Public health costs accounting of inorganic PM2.5 pollution in metropolitan areas of the United States using a risk-based source-receptor model

Quantifying the air quality impact of ship emissions in China's Bohai Bay

Bohai Bay, as a significant economic bay area in China, has experienced considerable ecological consequences during its rapid economic development. One of the major environmental challenges is the emission of air pollutants from ships, which has had a severe impact on regional air quality and the health of residents. To assess the influence of pollutants on the air quality around the Bohai Bay area, a Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model was established using a 9 km × 9 km high-resolution ship emission gridded inventory from 2018. The WRF-CMAQ model was employed to compare two scenarios: vessel emissions and non-vessel emissions, in order to evaluate the impact of ship emissions. By analyzing the pollutant concentrations in Bohai Bay and the degree of change in pollutant concentration in six cities under these two scenarios, significant differences were observed. Furthermore, a comparison of the hourly concentration contributions of ship emissions between port cities and inland cities within the same region revealed that inland cities were less affected by ship emissions. The main contributing factors to this disparity were identified as wind direction and wind speed.

EASIUR-HR: A Model To Evaluate Exposure Inequality Caused by Ground-Level Sources of Primary Fine Particulate Matter

People of color disproportionately bear the health impacts of air pollution, making air quality a critical environmental justice issue. However, quantitative analysis of the disproportionate impacts of emissions is rarely done due to a lack of suitable models. Our work develops a high-resolution reduced-complexity model (EASIUR-HR) to evaluate the disproportionate impacts of ground-level primary PM_2.5 emissions. Our approach combines a Gaussian plume model for near-source impacts of primary PM_2.5 with a previously developed reduced-complexity model, EASIUR, to predict primary PM_2.5 concentrations at a spatial resolution of 300 m across the contiguous United States. We find that low-resolution models underpredict important local spatial variation of air pollution exposure to primary PM_2.5 emissions, potentially underestimating the contribution of these emissions to national inequality in PM_2.5 exposure by more than a factor of 2. We apply EASIUR-HR to analyze the impacts of vehicle electrification on exposure disparities. While such a policy has small aggregate air quality impacts nationally, it reduces exposure disparity for race/ethnic minorities. Our high-resolution RCM for primary PM_2.5 emissions (EASIUR-HR) is a new, publicly available tool to assess inequality in air pollution exposure across the United States.

Inequitable Exposures to U.S. Coal Power Plant-Related PM2.5: 22 Years and Counting

BACKGROUND

Emissions from coal power plants have decreased over recent decades due to regulations and economics affecting costs of providing electricity generated by coal vis-à-vis its alternatives. These changes have improved regional air quality, but questions remain about whether benefits have accrued equitably across population groups.

OBJECTIVES

We aimed to quantify nationwide long-term changes in exposure to particulate matter (PM) with an aerodynamic diameter ≤2.5μm (PM2.5) associated with coal power plant SO2 emissions. We linked exposure reductions with three specific actions taken at individual power plants: scrubber installations, reduced operations, and retirements. We assessed how emissions changes in different locations have influenced exposure inequities, extending previous source-specific environmental justice analyses by accounting for location-specific differences in racial/ethnic population distributions.

METHODS

We developed a data set of annual PM2.5 source impacts ("coal PM2.5") associated with SO2 emissions at each of 1,237 U.S. coal-fired power plants across 1999-2020. We linked population-weighted exposure with information about each coal unit's operational and emissions-control status. We calculate changes in both relative and absolute exposure differences across demographic groups.

RESULTS

Nationwide population-weighted coal PM2.5 declined from 1.96μg/m3 in 1999 to 0.06 μg/m3 in 2020. Between 2007 and 2010, most of the exposure reduction is attributable to SO2 scrubber installations, and after 2010 most of the decrease is attributable to retirements. Black populations in the South and North Central United States and Native American populations in the western United States were inequitably exposed early in the study period. Although inequities decreased with falling emissions, facilities in states across the North Central United States continue to inequitably expose Black populations, and Native populations are inequitably exposed to emissions from facilities in the West.

DISCUSSION

We show that air quality controls, operational adjustments, and retirements since 1999 led to reduced exposure to coal power plant related PM2.5. Reduced exposure improved equity overall, but some populations continue to be inequitably exposed to PM2.5 associated with facilities in the North Central and western United States. https://doi.org/10.1289/EHP11605.

Air pollution disparities and equality assessments of US national decarbonization strategies

Energy transitions and decarbonization require rapid changes to a nation's electricity generation mix. There are many feasible decarbonization pathways for the electricity sector, yet there is vast uncertainty about how these pathways will advance or derail the nation's energy equality goals. We present a framework for investigating how decarbonization pathways, driven by a least-cost paradigm, will impact air pollution inequality across vulnerable groups (e.g., low-income, minorities) in the US. We find that if no decarbonization policies are implemented, Black and high-poverty communities may be burdened with 0.19-0.22 μg/m³ higher PM_2.5 concentrations than the national average during the energy transition. National mandates requiring more than 80% deployment of renewable or low-carbon technologies achieve equality of air pollution concentrations across all demographic groups. Thus, if least-cost optimization capacity expansion models remain the dominant decision-making paradigm, strict low-carbon or renewable energy technology mandates will have the greatest likelihood of achieving national distributional energy equality. Decarbonization is essential to achieving climate goals, but myopic decarbonization policies that ignore co-pollutants may leave Black and high-poverty communities up to 26-34% higher PM_2.5 exposure than national averages over the energy transition.

Sources of ambient PM2.5 exposure in 96 global cities

To improve air quality, knowledge of the sources and locations of air pollutant emissions is critical. However, for many global cities, no previous estimates exist of how much exposure to fine particulate matter (PM_2.5), the largest environmental cause of mortality, is caused by emissions within the city vs. outside its boundaries. We use the Intervention Model for Air Pollution (InMAP) global-through-urban reduced complexity air quality model with a high-resolution, global inventory of pollutant emissions to quantify the contribution of emissions by source type and location for 96 global cities. Among these cities, we find that the fraction of PM_2.5 exposure caused by within-city emissions varies widely (μ = 37%; σ = 22%) and is not well-explained by surrounding population density. The list of most-important sources also varies by city. Compared to a more mechanistically detailed model, InMAP predicts urban measured concentrations with lower bias and error but also lower correlation. Predictive accuracy in urban areas is not particularly high with either model, suggesting an opportunity for improving global urban air emission inventories. We expect the results herein can be useful as a screening tool for policy options and, in the absence of available resources for further analysis, to inform policy action to improve public health.

Optimizing Solar-Plus-Storage Deployment on Public Buildings for Climate, Health, Resilience, and Energy Bill Benefits

Climate change, public health, and resilience to power outages are of critical concern to local governments and are increasingly motivating investments in on-site solar and storage. However, designing a solar-plus-storage system to co-optimize for climate, health, resilience, and energy bill benefits requires complex trade-offs that are not captured in current analyses. To fill this gap, we integrate the climate and health impacts of grid-purchased electricity into the REopt Lite optimization model using forward-looking marginal emissions costs. Using this new model, we quantify the impact of including energy bill, climate, health, and/or power outage cost savings on the optimal sizing, battery dispatch, and economic returns of solar-plus-storage on three public building types (a hospital, school, and warehouse) across 14 U.S. cities. We find that monetizing and co-optimizing for climate and health benefits, as compared to only energy bill savings and resilience, increases the net present value of the solar-plus-storage systems by $200k to $5.2M and makes larger systems financially attractive. Our results illustrate significant differences across geographies and building types, highlighting the need for site-specific analyses and associated policies regarding the costs and benefits of solar-plus-storage.

Comparisons of simple and complex methods for quantifying exposure to individual point source air pollution emissions

Expanded use of reduced complexity approaches in epidemiology and environmental justice investigations motivates detailed evaluation of these modeling approaches. Chemical transport models (CTMs) remain the most complete representation of atmospheric processes but are limited in applications that require large numbers of runs, such as those that evaluate individual impacts from large numbers of sources. This limitation motivates comparisons between modern CTM-derived techniques and intentionally simpler alternatives. We model population-weighted PM_2.5 source impacts from each of greater than 1100 coal power plants operating in the United States in 2006 and 2011 using three approaches: (1) adjoint PM_2.5 sensitivities calculated by the GEOS-Chem CTM; (2) a wind field-based Lagrangian model called HyADS; and (3) a simple calculation based on emissions and inverse source-receptor distance. Annual individual power plants' nationwide population-weighted PM_2.5 source impacts calculated by HyADS and the inverse distance approach have normalized mean errors between 20 and 28% and root mean square error ranges between 0.0003 and 0.0005 µg m^-3 compared with adjoint sensitivities. Reduced complexity approaches are most similar to the GEOS-Chem adjoint sensitivities nearby and downwind of sources, with degrading performance farther from and upwind of sources particularly when wind fields are not accounted for.

Particulate matter exposure at a densely populated urban traffic intersection and crosswalk

Exposure to elevated particulate matter (PM) pollution is of great concern to both the general public and air quality management agencies. At urban traffic intersections, for example, pedestrians are often at a higher risk of exposure to near-source PM pollution from traffic while waiting on the roadside or while walking in the crosswalk. This study offers an in-depth investigation of pedestrian exposure to PM pollution at an urban traffic intersection. Fixed-site measurements near an urban intersection were conducted to examine the variations in particles of various sizes through traffic signal cycles. This process aids in the identification of major PM dispersion patterns on the roadside. In addition, mobile measurements of pedestrian exposure to PM were conducted across six time intervals that correspond to different segments of a pedestrian's journey when passing through the intersection. Measurement results are used to estimate and compare the cumulative deposited doses of PM by size categories and journey segments for pedestrians at an intersection. Furthermore, comparisons of pedestrian exposure to PM on a sunny day and a cloudy day were analyzed. The results indicate the importance of reducing PM pollution at intersections and provide policymakers with a foundation for possible measures to reduce pedestrian PM exposure at urban traffic intersections.

Multipollutant impacts to U.S. receptors of regional on-road freight in Ontario, Canada

On-road freight is a significant source of air pollutant and greenhouse gas emissions. The resulting economic damages can cross borders through processes of atmospheric fate and transport, regardless of whether that freight serves local or regional demand. Understanding patterns of freight demand and atmospheric processes can thus inform inter-jurisdictional efforts to mitigate multipollutant damages. We quantify how different freight trips across 49 census divisions in the Province of Ontario, Canada create an economic burden on downwind US receptors. We apply an integrated modeling approach combining a travel demand model, a mobile emissions simulator, and marginal damages from emissions. Economic damages include the increased risk of premature death from PM_2.5 related to primary PM_2.5 (represented by damages from inert primary PM_2.5), NO_X, SO₂, and NH₃, and the global effects of climate change from greenhouse gases (CO₂, CH₄, N₂O). Over 90% of the $1.4 billion (2010USD) in transboundary air pollutant damages at US receptors result from regional freight demand across Ontario in 2012. A single major freight corridor, the ON-401 expressway, contributes more than half of all damages. Most of these damages impact the states situated to the south and east of the province. Mean estimates of annual damages range from millions to tens of millions (2010USD) across major eastern metropolitan areas including New York, Boston, Philadelphia, and D.C. Most of these damages result from NO_X, which constitutes 95% of inorganic PM_2.5-related pollutant emissions by mass. Thus, targeting NOx from freight movements along the ON-401 expressway could avoid millions to tens of millions of damages annually in eastern US cities. These results indicate that local green freight policies may be unable to address the environmental burden at cross-border receptors. Cooperation is needed among local, provincial, and federal governments to encourage policies targeting the most harmful emissions along routes servicing regional freight demands. Implications: On-road freight movement in Ontario can yield billions of dollars in annual economic damages to US residents through its effects on air pollution and climate change. We use an integrated modeling approach combining an on-road freight travel demand, mobile emissions, and marginal damages of emissions to quantify and study these economic damages. Regional freight contributes approximately 90% of damages, with one major freight corridor, the ON-401 expressway, contributing 59%. Most damages derive from emissions of NOx and amount to millions to tens of millions of dollars in annual damages across major Eastern US cities. Thus, targeting NOx from freight movements along the ON-401 expressway could avoid millions of damages annually in eastern US cities.

Simulating the impacts of ship emissions on coastal air quality: Importance of a high-resolution emission inventory relative to cruise- and land-based observations

This work studied the impacts of ship emissions at a high temporal resolution on the real-time concentrations of PM_2.5, NO₂, and SO₂ in urban harbors and coastal sea areas, taking the Yangtze River Delta (YRD) as an example. The WRF-Chem model with 3 nested grids and ship emissions derived from an automatic identification system (AIS) were combined to simulate the air quality. The AIS data showed significant temporal fluctuations in ship emissions, with hourly mean fluxes of approximately 1082.41 ± 444.41 and 593.55 ± 404.95 g/h/km² near ports and in the channel waters of the YRD, respectively. The monthly mean contributions of shipping emissions reached 80.72% (2.15 ppbv) and 81.79% (8.79 ppbv) to ambient SO₂ and NO₂ in Ningbo Port, and 10.61% (6.96 μg/m³) to PM_2.5 in Shanghai Port, respectively, regions with dense ship traffic. The relative differences in the PM_2.5, SO₂, and NO₂ concentrations modeled using monthly and hourly ship emissions accounted for -10-15%, -10-30%, and - 5-30%, respectively. Compared with cruise- and land-based measurements, the simulations using hourly emissions were in much better agreement with the observations than those using monthly emissions and appropriately captured some air pollutant concentration peaks. Simulations during shipping-related periods with hourly ship emissions improved the normalized mean bias (NMBs) from -43.03%, 301.49%, and 223.02% to -27.28%, 90.45%, and 167.52%, respectively, for PM_2.5, SO₂, and NO₂, highlighting the importance of using ship emissions with a fine temporal resolution. Our study showed that ignoring hourly fluctuations in ship emissions during air quality modeling leads to considerable uncertainties, especially in coastal urban areas and harbors with high ship activities. These results imply that data with a high temporal resolution, such as hourly ship emissions, are necessary to understand the realistic impacts of shipping traffic and to implement more precise control policies to improve coastal air quality.

Fine particulate matter damages and value added in the US economy

Emissions of most pollutants that result in fine particulate matter (PM_2.5) formation have been decreasing in the United States. However, this trend has not been uniform across all sectors or regions of the economy. We use integrated assessment models (IAMs) to compute marginal damages for PM_2.5-related emissions for each county in the contiguous United States and match location-specific emissions with these marginal damages to compute economy-wide gross external damage (GED) due to premature mortality. We note 4 key findings: First, economy-wide, GED has decreased by more than 20% from 2008 to 2014. Second, while much of the air pollution policies have focused to date on the electricity sector, damages from farms are now larger than those from utilities. Indeed, farms have become the largest contributor to air pollution damages from PM_2.5-related emissions. Third, 4 sectors, comprising less than 20% of the national gross domestic product (GDP), are responsible for ∼75% of GED attributable to economic activities. Fourth, uncertainty in GED estimates tends to be high for sectors with predominantly ground-level emissions because these emissions are usually estimated and not measured. These findings suggest that policymakers should target further emissions reductions from such sectors, particularly in transportation and agriculture.

The air quality and health impacts of projected long-haul truck and rail freight transportation in the United States in 2050

Diesel emissions from freight transportation activities are a key threat to public health. This study examined the air quality and public health impacts of projected freight-related emissions in 2050 over the continental United States. Three emission scenarios were considered: (1) a projected business-as-usual socioeconomic growth with freight fleet turnover and stringent emission control (CTR); (2) the application of a carbon pricing climate policy (PO); and (3) further technology improvements to eliminate high-emitting conditions in the truck fleet (NS). The PO and NS cases are superimposed on the CTR case. Using a WRF-SMOKE-CMAQ-BenMAP modeling framework, we quantified the impacts of diesel fine particulate matter (PM_2.5) emissions change on air quality, health, and economic benefits. In the CTR case, we simulate a widespread reduction of PM_2.5 concentrations, between 0.5 and 1.5 μg m^-3, comparing to a base year of 2011. This translates into health benefits of 3600 (95% CI: 2400-4800) prevented premature deaths, corresponding to $38 (95% CI: $3.5-$100) billion. Compared to CTR case, the PO case can obtain ~9% more health benefits nationally, however, climate policy also affects the health outcomes regionally due to transition of demand from truck to rail; regions with fewer trucks could gain in health benefits, while regions with added rail freight may potentially experience a loss in health benefits due to air quality degradation. The NS case provides substantial additional benefits (~20%). These results support that a combination of continuous adoption of stringent emission standards and strong improvements in vehicle technology are necessary, as well as rewarding, to meet the sustainable freight and community health goals. States and metropolitan areas with high population density and usually high freight demand and emissions can take more immediate actions, such as accelerating vehicle technology improvements and removing high-emitting trucks, to improve air quality and health benefits.

The impact of ship emissions on PM2.5 and the deposition of nitrogen and sulfur in Yangtze River Delta, China

Ship emissions contribute significantly to the deterioration of air quality, while their impacts on ambient PM_2.5 and depositions have not been comprehensively evaluated. This is especially true for China because it has a long coastline, busy shipping routes and many large ports. To fill this gap, this study applied the SMOKE/WRF/CMAQ modeling system to quantifying the impacts of ships on PM_2.5 compositions, annual and seasonal contribution to PM_2.5 as well as the wet and dry deposition of nitrogen and sulfur compounds over the land areas in YRD region for 2014. The results showed that 4.0% of annual PM_2.5 concentrations over the land areas could be explained by ship emissions and the largest contribution could reach up to 35.0% in port areas. Temporally, the contribution to PM_2.5 exhibited an obviously seasonal variation. The highest contribution was predicted in autumn (6.2%), followed by summer (5.4%), spring (3.6%) and winter (1.2%) for the land areas. Spatially, the contribution reached up to 13.6% along the coastline and dropped to 2.1% 300 km inland. As for the impacts on PM_2.5 components, the primary components were relatively small and increased mainly along the shipping routes and the Yangtze River, whereas the secondary components played a more important role in both water and land areas. The sulfur deposition due to ship emissions was occurred generally along the shipping routes and was dominated by the dry SO₂ deposition. The nitrogen depositions, on the contrary, was observed not only along the shipping routes but also extend to wide land areas. Further investigation revealed that ship emissions have caused an evident increase of dry nitrogen deposition in NO₂ and HNO₃, while a slight decrease in NH₃ over YRD region. These results indicated that comprehensive regulations of ship emissions are required considering their adverse effects on the ambient concentration of PM_2.5 and the deposition of sulfur and nitrogen.

On-road emissions of ammonia: An underappreciated source of atmospheric nitrogen deposition

We provide updated spatial distribution and inventory data for on-road NH₃ emissions for the continental United States (U.S.) On-road NH₃ emissions were determined from on-road CO₂ emissions data and empirical NH₃:CO₂ vehicle emissions ratios. Emissions of NH₃ from on-road sources in urbanized regions are typically 0.1-1.3tkm^-2yr^-1 while NH₃ emissions in agricultural regions generally range from 0.4-5.5tkm^-2yr^-1, with a few hotspots as high as 5.5-11.2tkm^-2yr^-1. Counties with higher vehicle NH₃ emissions than from agriculture include 40% of the U.S.

POPULATION

The amount of wet inorganic N deposition as NH₄⁺ from the National Atmospheric Deposition Program (NADP) network ranged from 37 to 83% with a mean of 58.7%. Only 4% of the NADP sites across the U.S. had <45% of the N deposition as NH₄⁺ based on data from 2014 to 2016, illustrating the near-universal elevated proportions of NH₄⁺ in deposition across the U.S. Case studies of on-road NH₃ emissions in relation to N deposition include four urban sites in Oregon and Washington where the average NH₄-N:NO₃-N ratio in bulk deposition was 2.3. At urban sites in the greater Los Angeles Basin, bulk deposition of NH₄-N and NO₃-N were equivalent, while NH₄-N:NO₃-N in throughfall under shrubs ranged from 0.6 to 1.7. The NH₄-N:NO₃-N ratio at 7-10 sites in the Lake Tahoe Basin averaged 1.4 and 1.6 in bulk deposition and throughfall, and deposition of NH₄-N was strongly correlated with summertime NH₃ concentrations. On-road emissions of NH₃ should not be ignored as an important source of atmospheric NH₃, as a major contributor to particulate air pollution, and as a driver of N deposition in urban and urban-affected regions.