Climate action and energy access in Sub-Saharan Africa: insights from Covenant of Mayors signatories

According to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report, Africa is one of the continents with the most vulnerable human conditions to climate change1. This vulnerability is compounded by a range of factors, including widespread poverty, poor health outcomes, and rapid urbanisation, which together contribute to the continent’s limited adaptive capacity to climate impacts2. In Sub-Saharan Africa, the exposure of people and assets to climate hazards is increasing, driven by socio-economic dependence on climate-sensitive sectors, the growth of informal settlements, and the absence of essential infrastructure and services2. Urbanisation is expected to continue at a rapid pace, presenting significant challenges for both climate adaptation and mitigation3. Within this context, it is crucial to understand the local sustainable policies that municipalities in Sub-Saharan Africa are developing to tackle climate change mitigation, adaptation, and energy access. The Paris Agreement, alongside the Sustainable Development Goals (SDGs)4 and the Agenda 2063 of the African Union5, underscores the urgent need for coordinated climate action with social-economic prosperity and highlights the importance of building synergies to address climate change and create sustainable futures. All Sub-Saharan African nations have ratified the Paris Agreement and submitted their Nationally Determined Contributions (NDCs), with many of emphasising energy and clean cooking as key sectors for climate action.

Despite the growing urgency, climate research in Africa remains relatively underdeveloped compared to other regions, especially at the local level6,7. The body of literature on climate change mitigation and adaptation in African cities predominantly focuses on the impacts of climate change and the risks the region faces8. Recently, research on climate adaptation increasingly focuses on the implementation of policies and the roles of various stakeholders, including national governments, NGOs, and local communities9,10,11. These studies highlight the challenges of balancing top-down governance with bottom-up, participatory approaches12,13,14,15.

While the literature on urban climate action planning16 and local climate adaptation in Africa is expanding17,18, research on climate mitigation remains relatively limited8,15. While Africa has the lowest emissions globally, this is particularly concerning given the continent’s heavy reliance on high-emitting but also climate-sensitive sectors such as agriculture and energy19,20. There is also an emerging focus on the concept of “just transition” which explores how climate mitigation policies can simultaneously address social inequalities and promote inclusive development21. The just transition perspective is frequently linked with energy access issues, which remain widespread in Sub-Saharan Africa. More than 570 million people lacked access to electricity in 2022, of which 94 million in urban areas22. Despite the extensive discussion on energy access and just transition, studies frequently treat these issues isolated from climate mitigation and adaptation. This separation is especially evident in studies that treat climate adaptation and social resilience as distinct areas of research10. In addition, studies often examine the role of renewable energy and decentralised energy systems23. While some research highlights the potential of renewable energy to enhance energy access and climate-related framework7,24, energy access initiatives and broader climate action goals and strategies are often disconnected25,26. However, there is growing recognition that integrating energy access with climate action could yield significant synergies27.

At the local level, the interplay of poverty, health challenges, and rapid urbanisation further weakens the region’s adaptive and mitigative capacity, exacerbating the impacts of climate change and creating barriers for climate action28,29. Local adaptation measures—such as enhancing urban infrastructure resilience, improving water management, and supporting community-based initiatives—are critical to fostering long-term sustainability6,15. And studying the design and implementation of these measures is essential to understand the challenges cities face14. Yet research on the role of municipal policies and engagement are still limited and much of the existing literature fails to address how local governments develop and implement climate action plans, even though municipalities are frequently on the frontline of climate change impacts30. A more integrated approach is needed to develop comprehensive solutions that tackle the complex, interwoven challenges facing African cities31,32,33. Recent studies show how bridging the gap between climate change impacts and drivers, energy access, and resilience is essential for fostering sustainable development and ensuring that climate policies have a lasting, positive impact34.

The Covenant of Mayors in Sub-Saharan Africa (CoM SSA) initiative offers the opportunity for local governments to tackle climate change mitigation, adaptation, and energy access through an integrated and flexible approach. Under the CoM SSA, local authorities make a voluntarily political commitment to implement climate and energy actions in their communities and agree on a long-term vision to tackle the three pillars of climate mitigation, adaptation and energy access. These commitments are included and translated into actions in Sustainable Energy Access and Climate Action Plans (SEACAPs), which, based on an assessment of the current situation, define the municipalities’ vision and concrete goals.

By combining data directly reported by municipalities, information provided in Sustainable Energy Access and Climate Action Plans (SEACAP) developed by selected cities, and the structure provided by the Common Reporting Framework (CRF)35 of the Global Covenant of Mayors for Climate and Energy (GCoM) initiative, this study aims to understand in more details how Sub-Saharan African cities are preparing their climate plans and proposes an integrated approach to analyse the status, objectives, approaches and actions taken to tackle climate change and energy access in their communities within the CoM SSA framework. By doing so, this research seeks to bridge three research gaps emerging in the examined literature: (1) limited availability of data and analysis on how local governments in Sub-Saharan Africa are approaching the topic of local climate mitigation, adaptation and energy access, (2) deficit of a comprehensive and combined perspective on these three topics, (3) lack of focus on how local governments plan to move from analysis to taking action on these domains. The specific research objectives include: (1) present the status of selected municipalities, (2) analyse efforts in the domain of climate change mitigation, adaptation and energy access in terms of planning and ambition, (3) investigate the typology of actions designed by municipalities and understand the degree of integration among the areas of intervention.

This research has the potential to inform policy decisions on local climate action. Its findings can also guide municipalities, both in Sub-Saharan Africa and globally, as they initiate or strengthen their climate action and resilience efforts.

Results

This study analyses a sample composed of 17 local authorities from Sub-Saharan Africa signatories of CoM SSA. Local authorities have been selected based on the availability of their SEACAP (13 municipalities) or related data provided through the official CoM SSA reporting template (4 municipalities). The cities vary widely in terms of size, administrative status, and geographic distribution, offering a diverse representation across the region. Capital cities such as Dakar (Senegal), Abuja (Nigeria), and Maputo (Mozambique) are included, alongside large metropolitan areas like Nakuru County (Kenya) and urban districts within capitals such as Yaoundé III and Yaoundé IV (Cameroon). Several secondary cities are also represented, including Bouaké (Côte d’Ivoire), Bobo Dioulasso (Burkina Faso), and Garoua (Cameroon), as well as Ribeira Grande de Santiago (Cabo Verde) and Doumé (Cameroon). Population sizes range from under 10,000 to over two million inhabitants at the time of inventory, with projected growth expected in nearly all locations by 2030. This diversity provides a perspective of different urban contexts—capital versus secondary cities, large versus small populations, and varied regional dynamics within West, Central, and East Africa.

Population density varies significantly across the sample, reflecting variations in both urban morphology and land availability. Densely populated urban areas include Dakar (Senegal), Bangui (Central African Republic), and Pikine (Senegal), each exceeding 14,000 and 16,000 inhabitants per square kilometre, while more expansive territories such as Nakuru County (Kenya) and Abuja Municipal Council Area (Nigeria) show densities below 1500 inhabitants per square kilometre. At the national level, economic conditions also differ markedly: GDP per capita (in USD) at the time of inventory ranges from under $500 in the Central African Republic to over $3500 in Cabo Verde. Regarding climate and development vulnerability, as captured by the Notre Dame Global Adaptation Initiative (ND-GAIN) index—which measures a country’s vulnerability to climate change and its readiness to adapt36—strong variabilities are present. Considering the ranking from 1 to 187, where lower ranks indicate greater readiness and lower vulnerability, countries in the study range from a relatively favourable position of 82 (Cabo Verde) to a highly vulnerable ranking of 186 (Central African Republic). These indicators provide essential context for the socio-economic and environmental conditions in which local energy and climate plans are being developed.

Figure 1 provides a geographical contextualisation of the selected municipalities, while Table 1 summarises the main information of each signatory local authority.

Fig. 1: Geographic distribution and typology of municipalities included in the study.

Table 1 Municipality and country context overview

Full size table

Results are presented following the structure of the three CoM SSA thematic pillars: (1) mitigation to climate change, (2) adaptation to climate change, (3) energy access, and illustrate the status of related assessment, ambition and actions. The study presents the status of each municipality as outlined in the assessment phase of its SEACAP, including baseline conditions across the plan’s key pillars. For example, under the mitigation pillar, this refers to the level of greenhouse gas emissions reported for the inventory year chosen by the municipality. Ambition is defined by the targets set for 2030 in each pillar, reflecting the expected outcomes of planned actions in areas such as emissions reduction, climate adaptation, and energy access. Building on these definitions of status and ambition, the study explores selected themes—such as mitigation baselines, risk and vulnerability assessments, and future targets—as essential dimensions for understanding the scope and direction of local climate action. These elements highlight both the starting point and intended trajectory of each local authority’s SEACAP.

Mitigation to climate change: assessment and ambition

Concerning the mitigation to climate change assessment, and specifically the baseline emissions inventory, Fig. 2 presents the greenhouse gas (GHG) emissions for each municipality, expressed in tonnes of carbon dioxide equivalent (tCO2eq), in the baseline emission inventory (BEI) year. The BEI serves as a comparative benchmark against the projected emissions for the target year set in 2030 for all municipalities, when it is assumed that mitigation measures outlined in the SEACAP are in place. All the municipalities assessed have established both their BEI and the projected emissions for the target year. Most municipalities provide information on the BEI considering an inventory year between 2016 and 2019, while three municipalities use an inventory year that dates to 2010 and one municipality uses a recent inventory year, i.e. 2021. The spectrum of emissions in the BEI varies between 963 tCO2eq for the municipality of Ribeira Grande de Santiago in 2010, to 4,612,436 tCO2eq for the municipality of Maputo in 2019. When looking at the target year in 2030, the spectrum ranges from 5.578 tCO2eq for the municipality of Ribeira Grande de Santiago to 4,852,174 tCO2eq for the municipality of Pikine.

Fig. 2: Greenhouse gases emissions in inventory year and in target year when mitigation measures are in place.

Understanding the specific baseline conditions and trajectories of each municipality is important to comprehend their future pathways. As illustrated in Supplementary Fig. 1a, the Baseline Emissions Inventory (BEI) considers multiple emitting sectors—stationary energy (which includes emissions from residential buildings, industrial/commercial/institutional buildings and facilities, agriculture, forestry, fisheries and fugitive emissions), waste, transport, and others—each playing a unique role in shaping local baseline conditions. While stationary energy often accounts for the largest portion, each municipality’s BEI reflects its own distinct combination of emitting sources. The level of ambition of each municipality is represented by the status in the target year and the amount of emissions reduction. Fourteen municipalities have set a baseline scenario target, where the emission reduction levels in the target year are compared to a Business as Usual (BAU) baseline scenario, representing the expected emission levels if no mitigation measures would have been put in place. Three municipalities have set a base year emissions target, where the emission reduction levels are compared with the emissions in the base year inventory. These municipalities have a decreasing trend of emissions as shown in Fig. 2. Furthermore, Supplementary Fig. 1b provides detailed changes in per-capita emissions between the inventory year and the target year. It highlights that municipalities with overall emission increases can have varying per-person outcomes: eight have an increase, while two show a decrease. The remaining seven municipalities have both a decrease of overall emissions and decrease in per-capita emissions.

To have a complete understanding of the mitigation assessment it is important to evaluate changes in population and per capita emissions both in the base year and in the target year. In the BEI year, the smallest municipality, Ribeira Grande de Santiago, had a population of 8325 inhabitants in 2010. Conversely, the largest municipalities were Abuja, with over 1.9 million inhabitants, and Nakuru County, with a population exceeding 2 million. By the target year of 2030, Ribeira Grande de Santiago is projected to maintain a relatively stable population. In contrast, significant growth is expected in the larger municipalities, with Abuja’s population projected to reach 2.8 million and Nakuru County’s to increase to 3 million inhabitants.

Figure 3 displays the per capita emissions distribution of the 17 municipalities, considering municipal populations and emissions for the BEI and target years. The per capita emissions span from 0.062 tCO2eq/person to 2.512 tCO2eq/person in the BEI, and from 0.672 tCO2eq/person to 3.160 tCO2eq in the target year (2030).

Fig. 3: Comparison of greenhouse gases emissions per person of the 17 municipalities.

When it comes to consider the ambition in identifying mitigation goals, Fig. 4 displays the mitigation targets set by each municipality and compares them with the unconditional Nationally Determined Contribution (NDC) target of their respective country. NDCs are national climate action plans submitted under the Paris Agreement, outlining each country’s commitment to reduce greenhouse gas emissions. The ‘unconditional target’ refers to the level of emissions reduction a country commits to achieving without requiring external support37. Values above the NDC line indicate that the municipality is aiming for greater emissions reductions than the national target, while values below suggest a less ambitious local commitment.

Fig. 4: Sustainable energy access and climate action plan mitigation target versus Nationally Determined Contributions unconditional target.

For 14 municipalities out of 17, the mitigation goal set is either more ambitious or equal to the NDC. Within this sample, 11 municipalities have an ambition that overcomes the NDC target between +5 percentage points (pp) to +38pp. Three municipalities set a mitigation goal that is equal to the NDC. The remaining four municipalities decided to set a mitigation goal that is lower in ambition compared to the NDC, in this case the variation ranges from −1pp to −52pp.

Adaptation to climate change: assessment and ambition

All 17 municipalities have completed a Risks and Vulnerability Assessment (RVA) to identify, analyse, and prioritise the potential threats that climate change poses to their natural and human systems. Each municipality has identified its main climate hazards and sub-hazards, defining the relative estimated probability and impact, as well as sectors of interest.

Regarding the assessment of adaptation to climate change conditions, and in particular risks and vulnerabilities to climate change, Fig. 5a presents the climate hazards identified by the municipalities, along with their estimated impact and probability of occurrence. Figure 5b illustrates the sectors affected by these hazards, showing both the vulnerability of each sector and the number of hazards impacting it—acknowledging that multiple hazards can affect the same sector. The classification of hazards and sectors follow the categorisation used in the CRF and the scoring of probability, impact and vulnerability ranges from “low”, “medium” and “high”. Additional information on the categorisation and scoring system used is provided in the “Methods” section. Regarding climate hazards, the study shows that extreme heat is selected by 16 municipalities out of 17 and in most cases has a high probability or impact, or combination of both. Extreme cold is relevant for only 4 municipalities and with low probability and impact. Heavy precipitation (and related sub-hazards) has been identified by 12 municipalities and its probability and impact cover the full range of options from low impact and low probability to high impact and high probability. Floods and sea level rise are another preponderant climate hazard that, including its related sub-hazards, has been identified by 15 municipalities. The following climate hazards, droughts and water scarcity, have been selected by 14 municipalities and often with high impact and high probability. The climate hazard of storms is slightly less frequent, having been selected by 12 municipalities. A smaller group of local authorities selected the remaining climate hazards and related sub-hazards, including mass movement (6 municipalities), and other hazards (8). Additionally, Fig. 5a maps each of the selected climate hazards against the climate hazards identified in the NDC, showing that each municipality has identified at least one hazard that is relevant also at national level.

Fig. 5: Risks and vulnerability assessment considering climate hazards and sectors impacted.

Concerning the vulnerable sectors, the analysis shows that each municipality identifies at least two sectors impacted by climate hazards with a medium to high level of vulnerability. The municipality declaring to be impacted in more sectors is Maputo with 10 sectors, all with high or medium vulnerability levels. Based on the assessment made by cities, the sectors that are most preponderant are: buildings (13 municipalities), agriculture and forestry (11), health (13), environment and biodiversity (10). Another group of sectors has been selected on average by one in three municipalities. Here the sectors most selected by municipalities are: energy (6 municipalities), land use planning (7), informal housing (5), water (8) and transport (6). Finally, the least selected sectors are civil protection and emergency, society community and culture, tourism, education and waste. Also, for Fig. 5b, the selected sectors are mapped against those identified in the NDCs, showing that each municipality has identified at least one or more sectors that are relevant also at the national level.

The ambition by municipalities to take action on adaptation to climate change is elaborated and declared through the adaptation goal. Figure 6 depicts the typology of adaptation goals per each municipality, illustrating whether the municipality has chosen one or more adaptation goals, whether they are qualitative or quantitative and which climate hazard or sector they are targeting. All municipalities have identified at least one adaptation goal.

Fig. 6: Number and type of adaptation goals.

Municipalities can set more targets upon their choice and overall the number of adaptation goals set per each municipality ranges from one to five. Nine municipalities have set only one adaptation goal, two have set two adaptation goals, and the remaining six have set either four or five goals. During the SEACAP planning process, municipalities define an adaptation goal that can be either quantitative or qualitative and that is relevant to their RVA. Regarding this aspect, as illustrated in Fig. 6, out of the 17 municipalities with an adaptation goal, seven have one or more qualitative adaptation goals, nine have one or more quantitative adaptation goals, and one municipality has both qualitative and quantitative adaptation goals. Finally, the analysis illustrates how adaptation goals are allocated across various sectors, and highlights instances where these goals are in alignment with the sectors targeted by the NDC.

Energy access: assessment and ambition

In their SEACAP preparation effort, municipalities are also called to assess their initial level of energy access and set a target, specifically for access to electricity and access to clean cooking.

For each municipality, Fig. 7 presents the access to electricity baseline levels estimated by the municipality during the energy assessment phase and the related goal. To have a broader perspective, these values are compared against the SDG7 objective of achieving universal access to electricity22, when 100% of the population is reached, as well as the latest levels of urban electricity access at the country level and at the Sub-Saharan Africa level.

Seven municipalities have an electricity access baseline above 90%, with 3 already achieving near-universal access. The other ten municipalities show more variation, with baselines ranging from around 80% in Bouaké to as low as 3% in Datcheka. The ambition to improve access varies between 2 and 70 percentage points. Despite these efforts, six municipalities are still projected to have an access gap by 2030. For three, the gap will be around 10 percentage points or less, while the other three will face gaps of 40 to 50 percentage points.

When comparing current urban electricity access levels to national averages, only 4 out of 17 municipalities currently exceed their respective national electricity access levels. In Senegal (97% in 2022), Dakar and Pikine surpass the national average by 3 and 1 percentage points (p.p.), respectively. In Cameroon (94%), Yaoundé III exceeds the average by 5 p.p. In Burkina Faso (61%), Bobo Dioulasso is 3 p.p. above the national level. When considering regional-level statistics, eight municipalities surpass the Sub-Saharan Africa urban average (81% in 2022). Looking ahead to 2030 targets, 13 municipalities are projected to exceed their respective 2022 national averages, and 14 are expected to surpass the 2022 Sub-Saharan Africa urban average, indicating a strong commitment to improving electricity access at the local level.

For each municipality, Fig. 8 presents the access to clean cooking baseline levels estimated by the municipality during the energy assessment phase and the related goal. Also in this case, a comparison with the SDG7 objective of achieving universal access to clean cooking as well as the latest levels of urban clean cooking access at the country level and at the Sub-Saharan Africa level is provided.

Two municipalities have a clean cooking access baseline above 90%, and the other two above 80%. The other municipalities show baselines ranging from around 70% in Abuja and Bobo Dioulasso to as low as 0.6% in Datcheka. The ambition to improve access varies between 6 and 90 percentage points. Despite these efforts, nine municipalities are projected to have an access gap by 2030. For two, the gap will be around 15 percentage points or less, while the others will face gaps ranging from 30 to 85 percentage points.

When comparing current urban clean cooking access levels to national averages, 7 out of 17 municipalities currently exceed their respective national clean cooking access levels. In Senegal (59% in 2022), Pikine surpass the national average by 35 p.p. In Cameroon (49%), Yaoundé III exceeds the average by 37 p.p. In Burkina Faso (48%), Bobo Dioulasso is 24 p.p. above the national level. In Nigeria (45%), Nigeria surpass the national average by 26 p.p. In Côte d’Ivoire (72%), Bouaké exceeds the average by 13 p.p. In Mozambique (15%), Maputo is 27 p.p. above the national level. Finally, in Togo (24%), Kloto surpass the national average by 17 p.p. When considering regional-level statistics, eight municipalities surpass the Sub-Saharan Africa urban average (42% in 2022). Looking ahead to 2030 targets, 14 municipalities are projected to exceed their respective 2022 national averages, and 16 are expected to surpass the 2022 Sub-Saharan Africa urban average, indicating a strong commitment to improving clean cooking access at the local level

In exploring these municipal efforts, it is essential to consider the broader national energy context, as electricity and clean cooking access are also influenced by the performance and reach of national utilities An examination of the SEACAPs confirms this dependency: for instance, Abuja relies on the Abuja Electricity Distribution Company (AEDC), with 90% of the population connected to the grid, albeit with reported reliability and affordability issues. Bangui, served by the Central African Republic’s utility (ENERCA), has among the lowest access rates, with only 24% connected and a high prevalence (29%) of illegal connections. In Bobo Dioulasso, 60% have access via SONABEL, the national provider. Cities such as Doumè and Fokoué, served by Cameroon’s ENEO, report lower grid connection rates of 21.4% and 30%, respectively, while Garoua shows a relatively higher rate (61% of 64% connected) but also highlights informal access through shared connections (17%). Other municipalities such as Maputo (95%) and Nakuru (63.8%, with 95.5% of these connected to the grid) illustrate more advanced levels of electrification. These patterns underscore the crucial role that national utilities play in shaping urban electricity access. While local governments propose energy access initiatives through SEACAPs, their implementation is often constrained by broader systemic factors—including utility performance, national electrification strategies, and infrastructure investment—beyond municipal control. Similarly, local clean cooking initiatives depend on national supply chains and infrastructure, which can limit the ability of municipalities to achieve their SEACAP targets. This highlights the importance of integration between local plans and national energy policy frameworks and collaboration and partnerships across different levels of governance to enable cities to meet their SEACAP energy access targets and progress toward SDG7.

Overview of planned interventions

The SEACAPs include the list of actions that municipalities intend to implement to achieve their mitigation, adaptation and energy access goals and to target sensitive areas identified during the assessment phase. The SEACAP presents actions that are targeted specifically to each pillar. For example, an action completely focused on addressing climate mitigation, hence targeting the thematic pillar of mitigation. When actions are expected to impact more than one thematic pillar, they can be labelled as integrated. For example, a mitigation action can also have positive effects on adaptation. In this case, during the reporting phase, the action is recorded as a mitigation action impacting also adaptation to climate change and can be labelled as an integrated action.

Figure 9 illustrates how each municipality distributes its actions across different pillars and indicates the percentage of actions that have an impact on multiple pillars. Firstly, all municipalities are planning to take action in each pillar of the initiative, reporting actions for mitigation, adaptation and energy access, with some cities presenting also self-standing cross-cutting actions. Each municipality has a balanced approach and distribution of actions across pillars. Considering the aggregated list of actions from all the municipalities, the adaptation and mitigation pillars present the highest share of actions, with 36% and 34%, followed by energy access with 28% and cross-cutting actions with 2%. Secondly, 15 out of 17 municipalities reported actions as integrated. The degree of integration across signatories varies, with percentages of integrated actions ranging between 10 and 87%. Thirdly, there is a large variation of the absolute number of actions included in each plan. This can vary between 17 actions for Pikine and 118 for Dakar.

Fig. 9: Distribution and level of integration of actions across thematic pillars.

Municipalities employ diverse approaches when designing interventions. In this study, we used an adaptation of the Key Types of Measures (KTM)38 categorisation and we use a selection of the four KTMs to classify actions: (1) Physical and technological, (2) Governance and institutional, (3) Economic and financial and (4) Knowledge and behavioural change.

Analysing the distribution of KTMs across 17 municipalities reveals that physical and technological actions are the most prevalent, accounting for 42% to 85% of actions in 11 municipalities. In the remaining 6 municipalities, knowledge and behavioural change actions are the most prevalent, though their share remains below 50%. As shown in Fig. 10, governance and institutional measures, as well as economic and financial measures, represent smaller proportions, ranging from 4% to 33% and 2% to 12% respectively.

Fig. 10: Categorisation of actions based on key type measures per municipality and sector of intervention.

Aggregated data confirm this trend, with physical and technological actions comprising 45% of all interventions, followed by knowledge and behavioural change (32%), governance and institutional measures (20%), and economic and financial measures (3%). This distribution is also reflected in sector-specific analyses: physical and technological measures are most common for mitigation and adaptation actions, while knowledge and behavioural change measures are prevalent in energy access initiatives.

Two specific aspects using different groups of municipalities with sufficient data for the analysis were then separately examined.

Firstly, the study analysed a sub-sample of 14 municipalities having a completed SEACAPs to better understand the funding approaches adopted by municipalities, and to assess whether and which resource mobilisation options were identified to finance the implementation of planned actions. This revealed that 10 municipalities out of 14 had identified funding sources from either the public or private sectors.

Public sector funding options were the most frequently cited, including: (1) Municipal and national government budgets, (2) International financing from development agencies or international organisations, and (3) Local support through community contributions or partnerships with other municipalities. Private sector funding options, while less diverse, were often highlighted as critical in the SEACAPs. These included public-private partnerships and direct investments by private stakeholders.

Secondly, the study examined the SEACAPs or reporting data to verify whether the designed actions were supported by initial estimates of the investment costs required for implementation. Among the 17 municipalities analysed, 16 provided information on budget requirements for their actions. The number of actions having a correspondent budget entry was checked, finding that ten signatories provided information with varying levels of detail, with data covering between 11% and 68% of their actions, while six signatories reported detailed budget estimates for 95% to 100% of their planned actions. This latest sub-sample of six cities was selected for more in-depth analysis based on accurate data availability of cost estimates. These cities—Fokoué, Doumé, and Yaoundé IV in Cameroon; Praia and Ribeira Grande de Santiago in Cabo Verde; and Kloto in Togo—represent a mix of urban profiles. Three are secondary cities with smaller populations (Fokoué, Doumé, and Ribeira Grande de Santiago), while the remaining three include another secondary city (Kloto), however, with a larger population and with a fast growing projection, a district of a capital city (Yaoundé IV) and a primary city and national capital (Praia). Their geographic distribution spans West and Central Africa, offering useful regional contrasts in planning practices and emission profiles. The analysis aimed to quantify the total estimated budget requirement of each signatory, compare costs to GHG emissions reduction targets, and assess the distribution of budgets across the KTMs within each municipality.

The analysis shows that implementing all the actions in the six municipalities would require a total investment of € 522 million.

The potential correlation between emissions reduction targets and the budgets allocated only for mitigation actions across all cities was investigated. The data shows substantial variation, ranging from Ribeira Grande de Santiago allocating approximately € 0.89 million to reduce 1225 tCO₂e, to Yaoundé IV allocating over € 426 million to reduce 721,459 tCO₂e. However, a consistent correlation between emissions targets and budget allocation can be observed. When the Yaoundé IV is excluded, the relationship weakens considerably, suggesting that—also given the limited sample size and diverse characteristics of the municipalities—currently it is not possible to conclude that budgets scale consistently with the level of emissions to be reduced. Furthermore, the analysis revealed that physical and technological actions dominate the budget allocation in each municipality, accounting for 60% of the budget in Kloto and up to 99% in Yaoundé IV, as illustrated in Fig. 11. Governance and institutional measures, as well as knowledge and behavioural actions, collectively represent no more than 20% of the budget in any municipality.

Fig. 11: SEACAP budget allocation for selected municipalities.

Climate action trends by municipality type and population

The investigation proceeded by grouping municipalities according to type and population to identify potential related trends and patterns for mitigation, adaptation and energy access targets, as well as for number of actions and key type measures. While the sample limits the generalisation of findings, this section aims to set initial evidence that could be further expanded in future research with larger data sample.

The 17 municipalities were categorised in four groups: (1) Group XL, composed of the 6 largest municipalities including capital cities, primary cities and counties with population above 1 M inhabitants, (2) Group L, composed of 3 large municipalities including capital cities with population below 1 M inhabitants, (3) Group M, composed of 4 medium size municipalities including secondary cities with population above 100,000 inhabitants, (4) Group S, composed of 4 small municipalities including secondary cities with population below 40,000 inhabitants. A detailed composition of each group is provided in the “Methods” section.

The first step assessed how each group performed against the mitigation, adaptation and energy access targets. Regarding mitigation, on average, smaller municipalities in Group S exhibit the highest 2030 reduction targets (35%), while large municipalities in Group XL show the lowest ambition (18%). Intermediate cities, part of Group L and Group M, report targets of 24% and 25% respectively, as illustrated in Fig. 12a. These results suggest that smaller municipalities may be setting more ambitious climate mitigation targets, potentially due to lower baseline emissions, localised governance structures, or stronger alignment with external support frameworks and is consistent with the high level of ambition for single municipalities reported in Fig. 4. Concerning adaptation goals, the analysis reveals distinct patterns across city types, with the setting of quantitative targets appearing relevant across all groups. Specifically, large cities in Group XL report the highest number of qualitative goals (6) alongside a substantial number of quantitative targets (10). In contrast, smaller municipalities seem to tend to prioritise quantitative adaptation goals: Group M and Group S municipalities report 12 and 7 quantitative goals, respectively, with only one qualitative goal each, as illustrated in Fig. 12b. This suggests that while larger cities may favour broader, strategic objectives, smaller cities tend to focus on measurable, outcome-oriented planning, possibly reflecting limited resources and a need for clearer accountability.

Fig. 12: Comparison of mitigation, adaptation and energy access targets by municipality type and size.

A comparison across city types reveals differing approaches to mitigation and adaptation, with no clear correlation between the level of mitigation ambition and the number or type of adaptation targets. Smaller municipalities (Group S) report the highest mitigation targets (35%) and focus primarily on quantitative adaptation goals (7), with only one qualitative target. Medium-sized cities (Group M) follow a similar pattern with 25% mitigation targets and the highest number of quantitative goals (12). In contrast, the largest cities (Group XL) show the lowest mitigation ambition (18%) but the most balanced adaptation planning, combining 6 qualitative and 10 quantitative targets. These variations suggest that adaptation and mitigation strategies are shaped more by local capacities and planning approaches than by a unified level of climate ambition.

Finally, regarding energy access, the analysis indicates high ambition across all city types, particularly for electricity access. Group M cities report the highest target (94%), followed by Group XL (92%), while municipalities in Group L report the lowest (86%). Clean cooking targets are consistently lower across all categories compared to those of electricity access, ranging from 67% (Group L) to 83% Group XL and Group S), as illustrated in Fig. 12c. This discrepancy is supposedly related to the broader challenge of advancing clean cooking solutions, which often face greater technological, infrastructural, and behavioural barriers. Additionally, the lower baseline levels for clean cooking—46% on average across the sample compared to 66% for electricity access—indicate a larger gap that municipalities must address to reach their 2030 targets.

The last step analysed whether each group aligned against the number of planned actions in each pillar, and the distribution across different types of measures. The number of planned actions varies by domain and city size. Very large cities in Group XL and medium municipalities in Group M show a balanced distribution across mitigation, adaptation, and energy access, with each domain receiving similar attention. In contrast, Group L and Group S municipalities prioritise mitigation and adaptation, while energy access is addressed by significantly fewer actions, as depicted in Fig. 13a. This suggests that while larger and more urbanised municipalities adopt integrated approaches, other groups may lack the capacity or mandate to engage equally in energy access planning, or they could decide to prioritise and focus their intervention on mitigation and adaptation. Finally, concerning key type measures, the distribution of actions highlights clear differences across city sizes. Physical and technological measures dominate across all municipalities, with the highest number in Group XL municipalities (22) and the lowest in Group S (15). Governance and institutional, as well as knowledge and behavioural change actions, are also well represented—particularly in Group XL and Group M cities—indicating efforts to complement infrastructure with enabling frameworks and public engagement. Economic and financial measures, however, are notably limited, with few actions reported across all groups and none in the smallest municipalities of Group S, as illustrated in Fig. 13b. This suggests a potential gap in leveraging financial instruments to support climate and energy goals, particularly in resource-constrained contexts.

Fig. 13: Comparison of number of actions per pillar and per key type measures by municipality type and size.

Although the limited sample size constrains the scalability of the findings, this analysis serves as a preliminary exploration intended to provide initial insights. These findings can be further validated and expanded through future research based on a larger and more representative dataset.

Discussion

Urban climate action in Africa plays a critical role in addressing the continent’s vulnerabilities to climate change, fostering resilience, and driving low-carbon, sustainable development in rapidly growing cities2,3,8. This study provides the first systematic evidence of urban climate action in Sub-Saharan Africa (SSA) through the lens of the Covenant of Mayors (CoM) SSA initiative. The SEACAPs analysed highlight the potential for municipalities to lead in climate change mitigation, adaptation, and energy access, even in contexts of resource constraints and systemic vulnerabilities. These plans demonstrate promising approaches for integrating local sustainability actions contributing to achieving local goals aligned to broader national and international frameworks, such as the Paris Agreement and the Sustainable Development Goals (SDGs).

As pioneers within the CoM SSA initiative, these municipalities—through the development of their SEACAPs—have generated concrete examples of actions, data resources, methodologies, and practical insights, as reflected in the data analysed in this study. The relevance and quality of the analysis and information presented in these plans are consistent with the medium level of suitability found in similar plans examined in other studies16. These contributions offer valuable reference points for peer learning and capacity building and can serve as inspiration for other local governments in the region. This role is further supported by CoM SSA’s efforts to foster collaboration among cities, facilitating the exchange of knowledge and the uptake of locally tailored climate solutions39. City-to-city learning within climate networks has been recognised as a key mechanism for strengthening urban responses to climate change40. Moreover, participation in such networks enhances institutional capacity by encouraging local cooperation and inter-municipal collaboration—both essential for effective climate planning and governance41.

This study analyses and makes available the data reported by CoM SSA signatories following the GCoM Common Reporting Framework. In this way it contributes to start addressing the limited availability of data at the local level and indicates how municipalities can play a front-line role in producing data and local evidence. Moreover, the analysis reveals that municipalities in the region are interested in addressing climate change and are proactively adopting a multidimensional approach. This is evident from the completeness of the assessments across the three pillars, the ambitious targets set, as well as the actions which are distributed across all three thematic pillars of climate change mitigation, climate change adaptation and energy access, fostering an integrated focus.

In terms of assessment, the analysis of the Baseline Emission Inventories reported by the municipalities of the sample, highlights that the available data range between 2010 and 2021, a recent timeframe when compared to municipalities in other regions, such as Europe, having data for 2005 and back to 199042. This could be directly attributed to the timeline of the CoM SSA initiative’s implementation. Launched in 2015, the initiative enabled SSA cities to commence work on their climate action plans and collect informative data from 2018 onwards, with a time lag compared to cities in Europe which had a head start of about 10 years. Therefore, the methodological support provided by the CoM SSA initiative appears to have laid the foundation and driven the cities’ actions in developing and advancing their sustainability efforts.

Another significant finding from the analysis of the BEIs is that the GHG emissions in these municipalities are among the lowest in the world spanning from 0.062 tCO2eq/person to 2.512 tCO2eq/person. Signatories to the CoM in the EU, having a BEI in 2010 generated on average 4.3 t CO2eq per capita42. While Africa is one of the lowest contributors to greenhouse gas emissions, key sectors have already experienced losses and damages, and larger populations are vulnerable to climate hazards1. Therefore, it is not surprising that the RVAs of the assessed municipalities are duly developed identifying key hazards, impacted sectors and vulnerable groups. Energy access is also a key concern of local governments in the region. Signatories presented an adequate level of analysis for clean cooking and electricity access. It is also noteworthy that municipalities in Sub-Saharan Africa were among the first globally to respond to the Global Covenant of Mayors’ requirements on energy access and energy poverty. Although this pillar was only launched at the global level in 202243, cities in the region began engaging with it as early as 201944, following the establishment of the CoM SSA chapter in 201545. This demonstrates how the SEACAP process can proactively guide municipal action into emerging and previously underexplored areas of climate and energy policy.

Our comparison between the targets set by the local authorities across the pillars of mitigation, adaptation and energy access, with national commitments (NDCs) as well as international commitments (such as SDG7) aims to assess their interrelations and interdependencies.

This analysis shows that overall municipalities’ targets are mostly aligned to the national frameworks, i.e., the NDCs for climate change mitigation and adaptation, and with international goals, i.e., SDG7 for electricity and clean cooking, underscoring the potential contribution of the local level in addressing climate change globally and hence the importance of multi-level governance. However, the consideration of local specificities is also evident from this analysis. Most municipalities, have highly ambitious targets for GHG emissions reduction, often going beyond the objectives set in their countries’ NDCs. This level of ambition is common across both capital cities, primary and secondary cities, with no evidence that the type of city influences the level of ambition. A different finding emerges when looking at the commitments towards universal energy access, and particularly with regard to clean cooking. In this case, more than half municipalities set a lower target compared to the universal access, with Banguì and Yaoundé IV aiming at less than 50%. The limited level of ambition may be linked to the type of barriers municipalities face when implementing energy access measures, including challenges related to financing, data availability, local physical and human conditions, institutional capacity, policy frameworks, political leadership, and stakeholders’ engagement46. Another element to be considered is the limited powers that local governments tend to have when influencing urban energy assets and services46, as also emerged from the SEACAPs analysis when considering the role of national energy utilities in providing access to energy infrastructure. Overall, this indicates that for some municipalities significant efforts are needed to reach ambitious targets - such as those set in NDCs - and that progress strongly depend on their starting point and the specific local conditions within the territory.

The way these municipalities aim to achieve their goal is variegated, i.e., there are plans with more than hundred actions and others with a limited number, the types of actions planned also varies depending on numerous factors, such as resources, physical characteristics, planning processes, but the biggest share is covered by physical and technological actions. On average slightly more than one third of all actions included in SEACAPs focuses on mitigation, followed by the adaptation and energy access pillars. However, the SEACAPs report a high degree of integration among actions, with over 50% of actions impacting more than one pillar. This integrated approach underscores the municipalities’ recognition of the interconnected nature of urban sustainability challenges.

The analysis of the SEACAPs and the findings of this study consider that the CoM SSA initiative and methodology provides a model for guiding and scaling urban climate action across the region. Some key lessons learned include:

Active participation of municipalities: municipal size and administrative role are not key factors in determining active engagement; local authorities of all types—capital, primary, and secondary—have successfully completed SEACAPs and set targets with various degree of ambition, demonstrating the inclusive nature of the initiative.
Financing innovation: local authorities should put more focus on identifying existing funding sources and exploring diverse funding options, including an increased attention towards private sector funding and new instruments such as public-private partnerships or community-based crowdfunding, to address financial gaps.
Integrated approaches: expanding cross-sectoral integration in climate action planning can enhance effectiveness and sustainability.

At the same time, the analysis shows that several challenges hinder effective climate action that are consistent with previous studies, including:

Resource and capacity constraints: municipalities report difficulties in securing funding and technical expertise, which limit the scope and scale of their plans17,47.
Data gaps and reliability: limited access to local-level data affects the accuracy and consistency of assessments and target-setting, and there is a need for shared accounting methodologies, especially in new sectors such as energy access to improve data comparability48.
Governance and engagement: coordination across stakeholders remains a challenge, particularly in aligning local plans with national policies17,46,49.

Our analysis is aligned with findings from previous studies regarding the suitability of urban climate action plans16, the type of decarbonisation pathways13 as well as planning and implementation challenges faced by selected municipalities17. Our study advances the field by combining both quantitative and qualitative analysis across the three domains of mitigation, adaptation, and energy access—an approach that is currently lacking in the literature. This represents a concrete step forward in operationalising the nexus between energy access and climate resilience at the urban level.

The findings are based on a limited sample and rely on self-reported data; however, they can be already a reference for other municipalities who have started or intend to embark in a green and climate transition process. Over time, the sample could be expanded to include SEACAPs from nearly 400 COM SSA signatories, as they complete their action plan and report data. However, data availability and the possibility to analyse it will depend on each municipality’s SEACAP timeline. In addition, variability in the quality and completeness of SEACAPs—due to differences in technical capacity and resources—as well as the potential role of external consultants in drafting the plans, may limit comparability. Furthermore, being the first of its kind, the study does not include longitudinal data on implementation outcomes. This topic should be addressed in the future to better assess SEACAPs’ long-term impact and effectiveness. Expanding the sample, enhancing data quality, monitoring the implementation outcomes and examining the way funding is allocated for the implementation of the actions are key areas for future research.

Finally, the results of this study underscore that despite challenges, the local governments in SSA are paving the way providing valuable guidance for designing more impactful urban climate action strategies in the region. This study contributes to the growing literature on the climate challenges of local level of governance in Sub-Saharan Africa providing insights into how municipalities are concretely contributing to the global goals.

Methods

We assessed progresses and practices towards increased urban sustainability of local authorities in Sub-Saharan Africa, who are part of CoM SSA, a regional Covenant of the Global Covenant of Mayors (GCoM) initiative.

The backbone of GCoM methodology consists of the assessment of the initial condition (status), setting targets and planning actions and monitoring across the pillars of (1) climate change mitigation, (2) climate change adaptation and (3) energy access and poverty, framed in a set of standardised recommendations, yet flexible to accommodate regional needs (Common Reporting Framework35). By following this framework, the contents of the Sustainable Energy Access and Climate Action plans have a minimum common ground, and the data reported by cities are comparable. Building on this structure, our analysis follows the framework presented in Fig. 14 and is focused to a well-defined sample of municipalities.

To define the sample, we first considered the overall number of signatories in COM SSA, which at the end of 2024 accounted to 396 municipalities. From this sample, we then verified how many municipalities had either: (1) completed their SEACAP, (2) reported information through one of the official reporting platforms (the offline reporting tool, MyCovenant or the CDP-ICLEI Track). For this study, we only included municipalities reporting through the offline reporting tool, resulting in 14 municipalities with a completed SEACAP and four municipalities with data on the offline reporting template50. Finally, after a last data quality check, one municipality with only data in the offline reporting tool was discarded as the information reported was limited and not sufficient to carry out the planned analysis. This led to the final definition of the sample of 17 municipalities (14 municipalities having completed their SEACAP and having reported data through the offline reporting tool, three municipalities having only reported data through the offline reporting tool). Within the COM SSA, all cities reporting data through the offline reporting tool went through a “first-level” validation, a process checking the completeness and compliance of the data reported with the GCoM reporting requirements. In addition, municipalities that also complete the SEACAP undergo through a “second-level validation”, a thorough analysis of the plans to assess the robustness, the consistency between assessment, planning and monitoring phases and to evaluate whether the city’s proposed strategies are suitable for the established targets. This allowed an enhanced quality of data and deep assessment of the SEACAP development and context. On a final methodological note, while there are 14 municipalities with a completed SEACAP, the actual number of SEACAPs is 13, as the cities of Praia and Ribeira Grande de Santiago (Cabo Verde) decided to cooperate in their climate action and presented a joint action plan.

In our analysis, we delved into the SEACAPs and the data reported by municipalities and we mapped the alignments or gaps of the pillars’ ambition with the national or international established targets. We also looked at the planned actions disclosing the approaches municipalities selected to achieve the targets and evaluating potential synergies across measures and common pathways among signatories.

Data extracted from the SEACAPs and the reporting platform have been integrated into a dataset that serves as the foundation for this study. Additionally, NDCs data retrieved from the UNFCCC platform have been integrated. The dataset is organised in six main tables, summarised below, which are aligned with the methodology’s steps.

1. Data overview—the dataset includes municipalities’ geographical and demographic information, the type of submission (if only the completed reporting template or also the SEACAP document) and the pillars covered. CoM SSA signatories can develop their climate action strategies per pillar or comprehensively.
2. Climate change mitigation—the main source of this table is the GHG emissions inventory (BEI) and the established mitigation target declared by the signatories through their emission inventories from SEACAPs. For each entry of the sample, the dataset contains energy and related GHG emissions, covering the sectors of stationary energy (emissions from fuel combustion and use of grid-supplied energy by buildings, equipment and facilities within city boundary), transport (emissions from fuel combustion and use of grid-supplied energy for all modes of transportation activities within city boundary) and, non-energy related GHG emissions, covering the waste sector (non-energy related emissions from disposal and treatment of waste generated within the city boundary). The dataset includes the selected GHG emissions reduction target by 2030, the Business As Usual scenario (BAU) in 2030, the amount of GHG emissions in 2030 with SEACAP actions and per-capita emissions in inventory years and target year. The target data from countries’ NDCs on climate mitigation have been included for comparison.
3.1. Climate change adaptation—the main source of this table is the Risk and Vulnerability Assessment developed by each local government in its SEACAP. For each municipality, the dataset contains current climate hazards, with related probability of occurrence and impacts, impacted vulnerable sectors and related levels of vulnerability. The hazards are classified in main hazards and sub-hazards as per the CRF. As an example, the hazard “Flood and sea level rise” include the sub-hazards of: “Flash/surface flood”, “River flood”, “Coastal flood”, “Groundwater flood” and “Permanent inundation”. In their RVAs, municipalities can either identify only main hazards or provide details on sub-hazards. The levels of probability, impact and vulnerability range from “low”, “medium” and “high”, which in the dataset, have been translated into the numerical values of “1”, “2”, and “3”, corresponding respectively to low, medium and high. For each municipality only the hazards for which information was reported have been maintained. If a hazard was not deemed relevant by the municipality in its RVA, it does not appear in the table. When reported, the hazards and vulnerable sectors assessed in the RVAs are harmonised according to the CRF which provides a list of the main vulnerable sectors and groups. The countries’ NDCs on climate adaptation have been included for comparison.
For the sake of harmonisation, the CRF also provides a comprehensive list of vulnerable sectors and vulnerable groups from which local authorities could identify the suitable ones per each hazards.
3.2. Adaptation goals—the table contains the adaptation goals selected by the municipalities, as reported in their SEACAPs. When developing their climate adaptation strategies in the SEACAP, municipalities set their adaptation goals. Although quantitative adaptation goals could be better tracked during the SEACAP implementation phase, often municipalities define only qualitative goals. We, hence, classified the reported adaptation goals into “qualitative” and quantitative” adaptation goals and linked the corresponding impacted sectors or topic of the goal. When the set goal had a broad approach intended to reduce the whole vulnerability of the municipality, we assigned the topic “Resilience”.
4. Energy access—the main source of this table is the Energy Access Assessment as developed by local governments in their SEACAPs. For each entry of the sample, the dataset contains the electricity and clean cooking access baseline values, collected through the overall indicators for Electricity Access and Clean Cooking Access as per the CoM SSA methodology44 in place between 2018 and 2024. The targets set by local governments on increased access to electricity and clean cooking have been also included. Finally, for the sake of comparison, the table contains the values for universal energy access (set at 100% in alignment with SDG7) and data retrieved from “Tracking SDG 7” in 2022 on Urban Electricity Access at Country Level, Urban Electricity Access in SSA, Urban Clean Cooking Access at Country Level, Urban Clean Cooking Access in SSA22.
5. Actions—the main source of this table is the action’s fiches included in the SEACAPs. We translated in English the actions reported in French and classified the actions in four groups representing the Key Type of Measure (KTM): “Physical and Technological”, “Economic and Finance”, “Governance and Institutional”, “Knowledge and Behavioural Change”, where “Physical and technological” also includes nature based solutions and refers to new or upgrade of grey/green/blue infrastructures or technological options; “Economic and finance ”refer to financing related actions; “Governance and institutional” refer to policies aiming at institutional and governance changes and to the creation or review of policies and related instruments; and “Knowledge and behaviour change” refer to information, awareness raising and capacity building measures. The dataset contains all the actions reported by signatories, providing for each action its title in English, the relevance to climate mitigation, adaptation, and energy access, the indication of integration with other pillars, the KTM class and the investment cost, if available.

Building upon the described dataset, we first conducted basic statistics of the sample to overview contexts and characteristics of the selected municipalities. The second step of our methodology focused on the climate change mitigation pillar. Based on the emission inventories of signatories and the reported GHG emission reduction targets the GHG emissions reduction trends in absolute and per capita terms from the base year to the target year were estimated. In addition, for each signatory the target set in the SEACAP was compared to the NDCs of the country. We collected the emission reduction potential of each mitigation action as estimated in the SEACAPs, and we determined the contribution of mitigation measures towards the target.

Subsequently, we focused on the adaptation to climate change pillar. We mapped climate hazards reported by local governments alongside the impacted sectors, then compared these sectors to those identified in the NDCs to assess their relevance at the national level. Similarly to the steps adopted for the mitigation pillar, we collected the climate hazards and sectors targeted by the defined adaptation goals, as reported by local government in their SEACAPs, and highlighted alignments between local adaptation goals and the corresponding country’s NDC. As fourth step, the access to electricity and clean cooking baseline levels estimated by the city during the energy assessment phase were mapped and compared to data at country level in SSA. We then compared the related electricity and clean cooking access goals to the universal energy access as per SDG7 to highlight the existing gap.

Finally, we delved into the actions planned by municipalities and assessed which types of actions they rely on to achieve their targets. We also examined existing synergies across actions and the integration of the pillars in the developed strategies of municipalities to gain insights into the capacity and potentials of the plans to go beyond silos approaches and embrace climate action as a coordinated approach. We also analysed the amount spent per each type of action to highlight the type of funding source employed to finance the actions in the SEACAPs.

To analyse climate action trends and patterns, municipalities were classified according to their type (capital city, primary city, county, or secondary city) and population. Large municipalities—comprising capital cities, primary cities, and counties—were divided into two groups using a threshold of 1 million inhabitants. Small municipalities—consisting of secondary cities—were further divided into two categories: those with a population above 100,000 and those with fewer than 40,000 inhabitants. Based on this classification, the following groups were established:

Group XL—capital cities, primary cities and county with population above 1 M inhabitants: Dakar, Bangui, Abuja Municipal Council Area, Nakuru County, Maputo Metropolitan Area, Pikine;
Group L—primary cities with population below 1 M inhabitants: Yaoundé IV, Yaoundé III, Praia;
Group M—secondary cities with population above 100.000 inhabitants: Bouaké, Bobo Dioulasso, Garoua, Kloto;
Group S—secondary cities with population below 40.000 inhabitants: Fokoué, Doumé, Datcheka, Ribeira Grande de Santiago.

As a methodological note, for four cases, some inconsistency’s issues were detected between the action plan and the reported data through the reporting platform during the SEACAP second-level evaluation. Hence, the data reported through the offline reporting tool and included in the SEACAP full document were compared and assessed to understand the order of magnitude of the discrepancies and to select values that are plausibly correct for the present study. For three out of four cities, the correct inputs were the ones reported through the platform, while for the city of Dakar we considered the data included in the SEACAP47.

Data availability

The data supporting the findings of this study are available upon request from the corresponding author (M.P.).

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Climate action and energy access in Sub-Saharan Africa: insights from Covenant of Mayors signatories

Climate action and energy access in Sub-Saharan Africa: insights from Covenant of Mayors signatories

Results

Mitigation to climate change: assessment and ambition

Adaptation to climate change: assessment and ambition

Energy access: assessment and ambition

Overview of planned interventions

Climate action trends by municipality type and population

Discussion

Methods

Data availability

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Climate action and energy access in Sub-Saharan Africa: insights from Covenant of Mayors signatories

Climate action and energy access in Sub-Saharan Africa: insights from Covenant of Mayors signatories

Results

Mitigation to climate change: assessment and ambition

Adaptation to climate change: assessment and ambition

Energy access: assessment and ambition

Overview of planned interventions

Climate action trends by municipality type and population

Discussion

Methods

Data availability

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