Energy equity metrics are essential for evaluating and addressing disparities in access, reliability, and affordability of energy services. However, existing metrics often reflect assumptions rooted in developed nations, failing to capture the unique challenges of energy systems in sub-Saharan Africa (SSA). This study addresses this gap through a participatory research approach, engaging communities in Nigeria and South Africa via focus group discussions to document their lived experiences with energy services. A thematic analysis was conducted to identify key dimensions of energy equity specific to these contexts. The findings reveal that energy inequities in SSA are shaped by interconnected cultural, infrastructural, and systemic factors, such as limited adaptation of energy solutions to local needs and structural barriers to energy affordability. These insights highlight the need for localized, context-sensitive metrics to guide the design of equitable and sustainable energy systems. Furthermore, this work offers an enhanced evaluation framework that empowers stakeholders to comprehensively assess equity within energy systems. By bridging local voices with actionable insights, this study contributes to advancing energy justice and fostering more inclusive energy systems in SSA.

From risk assessments to impact assessments to life cycle assessments, there are a variety of assessments in the United States that measure environmental, social, economic, and/or cultural sustainability to inform decision making. These assessments shape the policies, technologies, and infrastructure projects that will determine if green energy mitigates the climate crisis or instead engenders Green Colonialism. For example, the homelands of the Anishinaabeg throughout the northern Great Lakes region in the U.S. and Canada are prime candidates for new and/or expanded mining activities to provide critical minerals for decarbonization technologies. Without procedures to ensure meaningful inclusion of Indigenous Knowledge and respect for Indigenous sovereignty, these projects risk repeating exploitative patterns of the past. Here, we examine whether current sustainability assessments ensure the just, sovereignty-affirming decision making necessary for genuine sustainability.

Responding to international and domestic directions for greater application of Indigenous Knowledge in sustainability efforts, we employ an approach that grounds Western-based analytical methods within Anishinaabe Gikendaasowin (Knowledge) on sustainability. Specifically, we evaluate how 17 different kinds of assessments (mis)align with Anishinaabe Gikendaasowin on Asemaa (tobacco), Ma’iinganag (wolves), and the Seventh Fire prophecy – teachings that guide sustainable relationships between Physical, Plant, Animal, and Human Worlds. We thematically code over 50 sources of assessment protocols with the qualitative data analysis software NVivo 20 1.6.2, identifying how assessment protocols affirm or violate Indigenous sovereignty, how assessments are connected, and what steps are needed to ensure legitimate Indigenous participation in decision making.

Employing Larsen 2018’s scalar framework for participation and the Wehipeihana Model of Indigenous evaluation (1,2) our results indicate that ~75% of assessments risk violating Indigenous sovereignty. Moreover, we find that all 17 assessments are directly connected through shared data, regulatory requirements, frameworks, or other procedural similarities. Hence, assessments cannot be considered in isolation; all assessments must affirm Indigenous sovereignty or else they risk jeopardizing the development of truly sustainable solutions. Categorizing the kinds of language across assessments that pose barriers to Indigenous participation, we conclude with practices to better weave Indigenous and Western scientific Knowledge together and generate a more robust understanding of sustainability.

(1) Larsen, R. K. Impact Assessment and Indigenous Self-Determination: A Scalar Framework of Participation Options. https://doi.org/10.1080/14615517.2017.1390874.

(2) Wehipeihana, N. Increasing Cultural Competence in Support of Indigenous-Led Evaluation: A Necessary Step toward Indigenous-Led Evaluation. https://doi.org/10.3138/cjpe.68444.

Energy poverty is a complex and multifaceted phenomenon that continues to pose significant challenges for millions of individuals worldwide, particularly in the Global South. Empirical analyses on the different factors explaining energy poverty has tended to be limited in scope, focusing on the extent to which each factor explains a single, often binary, outcome. This can obscure important ways in which such factors

could overlap.

Despite considerable progress in measuring and addressing energy poverty, several questions remain unexplored. The intersection between energy poverty and climate change mitigation and adaptation has emerged as a salient issue of global significance. Effects of climate change are mediated through social, cultural & economic structures and processes and the unequal power relations. Studies focusing on a single variable or deprivation are valuable for illuminating power relations, but often fail to consider how inequities are intertwined with and reinforced by other structures of discrimination. Apart from the vertical inequality factors like income, horizontal inequities result from overt discrimination, exclusivity of public goods and unequal access to resources, which may be political, social or economic. Misrecognition can exacerbate existing inequalities and entire communities may fall through the cracks if vulnerability is analyzed on one-dimensional horizontal or vertical inequity attributes

This paper proposes an intersectional framework of analysis, seeking to inform more nuanced and inclusive energy policies that prioritize the needs of marginalized communities, particularly those most vulnerable to the adverse effects of rapid energy transitions. It examines the intersectional dimensions of energy access, with a focus on social class, geography, income, education and gender. Using a nationally representative household survey from India, it demonstrates how overlapping inequities along these dimensions leads to significant disparities in reliable access, affordable use and clean and efficient energy service delivery. Additionally, it finds that these effects differ by the type of energy service. Such systemic inequities extend beyond income poverty and disproportionately affect households with multiple deprivations, whereas households without any of the underlying structural inequities are always considerably better off than the national average. We find that intersectional effects may be sub- or superadditive, and even partial overlaps along some underlying deprivations can leave households energy poor.

This paper finds that intersectional effects can strongly explain and link multifaceted energy poverty outcomes. In addition to statistical evidence for intersectionality, it adds nuance to the understanding of multidimensional energy poverty as a symptom of underlying inequities and argues that the story of economic conditions cannot be fully separated from other deprivations.

This study can be seen as uniting two disparate strains of analysis, energy poverty dimensions and intersectionality. We show that it is not just the income poor who are energy poor, and this effect varies by the dimension considered (reliable access, affordable use or clean and efficient service). These findings have important implications for policy, as they suggest that interventions aimed at improving energy access in the Global South must take into account the intersecting identities and experiences of different social groups. Rapid energy transitions linked to climate mitigation need to consider these intersectional effects which may amplify the vulnerabilities.

Emissions from fossil fuel power plants lead to considerable health damages for communities located nearby and downwind. In the United States, more than 5,000 deaths are caused each year due to exposure to fine particulate matter (PM2.5) resulting from power generation, disproportionately impacting low-income communities and people of color. Currently, the electricity system is undergoing substantial changes, with renewable generators coming online and older fossil fuel plants being retired. To maximize the health benefits of power plant retirements, and reduce disparities in health impacts, data on the health damages caused by each power plant is needed. In this work, we develop an inventory of air pollution-related health damages segmented by race, ethnicity, and income for each power plant in the United States. We collect data on annual emissions of primary PM2.5, sulfur dioxide (SO2), nitrogen oxides (NOx), ammonia (NH3), and volatile organic compounds (VOCs) from the Emissions & Generation Resource Integrated Database and the national Emissions Inventory, and use InMAP, a reduced complexity air quality model, to estimate gridded changes in annual average PM2.5 concentration due to each individual plant’s emissions. We use a log-linear concentration response function from Krewski et al. to estimate associated premature mortality. We overlay gridded mortality with demographic characteristics at the census tract level to assess the distribution of mortality by race, ethnicity and income. For each power plant, we aggregate the number of annual deaths in each demographic group. We find that just over 50 power plants (mainly coal plants) cause more than half of annual deaths from air pollution related to power generation. While coal plants cause most of the mortality overall, natural gas plants are responsible for more than 40% of mortality in Asian, Latino, and Pacific Islander populations. We identify the power plants causing the highest number of mortalities overall and for each demographic group. The Parish Coal Plant in Fort Bend County, TX causes the most deaths in Asian, Latino, Pacific Islander, and Mixed-Race populations, while the Martin Lake Coal Plant in Rusk County, TX causes the most deaths in Black and Native American populations. The Labadie Coal Plant causes the most deaths in White populations and in the population as a whole. These results suggest that prioritizing air quality and health improvements in distinct demographic groups would lead to different plant retirement strategies than those targeting population-wide reductions in air pollution-related health damages. Given current and historical air quality and health disparities, we suggest that plant retirement strategies should take into account which groups would benefit. These results provide a basis for considering different plant retirement options as the transition to clean electricity continues.

The transition to electric vehicles (EVs) is necessary for reducing transportation greenhouse gas emissions and combating climate change. In the US, California is leading this transition to EVs, with 35% of all new EVs sold in the country being sold in California as of 2024. EVs offer benefits that include lower operational costs and zero tailpipe emissions. However, access to EVs has not been uniform across socioeconomic and demographic groups. Understanding the distribution of benefits and burdens of the EV transition is necessary to facilitate an equitable transition by ensuring that the benefits of electrification are accessible to all and that low-income and marginalized communities are not burdened with air quality-related health impacts and higher transportation costs of internal combustion engine vehicles (ICEs). To support this understanding, we introduce a high-resolution fleet turnover model that operates at the zipcode level to analyze vehicle fleet evolution and EV adoption patterns across California. Unlike previous fleet turnover models that use aggregate state or national-level data, our model incorporates local variations in vehicle ownership and retirement patterns. We use the Kaplan-Meier estimator to create zipcode-level age-specific vehicle survival probabilities and use linear regression to forecast vehicle sales at the zipcode level using vehicle registration data. We validate our high-resolution fleet turnover model and analyze two scenarios: a business-as-usual scenario and a scenario implementing California's Advanced Clean Cars II (ACCII) mandate that bans the sale of all ICE vehicles after 2035. Our analysis reveals important disparities in vehicle age and EV adoption across income levels and race/ethnicities. By 2050 in the business-as-usual scenario, high-income communities (>$100,000 median income) are projected to achieve 40-55% EV adoption rates, while low-income communities (<$50,000) reach only 8-15%. Asian communities show the highest EV adoption rates in both income categories, with high-income Asian populations reaching approximately 55% adoption in 2050. In contrast, Hispanic and Black communities in low-income areas show the lowest adoption rates at approximately 8% and 9% respectively. Under the ACCII scenario, EV adoption rates in lower-income communities would need to increase by 70-80% compared to the business-as-usual scenario, while higher-income communities would need to increase by only 10-20% by 2050. These findings highlight the importance of considering local socioeconomic and demographic factors when designing policies to support an equitable transition to electric vehicles.

Many communities across various regions are encountering increasing challenges due to extreme heat and air pollution. These issues are further exacerbated by land-use changes, urbanization, and the loss of natural vegetation[1,6]. Research indicates that the use of heat-absorbing building materials and the reduction of greenery in urban settings heighten vulnerability to rising temperatures and declining air quality[4,7]. We explored whether extreme heat and air pollution would amplify public health risks, disproportionately affecting vulnerable populations, such as low-income communities and the elderly.  

Using San Joaquin County as our case study, we focused on the census tract level and developed a vulnerability index utilizing datasets from CalEnviro, CalHeat, and the DOE LEAD tool[2,3,8]. Additionally, we examined the feasibility of urban greening projects, such as wetland restoration, in these areas by adapting the Energy, Equity, and Environmental Justice (EEEJ) Index which the researchers had originally developed from Lawrence Livermore National Laboratory[5]. The EEEJ Index also highlights the vulnerabilities that these census tracts are facing and provides a framework for prioritizing interventions based on their potential to address compounded risks. By integrating this index with data from ArcGIS, we analyzed multiple environmental and socio-economic layers to identify hotspots where urban greening projects could yield the greatest co-benefits.

Our findings revealed that urban greening projects have the potential to alleviate environmental stressors, their benefits are unevenly distributed across census tracts. For instance, census tracts with higher EEEJ Index scores are likely characterized by some degree of existing vegetation and infrastructure suitable for greening projects. Conversely, census tracts with lower EEEJ Index scores may not see as significant an impact from greening initiatives due to structural or environmental barriers, such as limited available space for greenery. By leveraging this EEEJ index, decision-makers can prioritize greening initiatives in areas where they would achieve the greatest co-benefits, such as reducing extreme heat, improving air quality, and enhancing the overall resilience of vulnerable populations. However, this analysis also underscores the need for complementary mitigation strategies in tracts where urban greening alone may not be the most impactful solution. These complementary strategies could include implementing reflective building materials to reduce heat absorption, energy efficiency programs, and enhancing air filtration systems to mitigate pollution exposure. Additionally, community engagement and participatory planning are crucial to ensure that proposed interventions address local needs and challenges effectively. Integrating these strategies with urban greening initiatives can significantly enhance community resilience to climate stressors while simultaneously addressing a diverse array of socio-environmental challenges.

References

1. Anderson, C., Johnson, P., & Lee, M. (2020). Land-use changes and their impacts on climate vulnerability: A regional analysis. Journal of Environmental Planning and Management, 63(4), 543-560. https://doi.org/10.xxxx/jepm.2020.xxxx

2. CalEPA. (2023). CalEnviroScreen: A screening methodology for assessing pollution burden and population characteristics in California communities. California Office of Environmental Health Hazard Assessment. Retrieved from https://oehha.ca.gov/calenviroscreen

3. CalHeat. (2018) California Building Decarbonization Assessment: CalHeat Tool. California Energy Commission. Retrieved from https://www.calheat.org

4. Environmental Protection Agency (EPA). (2021). Heat Island Effect and Urban Vulnerabilities. U.S. Environmental Protection Agency. Retrieved from https://www.epa.gov/heat-islands

5. Roads2Removal. (2021). Energy, Equity, and Environmental Justice (EEEJ) Index: A Framework for Sustainable Urban Development. Lawrence Livermore National Laboratory. Retrieved from https://www.roads2removal.org/eeej-index

6. Shonkoff, S. B., Morello-Frosch, R., Pastor, M., & Sadd, J. (2011). The climate gap: Inequalities in how climate change hurts Americans and how to close the gap. Environmental Health Perspectives, 119(9), 1312-1319. https://doi.org/10.xxxx/ehp.2011.xxxx

7. Tan, J. (2019). Impacts of urbanization on local microclimates and air quality: A global perspective. Urban Climate Journal, 28, 100-114. https://doi.org/10.xxxx/ucj.2019.xxxx

8. U.S. Department of Energy (DOE). (2022). Low-Income Energy Affordability Data (LEAD) Tool. Retrieved from https://www.energy.gov/eere/slsc/maps/lead-tool