 0 Apr Sep May Aug Jun Jul Ghana WHO AQG Iterim target 1 Iterim target 2 Interim target 3 Iterim target 4 Source: Staff calculation using 2018-2022 data from Source: Source: Staff calculation using 2018-2022 data von Dankelaar et. al. (2024) from von Dankelaar et. al. (2024) Note: The color gradient cutoffs are WHO Air Quality Guideline level and interim target levels. The WHO’s Air Quality Guidelines (AQG) recommend maintaining particulate air pollution below 5 µg/m3. E. Annual drought index (mean) F. Share of the population exposed to high flood risk (mean) Note: Drought risk is derived from the SPEI index, Source: Staff calculations using 2021 population and which ranges from -3 to 3. Data for Ghana ranges housing census data from the Ghana Statistical Service 4 from -1 to +1.8, which indicates moderate drought along with Fathom3 flood data for a once-in-a-century risk. flood event (1 in 100 years event) as projected by 2080- 2099. Figure 2: Share of gird population burning waste Source: Ghana Statistical Service, Population and Housing Census (2021) 5 Ghana’s Exposure to Natural Hazards Ghana’s north-south divide is also apparent when looking into the occurrence of natural hazards. Climate change is projected to increase the frequency and intensity of natural hazard events (i.e. droughts, floods, extreme storms, etc.) worldwide. When they occur, natural hazards can cause loss of life and infrastructure damages. The geographic disaggregation of each natural hazard helps compare their geolocation with elements of exposure and vulnerability to determine the level of disaster risk in each region of the country (Figure 3). Much of Ghana is at high risk of flooding, whether river, urban (pluvial), or coastal flooding along the Atlantic coastline. Much of the country is also at high risk of wildfires, and the northern half is more susceptible to experiencing heat waves and water scarcity than the southern half, in line with observed trends illustrated in Figure 1. Southern regions are also more likely to experience earthquakes and landslides. Hazard events, when combined with vulnerability and exposure factors, can lead to disasters involving loss of life, injury, and damage from natural hazards, distinct from man-made catastrophes. The occurrence of a hazard event does not mean that the event will cause extensive human and asset loss and damage. However, the combination of a natural hazard event with factors that make people vulnerable and exposed can lead to a disaster. Disaster risk is the likelihood of loss of life, injury, or destruction and damage from a natural hazard – to be differentiated from man-made catastrophe - in a given time period. Figure 3. Ghana’s natural hazards profile A. River flood B. Urban flood C. Coastal flood D. Extreme heat E. Water scarcity F. Wildfire 6 G. Earthquake H. Landslide Risk level High Medium Low Very low NA Source: GFDRR (2020) ThinkHazard! Climate Change and its Potential Impacts in Ghana In Ghana, flooding, extreme heat and drought-related risks, including wildfires and water- scarcity, are high, and are projected to worsen with climate change. The risk is particularly elevated in regions characterized by high rates of manual labor, such as agriculture and mining, which are also characterized by low wages. In these areas, workers often face increased exposure to hazards. Additionally, areas with simultaneous high poverty rates and significant exposure to specific hazards pose heightened risks. Poverty constrains people's ability to cope with and recover from external shocks, further exacerbating vulnerability in these regions. The World Bank’s Unbreakable report found that Ghana is among the 3 countries in Western Africa where the poor are most exposed to drought. Literature on poverty risk distinguishes between two closely interlinked sources of vulnerability, structural and risk-induced (Skouffias (2004); Gunther and Harttgen (2009); World Bank 2019). First, household vulnerability can stem from limited capacity to generate welfare due to low levels of human capital. This increases the risk of falling into poverty when the household or broader economic conditions undergo changes. This first bucket is poverty-induced or 7 structural vulnerability. The second source of vulnerability is about being more exposed or sensitive to economic fluctuations that can affect income, disproportionately affecting households that are less able to cope with these shocks (i.e. they are less resilient). This second bucket is risk-induced vulnerability. While these vulnerabilities are closely connected, differentiating them helps identify appropriate policy measures (World Bank 2019). Addressing poverty-induced vulnerability may require enhancing social assistance programs and bolstering the human capital of persistently impoverished individuals, whereas risk-induced vulnerability could be mitigated through measures such as risk insurance and efforts to enhance economic resilience. Visualizing weather patterns, climate change, and hazards helps identify exposure of entire communities or regions, and possible co-location with poverty, highlighting vulnerability predominantly induced by risk. Climate change will have different impacts across Ghana. Over the next two decades, average annual temperatures are expected to increase by 1.2 to 1.5C when compared with a decade ago. The greatest increases are projected to occur in the northern half of the country, in regions that are already the warmest in the country (Figure 4 panel A). Looking at how climate change is expected to impact temperature changes illustrates the change in the likelihood of an extreme heat hazard occurring. Elevated temperatures across Ghana can hinder learning, reduce labor productivity, and impact agricultural output. The impact of rising heat is particularly noticeable in manual labor, with estimates suggesting a potential productivity decline of up to 4 percent per degree Celsius when temperatures exceed 27°C (Somanathan et al. 2021). Rainfall patterns are also projected to shift significantly over the next two decades (Figure 4 panel B). Presently rainfall-abundant south-western regions, which also harbor more commercial agriculture, are set to experience the largest decrease in rainfall, both in terms of annual average, as well as in terms of extreme events – although relatively moderate, averaging at most 30 millimeters on average per year. The northern half of the country on the other hand, will become both significantly hotter and wetter. The increased variability in rainfall patterns is expected to negatively affect crop yields (Shrotridge 2019) which could push many vulnerable farmers into poverty and act as a migratory push factor. The effects of increased temperatures and rainfall will be widely felt throughout Ghana. Figure 4 panel C presents the increase in the number of days with a Heat Index of 35°C or higher compared to the baseline and highlights that Ghana’s agriculturally- and mining- The Heat Index, also called apparent temperature, is a measure of intensive regions of the southwest, the temperature felt by the body when air temperature is combined with relative humidity. According to the Heat Index chart, although on the low-end of the a heat index that exceeds 27°C should trigger a possible heat scale, will experience an increase disorder warning for people in high-risk groups. A heat index of in the number of “extreme 32°C and above calls for extreme caution, due to the risk of caution” days of at least 50 days sunstroke, muscle cramps, and/or heat exhaustion due to per year. This number increases in prolonged exposed and/or prolonged physical activity. The warning northern regions and is expected category increases with the heat index, reaching a danger category to surpass 100 extra days in south- when it exceeds 41°C and an extreme danger at 54°C or higher. eastern regions of Greater Accra 8 and Volta. With increased heat, workers need to take more frequent breaks and become less productive. Higher temperatures also negatively affect livestock and poultry placing further stress on food security (Asseng et al. 2021). The effects of heat stress is likely to be highest in sub- Saharan Africa, where a 3 degree Celsius increase is expected to reduce labor capacity between 30 to 50 percent (Lima et al. 2021) The number of Tropical Nights is relevant to human health and labor productivity. It is based on the number of consecutive days that exceed a minimum temperature, and the higher the minimum temperature, the greater the physiological discomfort as high temperatures prevent the body to cool off during the night. The greater the number of tropical nights, the greater the stress on human health caused by extreme minimum temperatures.2 Figure 4 panel E is based on an extreme threshold of 26C to illustrate the severity of the temperature increase set to occur in eastern and south-eastern regions of Ghana, and more severely so in the Greater Accra region. Insufficient or poor sleep can lead to considerable labor productivity loss and may lead to considerable negative health outcomes (Hafner et al. 2017). Figure 4. Ghana’s climate change profile Projected changes in annual temperature (left) and precipitation (right) patterns by the middle of the century (2040-2059) relative to the 1995-2014 baseline. A. Mean temperature B. Mean precipitation C. Number of days with Heat Index >35°C D. Number of days with precipitation >20mm 2 https://climate-adapt.eea.europa.eu/en/metadata/indicators/tropical-nights 9 E. Number of tropical nights >26°C F. Largest 1-day rainfall event Source: Staff visualizations based on data obtained on the World Bank Climate Change Knowledge Portal (2024) Note: The figure presents the projected change in annual trends by region. It was created using Coupled Model Inter- comparison Project Phase 6 (CMIP6) data from the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. The current emissions scenario, SSP3-7.0, assumes countries will continue to work towards reducing global greenhouse gas emissions enough that global warming will not exceed 3°C. This trajectory, rather than being the most pessimistic or optimistic of all scenarios, is the most realistic one. Agriculture is a significant source of employment in Ghana. Figure 5 panel A shows that the entire country heavily relies on agriculture, especially in the poorer regions of the north-east, and in the southwestern half of the country. Cocoa is a significant cash-crop in Ghana, on which a lot of people depend for income. Cacao trees are sensitive to changes in weather, and in particular to intense rains, which have already upended harvests in West Africa, a region that produces three quarters of the world’s cocoa. Between 2022 and 2023, Ghana and Cote d’Ivoire produced 58 percent of the global supply of cocoa. Yet high precipitation and humidity have led to a flare up of swollen shoot virus and black pod disease which causes cocoa pods to rot and harden, causing a global shortfall of supply and a sharp increase in global prices (UNCTAD, 2023). Projected changes in average annual precipitation and temperatures by mid-century will change Ghana’s agricultural landscape, albeit not without uncertainty. Projections indicate potentially more favorable 10 cocoa production conditions in the northern half of the country, with temperatures and an increase in precipitation that remain within favorable ranges for cocoa (Schroth et al, 2016). However, the projected increases in heat and humidity may significantly impede manual labor productivity in agricultural and mining-intensive southwestern regions of Ghana, while the increase in humidity and the increased risk of extreme rainfall and flooding threaten yields through the propagation of disease. Coupled with moderate to high drought risk across the country, these trends show rather unfavorable extremes nation-wide that farmers and miners will have to mitigate. In agriculture, to mitigate for the increase in heat, farmers can plant shade trees on their farms. A study found that over 70 percent of interviewed farmers used this technique, but a lack of education and training on the causes of climate change and coping mechanisms, along with prevalent superstitious beliefs impede farmer’s adaptation capacity (Afele et. al. 2024). The effects of climate change can be more severe in manual labor-intensive and in poorer regions. Agriculture and mining are highly prevalent in Ghana, and tend to be concentrated in southwestern regions (Figure 5 panel C). On the one hand, the poor tend to lose more as a share of what they own than the non-poor (Hallegatte et. al. 2017). They are thus more vulnerable to the impacts of severe weather, climate change and hazard events. On the other hand, the effects of climate change can be felt indirectly, when changes in temperatures, precipitation, and humidity, along with more severe and frequent hazards, impede the productivity of outdoor workers. Furthermore, weather-dependent crops can be sensitive to sudden and/or extreme changes in rainfall and temperatures. Figure 5. Agriculture and mining in Ghana A. Share of the population that works in agriculture B. Ghana’s coco production Source: Ghana’s population and housing census 2021 Source: Kalischeck et al 2023 provided by the Ghana Statistical Service. Note: Cocoa farms are identified at 70% confidence level and data is aggregated at district level. 11 C. Geographic distribution of coco production and mineral resources Source: Ghana Minerals Commission 2010 and Kalischeck et al. (2023) The vulnerability of the northern half of Ghana is further strengthened by the clear spatial distribution of poverty and lack of road infrastructure. Districts with high poverty headcount (Figure 6 panel A) are primarily located in the North. The hotspot analysis (Figure 6 panel B) shows a significant spatial correlation in poverty distribution across the country. Specifically, the Northern and Northern East regions present high poverty rates, while the Savannah and Upper West regions also exceed the national average. Southern regions harbor below-average poverty rates, especially in Greater Accra, Eastern, and Ashanti regions. This socioeconomic divide in welfare distribution is intricately linked to the geographic distribution of two fundamental pillars of Ghana's economy: mining and agriculture. The southwest of the country, notably Ashanti and Greater Accra, host the majority of operational mines in Ghana (Ghana Mineral Commission, 2024). In contrast, minerally-deficient northern regions also contend with severe weather conditions that have limited opportunities for cultivating lucrative cash crops such as cocoa beans. Figure 7 highlights the concentration of Ghana’s road network development in agriculturally- and mining-intensive regions in the south-western part of the country. The limited connectivity between the north and south of the country can trace its roots to the country’s colonial legacy where the north of the country was incorporated to the south much later. 12 Figure 6. Poverty overview A. Poverty headcount B. Poverty hotspot Source: Small Area Estimations of poverty (2017) Note: Gretis-Ord Statistics with a confidence level of provided by the Ghana Statistical Service (mimeo) 99% 13 Figure 7. Ghana’s road network A. By road classification B. By road type Source: Staff estimations derived from analysis of satellite imagery. Note: Road network focused on the major roads across the country, not on the smaller feeder roads within cities. Climate change will increasingly expose Ghana's economically vulnerable populations to the threat of flooding. Regions susceptible to flooding often coincide with areas experiencing high levels of poverty (Figure 8 panel A). In the relatively frequent event of a 1-in-10-years flood scenario (with a 65 percent chance of occurring in a given decade), affluent areas are largely spared, while the burden falls disproportionately on impoverished communities, particularly those residing near the Volta River in the South, highlighting the increased exposure of more vulnerable populations. In less frequent though severe 1-in-100 years flood scenarios (with a 9.5 percent chance of occurring in a given decade), several regions with lower poverty rates will also be affected (Figure 8 panel B). However, given the pervasive poverty across the country, the majority of those impacted will still be from impoverished backgrounds. Households with limited financial means are especially susceptible to the adverse effects of flooding, as they both tend to lose more as a share of what they own and are least able to cope (Hallegatte et. al. 2017). Disruptions to critical infrastructure, access to critical services, and substantial losses in agricultural output exacerbate the challenges faced by these vulnerable communities. Access to clean water can become compromised, medical assistance becomes harder to access, and difficult access to markets can rapidly turn into food scarcity for entire communities in the event of a flood. These compounding issues can place a heavy burden on the Ghanaian government in terms of disaster recovery, especially in remote areas. Addressing these challenges effectively requires early targeted interventions to strengthen disaster risk preparedness, including in terms of water management in the most vulnerable regions. 14 Figure 8. Flood Risk and Poverty Rate Matrix A. 1 in 10 years cumulative flood risk B. 1 in 100 years cumulative flood risk Source: staff calculations using 2021 population and housing census data provided by the Ghana Statistical Service and Fathom3 flood data as projected by 2080-2099 under SP3-7.0. Poverty rates coincide with small area estimates of poverty. The poverty rate of a district is applied uniformly across grids within the district. Hence, within grids in the same district the number of poor may differ, but the proportion classified as poor is the same. Notes: Flood risk is considered high if a grid is exposed to at least 15 cm of floodwater. Poverty is considered high if the grid poverty rate is higher than 30%. The risk of flooding in Ghana is most pronounced in southwestern and coastal regions. In the northern areas, the majority of communities have less than 10 percent of their population exposed to flood risks, even in rare 1-in-100-years flood scenario. However, in the south, particularly in areas adjacent to the Volta River, heightened attention is warranted as even ordinary rainfall can lead to significant flooding (see Figure 9 panel A). Fluvial risk, stemming from an overflow of rivers and water bodies as a result of excessive rainfall upstream, is the primary driving factor in 1-in-10-year flood scenarios, making areas near rivers and streams particularly vulnerable to flooding (see Figure 9 panel B). While major cities like Accra and Kumasi are generally safe from frequent flooding, they could face significant risks in the event of a 1-in-100-years flood (see Figure 9 panel C). In such extreme scenarios, pluvial risk, associated with intense rainfall, poses the greatest threat, potentially resulting in severe human and economic losses. 15 Figure 9. Share of the population exposed to different flood intensity levels A. Common Flood B. Frequent Flood C. Historical Flood Source: staff calculations using 2021 population and housing census data provided by the Ghana Statistical Service and Fathom3 flood data as projected by 2080-2099 under SP3-7.0. Note: Population is exposed to flood risk if the floodwaters reach a depth of at least 15 cm. Ghana’s coastline shifts further highlights the co-location of economic activity and infrastructure. Ghana is dotted with a significant coastline, and the country has experienced moderate coastal erosion in rural areas of the coastline. Figure 10 highlights areas of positive coastline changes, where it has gained terrain over the shore – rather than lost it through sea- level rise, severe storms or coastal erosion. This is often due to port infrastructure built in recent decades near mining and agriculturally intensive regions of the south-west, and close to the Accra metropolitan area. Other shifts have naturally occurred near river-mouths. Figure 10. Coastal Shift between 2001 and 2021 Source: Staff calculations using coastal data from Digital Earth Africa Coastlines. In areas with limited infrastructure access, the impact of flood events is most severe . Even in times without flooding, rural residents often face the longest journeys to reach essential services 16 (Figure 11, Figure 12, and Figure 13 panel A). Particularly in the North East region, many residents must travel over an hour by motor vehicle to access schools or medical facilities. Another group significantly affected by service accessibility challenges are the islanders in Lake Volta. While a majority of areas boast decent road networks facilitating journeys to schools or hospitals within 30 minutes, frequent flooding poses a significant threat to accessibility, particularly in areas already facing transportation difficulties. Figure 11, Figure 12, and Figure 13 panel B illustrate those residents in major metropolitan areas such as Accra, Kumasi, and Tamale experience minimal disruptions in accessing services. Conversely, those enduring the longest travel delays coincide with regions already grappling with lengthy travel distances under normal circumstances. This underscores both a nationwide infrastructure disparity and an unreliable rural road network. Regular flooding exacerbates these challenges, hindering routine activities and leaving individuals more vulnerable to health hazards and economic setbacks. Ghana’s road network is underprepared for extreme flooding events. During one in a century flood events, a substantial portion of the country faces near-total isolation from vital infrastructure (Figure 11, Figure 12, and Figure 13 panel C). The data indicates that nearly all rural residents would lose access to health services in the event of a catastrophic flood hitting Ghana. With the persistent effects of climate change, the likelihood of such devastating flood events occurring with greater frequency is projected to significantly increase, necessitating proactive preparedness measures by the Ghanaian government. Figure 11. Average travel time to Schools A. In the absence of flooding B. During frequent flooding C. Under historic flood Source: Staff calculations using ESRI Network Analyst, OpenStreetMap roads and schools data, GRID3 settlement location centroids, and Fathom3 flood data as projected by 2080-2099 under SP3-7.0. Note: 1. Drive time is calculated using network distance from OpenStreetMap; 2. School locations are extracted from 2023 OpenStreetMap; 3. Travel starting point is centroid of each grid; 4. NA values represent closest accessible road is at least 5 kilometers away. 17 Figure 12. Average travel time to health facilities A. In the absence of flooding B. During frequent flooding C. Under historic flood Source: Source: Staff calculations using ESRI Network Analyst, OpenStreetMap roads data, GRID3 settlement location centroids, and Fathom3 flood data as projected by 2080-2099 under SP3-7.0. Note: 1. Drive time is calculated using network distance from OpenStreetMap; 2. Health facility locations are provided by WHO databae (Maina et al 2019); 3. Travel starting point is centroid of each grid; 4. NA values represent closest accessible road is at least 5 kilometers away. Figure 13. Average travel time to markets, as proxied by the nearest urban area A. In the absence of flooding B. During frequent flooding C. Under historic flood Source: Staff calculations using ESRI Network Analyst, OpenStreetMap roads data, GRID3 settlement location centroids, and Fathom3 flood data as projected by 2080-2099 under SP3-7.0. Note: 1. Drive time is calculated using network distance from OpenStreetMap; 2. Market locations are settlement gocations that have 50,000 people or more, with a density of 1,500 people per square kilometer; 3. Travel starting point is centroid of each grid; 4. NA values represent closest accessible road is at least 5 kilometers away. 18 Conclusions Due to climate change, Ghana could experience considerable undoing of the progress it has achieved over the past decades. The country’s economy, heavily reliant on natural resource extraction, is substantially exposed to the damaging effects of climate change. The uneven distribution of climate conditions contributes to varied risks and impacts across the country, influencing sectors like agriculture, health, and infrastructure differently in different regions. The concentration of poverty in northern Ghana aligns with areas most susceptible to climate hazards, emphasizing the intersection of socioeconomic vulnerability and climate risks. Populations in the north of Ghana are more likely to be poor, which constrains their ability to cope and adapt, and the area is also where temperatures are expected to increase the most. Rainfall anomalies are also expected to be higher in the area. The area also already is at high risk of water scarcity. The main source of livelihood for people in the north of Ghana is agriculture, a sector that will be negatively impacted moving forward which will likely push many into deeper poverty. Under extreme flooding scenarios the region’s accessibility, due to limited road infrastructure, is also limited which can make the delivery of assistance during extreme climate events quite challenging. Vulnerable regions with high poverty rates and limited infrastructure are particularly at risk. This is because of the expected increase in the frequency and severity of natural hazards, including floods, droughts, and extreme weather events risks that people are cut off from the rest of the country and delivering assistance is further complicated. A shock could put at peril a vulnerable region’s food security and access to schooling, negatively affecting children’s human capital limiting their future income generating potential. Ghana's agriculture sector, particularly reliant on cash crops like cocoa, faces significant risks from changing temperature and rainfall patterns. Rising temperatures will make outside work more hazardous and strenuous and will lead to a considerable drop in productivity which will likely hit unskilled workers the hardest leading to higher vulnerability to poverty. Extreme weather patterns risk considerable reduction in crop yields which can lead to heightened precarity, leading to economic losses and food insecurity. The impacts of climate change on manual labor-intensive sectors underscore the need for adaptive strategies to safeguard livelihoods and enhance resilience. Effective adaptation and disaster preparedness measures are essential to mitigate climate risks and protect vulnerable communities. Investments in infrastructure, social safety nets, and climate-resilient agriculture practices are crucial to build resilience and sustain development in the face of ongoing climate variability and future climate change impacts. Proactive interventions are needed to address the complex interactions between climate, poverty, health, and infrastructure challenges in Ghana, ensuring a sustainable and equitable pathway forward amidst climate uncertainty. 19 References Afele et. al. 2024. Understanding and addressing climate change impacts on cocoa farming in Ghana https://www.sciencedirect.com/science/article/pii/S2667010023001464 Asseng, S., Spänkuch, D., Hernandez-Ochoa, I. M., & Laporta, J. (2021). The upper temperature thresholds of life. The Lancet Planetary Health, 5(6), e378-e385. Ghana Mineral Commissions. 2024. Major Operating Mines in Ghana. https://www.mincom.gov.gh/operating-mines. Kalischek, N., Lang, N., Renier, C., Daudt, R. C., Addoah, T., Thompson, W., ... & Wegner, J. D. (2022). Satellite-based high-resolution maps of cocoa planted area for Cote d'Ivoire and Ghana. arXiv preprint arXiv:2206.06119. Schroth, Läderach, Martinez-Valle, Bunn, Jassogne. 2016. Vulnerability to climate change of cocoa in West Africa: Patterns, opportunities and limits to adaptation, Science of The Total Environment, Volume 556, Pages 231-241, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2016.03.024. Institute for Health Metrics and Evaluation (IHME). 2019. Global Burden of Disease Study 2019 (GBD 2019) Air Pollution Exposure Estimates 1990-2019. https://ghdx.healthdata.org/record/global-burden-disease-study-2019- gbd-2019-air-pollution-exposure-estimates-1990-2019. De Lima, C. Z., Buzan, J. R., Moore, F. C., Baldos, U. L. C., Huber, M., & Hertel, T. W. (2021). Heat stress on agricultural workers exacerbates crop impacts of climate change. Environmental Research Letters, 16(4), 044020. Hafner, M., Stepanek, M., Taylor, J., Troxel, W. M., & Van Stolk, C. (2017). Why sleep matters—the economic costs of insufficient sleep: a cross-country comparative analysis. Rand health quarterly, 6(4). Maina, J., Ouma, P. O., Macharia, P. M., Alegana, V. A., Mitto, B., Fall, I. S., ... & Okiro, E. A. (2019). A spatial database of health facilities managed by the public health sector in sub Saharan Africa. Scientific data, 6(1), 134. World Health Organization (WHO). 2021. WHO global air quality guidelines: particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide. https://www.who.int/publications/i/item/9789240034228. Roberts et al 2023 https://www.worldbank.org/en/region/eap/publication/unlivable-what-the-urban-heat-island- effect-means-for-east-asia-s-cities UNCTAD 2023 https://unctad.org/news/chocolate-price-hikes-bittersweet-reason-care-about-climate-change Ghana minerals commission. 2010. https://data.gov.gh/dataset/shapefiles-mineral-resource-ghana-2010 GFDRR (2020). ThinkHazard! Washington, DC: World Bank. https://www.thinkhazard.org/ Hallegatte, S., Vogt-Schilb, A., Bangalore, M., & Rozenberg, J. (2017). Unbreakable: building the resilience of the poor in the face of natural disasters. World Bank Publications Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes. Scientific data. 2015;2(1), 1-21. The World Bank. (2024). World Bank Climate Change Knowledge Portal (2024). Shortridge, J. Observed trends in daily rainfall variability result in more severe climate change impacts to agriculture. Climatic Change 157, 429–444 (2019). https://doi.org/10.1007/s10584-019-02555-x Van Donkelaar, A., Hammer, M. S., Bindle, L., Brauer, M., Brook, J. R., Garay, M. J., Hsu, N. C, Kalashnikova, O. V., Kahn, R. A., Lee, C., Levy, R. C., Lyapustin, A., Sayer, A. M., & Martin, R. V. (2021). Monthly global estimates of fine particulate matter and their uncertainty. Environmental Science & Technology. 2021; 55(22), 15287-15300 20 21