Public Health Costs of Primary PM2.5 and Inorganic PM2.5 Precursor Emissions in the United States

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

Introduction

Many decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NOx), and sulfur dioxide (SO2), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution.

Methods

To address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities.

Results

Version 1.0 of LOCAETA displays the estimated primary PM2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics.

Discussion

LOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

Mapping the spatial distribution of primary and secondary PM2.5 in a multi-industrial city by combining monitoring and modeling results

Industrial cities are strongly influenced by primary emissions of PM2.5 from local industries. In addition, gaseous precursors, such as sulfur oxides (SOX), nitrogen oxides (NOX), and volatile organic compounds (VOCs), emitted from industrial sources, undergo conversion into secondary inorganic and organic aerosols (SIAs and SOAs). In this study, the spatial distributions of primary and secondary PM2.5 in Ulsan, the largest industrial city in South Korea, were visualized. PM2.5 components (ions, carbons, and metals) and PM2.5 precursors (SO2, NO2, NH3, and VOCs) were measured to estimate the concentrations of secondary inorganic ions (SO42-, NO3-, and NH4+) and secondary organic aerosol formation potential (SOAFP). The spatial distributions of SIAs and SOAs were then plotted by combining atmospheric dispersion modeling, receptor modeling, and monitoring data. Spatial distribution maps of primary and secondary PM2.5 provide fundamental insights for formulating management policies in different districts of Ulsan. For instance, among the five districts in Ulsan, Nam-gu exhibited the highest levels of primary PM2.5 and secondary nitrate. Consequently, controlling both PM2.5 and NO2 emissions becomes essential in this district. The methodology developed in this study successfully identified areas with dominant contributions from both primary emissions and secondary formation. This approach can be further applied to prioritize control measures during periods of elevated PM levels in other industrial cities.

Data Gap: Air Quality Networks Miss Air Pollution from Concentrated Animal Feeding Operations

In the U.S., the agricultural sector is the largest controllable source of several air pollutants, including ammonia (NH3), which is a key precursor to PM2.5 formation. Livestock waste is the dominant contributor to ammonia emissions. In contrast to most controllable air pollutants, satellite records show ammonia mixing ratios are rising. The number of confined animal feeding operations (CAFOs) that generate considerable livestock waste is also increasing. Spatial and temporal trends in USDA-reported animal numbers normalized by county area at medium and large CAFOs provide plausible explanations for patterns in satellite-derived NH3 over the contiguous U.S. (CONUS). The correlation between summertime ammonia derived from the European Space Agency's (ESA) Infrared Atmospheric Sounding Interferometer (IASI) and CAFO animal unit density in 2017 is positive and significant (r = 0.642; p ≈ 0). The temporal changes from 2002 to 2017 in animal unit density and NH3 derived from NASA's Atmospheric Infrared Sounder (AIRS) are spatially similar. Trends and ambient concentrations of PM2.5 mass in agricultural regions are difficult to assess relative to those of urban population centers given the sparseness of rural monitors in regulatory surface networks. Results suggest that in agricultural areas where ammonia concentrations and animal density are highest, air quality improvement lags behind the national average.

Source-Receptor Relationships Between Precursor Emissions and O3 and PM2.5 Air Pollution Impacts

Reduced complexity tools that provide a representation of both primarily emitted particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5), secondarily formed PM2.5, and ozone (O3) allow for a quick assessment of many iterations of pollution control scenarios. Here, a new reduced complexity tool, Pattern Constructed Air Pollution Surfaces (PCAPS), that estimates annual average PM2.5 and seasonal average maximum daily average 8 h (MDA8) O3 for any source location in the United States is described and evaluated. Typically, reduced complexity tools are not evaluated for skill in predicting change in air pollution by comparison with more sophisticated modeling systems. Here, PCAPS was compared against multiple types of emission control scenarios predicted with state-of-the-science photochemical grid models to provide confidence that the model is realistically capturing the change in air pollution due to changing emissions. PCAPS was also applied with all anthropogenic emissions sources for multiple retrospective years to predict PM2.5 chemical components for comparison against routine surface measurements. PCAPS predicted similar magnitudes and regional variations in spatial gradients of measured chemical components of PM2.5. Model performance for capturing ambient measurements was consistent with other reduced complexity tools. PCAPS also did well at capturing the magnitude and spatial features of changes predicted by photochemical transport models for multiple emissions scenarios for both O3 and PM2.5. PCAPS is a flexible tool that provides source-receptor relationships using patterns of air quality gradients from a training data set of generic modeled sources to create interpolated air pollution gradients for new locations not part of the training database. The flexibility provided for both sources and receptors makes this tool ideal for integration into larger frameworks that provide emissions changes and need estimates of air quality to inform downstream analytics, which often includes an estimate of monetized health effects.

Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition

Estimating health benefits of reducing fossil fuel use from improved air quality provides important rationales for carbon emissions abatement. Simulating pollution concentration is a crucial step of the estimation, but traditional approaches often rely on complicated chemical transport models that require extensive expertise and computational resources. In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. Applications of the framework with Chinese data reveal highly heterogeneous health benefits of avoiding premature mortality by reducing fossil fuel use in different sectors and regions in China with a mean of $19/tCO2 and a standard deviation of $38/tCO2. Reducing rural and residential coal use offers the highest co-benefits with a mean of $151/tCO2. Our findings prompt careful policy designs to maximize cost-effectiveness in the transition toward a carbon-neutral energy system.

Polluting under the Radar: Emissions, Inequality, and Concrete Batch Plants in Houston

Small industrial sources collectively release large amounts of pollution, including particulate matter (PM) that contributes to air quality problems in the United States and elsewhere. We study one such type of industrial facility, concrete batch plants, and analyze PM emissions and siting patterns of 131 plants located in Harris County, Texas. We find that concrete batch plants in Harris County are collectively a major pollution source, contributing between 38 and 111 tons of primary PM2.5 emissions (between 26%-76% of PM2.5 from the median Texas oil refinery) and between 109 and 493 tons of primary PM10 emissions (between 64%-290% of PM10 from the median refinery). Estimates from an integrated assessment model suggest that health damages from the PM2.5 emissions alone amount to $29 million annually, reflecting two additional premature deaths per year. We further find that concrete batch plants in Harris County are disproportionately located in census tracts with more low-income, Hispanic, and Black populations, thereby raising important environmental justice questions. On the basis of these findings, we argue that small pollution sources require more air quality monitoring and emissions reporting and that regulatory agencies should consider cumulative environmental and health impacts of these sources as part of the permitting process.

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.

Associations between long-term fine particulate matter exposure and hospital procedures in heart failure patients

BACKGROUND

Ambient fine particulate matter (PM2.5) contributes to global morbidity and mortality. One way to understand the health effects of PM2.5 is by examining its impact on performed hospital procedures, particularly among those with existing chronic disease. However, such studies are rare. Here, we investigated the associations between annual average PM2.5 and hospital procedures among individuals with heart failure.

METHODS

Using electronic health records from the University of North Carolina Healthcare System, we created a retrospective cohort of 15,979 heart failure patients who had at least one of 53 common (frequency > 10%) procedures. We used daily modeled PM2.5 at 1x1 km resolution to estimate the annual average PM2.5 at the time of heart failure diagnosis. We used quasi-Poisson models to estimate associations between PM2.5 and the number of performed hospital procedures over the follow-up period (12/31/2016 or date of death) while adjusting for age at heart failure diagnosis, race, sex, year of visit, and socioeconomic status.

RESULTS

A 1 μg/m3 increase in annual average PM2.5 was associated with increased glycosylated hemoglobin tests (10.8%; 95% confidence interval = 6.56%, 15.1%), prothrombin time tests (15.8%; 95% confidence interval = 9.07%, 22.9%), and stress tests (6.84%; 95% confidence interval = 3.65%, 10.1%). Results were stable under multiple sensitivity analyses.

CONCLUSIONS

These results suggest that long-term PM2.5 exposure is associated with an increased need for diagnostic testing on heart failure patients. Overall, these associations give a unique lens into patient morbidity and potential drivers of healthcare costs linked to PM2.5 exposure.

Communities of color are disproportionately exposed to long-term and short-term PM2.5 in metropolitan America

We conducted a novel investigation of neighborhood-level racial/ethnic exposure disparities employing measures aligned with long-term and short-term PM_2.5 air pollution benchmarks across metropolitan contexts of the contiguous United States, 2012-2016. We used multivariable generalized estimating equations (GEE) to quantify PM_2.5 exposure disparities based on the census tract composition of people of color (POC) and POC groups (Hispanic/Latina/x/o, Black, Asian). We examined eight census tract-level measures of longer-to-shorter term exposures derived from data on modeled daily ambient PM_2.5 concentrations. We found associations between increased POC composition and greater exposure to all PM_2.5 measures, with associations strengthening across measures of longer-to-shorter term exposures. In a GEE with a negative binomial distribution, a standard deviation increase in POC composition predicted a 0.6% increase (incidence rate ratio (IRR): 1.006, 95% confidence interval (CI): 1.005-1.008) in the number of days PM_2.5 concentrations were ≥5 μg/m³ (longest-term benchmark). In a GEE with an inverse Gaussian distribution, a standard deviation increase in POC composition predicted a 0.110 μg/m³ (1.0%) increase (B: 0.110, 95% CI: 0.076-0.143) in mean PM_2.5 concentration. In GEEs with a negative binomial distribution, the effect of a standard deviation increase in POC composition on exposure strengthened to 2.6% (IRR:1.026, 95% CI:1.017-1.035), 3.4% (IRR:1.034, 95% CI:1.022-1.047), 4.2% (IRR:1.042, 95% CI:1.025-1.058), 16.2% (IRR:1.162, 95% CI:1.117-1.210), 22.7% (IRR:1.227, 95% CI:1.137-1.325) and 28.3% (IRR:1.283, 95% CI:1.144-1.439) with respect to the number of days PM_2.5 concentrations were ≥10, 12, 15, 25, 35 and 55.5 μg/m³. POC group models indicated exposure disparities based on greater Hispanic/Latina/x/o, Asian, and Black composition. Evidence for stronger POC associations with shorter-term (higher concentration) PM_2.5 exceedances suggests that reducing PM_2.5 would attenuate racial/ethnic exposure disparities.

Life Cycle Greenhouse Gas Emissions of the USPS Next-Generation Delivery Vehicle Fleet

The United States Postal Service (USPS) plans to purchase 165,000 next-generation delivery vehicles (NGDVs) between 2023 and 2032. The USPS submitted an environmental impact statement (EIS) for two NGDV procurement scenarios: (1) 90% internal combustion engine vehicles (ICEVs) and 10% battery electric vehicles (BEVs) ("ICEV scenario") and (2) 100% BEVs ("BEV scenario"). To correct several significant deficiencies in the EIS, we conduct a cradle-to-grave life cycle greenhouse gas (GHG) assessment of these two scenarios. Our analysis improves upon the USPS's EIS by including vehicle production and end-of-life emissions, future grid decarbonization, and more accurate vehicle operating emissions. In our base case, we find that the ICEV and BEV scenarios would result in 15% greater and 8% fewer GHG emissions, respectively, than the USPS estimate. Favorable vehicle and grid development would result in 63% lower BEV scenario emissions than the USPS estimate. Consequently, we calculate a cumulative lifetime emission reduction of 57-82% (14.7-21.4 Mt CO₂e) from procuring 100% BEVs instead of 10% BEVs, compared to the USPS's estimate of 10.3 Mt. Given the long NGDV lifetimes, committing to the ICEV scenario squanders an ideal use case for BEVs, jeopardizes meeting our climate goals, and forgoes potential climate and environmental justice co-benefits.

Diverse Pathways for Power Sector Decarbonization in Texas Yield Health Cobenefits but Fail to Alleviate Air Pollution Exposure Inequities

Decarbonizing power systems is a critical component of climate change mitigation, which can have public health cobenefits by reducing air pollution. Many studies have examined strategies to decarbonize power grids and quantified their health cobenefits. However, few of them focus on near-term cobenefits at community levels, while comparing various decarbonization pathways. Here, we use a coupled power system and air quality modeling framework to quantify the costs and benefits of decarbonizing the Texas power grid through a carbon tax; replacing coal with natural gas, solar, or wind; and internalizing human health impacts into operations. Our results show that all decarbonization pathways can result in major reductions in CO₂ emissions and public health impacts from power sector emissions, leading to large net benefits when considering the costs to implement these strategies. Operational changes with existing infrastructure can serve as a transitional strategy during the process of replacing coal with renewable energy, which offers the largest benefits. However, we also find that Black and lower-income populations receive disproportionately higher air pollution damages and that none of the examined decarbonization strategies mitigate this disparity. These findings suggest that additional interventions are necessary to mitigate environmental inequity while decarbonizing power grids.

Integrated Modeling of U.S. Agricultural Soil Emissions of Reactive Nitrogen and Associated Impacts on Air Pollution, Health, and Climate

Agricultural soils are leading sources of reactive nitrogen (Nr) species including nitrogen oxides (NO_x), ammonia (NH₃), and nitrous oxide (N₂O). The propensity of NO_x and NH₃ to generate ozone and fine particulate matter and associated impacts on health are highly variable, whereas the climate impacts of long-lived N₂O are independent of emission timing and location. However, these impacts have rarely been compared on a spatially resolved monetized basis. In this study, we update the nitrogen scheme in an agroecosystem model to simulate the Nr emissions from fertilized soils across the contiguous United States. We then apply a reduced-form air pollution health effect model to assess air quality impacts from NO_x and NH₃ and a social cost of N₂O to assess the climate impacts. Assuming an $8.2 million value of a statistical life and a $13,100/ton social cost of N₂O, the air quality impacts are a factor of ∼7 to 15 times as large as the climate impacts in heavily populated coastal regions, whereas the ratios are closer to 2.5 in sparsely populated regions. Our results show that air pollution, health, and climate should be considered jointly in future assessments of how farming practices affect Nr emissions.

Sensitivity of Air Pollution Exposure and Disease Burden to Emission Changes in China Using Machine Learning Emulation

Machine learning models can emulate chemical transport models, reducing computational costs and enabling more experimentation. We developed emulators to predict annual-mean fine particulate matter (PM_2.5) and ozone (O₃) concentrations and their associated chronic health impacts from changes in five major emission sectors (residential, industrial, land transport, agriculture, and power generation) in China. The emulators predicted 99.9% of the variance in PM_2.5 and O₃ concentrations. We used these emulators to estimate how emission reductions can attain air quality targets. In 2015, we estimate that PM_2.5 exposure was 47.4 μg m^-3 and O₃ exposure was 43.8 ppb, associated with 2,189,700 (95% uncertainty interval, 95UI: 1,948,000-2,427,300) premature deaths per year, primarily from PM_2.5 exposure (98%). PM_2.5 exposure and the associated disease burden were most sensitive to industry and residential emissions. We explore the sensitivity of exposure and health to different combinations of emission reductions. The National Air Quality Target (35 μg m^-3) for PM_2.5 concentrations can be attained nationally with emission reductions of 72% in industrial, 57% in residential, 36% in land transport, 35% in agricultural, and 33% in power generation emissions. We show that complete removal of emissions from these five sectors does not enable the attainment of the WHO Annual Guideline (5 μg m^-3) due to remaining air pollution from other sources. Our work provides the first assessment of how air pollution exposure and disease burden in China varies as emissions change across these five sectors and highlights the value of emulators in air quality research.

Evaluating PM2.5 -Related health costs in China-Evidence from 140 Chinese cities

INTRODUCTION

In recent years, China's economy has grown rapidly, and the health condition of Chinese residents has significantly improved. However, this rapid economic and social development has also brought a series of environmental problems, such as serious haze pollution, of which the main contents are PM_2.5 particles. The objective of this study is to quantitatively estimate the PM_2.5 -related health costs in China.

METHODS

Based on city-level data from 140 major Chinese cities as well as the Beijing-Tianjin-Hebei, Yangtze River Delta, and Pearl River Delta city clusters in 2010, the value of a statistical life method based on willingness to pay was employed. Moreover, global and local Moran's I values were calculated to examine the spatial distribution of the health cost of haze pollution in China.

RESULTS

In areas with heavy haze pollution or a high level of economic development, residents' health costs will also be higher. In addition, there is a spatial aggregation phenomenon in the spatial distribution of health costs in China, which is mainly in the form of "high-high" aggregation, with high-value cities converging with other high-value cities.

CONCLUSIONS

The health cost of haze pollution in China is very considerable, and there are regional differences.

Spatiotemporal variations of air pollutants based on ground observation and emission sources over 19 Chinese urban agglomerations during 2015-2019

The "comparative attitude" of urban agglomerations involves multidimensional perspectives such as infrastructure, ecological protection, and air pollution. Based on monitoring station data, comparative studies of multispatial, multitimescale and multiemission pollution sources of air quality on 19 urban agglomerations during the 13th Five-Year Plan period in China were explored by mathematical statistics. The comparison results are all visualized and show that clean air days gradually increased and occurred mainly in summer, especially in South and Southwest China. PM_2.5, PM₁₀ and O₃ were still the main primary pollutants. PM_2.5 is mainly concentrated in December, January and February, and PM₁₀ is mainly concentrated in October–November and March–April. The O₃ pollution in the Pearl River Delta and Beibu Gulf urban agglomerations located in the south is mainly concentrated from August to November, which is different from others from May to September. Second, from 2015 to 2019, the increasing rate of O₃ concentration in any hour is higher than that of particulate matter (PM). Diurnal trends in O₃ concentration in all directions also showed a single peak, with the largest increments that appeared between 13:00 and 16:00, while the spatial distribution of this peak was significantly regional, earlier in the east but later in the west. Third, this analysis indicated that the annual average air quality index (AQI) showed a gradually decreasing trend outward, taking the Central Plain urban agglomeration as the center. The ambient air pollutants are gradually moving southward and mainly concentrated in the Central Plains urban agglomeration from 2015 to 2019. Furthermore, in each urban agglomeration, the cumulative emission of PM_2.5 is consisted of the four average emissions, which is approximately 2.5 times of that of PM_10, and industries are the main sources of PM_2.5, PM₁₀ and VOCs (volatile organic compounds). VOCs and NO_X increased in half of the urban agglomerations, which are the reasons for the increase in ozone pollution. The outcomes of this study will provide targeted insights on pollution prevention in urban agglomerations in the future.

Black Carbon Emissions and Associated Health Impacts of Gas Flaring in the United States

Gas flaring from oil and gas fields is a significant source of black carbon (BC) emissions, a component of particulate matter that damages health and warms the climate. Observations from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite instrument indicate that approximately 17.2 billion cubic meters (bcm) of gas was flared from upstream oil and gas operations in the United States in 2019. Based on an emissions factor equation that accounts for the higher heating value of the gas, that corresponded to nearly 16,000 tons of BC emitted, though estimates vary widely across published emissions factors. In this study, we used three reduced-form air quality and health effect models to estimate the health impacts from the flaring-emitted BC particulate matter in the United States. The three models—EASIUR, AP3, and InMAP—predict 26, 48, and 53 premature deaths, respectively, in 2019. The mortality range expands from 5 to 360 deaths annually if alternative emission factors are used. This study shows that reduced-form models can be useful to estimate the impacts of numerous dispersed emissions sources such as flares, and that further research is needed to better quantify BC emissions factors from flares.

Ultrafine Particles Emitted through Routine Operation of a Hairdryer

Particulate matter is a large concern for human health. Fine and ultrafine particulate matter has been shown to negatively impact human health; for example, it causes cardiopulmonary diseases. Current regulation targets the size of the particles, but composition also impacts toxicity. Indoor sources of air pollution pose unique challenges for human health due to the potential for human exposure to high concentrations in confined spaces. In this work, six hairdryers were each operated within a plexiglass chamber, and their emissions were analyzed with transmission electron microscopy and energy-dispersive spectroscopy. All hairdryers were found to emit ultrafine iron, carbon, and copper. In addition, emissions from two hairdryers primarily contained silver nanoparticles in the ultrafine range (<100 nm). The ultrafine particle emission rates for the hairdryers that did not contain silver were measured and found to be lower than ultrafine particle emissions by gas stoves and electric burners. Based on their size, these particles can either remain in the lung or enter the bloodstream after inhalation and potentially cause long-term health effects.

Health and Climate Impacts from Long-Haul Truck Electrification

Long-haul truck electrification has attracted nascent policy support, but the potential health and climate impacts remain uncertain. Here, we developed an integrated assessment approach with high spatial-temporal (km and hourly) resolution to characterize the causal chain from truck operation to charging loads, electricity grid response, changes in emissions and atmospheric concentrations, and the resulting health and climate impacts across the United States. Compared to future diesel trucks, electrified trucking's net health benefits are concentrated only along the West Coast with a business-as-usual electricity grid. However, with an 80%-renewable electricity grid, most regions would experience net health benefits, and the economic value of avoided climate and health damages exceeds $5 billion annually, an 80% reduction relative to future diesel trucks. Electric trucks with larger batteries may increase health and climate impacts due to additional trips needed to compensate for the payload penalty, but a 2× improvement in the battery specific energy (to ∼320 Wh/kg) could eliminate the additional trips.

Assessing the emission sources and reduction potential of atmospheric ammonia at an urban site in Northeast China

Atmospheric ammonium and ammonia have brought negative environmental impacts and adverse health effects. However, ammonia emissions are generally less regulated worldwide. This study analyzed ammonium pollution character, quantified the dominant ammonia emission sources, and assessed ammonia reduction potential in urban Harbin (China). The results showed that ammonium recorded low concentration in the non-heating season (1.34 ± 1.57 μg/m³), and recorded sharply increased concentration (6.50 ± 7.02 μg/m³) and relative abundance in the heating season. It was closely correlated with vehicle-related pollutants (CO) in non-heating season, while with biomass burning-related pollutants (K⁺, Cl^-) in the heating season. Bayesian Mixing Model emphasized the increasing contribution of biomass burning and decreasing contribution of fertilizer as the pollution levels escalate. The results from the thermodynamic equilibrium model showed that a 50%-60% ammonium decrease could bring marketable decrements of the aerosol pH, aerosol water content, ammonium nitrate concentration, and inorganic ion mass. The results of this study would provide scientific bases for ammonia emission reduction and haze pollution control in urban Harbin.

Technoeconomic analysis for biofuels and bioproducts

Technoeconomic analysis (TEA) is an approach for conducting process design and simulation, informed by empirical data, to estimate capital costs, operating costs, mass balances, and energy balances for a commercial scale biorefinery. TEA serves as a useful method to screen potential research priorities, identify cost bottlenecks at the earliest stages of research, and provide the mass and energy data needed to conduct life-cycle environmental assessments. Recent studies have produced new tools and methods to enable faster iteration on potential designs, more robust uncertainty analysis, and greater accessibility through the use of open-source platforms. There is also a trend toward more expansive system boundaries to incorporate the impact of policy incentives, use-phase performance differences, and potential impacts on global market supply.

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.

Health and climate benefits of Electric Vehicle Deployment in the Greater Toronto and Hamilton Area

This study presents the results of an integrated model developed to evaluate the environmental and health impacts of Electric Vehicle (EV) deployment in a large metropolitan area. The model combines a high-resolution chemical transport model with an emission inventory established with detailed transportation and power plant information, as well as a framework to characterize and monetize the health impacts. Our study is set in the Greater Toronto and Hamilton Area (GTHA) in Canada with bounding scenarios for 25% and 100% EV penetration rates. Our results indicate that even with the worst-case assumptions for EV electricity supply (100% natural gas), vehicle electrification can deliver substantial health benefits in the GTHA, equivalent to reductions of about 50 and 260 premature deaths per year for 25% and 100% EV penetration, compared to the base case scenario. If EVs are charged with renewable energy sources only, then electrifying all passenger vehicles can prevent 330 premature deaths per year, which is equivalent to $3.8 Billion (2016$CAD) in social benefits. When the benefit of EV deployment is normalized per vehicle, it is higher than most incentives provided by the government, indicating that EV incentives can generate high social benefits.

Assessment of PM2.5-bound nitrogen-containing organic compounds (NOCs) during winter at urban sites in China and Korea

In this study, ambient fine particles (PM_2.5) were collected in two urban cities in China and Korea (Beijing and Gwangju, respectively) simultaneously in January 2018. Analysis of the nonpolar and semipolar organic matter (OM) using atmospheric pressure photoionization (APPI) Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) revealed that compounds containing only C, H, and O (CHO) and those containing C, H, O, and N (CHON) accounted for more than 90% of the total intensity of the OM peaks. Higher proportions of CHON compounds were observed during days with abnormally high PM_2.5 concentrations at both sites than on regular or non-event days. The proportion of CHON species at the Beijing site was not correlated with secondary ionic species (i.e., NO₃^-, SO₄^2-, and NH₄⁺) or gaseous components (i.e., O₃, NO₂, and SO₂). In contrast, the proportion of CHON species at the Gwangju site was positively correlated with the concentrations of particulate nitrate and ammonium ions, assuming that ambient ammonium nitrate plays a role in the atmospheric formation of nitrogen-containing organic compounds (NOCs) at the Gwangju site and that Gwangju is more strongly influenced by secondary aerosols than Beijing is. In particular, a significant proportion of the compounds observed at the Beijing site contained only C, H and N (CHN), while negligible amounts of CHN were detected at the Gwangju site. The CHN species in Beijing were identified as quinoline compounds and the corresponding -CH₂ homologous series using complementary GC × GC-TOF MS analysis. These results suggest that NOCs and their -CH₂ homologous series from primary emissions may be significant contributors to nonpolar and semipolar OM during winter in Beijing, while NOCs with high oxidation states, likely formed via ambient-phase nitrate-mediated reactions, may be the dominant OM constituents in Gwangju.

Climate and Health Benefits of Rapid Coal-to-Gas Fuel Switching in the U.S. Power Sector Offset Methane Leakage and Production Cost Increases

In this paper, we ask whether rapidly displacing coal electricity generation with underutilized, existing natural gas capacity has net societal benefits or net costs when considering climate change, economics, and air pollution. We use a power plant dispatch model to quantify the effects of dispatching because of a tax on carbon or because of a tax on carbon, methane leakage, and air pollution. We explicitly model exhaust stack CO₂ emissions, production costs, health damages caused by criteria air pollutants, and methane leakage from the natural gas infrastructure. We show that (1) the optimal coal-to-gas redispatch displaces 62-77% of coal energy, leaving some coal online, (2) the health benefits of redispatch are larger in magnitude than the climate benefits, (3) reducing methane leakage rates from 2.3 to 2.0% increases the net climate benefits of redispatch by $1.1B-$1.4B, (4) although internalizing methane leakage, climate damages, and health damages in the power plant dispatch maximizes the net benefits of redispatch, 75-87% of these benefits can be achieved using a carbon tax mechanism alone, and (5) when choosing an optimal carbon tax, focusing on climate at the exclusion of health-and vice-versa-provides less net benefit than looking at both issues jointly.

Life-Cycle Greenhouse Gas Emissions and Human Health Trade-Offs of Organic Waste Management Strategies

Waste-to-energy systems can play an important role in diverting organic waste from landfills. However, real-world waste management can differ from idealized practices, and emissions driven by microbial communities and complex chemical processes are poorly understood. This study presents a comprehensive life-cycle assessment, using reported and measured data, of competing management alternatives for organic municipal solid waste including landfilling, composting, dry anaerobic digestion (AD) for the production of renewable natural gas (RNG), and dry AD with electricity generation. Landfilling is the most greenhouse gas (GHG)-intensive option, emitting nearly 400 kg CO_2e per tonne of organic waste. Composting raw organics resulted in the lowest GHG emissions, at -41 kg CO_2e per tonne of waste, while upgrading biogas to RNG after dry AD resulted in -36 to -2 kg CO_2e per tonne. Monetizing the results based on social costs of carbon and other air pollutant emissions highlights the importance of ground-level NH₃ emissions from composting nitrogen-rich organic waste or post-AD solids. However, better characterization of material-specific NH₃ emissions from landfills and land-application of digestate is essential to fully understand the trade-offs between alternatives.

A study of cardiorespiratory related mortality as a result of exposure to black carbon

INTRODUCTION

Air pollution is a global phenomenon which invariably leads to a serious environmental and health related sequalae. "Black carbon" (BC), a subset of fine particulate matter ≤2.5 μm (PM_2.5), is a fossil fuel emission by-product and has more recently been recognized as a major health hazard. The objective of this study is to statistically analyze the BC concentration and its correlation with cardiorespiratory related mortality and to estimate the benefits of BC reduction on the health of the population in the capital city of Tehran.

METHODS

We analyzed the ambient air BC concentration and its correlation with cardiorespiratory related mortality and conducted health impact assessment of BC in Tehran (Jan 2018-Jan 2019). The data pertaining to BC concentration was obtained from Tehran's four major pollution monitoring stations. The mortality data was obtained from Tehran's cemetery registry. We calculated and analyzed BC concentration statistics including the mean, standard deviation, coefficient of variation, skewness, and kurtosis. We then assessed the cross-correlation and temporal relationship (0-7 days) between the daily mean concentration of BC for the entire city and cardiorespiratory related mortality. The BenMAP software was utilized to estimate the potential reduction in cardiorespiratory related mortality rates if BC concentration is reduced. Three hypothetical scenarios were employed in the analysis, utilizing the BenMAP software: (I) BC concentration was completely removed from the ambient air; (II) BC concentration was eliminated, and the remaining (non-BC portion of) PM_2.5 concentration was reverted to the United States Environmental Protection Agency (EPA)'s standard level (i.e., 35 μg/m³); and (III) The BC emission during the night (22:00 h-6:00 h, when heavy-duty vehicles (HDVs) are allowed to commute in the city) was distributed throughout the whole day. Since the planetary boundary layer during daytime is much higher than that of nighttime, with the same rate of emission, lower concentrations are spread during the whole day.

RESULTS

The trend of BC concentration variation revealed a persistently higher emission of BC during the nighttime, which is consistent with the large-scale operation of HDVs during these hours in the city of Tehran. We observed a direct correlation between BC concentration and cardiorespiratory related mortality. Analysis also showed a 1.4-day lag period from the time of exposure to BC polluted air and respiratory related deaths, and 2 days for cardiovascular related deaths. As a result, the reduction in BC has significant beneficial effects in reducing potentially preventable cardiorespiratory related mortality. The aforementioned three scenarios for age groups of 30 and above yielded the following results: (I) 11,369 (126 per 100,000 population), (II) 15,386 (171 per 100,000 population), and (III) 2552 (28 per 100,000 population) potentially preventable all-cause (including cardiorespiratory) related deaths annually.

CONCLUSIONS

The BC concentration is relatively high in Tehran and HDVs have a major role in emission of this pollutant. A direct correlation between BC concentration and cardiorespiratory related mortality is observed. There are considerable health benefits in reducing BC concentration in this city. Our findings highlight the urgent need to actively curtail emissions of this harmful pollutant. This can be achieved through utilizing control mechanisms such as particulate filters or amending traffic laws.

Estimation of abatement potentials and costs of air pollution emissions in China

Understanding the air pollution emission abatement potential and associated control cost is a prerequisite to design cost efficient control policies. In this study, a linear programming algorithm model, International Control Cost Estimate Tool, was updated with cost data for applications of 56 types of end-of-pipe technologies and five types of renewable energy in 10 major sectors namely power generation, industry combustion, cement production, iron and steel production, other industry processes, domestic combustion, transportation, solvent use, livestock rearing, and fertilizer use. The updated model was implemented to estimate the abatement potential and marginal cost of multiple pollutants in China. The total maximum abatement potentials of sulfur dioxide (SO₂), nitrogen oxides (NO_x), primary particulate matter (PM_2.5), non-volatile organic compounds (NMVOCs), and ammonia (NH₃) in China were estimated to be 19.2, 20.8, 9.1, 17.2 and 8.6 Mt, respectively, which accounted for 89.7%, 89.9%, 94.6%, 74.0%, and 80.2% of their total emissions in 2014, respectively. The associated control cost of such reductions was estimated as 92.5, 469.7, 75.7, 449.0, and 361.8 billion CNY in SO₂, NO_x, primary PM_2.5, NMVOCs and NH₃, respectively. Shandong, Jiangsu, Henan, Zhejiang, and Guangdong provinces exhibited large abatement potentials for all pollutants. Provincial disparity analysis shows that high GDP regions tend to have higher reduction potential and total abatement costs. End-of-pipe technologies tended be a cost-efficient way to control pollution in industries processes (i.e., cement plants, iron and steel plants, lime production, building ceramic production, glass and brick production), whereas such technologies were less cost-effective in fossil fuel-related sectors (i.e., power plants, industry combustion, domestic combustion, and transportation) compared with renewable energy. The abatement potentials and marginal abatement cost curves developed in this study can further be used as a crucial component in an integrated model to design optimized cost-efficient control policies.

Air pollution control strategies directly limiting national health damages in the US

Exposure to fine particulate matter (PM2.5) from fuel combustion significantly contributes to global and US mortality. Traditional control strategies typically reduce emissions for specific air pollutants and sectors to maintain pollutant concentrations below standards. Here we directly set national PM2.5 mortality cost reduction targets within a global human-earth system model with US state-level energy systems, in scenarios to 2050, to identify endogenously the control actions, sectors, and locations that most cost-effectively reduce PM2.5 mortality. We show that substantial health benefits can be cost-effectively achieved by electrifying sources with high primary PM2.5 emission intensities, including industrial coal, building biomass, and industrial liquids. More stringent PM2.5 reduction targets expedite the phaseout of high emission intensity sources, leading to larger declines in major pollutant emissions, but very limited co-benefits in reducing CO2 emissions. Control strategies limiting health damages achieve the greatest emission reductions in the East North Central and Middle Atlantic states.

State-level drivers of future fine particulate matter mortality in the United States

Future fine particulate matter (PM₂.₅) concentrations and resulting health impacts will be largely determined by factors such as energy use, fuel choices, emission controls, state and national policies, and demographcs. In this study, a human-earth system model is used to estimate PM_2.5 mortality costs (PMMC) due to air pollutant emissions from each US state over the period 2015 to 2050, considering current major air quality and energy regulations. Contributions of various socioeconomic and energy factors to PMMC are quantified using the Logarithmic Mean Divisia Index. National PMMC are estimated to decrease 25% from 2015 to 2050, driven by decreases in energy intensity and PMMC per unit consumption of electric sector coal and transportation liquids. These factors together contribute 68% of the decrease, primarily from technology improvements and air quality regulations. States with greater population and economic growth, but with fewer clean energy resources, are more likely to face significant challenges in reducing future PMMC from their emissions. In contrast, states with larger projected decreases in PMMC have smaller increases in population and per capita GDP, and greater decreases in electric sector coal share and PMMC per unit fuel consumption.

Control Technology-Driven Changes to In-Use Heavy-Duty Diesel Truck Emissions of Nitrogenous Species and Related Environmental Impacts

Emissions from thousands of in-use heavy-duty diesel trucks were sampled at a highway and an arterial street location in the San Francisco Bay Area, spanning a time period when use of diesel particle filters (DPFs) and selective catalytic reduction (SCR) increased rapidly. At the highway site where a diverse mix of trucks is observed, SCR systems on 2010 and newer engines reduce emitted nitrogen oxides (NO_x) by 87 ± 5% relative to pre-2004 engines. SCR also mitigates DPF-related increases in nitrogen dioxide (NO₂) emissions. However, a majority of trucks had in-use NO_x emission rates that exceeded applicable emission standards. SCR systems increase emissions of nitrous oxide (N₂O) and ammonia (NH₃) from near-zero levels to 0.93 ± 0.13 and 0.18 ± 0.07 g kg^-1, respectively. Emissions of all nitrogenous species and especially NH₃ are skewed; 10% of trucks contribute 95% of the on-road fleet's total NH₃ emissions. Similar emission changes are observed at the arterial street site where exclusively drayage trucks operate. The environmental effects of decreased black carbon, NO_x, and carbon dioxide (CO₂) emissions and increased N₂O and NH₃ emissions due to the rapid adoption of DPF and SCR systems by the California truck fleet are: (1) a 65% net decrease in the social cost of statewide exposure to diesel truck emissions (-3.3 billion 2018 US dollars per year), and (2) a 3% net decrease in the global warming potential-weighted emission factor (-27 g CO₂-eq km^-1).

PM2.5-Associated Health Impacts of Beehive Coke Oven Ban in China

Historically, beehive coke ovens (BCOs) were extensively operated in China and emitted large quantities of pollutants, including primary PM_2.5 and secondary PM_2.5 precursors, and other climate forcers. Although these ovens were legally banned in 1996 by the Coal Law, the process of phasing them out took over a decade to accomplish. Based on historical operation data derived from remote sensing images, temporal trends and the spatial distribution of the emissions of various pollutants from BCOs were compiled and used to model the resulting perturbation in ambient PM_2.5, population exposure, and PM_2.5-associated adverse health impacts. Historically, PM_2.5 originating from BCOs affected a vast region across China, which peaked in approximately 1996 and decreased afterward until the ovens' final elimination in 2011. According to the results of a supply-demand model, emissions from the BCOs would have continued to increase after 1996 if they had not been banned. As a result, national average PM_2.5 attributable to BCOs in 2014 would have been more than three times as high as that in 1996. It was estimated that the cumulative number of premature deaths associated with BCO-originating PM_2.5 from 1982 to 2014 was as high as 365 000 (95% confidence interval 259 000-402 000). The number would have nearly tripled if BCOs had not been banned and halved if the ban had been implemented immediately after the regulation was in force, suggesting the importance of legislation implementation.

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.

Fine-scale damage estimates of particulate matter air pollution reveal opportunities for location-specific mitigation of emissions

Fine particulate matter (PM2.5) air pollution has been recognized as a major source of mortality in the United States for at least 25 years, yet much remains unknown about which sources are the most harmful, let alone how best to target policies to mitigate them. Such efforts can be improved by employing high-resolution geographically explicit methods for quantifying human health impacts of emissions of PM2.5 and its precursors. Here, we provide a detailed examination of the health and economic impacts of PM2.5 pollution in the United States by linking emission sources with resulting pollution concentrations. We estimate that anthropogenic PM2.5 was responsible for 107,000 premature deaths in 2011, at a cost to society of $886 billion. Of these deaths, 57% were associated with pollution caused by energy consumption [e.g., transportation (28%) and electricity generation (14%)]; another 15% with pollution caused by agricultural activities. A small fraction of emissions, concentrated in or near densely populated areas, plays an outsized role in damaging human health with the most damaging 10% of total emissions accounting for 40% of total damages. We find that 33% of damages occur within 8 km of emission sources, but 25% occur more than 256 km away, emphasizing the importance of tracking both local and long-range impacts. Our paper highlights the importance of a fine-scale approach as marginal damages can vary by over an order of magnitude within a single county. Information presented here can assist mitigation efforts by identifying those sources with the greatest health effects.

Nonlinear relationships between air pollutant emissions and PM2.5-related health impacts in the Beijing-Tianjin-Hebei region

A direct and quantitative linkage of air pollution-related health effects to emissions from different sources is critically important for decision-making. While a number of studies have attributed the PM_2.5-related health impacts to emission sources, they have seldom examined the complicated nonlinear relationships between them. Here we investigate the nonlinear relationships between PM_2.5-related premature mortality in the Beijing-Tianjin-Hebei (BTH) region, one of the most polluted regions in the world, and emissions of different pollutants from multiple sectors and regions, through a combination of chemical transport model (CTM), extended response surface model (ERSM), and concentration-response functions (CRFs). The mortalities due to both long-term and short-term exposures to PM_2.5 are most sensitive to the emission reductions of primary PM_2.5, followed by NH₃, nonmethane volatile organic compounds and intermediate volatility organic compounds (NMVOC+IVOC). The sensitivities of long-term mortality to emissions of primary organic aerosol (POA), NMVOC+IVOC and SO₂ do not change much with reduction ratio, whereas the sensitivities to primary inorganic PM_2.5 (defined as all chemical components of primary PM_2.5 other than POA), NH₃ and NO_x increase significantly with the increase of reduction ratio. The emissions of primary PM_2.5, especially those from the residential and commercial sectors, contribute a larger fraction of mortality in winter (57-70%) than in other seasons (28-42%). When emissions of multiple pollutants or those from both local and regional emissions are controlled simultaneously, the overall sensitivity of long-term mortality is much larger than the arithmetic sum of the sensitivities to emissions of individual pollutants or from individual regions. This implies that a multi-pollutant, multi-sector and regional joint control strategy should be implemented to maximize the marginal health benefits. For NO_x emissions, we suggest a nationwide control strategy which significantly enhances the effectiveness for reducing mortality by avoiding possible side effects when only the emissions within the BTH region are reduced.

Inequity in consumption of goods and services adds to racial-ethnic disparities in air pollution exposure

Fine particulate matter (PM2.5) air pollution exposure is the largest environmental health risk factor in the United States. Here, we link PM2.5 exposure to the human activities responsible for PM2.5 pollution. We use these results to explore "pollution inequity": the difference between the environmental health damage caused by a racial-ethnic group and the damage that group experiences. We show that, in the United States, PM2.5 exposure is disproportionately caused by consumption of goods and services mainly by the non-Hispanic white majority, but disproportionately inhaled by black and Hispanic minorities. On average, non-Hispanic whites experience a "pollution advantage": They experience ∼17% less air pollution exposure than is caused by their consumption. Blacks and Hispanics on average bear a "pollution burden" of 56% and 63% excess exposure, respectively, relative to the exposure caused by their consumption. The total disparity is caused as much by how much people consume as by how much pollution they breathe. Differences in the types of goods and services consumed by each group are less important. PM2.5 exposures declined ∼50% during 2002-2015 for all three racial-ethnic groups, but pollution inequity has remained high.

Air quality and health benefits from potential coal power plant closures in Texas

As power production from renewable energy and natural gas grows, closures of some coal-fired power plants in Texas become increasingly likely. In this study, the potential effects of such closures on air quality and human health were analyzed by linking a regional photochemical model with a health impacts assessment tool. The impacts varied significantly across 13 of the state's largest coal-fired power plants, sometimes by more than an order of magnitude, even after normalizing by generation. While some power plants had negligible impacts on concentrations at important monitors, average impacts up to 0.5 parts per billion (ppb) and 0.2 µg/m³ and maximum impacts up to 3.3 ppb and 0.9 µg/m³ were seen for ozone and fine particulate matter (PM_2.5), respectively. Individual power plants impacted average visibility by up to 0.25 deciviews in Class I Areas. Health impacts arose mostly from PM_2.5 and were an order of magnitude higher for plants that lack scrubbers for SO₂. Rankings of health impacts were largely consistent across the base model results and two reduced form models. Carbon dioxide emissions were relatively uniform, ranging from 1.00 to 1.26 short tons/MWh, and can be monetized based on a social cost of carbon. Despite all of these unpaid externalities, estimated direct costs of each power plant exceeded wholesale power prices in 2016. Implications: While their CO₂ emission rates are fairly similar, sharply different NO_x and SO₂ emission rates and spatial factors cause coal-fired power plants to vary by an order of magnitude in their impacts on ozone, particulate matter, and associated health and visibility outcomes. On a monetized basis, the air pollution health impacts often exceed the value of the electricity generated and are of similar magnitude to climate impacts. This suggests that both air pollution and climate should be considered if externalities are used to inform decision making about power-plant dispatch and retirement.

Assessing Contributions of Agricultural and Nonagricultural Emissions to Atmospheric Ammonia in a Chinese Megacity

Ammonia (NH₃) is the predominant alkaline gas in the atmosphere contributing to formation of fine particles-a leading environmental cause of increased morbidity and mortality worldwide. Prior findings suggest that NH₃ in the urban atmosphere derives from a complex mixture of agricultural (mainly livestock production and fertilizer application) and nonagricultural (e.g., urban waste, fossil fuel-related emissions) sources; however, a citywide holistic assessment is hitherto lacking. Here we show that NH₃ from nonagricultural sources rivals agricultural NH₃ source contributions in the Shanghai urban atmosphere. We base our conclusion on four independent approaches: (i) a full-year operation of a passive NH₃ monitoring network at 14 locations covering urban, suburban, and rural landscapes; (ii) model-measurement comparison of hourly NH₃ concentrations at a pair of urban and rural supersites; (iii) source-specific NH₃ measurements from emission sources; and (iv) localized isotopic signatures of NH₃ sources integrated in a Bayesian isotope mixing model to make isotope-based source apportionment estimates of ambient NH₃. Results indicate that nonagricultural sources and agricultural sources are both important contributors to NH₃ in the urban atmosphere. These findings highlight opportunities to limit NH₃ emissions from nonagricultural sources to help curb PM_2.5 pollution in urban China.

Monetized health benefits attributable to mobile source emission reductions across the United States in 2025

By-products of mobile source combustion processes, such as those associated with gasoline- and diesel-powered engines, include direct emissions of particulate matter as well as precursors to particulate matter and ground-level ozone. Human exposure to fine particulate matter with an aerodynamic diameter smaller than 2.5 μm (PM_2.5) is associated with increased incidence of premature mortality and morbidity outcomes. This study builds upon recent, detailed source-apportionment air quality modeling to project the health-related benefits of reducing PM_2.5 from mobile sources across the contiguous U.S. in 2025. Updating a previously published benefits analysis approach, we develop national-level benefit per ton estimates for directly emitted PM_2.5, SO₂/pSO₄, and NO_X for 16 mobile source sectors spanning onroad vehicles, nonroad engines and equipment, trains, marine vessels, and aircraft. These benefit per ton estimates provide a reduced-form tool for estimating and comparing benefits across multiple mobile source emission scenarios and can be applied to assess the benefits of mobile source policies designed to improve air quality. We found the benefit per ton of directly emitted PM_2.5 in 2025 ranges from $110,000 for nonroad agriculture sources to $700,000 for onroad light duty gas cars and motorcycles (in 2015 dollars and based on an estimate of PM-related mortality derived from the American Cancer Society cohort study). Benefit per ton values for SO₂/pSO₄ range from $52,000 for aircraft sources (including emissions from ground support vehicles) to $300,000 for onroad light duty diesel emissions. Benefit per ton values for NO_X range from $2100 for C1 and C2 marine vessels to $7500 for "nonroad all other" mobile sources, including industrial, logging, and oil field sources. Benefit per ton estimates increase approximately 2.26-fold when using an alternative concentration response function to derive PM_2.5-related mortality. We also report benefit per ton values for the eastern and western U.S. to account for broad spatial heterogeneity patterns in emissions reductions, population exposure and air quality benefits.

Distinguishing Emission-Associated Ambient Air PM2.5 Concentrations and Meteorological Factor-Induced Fluctuations

Although PM_2.5 (particulate matter with aerodynamic diameters less than 2.5 μm) in the air originates from emissions, its concentrations are often affected by confounding meteorological effects. Therefore, direct comparisons of PM_2.5 concentrations made across two periods, which are commonly used by environmental protection administrations to measure the effectiveness of mitigation efforts, can be misleading. Here, we developed a two-step method to distinguish the significance of emissions and meteorological factors and assess the effectiveness of emission mitigation efforts. We modeled ambient PM_2.5 concentrations from 1980 to 2014 based on three conditional scenarios: realistic conditions, fixed emissions, and fixed meteorology. The differences found between the model outputs were analyzed to quantify the relative contributions of emissions and meteorological factors. Emission-related gridded PM_2.5 concentrations excluding the meteorological effects were predicted using multivariate regression models, whereas meteorological confounding effects on PM_2.5 fluctuations were characterized by probabilistic functions. When the regression models and probabilistic functions were combined, fluctuations in the PM_2.5 concentrations induced by emissions and meteorological factors were quantified for all model grid cells and regions. The method was then applied to assess the historical and future trends of PM_2.5 concentrations and potential fluctuations on global, national, and city scales. The proposed method may thus be used to assess the effectiveness of mitigation actions.

Molecular Adsorption Mechanism of Elemental Carbon Particles on Leaf Surface

Plant leaves can effectively capture and retain particulate matter (PM), improving air quality and human health. However, little is known about the adsorption mechanism of PM on leaf surface. Black carbon (BC) has great adverse impact on climate and environment. Four types of elemental carbon (EC) particles, carbon black as a simple model for BC, graphite, reduced graphene oxide, and graphene oxide, and C₃₆H₇₄/C₄₄H₈₈O₂ as model compounds for epicuticular wax were chosen to study their interaction and its impact at the molecular level using powder X-ray diffraction and vibrational spectroscopy (infrared and Raman). The results indicate that EC particles and wax can form C-H···π type hydrogen bonding with charge transfer from carbon to wax; therefore, strong attraction is expected between them due to the cooperativity of hydrogen bonding and London dispersion from instantaneous dipoles. In reality, once settled on the leaf surface, especially without wax ultrastructures, BC with extremely large surface-to-volume ratio will likely stick and stay. On the other hand, BC particles can lead to phase transition of epicuticular wax from crystalline to amorphous structures by creating packing disorder and end- gauche defects of wax molecular chain, potentially causing water loss and thereby damage of plants.

Understanding Excess Emissions from Industrial Facilities: Evidence from Texas

We analyze excess emissions from industrial facilities in Texas using data from the Texas Commission on Environmental Quality. Emissions are characterized as excess if they are beyond a facility's permitted levels and if they occur during startups, shutdowns, or malfunctions. We provide summary data on both the pollutants most often emitted as excess emissions and the industrial sectors and facilities responsible for those emissions. Excess emissions often represent a substantial share of a facility's routine (or permitted) emissions. We find that while excess emissions events are frequent, the majority of excess emissions are emitted by the largest events. That is, the sum of emissions in the 96-100th percentile is often several orders of magnitude larger than the remaining excess emissions (i.e., the sum of emissions below the 95th percentile). Thus, the majority of events emit a small amount of pollution relative to the total amount emitted. In addition, a small group of high emitting facilities in the most polluting industrial sectors are responsible for the vast majority of excess emissions. Using an integrated assessment model, we estimate that the health damages in Texas from excess emissions are approximately $150 million annually.

Screening of peptide probe binding to particulate matter with a high metal content

Particulate matter (PM) is becoming an increasing health concern and there is a need to develop detection methods to keep its harmful effects in check. Generation of reactive oxygen species (ROS) by PM is often associated with metal compounds, hence our aim is to screen for a peptide probe towards improved collection and the detection of PM having a high metal content. Peptides are putative recognition molecules due to their versatility and ease of modification to enhance their binding selectivities. PM binding peptides were screened using the peptide array and different binding behaviors in terms of different spot colors (yellow, mixed and gray), indicating the different composition of bound PMs, were observed. The strongest binding peptides were identified as follows: NHVNTNYYPTLH (gray), NGYYPHSHSYHQ (mixed) and HHLHWPHHHSYT (yellow), with relative binding ratios of 125%, 144% and 136%, in comparison with WQDFGAVRSTRS, a peptide screened from a phage display in our previous study. Inductively coupled plasma mass spectrometry (ICPMS) analyses revealed that Co, Ni and Zn content in the PM bound to the HHLHWPHHHSYT peptide spot were respectively 12.5, 15.8 and 7.8 times that of the PM bound to no peptide spot, suggesting this peptide probe is applicable to collect PM with a high metal content.

Using peptide array, peptides binding to particulate matter with high metal content were screened and characterized by focusing on the different spot colors (yellow, mixed and gray).

Air Emissions Damages from Municipal Drinking Water Treatment Under Current and Proposed Regulatory Standards

Water treatment processes present intersectoral and cross-media risk trade-offs that are not presently considered in Safe Drinking Water Act regulatory analyses. This paper develops a method for assessing the air emission implications of common municipal water treatment processes used to comply with recently promulgated and proposed regulatory standards, including concentration limits for, lead and copper, disinfection byproducts, chromium(VI), strontium, and PFOA/PFOS. Life-cycle models of electricity and chemical consumption for individual drinking water unit processes are used to estimate embedded NO_x, SO₂, PM_2.5, and CO₂ emissions on a cubic meter basis. We estimate air emission damages from currently installed treatment processes at U.S. drinking water facilities to be on the order of $500 million USD annually. Fully complying with six promulgated and proposed rules would increase baseline air emission damages by approximately 50%, with three-quarters of these damages originating from chemical manufacturing. Despite the magnitude of these air emission damages, the net benefit of currently implemented rules remains positive. For some proposed rules, however, the promise of net benefits remains contingent on technology choice.

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

In order to design effective strategies to reduce the public health burden of ambient fine particulate matter (PM_2.5) imposed in an area, it is necessary to identify the emissions sources affecting that location and quantify their contributions. However, it is challenging because PM_2.5 travels long distances and most constituents are the result of complex chemical processes. We developed a reduced-form source-receptor model for estimating locations and magnitudes of downwind health costs from a source or, conversely, the upwind sources that contribute to health costs at a receptor location. Built upon outputs from a state-of-the-art air quality model, our model produces comprehensive risk-based source apportionment results with trivial computational costs. Using the model, we analyzed all the sources contributing to the inorganic PM_2.5 health burden in 14 metropolitan statistical areas (MSAs) in the United States. Our analysis for 12 source categories shows that 80-90% of the burden borne by these areas originates from emissions sources outside of the area and that emissions sources up to 800 km away need to be included to account for 80% of the burden. Conversely, 60-80% of the impacts of an MSA's emissions occurs outside of that MSA. The results demonstrate the importance of regionally coordinated measures to improve air quality in metropolitan areas.

Non-linear increase of respiratory diseases and their costs under severe air pollution

China is experiencing severe and persistent air pollution, with concentrations of fine particulate matters (PM_2.5) reaching unprecedentedly high levels in many cities. Quantifying the detrimental effects on health and their costs derived from high PM_2.5 levels is crucial because of the unsolved challenges to mitigate air pollution in the following decades. Using the daily monitoring data on PM_2.5 concentrations and clinic visits, we found a non-linear increase of respiratory diseases, but not for other diseases (e.g., digestive diseases) under severe air pollution. We found an increase of respiratory diseases by 1% for each 10 μg m^-3 increase in PM_2.5 when the annual average daily PM_2.5 concentration was less than 50 μg m^-3; while this ratio was doubled (around 2%) with the daily PM_2.5 concentration larger than 50 μg m^-3. Under severe air pollution (PM_2.5 concentration >150 μg m^-3), the respiratory diseases increased by over 50% compared to that in clean days. Children are more sensitive to the severe air pollution. The increase of clinic visits, especially for adults, was observed mainly in bigger (>500 beds) hospitals. Re-allocating medical resources (e.g., doctors) from big hospitals to community hospitals can benefit the respiratory patients due to air pollution. The total medical cost of clinic visits of respiratory diseases derived from PM_2.5 pollution was estimated at 17.2-57.0 billion Yuan in 2014 in China, accounting for 0.5-1.6% of national total health expenditure. Because these medical costs only represent a small part of total health cost derived from air pollution, the reduction of associated health costs would be an important co-benefit of implementation of air pollution preventive strategies.

Spatially resolved air-water emissions tradeoffs improve regulatory impact analyses for electricity generation

Coal-fired power plants (CFPPs) generate air, water, and solids emissions that impose substantial human health, environmental, and climate change (HEC) damages. This work demonstrates the importance of accounting for cross-media emissions tradeoffs, plant and regional emissions factors, and spatially variation in the marginal damages of air emissions when performing regulatory impact analyses for electric power generation. As a case study, we assess the benefits and costs of treating wet flue gas desulfurization (FGD) wastewater at US CFPPs using the two best available treatment technology options specified in the 2015 Effluent Limitation Guidelines (ELGs). We perform a life-cycle inventory of electricity and chemical inputs to FGD wastewater treatment processes and quantify the marginal HEC damages of associated air emissions. We combine these spatially resolved damage estimates with Environmental Protection Agency estimates of water quality benefits, fuel-switching benefits, and regulatory compliance costs. We estimate that the ELGs will impose average net costs of $3.01 per cubic meter for chemical precipitation and biological wastewater treatment and $11.26 per cubic meter for zero-liquid discharge wastewater treatment (expected cost-benefit ratios of 1.8 and 1.7, respectively), with damages concentrated in regions containing a high fraction of coal generation or a large chemical manufacturing industry. Findings of net cost for FGD wastewater treatment are robust to uncertainty in auxiliary power source, location of chemical manufacturing, and binding air emissions limits in noncompliant regions, among other variables. Future regulatory design will minimize compliance costs and HEC tradeoffs by regulating air, water, and solids emissions simultaneously and performing regulatory assessments that account for spatial variation in emissions impacts.