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Residential wood combustion (RWC) is a primary heating fuel in just 2% of US homes. However, the 2023 release of the US Environmental Protection Agency’s National Emissions Inventory (NEI) found that RWC contributes ~28% of total wintertime fine particulate matter (PM_2.5) emissions, suggesting that ambient PM_2.5concentrations could be substantially reduced if RWC were curtailed. Despite its contribution to PM_2.5emissions, an assessment of the air quality, health, and distributional impacts of RWC using the updated NEI has not been performed. Here, we use a high-resolution (4 kilometers) air quality model and the updated NEI to evaluate wintertime RWC impacts over the contiguous United States. We find that RWC contributes 2.43 micrograms per cubic meter (21.9%) of winter population-weighted mean PM_2.5concentrations, leading to ~8600 (confidence interval: 6500 to 9600) premature deaths annually. Moreover, nonwhite communities are disproportionately affected by RWC-related PM_2.5and associated mortality, especially in urban areas. We suggest that policies targeting RWC could substantially reduce air pollution, improve health, and address distributional disparities. 

Abstract As wildfires increase in frequency and intensity, accurately representing the vertical distribution of smoke in numerical models is critical for assessing impacts to air quality, but remains highly uncertain. In this study, we leverage satellite retrievals of total column carbon monoxide (CO) and aerosol layer height (ALH) to evaluate two state-of-the-art regionals and global models, one using a plume rise parameterization to estimate smoke injection height (RAP-Chem) and another placing smoke at the surface (MOMO-Chem). We introduce a novel metric that utilizes the differing vertical sensitivities of two satellite sensors observing CO (TROPOMI and CrIS) to infer the vertical distribution of wildfire smoke using a joint CO column ratio. We find that RAP-Chem better captures the distribution of CO and ALH related to the 2020 western US megafire event than MOMO-Chem. However, RAP-Chem underestimates surface CO concentrations, revealing that current plume rise parameterizations are limited in their ability to partition smoke correctly in the vertical column. These results show that synergistic use of satellite data can provide additional constraints on the vertical distribution of smoke, thus providing insights into the strengths and limitations of current plume rise parameterizations and a pathway to improvement. 

Abstract Electric vehicle adoption strategies have the potential to reduce greenhouse gas and air pollutant emissions. However, the effectiveness of this transition may depend on which vehicles are electrified, and where. To assess the efficacy of different modes of transportation electrification, we apply a watts-to-wheel analysis framework that accounts for upstream emission increases from battery charging and downstream reductions in tailpipe emissions. Using the WRF-CMAQ chemical transport model at ∼1 km²resolution, we compare the greenhouse gas, air quality, and public health impacts of electrifying 30% of light-duty vehicles (eLDVs) versus 30% of heavy-duty vehicles (eHDVs) across a U.S. Midwestern domain. Both electrification scenarios achieve net reductions in CO₂emissions despite increased emissions from electricity generation units, with greater total reductions from eLDVs (∼7 Mt CO₂/year, −4.5%) than eHDVs (∼1.6 Mt CO₂/year, −1.1%). However, air quality benefits are greater in the eHDV scenario, where cumulative reductions in health-harming air pollutants such as nitrogen dioxide (NO₂) and elemental carbon (EC) exceed those in the eLDV scenario. Both scenarios show modest increases in daily 8 h average ozone (MDA8 O₃), with disbenefits largest in the eHDV scenario. Estimated health benefits of the eHDV scenario exceed those of the eLDV scenario, with 70 (50) more avoided premature deaths annually from reduced NO₂(EC), offset by 50 additional deaths from MDA8 O₃increases. In both scenarios, the largest health benefits occur in communities with higher proportions of Black and Hispanic residents. However, long-standing relative exposure disparities persist. On a per-vehicle basis, we find that electrifying one HDV yields nearly 5× more CO₂reduction-based economic benefits and 23× more NO₂reduction-based economic health benefits than a single eLDV. Our results demonstrate that multi-modal and multi-pollutant assessments are critical for informing more effective and equitable decarbonization and air pollutant remediation strategies. 

Abstract Heavy-duty vehicles (HDVs) disproportionately contribute to the creation of air pollutants and emission of greenhouse gases—with marginalized populations unequally burdened by the impacts of each. Shifting to non-emitting technologies, such as electric HDVs (eHDVs), is underway; however, the associated air quality and health implications have not been resolved at equity-relevant scales. Here we use a neighbourhood-scale (~1 km) air quality model to evaluate air pollution, public health and equity implications of a 30% transition of predominantly diesel HDVs to eHDVs over the region surrounding North America’s largest freight hub, Chicago, IL. We find decreases in nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) concentrations but ozone (O₃) increases, particularly in urban settings. Over our simulation domain NO₂and PM_2.5reductions translate to ~590 (95% confidence interval (CI) 150–900) and ~70 (95% CI 20–110) avoided premature deaths per year, respectively, while O₃increases add ~50 (95% CI 30–110) deaths per year. The largest pollutant and health benefits simulated are within communities with higher proportions of Black and Hispanic/Latino residents, highlighting the potential for eHDVs to reduce disproportionate and unjust air pollution and associated air-pollution attributable health burdens within historically marginalized populations. 

Abstract Electric vehicles (EVs) constitute just a fraction of the current U.S. transportation fleet; however, EV market share is surging. EV adoption reduces on-road transportation greenhouse gas emissions by decoupling transportation services from petroleum, but impacts on air quality and public health depend on the nature and location of vehicle usage and electricity generation. Here, we use a regulatory-grade chemical transport model and a vehicle-to-electricity generation unit electricity assignment algorithm to characterize neighborhood-scale (∼1 km) air quality and public health benefits and tradeoffs associated with a multi-modal EV transition. We focus on a Chicago-centric regional domain wherein 30% of the on-road transportation fleet is instantaneously electrified and changes in on-road, refueling, and power plant emissions are considered. We find decreases in annual population-weighted domain mean NO₂(−11.83%) and PM_2.5(−2.46%) with concentration reductions of up to −5.1 ppb and −0.98µg m⁻³in urban cores. Conversely, annual population-weighted domain mean maximum daily 8 h average ozone (MDA8O₃) concentrations increase +0.64%, with notable intra-urban changes of up to +2.3 ppb. Despite mixed pollutant concentration outcomes, we find overall positive public health outcomes, largely driven by NO₂concentration reductions that result in outsized mortality rate reductions for people of color, particularly for the Black populations within our domain. 

Wildfires and meteorological conditions influence the co-occurrence of multiple harmful air pollutants including fine particulate matter (PM 2.5 ) and ground-level ozone. We examine the spatiotemporal characteristics of PM 2.5 /ozone co-occurrences and associated population exposure in the western United States (US). The frequency, spatial extent, and temporal persistence of extreme PM 2.5 /ozone co-occurrences have increased significantly between 2001 and 2020, increasing annual population exposure to multiple harmful air pollutants by ~25 million person-days/year. Using a clustering methodology to characterize daily weather patterns, we identify significant increases in atmospheric ridging patterns conducive to widespread PM 2.5 /ozone co-occurrences and population exposure. We further link the spatial extent of co-occurrence to the extent of extreme heat and wildfires. Our results suggest an increasing potential for co-occurring air pollution episodes in the western US with continued climate change.