Air quality related equity implications of U.S. decarbonization policy

Air pollution, particularly PM2.5, causes significant mortality in the US, disproportionately affecting racial/ethnic minorities and low-income populations. Policies aimed at reducing greenhouse gas (GHG) emissions often offer co-benefits in terms of improved air quality. However, the impact of these policies on existing air pollution disparities remains debated. This study addresses this gap by quantifying potential air pollution exposure reductions under various US federal carbon policies, specifically those aiming for 40-60% CO2 emission reductions by 2030 compared to 2005 levels. The study's significance lies in its assessment of whether such policies effectively contribute to reducing existing pollution disparities, a crucial aspect given the US government's commitment to directing a significant portion of federal investments towards disadvantaged communities. Previous research on air pollution equity impacts of climate policy has yielded mixed results, often focusing on retrospective analyses of specific policies or regions. This study provides a national-scale, economy-wide perspective, offering valuable insights into the potential trade-offs and limitations of CO2-based strategies for achieving both climate and equity goals.

Existing literature demonstrates the link between GHG emissions and PM2.5 formation, highlighting the potential health co-benefits of climate policies. However, studies on the equity implications of these policies present mixed findings. Some studies, primarily focused on California, have shown limited or mixed effects on equity outcomes, with some suggesting that policies might even exacerbate existing disparities. Other studies have considered future decarbonization scenarios, often at regional levels, producing varying results. This disparity in findings underscores the need for a comprehensive national-scale analysis examining the impact of various decarbonization scenarios on air pollution disparities across different racial/ethnic groups. The authors reference several studies that quantified the health benefits of climate and clean energy policies, showing that air pollution related health benefits often exceed the costs of policy implementation. The fact that local exposure is affected despite emission changes being independent of location, means the benefits are unevenly distributed. Studies show that communities near sources with lower abatement costs are expected to benefit most, with potential for increased emissions outside policy coverage (leakage).

This study employs a two-pronged approach. First, it utilizes energy-economic scenarios generated by an integrated energy-economic model (USREP-REEDS) to project energy sector activity and emissions under different carbon policies (40%, 50%, and 60% CO2 reductions by 2030 compared to 2005). These scenarios account for a range of technology cost assumptions and emissions allowance allocation schemes. Second, it uses a reduced-form air quality model (InMAP) to estimate PM2.5 concentrations and population exposures across the continental US, using the projected emissions data as input. InMAP provides a fine-scale spatial resolution, allowing for the assessment of exposure disparities across different racial/ethnic groups. The study leverages emission inventories from the EPA’s National Emission Inventory (NEI) 2017, incorporating both point and area sources, and allocating emissions spatially to grid cells using the NEI 2014 spatial modeling data. Emissions are scaled to 2030 based on USREP-REEDS projections, holding emission factors constant at 2017 levels. The researchers also incorporate spatial uncertainty in emissions reduction, generating sensitivity scenarios to assess the robustness of their results. The analysis uses population data from the 2012 American Community Survey, scaled to 2030 using state-level population growth rates, to assess the exposure disparities across racial and ethnic groups. Finally, optimization scenarios are developed to explore whether different distributions of CO2 emissions reductions can lead to better outcomes in terms of air pollution disparities. This involves minimizing PM2.5-associated mortality for racial/ethnic minorities, subject to constraints on overall CO2 reduction targets. The model uses marginal mortality values calculated from an existing concentration-response function and mortality incidence rates.

The primary policy case (50% CO2 reduction) shows that while average PM2.5 exposure decreases for all racial/ethnic groups relative to a baseline scenario without carbon policy, relative disparities mostly persist or even worsen for several minority groups. The greatest absolute reductions in PM2.5 exposure were observed for Black and white populations. The analysis reveals that reductions are primarily driven by decreased emissions in the electricity sector (77%), particularly from coal, followed by transportation, industry and residential sectors. The study demonstrates that the observed widening of disparities is not due to geographical distribution of emission reduction but rather the sources responsible for pollution. Coal powered electricity generation only disproportionately harms Black and white populations and contributes a small fraction to population exposure. Key disparities arise from sectors such as industry and heavy-duty diesel transportation where pollution is persistent even after 50% CO2 reduction. A sensitivity analysis considering the uncertainty in the spatial distribution of source reductions confirmed the robustness of these findings. Optimization scenarios, exploring alternative emissions reduction distributions while maintaining the same total CO2 reductions, show that minimizing racial/ethnic minority mortality can reduce PM2.5 exposure for all groups, but the reduction in disparity remains limited. Even in the most effective optimization scenario, disparities are only reduced marginally. The study also analyzed changes in disparities at the state and urban area levels, showing large regional variations in impacts. Increasing the carbon reduction target to 60% further reduces exposure, but the change in disparity relative to the baseline is smaller. Conversely, a less ambitious 40% reduction goal results in a larger change in disparity, but lower overall PM2.5 exposure benefits.

This study's findings challenge the assumption that solely focusing on CO2 reduction strategies will adequately address air pollution disparities. The results highlight the limitations of CO2-based policies in achieving significant reductions in exposure disparities, even when emissions are optimally distributed. While such policies reduce overall PM2.5 exposure, they often fail to effectively target the specific sources that disproportionately affect minority populations. The limited impact on disparities emphasizes the need for policy interventions that go beyond CO2 reduction, addressing sector-specific sources, particularly those associated with transportation and industrial emissions. The findings align with other research suggesting a complex interplay between climate policies, air quality benefits, and pollution inequities, demonstrating that strategies maximizing overall air quality benefits do not always minimize pollution disparities. The authors suggest that the observed results may be because the tension between employing large scale policies for air pollutants and efforts to reduce pollution disparities for disadvantaged communities who are affected by various pollutants. This study provides important insights for policymakers in designing effective interventions to simultaneously tackle climate change and address environmental injustices.

This study demonstrates that CO2 reduction policies alone, even with optimal emissions distribution, are insufficient to substantially reduce existing air pollution exposure disparities among racial/ethnic groups in the US. Achieving meaningful equity goals will require additional targeted interventions, such as sector-specific policies and community-focused mitigation measures that directly address sources of pollution disproportionately impacting minorities. Future research could explore the effectiveness of such targeted interventions, integrating them within broader climate policy frameworks to achieve more equitable outcomes. More aggressive carbon reduction policies, though having potentially larger effects eventually, will take a long time to implement, leaving disparities unaddressed for more than a decade.

The study relies on a reduced-complexity air quality model (InMAP), which may not fully capture the complex atmospheric chemistry and transport processes influencing PM2.5 concentrations. The use of fixed 2017 emission factors for non-CO2 pollutants may also introduce some uncertainties. The analysis focuses on a specific set of carbon policies and does not explore all potential policy instruments or combinations. Further, the study primarily focuses on PM2.5 exposure and does not directly assess other health outcomes related to air pollution, such as morbidity.