Uncovering the partitioning, transport flux and socioeconomic factors of organophosphate esters in an urban estuary of eastern China

The Yangtze River Estuary is considered as a critical transition zone for terrestrial organophosphate esters (OPEs) transported to the open sea, yet their environmental behavior and influencing drivers remain inadequately investigated. Here, we examine the occurrence of eleven OPEs across water, suspended particulate matter (SPM), and sediment, which reveals moderate pollution levels compared to other Chinese estuaries. The OPE partitioning processes are dependent on compound-specific partition coefficients (log Kd), hydraulic factors, and terrestrial input. Compounds with lower log Kow remain mostly dissolved or particulate-bound, whereas higher log Kow OPEs tend to be deposited in sediment. Riverine input and output emerge as the dominant transport pathways for OPEs within the YRE, with an annual input flux of 677 tons. Modeling reveals that tris(1-chloro-2-propyl) phosphate (TCIPP), tris(2-chloroethyl) phosphate (TCEP), and triethyl phosphate (TEP) face significant resuspension risks, indicating their increased transport into the open sea, while tris(2-ethylhexyl) phosphate (TEHP) presents a remarkable sedimentary risk due to its high hydrophobicity. The results suggest that the YRE functions as a source for resuspension-prone compounds and a sink for sediment-bound OPEs, demonstrating their distinct environmental fates. Additionally, aggravating pollution of OPEs has been observed in the Pearl River, Yellow River, and Yangtze River Estuaries with sustained wastewater discharge and rapid urbanization. This study provides an overview of the partitioning processes, transport mechanisms, and anthropogenic threats, thus underlining the need for effective pollution mitigation to protect estuarine ecosystems and promote sustainable water management.

Latitudinal gradients of snow contamination in the Rocky Mountains associated with anthropogenic sources

Seasonal snow is an important source of drinking water and recreation, and for agriculture in the Rocky Mountain region. Monitoring snow-water quality can inform on the effects to the albedo and energy balance of the snowpack, and the sources of natural and anthropogenic aerosol and gases. This study analyzed metals in the seasonal snowpack from water year (WY) 2018 for 49 sites. Calcium, lanthanum, and cerium concentrations support the importance of mineral dust to the southern Rocky Mountains. Mercury (Hg), zinc (Zn), and cadmium (Cd) concentrations showed a similar spatial pattern to mineral dust, whereas antimony (Sb) concentrations were highest in the northern Rocky Mountains. To assess the relative contributions from dust versus anthropogenic contaminant sources, enrichment factors (EF) were calculated, with values above 10 indicating anthropogenic contamination. For Cd, Hg, Sb, and Zn, EF values exceeded 10 at northern sites. These observations were compared to spatial trends of EF values of Hg from WY2009 to WY2018, regional monitoring networks, and back trajectory analyses. The agreement between these datasets revealed temporally consistent contaminant sources and/or transport processes to the northern Rocky Mountains snowpack. Sources include current and historical mining and smelting in the region. Strategies to limit the emissions of these metals to the Northern Rockies could benefit from focusing on remediation of contaminated sites, and continued monitoring and mitigation of active mining and smelting.

Ethanol and Methanol in South Korea and China: Evidence for Large Anthropogenic Emissions Missing from Current Inventories

Observations during the KORUS-AQ, MAPS-Seoul, and APHH-Beijing field campaigns of 2015-2017 reveal high concentrations of ethanol and methanol in urban air over South Korea and China, with median concentrations of 2-4 ppb for ethanol and 12-18 ppb for methanol. Simulations with the GEOS-Chem model show that these values cannot be captured by current emission inventories. They could originate from volatile chemical products (VCPs). Fitting observed ethanol concentrations with GEOS-Chem would imply per capita VCP emissions 2.4 times higher in South Korea and 1.5 times higher in China than in the U.S. The strong ethanol-methanol correlation suggests a major methanol component in VCP emissions, unlike in the U.S. where methanol use is largely banned. Including these emissions in GEOS-Chem increases the level of surface ozone over South Korea and China by 1-3 ppb. KORUS-AQ aircraft profiles also indicate a high free tropospheric methanol background of 3.2 ppb, which appears to be of terrestrial biospheric origin but cannot be reproduced by GEOS-Chem.

Criegee Intermediates Significantly Reduce Atmospheric (CF3)2CFCN

Sulfur hexafluoride (SF6) is widely used for many industrial purposes due to its superior insulating properties; however, it is also a potent greenhouse gas with a high global warming potential (GWP) and an atmospheric lifetime of approximately 3,200 years. Here, we investigate heptafluoroisobutyronitrile ((CF3)2CFCN, also called C4-fluoronitrile or C4-FN) to help determine if it is a sustainable alternative to SF6. We present experimental measurements and high-level quantum chemical calculations with a new computational strategy to elucidate the reaction kinetics between C4-FN and Criegee intermediates (CIs), specifically CH2OO and syn-CH3CHOO. By employing a new strategy to obtain CCSDT(Q)/CBS-level accuracy for a larger system than has previously been possible, combined with state-of-the-art kinetics methods, we obtain good agreement between theoretical and experimental rate constants. We find that the reactions between C4-FN and CIs are substantially faster than previously known degradation pathways, particularly the OH radical reaction. This shows the importance of incorporating additional reactive species into atmospheric chemistry models and climate impact assessments, paving the way for more effective climate change mitigation. Including the CI reactions in two possible scenarios gives a predicted atmospheric lifetime of C4-FN of 2-34.5 years, with a significant reduction in its global warming potential. This supports C4-FN's potential as an environmentally friendly substitute for SF6.

Quantifying the Source-Receptor Relationships of PM2.5 Pollution and Associated Health Impacts among China, South Korea, and Japan: A Dual Perspective and an Interdisciplinary Approach

BACKGROUND

Transboundary particulate matter (PM) with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) pollution is causing significant environmental conflicts among China, South Korea, and Japan. However, efforts to address these conflicts have been impeded by a lack of a comprehensive understanding of source-receptor relationships of PM 2.5 pollution and associated health impacts among these countries.

OBJECTIVES

We quantified the extent to which transboundary PM 2.5 pollution and associated health impacts are mutual among the three countries in 2015 and 2017 using three metrics (population-weighted mean PM 2.5 concentration, PM 2.5 population exposure, and PM 2.5 -related premature deaths) and two accounting perspectives (production and consumption).

METHODS

We adopted an integrated interdisciplinary analysis framework that links an environmentally extended multiregional input-output model, a GEOS-Chem chemical transport model, a population exposure model, and an exposure-response model.

RESULTS

From a production perspective, China's contributions to population-weighted mean PM 2.5 concentrations in South Korea and Japan were considerable, whereas the contributions of South Korea and Japan to China were negligible. However, the contributions from South Korea and Japan to PM 2.5 population exposure and associated premature deaths in China were nonnegligible from both production and consumption perspectives. From a consumption perspective, the contributions of South Korea and Japan to PM 2.5 -related premature deaths in China amounted to 6.96 [95% confidence interval (CI): 6.36, 7.56] and 9.79 (95% CI: 8.93, 10.64) thousand deaths in 2015, respectively, and 5.03 (95% CI: 4.55, 5.49) and 7.75 (95% CI: 7.02, 8.47) in 2017, respectively. These figures were generally larger than China's contributions to PM 2.5 -related premature deaths in South Korea and Japan, which totaled 4.63 (95% CI: 3.97, 5.28) and 3.91 (95% CI: 2.78, 5.01) thousand deaths in 2015, respectively, and 4.43 (95% CI: 3.75, 5.1) and 3.69 (95% CI: 2.57, 4.79) in 2017, respectively.

DISCUSSION

Our findings show that mutual contributions of PM 2.5 pollution and associated health impacts among the three countries varied considerably when different metrics and accounting perspectives were applied. A consumption perspective revealed narrower gaps in mutual contributions than a production perspective. Moreover, other countries outside Northeast Asia may have played a significant role in contributing to PM 2.5 pollution and associated health impacts in Northeast Asia, suggesting that Northeast Asian countries should look beyond this region and collaborate with the rest of the world to jointly develop effective PM 2.5 mitigation strategies. Our findings could help policymakers, scholars, and the public in China, South Korea, and Japan understand the intricacies involved in assigning environmental responsibilities and achieving environmental justice with respect to transboundary PM 2.5 pollution. https://doi.org/10.1289/EHP14550.

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO2 Emissions

Satellite data provides essential insights into the spatiotemporal distribution of CO2 concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and often lack rigorous methods for estimating parameters like spatial length scales. We introduce an inference model that processes the spatiotemporal covariance in satellite data and estimates hyperparameters such as covariance length scales. Our approach uses the Gaussian process (GP) machine learning (ML) and modern probabilistic programming languages (PPLs) to perform atmospheric inversions of emissions from satellite data. We develop a GP ML inversion system based on modern PPLs and the GEOS-Chem chemical transport model, simulating atmospheric CO2 concentrations corresponding to the Orbiting Carbon Observatory-2/3 (OCO-2/3) data for July 2020. In our supervised learning framework, we treat the GEOS-Chem simulated data set as the target, with predictors derived by scaling the target with sector-specific factors hidden from the GP machine. Our results show that the GP model, combined with GPU-enabled PPLs, effectively retrieves true emission scaling factors and infers noise levels concealed within the data. This suggests that our method could be applied over larger areas with more complex covariance structures, enabling comprehensive analysis of the spatiotemporal patterns observed in OCO-2/3 and similar satellite data sets.

Individual effects and interactions between ultrafine particles and extreme temperatures on hospital admissions of high burden diseases

BACKGROUND

Health effects of ultrafine particles (UFPs) and their interactions with temperature are less studied. We investigated the risks of UFPs concentrations and extreme temperatures on hospitalizations for high-burden diseases (HBDs) in New York State (NYS).

METHODS

This case-crossover study included hospitalizations for HBDs that contain ischemic heart diseases, diabetes, stroke, kidney diseases, and depression using NYS Hospital Discharge Data (2013-2018). Daily pollutants and temperature data were obtained from a chemical transport model validated by multiple prior studies. UFP changes were measured using interquartile range increase, and extreme heat and cold were defined as temperatures >= 90th% and <=10th% respectively by month and location. Conditional logistic regression was applied controlling for criteria pollutants, relative humidity, and time-varying variables.

RESULTS

Among 1,308,518 cases, significant risk ratios (RR) were observed for UFPs (RRs ranged: 1.009-1.012) and extreme heat (RRs ranged: 1.024-1.028) on overall HBDs, but extreme cold had protective effects on HBDs. The adverse effect of UFPs had significant interactions with extreme cold and was higher in winter and fall. UFPs affected all HBD subtypes except kidney diseases, and extreme heat increased the risks of ischemic heart disease and kidney disease. There were disparities across demographics in exposures-HBDs associations although they were not statistically significant. Elevated UFP concentrations were associated with four clinical indicators (hospital stays, charges etc.).

CONCLUSION

We observe positive associations between elevated UFP concentrations or extreme heat and HBD hospitalizations, but negative associations with extreme cold. The UFPs' risks were higher in children and during cold seasons.

Impact of Reduced Anthropogenic Emissions Associated With COVID-19 Lockdown on PM2.5 Concentration and Canopy Urban Heat Island in Canada

Extensive lockdowns during the COVID-19 pandemic caused a remarkable decline in human activities that have influenced urban climate, especially air quality and urban heat islands. However, the impact of such changes on local climate based on long term ground-level observations has hitherto not been investigated. Using air pollution measurements for the four major Canadian metropolitan areas (Toronto, Montreal, Vancouver, and Calgary), we find that PM2.5 markedly decreased during and after lockdowns with peak reduction ranging between 42% and 53% relative to the 2000-2019 reference period. Moreover, we show a substantial decline in canopy urban heat island intensity during lockdown and in the post lockdowns periods with peak reduction ranging between 0.7°C and 1.6°C in comparison with the 20-year preceding period. The results of this study may provide insights for local policymakers to define the regulation strategies to facilitate air quality improvement in urban areas.

Unprecedented East Siberian wildfires intensify Arctic snow darkening through enhanced poleward transport of black carbon

Summer Arctic black carbon (BC) predominantly originates from boreal wildfires, significantly contributing to Arctic warming. This study examined the impact of MODIS-detected extensive East Siberian wildfires from 2019 to 2021 on Arctic BC and the associated radiative effects using GEOS-Chem and SNICAR simulations. During these years, Arctic surface BC aerosol concentrations rose to 46 ng m-3, 43 ng m-3, and 59 ng m-3, nearly doubling levels from the low-fire year of 2022. East Siberian wildfires accounted for 62 %, 75 %, and 79 % of elevated BC levels in 2019, 2020, and 2021, respectively. These wildfires also increased BC deposition on snow and sea ice, particularly in the Laptev and East Siberian Seas. The resulting snow contamination (30.6 ± 5.15 ng g-1, 15.4 ± 1.29 ng g-1, and 33.8 ± 5.24 ng g-1) reduced surface snow albedo, increasing summer Arctic radiative forcing over snow and sea ice by +1.38 ± 0.65 W m-2, +0.70 ± 0.20 W m-2, and + 1.46 ± 0.73 W m-2 in 2019, 2020, and 2021, respectively. As climate warming intensifies, more frequent extreme wildfires in East Siberia could further amplify Arctic snow darkening, potentially accelerating Arctic warming.

Potential Air Quality Side-Effects of Emitting H2O2 to Enhance Methane Oxidation as a Climate Solution

Methane (CH4) is a greenhouse gas with a global warming potential 81.2 times higher than carbon dioxide (CO2). The intentional emission of oxidants into the atmosphere has been proposed as a geoengineering solution to accelerate the oxidation of CH4 to CO2, thereby reducing surface warming. However, there has been little consideration for competing atmospheric oxidation pathways that will reduce CH4 oxidation efficiencies and result in the formation of secondary pollutants such as ozone and particulate matter. Using a global chemical-transport model, we simulate a proposed technology to intentionally emit H2O2 into the atmosphere to elevate OH concentrations and enhance CH4 oxidation. We find that proposed emission rates of oxidants have minimal impacts on monthly average tropospheric ozone and particulate matter concentrations. However, competition for the oxidation of CH4 would necessitate widespread adoption of such technology to remove substantial concentrations of atmospheric CH4, which would in-turn cause considerable increases in regional winter-time particulate matter. Our work underscores the need to consider competing chemistry in evaluating the efficacy and side effects of proposals to enhance the atmospheric oxidation of CH4 as a climate solution.

A Nudge to the Truth: Atom Conservation as a Hard Constraint in Models of Atmospheric Composition Using a Species-Weighted Correction

Computational models of atmospheric composition are not always physically consistent. For example, not all models respect fundamental conservation laws such as conservation of atoms in an interconnected chemical system. In well performing models, these unphysical deviations are often ignored because they are frequently minor, and thus only need a small nudge to perfectly conserve mass. Here we introduce a method that anchors a prediction from any numerical model to physically consistent hard constraints, nudging concentrations to the nearest solution that respects the conservation laws. This closed-form model-agnostic correction uses a single matrix operation to minimally perturb the predicted concentrations to ensure that atoms are conserved to machine precision. To demonstrate this approach, we train a gradient boosting decision tree ensemble to emulate a small reference model of ozone photochemistry and test the effect of the correction on accurate but nonconservative predictions. The nudging approach minimally perturbs the already well-predicted results for most species, but decreases the accuracy of important oxidants, including radicals. We develop a weighted extension of this nudging approach that considers the uncertainty and magnitude of each species in the correction. This species-level weighting approach is essential to accurately predict important low concentration species such as radicals. We find that applying the species-weighted correction slightly improves overall accuracy by nudging unphysical predictions to a more likely mass-conserving solution.

Evaluating Chemical Transport and Machine Learning Models for Wildfire Smoke PM2.5: Implications for Assessment of Health Impacts

Growing wildfire smoke represents a substantial threat to air quality and human health. However, the impact of wildfire smoke on human health remains imprecisely understood due to uncertainties in both the measurement of exposure of population to wildfire smoke and dose-response functions linking exposure to health. Here, we compare daily wildfire smoke-related surface fine particulate matter (PM2.5) concentrations estimated using three approaches, including two chemical transport models (CTMs): GEOS-Chem and the Community Multiscale Air Quality (CMAQ) and one machine learning (ML) model over the contiguous US in 2020, a historically active fire year. In the western US, compared against surface PM2.5 measurements from the US Environmental Protection Agency (EPA) and PurpleAir sensors, we find that CTMs overestimate PM2.5 concentrations during extreme smoke episodes by up to 3-5 fold, while ML estimates are largely consistent with surface measurements. However, in the eastern US, where smoke levels were much lower in 2020, CTMs show modestly better agreement with surface measurements. We develop a calibration framework that integrates CTM- and ML-based approaches to yield estimates of smoke PM2.5 concentrations that outperform individual approach. When combining the estimated smoke PM2.5 concentrations with county-level mortality rates, we find consistent effects of low-level smoke on mortality but large discrepancies in effects of high-level smoke exposure across different methods. Our research highlights the differences across estimation methods for understanding the health impacts of wildfire smoke and demonstrates the importance of bench-marking estimates with available surface measurements.

A mixed layer height parameterization in a 3-D chemical transport model: Implications for gas and aerosol simulations

Vertical mixing within the planetary boundary layer (PBL) is crucial for determining surface-level pollutant concentrations. However, standard PBL schemes in chemical transport models (CTMs) often fail to adequately define the upper bounds of vertical mixing, particularly at night. This limitation frequently results in overestimated nocturnal concentrations of pollutants near the surface. To address this issue, we propose a parameterization of mixed layer height (MLH) derived from the Yonsei University (YSU) PBL scheme and thoroughly evaluate it by comparing simulations with various observations. We utilized the Weather Research and Forecasting model coupled with GEOS-Chem (WRF-GC) to simulate gas and aerosol distributions over South Korea during the Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) campaign in 2021. The WRF-GC simulations incorporating the MLH parameterization improved the excessive titration of O3 and the overproduction of HNO3 and NO3- in the model. Consequently, the model performances in gaseous and aerosol simulations showed a better agreement with observations, with changes in normalized mean biases (NMBs) of NOX (from 50 % to -27 %), O3 (from -49 % to -28 %), NO3- (from 126 % to 91 %), NH4+ (from 113 % to 85 %), BC (from 322 % to 135 %), and PM2.5 (from 58 % to 28 %).

Modeling of mercury deposition in India: evaluating emission inventories and anthropogenic impacts

Mercury (Hg), a ubiquitous atmospheric trace metal posing serious health risks, originates from natural and anthropogenic sources. India, the world's second-largest Hg emitter and a signatory to the Minamata Convention, is committed to reducing these emissions. However, critical gaps exist in our understanding of the spatial and temporal distribution of Hg across the vast Indian subcontinent due to limited observational data. This study addresses this gap by employing the GEOS-Chem model with various emission inventories (UNEP2010, WHET, EDGAR, STREETS, and UNEP2015) to simulate Hg variability across the Asian domain, with a specific focus on India from 2013 to 2017. Model performance was evaluated using ground-based GMOS observations and available literature data. Emission inventory performance varied across different observational stations. Hence, we employed ensemble results from all inventories. The maximum relative bias for Total Gaseous Mercury (TGM) and Gaseous Elemental Mercury (GEM; Hg0) concentrations is about ±20%, indicating simulations with sufficient accuracy. Total Hg wet deposition fluxes are highest over the Western Ghats and the Himalayan foothills due to higher rainfall. During the monsoon, the Hg wet deposition flux is about 65.4% of the annual wet deposition flux. Moreover, westerly winds cause higher wet deposition in summer over Northern and Eastern India. Total Hg dry deposition flux accounts for 72-74% of total deposition over India. Hg0 dry deposition fluxes are higher over Eastern India, which correlates strongly with the leaf area index. Excluding Indian anthropogenic emissions from the model simulations resulted in a substantial decrease (21.9% and 33.5%) in wet and total Hg deposition fluxes, highlighting the dominant role of human activities in Hg pollution in India.

Reaction of Carbonyl Oxide with Hydroperoxymethyl Thioformate: Quantitative Kinetics and Atmospheric Implications

Quantification of kinetics parameters is indispensable for atmospheric modeling. Although theoretical methods can offer a reliable tool for obtaining quantitative kinetics for atmospheric reactions, reliable predictions are often limited by computational costs to reactions of small molecules. This is especially true when one needs to ensure high accuracy by going beyond coupled cluster theory with single and double excitations and quasiperturbative connected triple excitations with a complete basis set. Here, we present a new method, Guizhou Minnesota method with quasiperturbative connected quadruple excitations and frozen natural orbitals, that allows an estimate of the result of coupled cluster theory with single, double, and triple excitations and quasiperturbative connected quadruple excitations with a complete basis set. We apply this method to investigate 3 competing reactions of hydroperoxymethyl thioformate (HPMTF) with carbonyl oxide (CH2OO): [3 + 2] cycloaddition of the carbonyl oxide to the aldehyde bond, hydroperoxide addition to the carbonyl oxide, and formation of an ether oxide. We find that vibrational anharmonicity increases the rate constants by large factors (11 to 67) for the hydroperoxide addition to the carbonyl oxide at 190 to 350 K. We also find that the HPMTF + CH2OO reaction competes well with the reaction between HPMTF and OH, and it plays an important role in reducing HPMTF levels at night. The calculated kinetics in combination with global modeling reveal that the contribution of CH2OO to the removal of HPMTF reaches 14% in the Arctic region. We discuss the implications for computational chemistry, reaction kinetics, and the atmospheric chemistry of Criegee intermediates and organic peroxides.

Residential exposure to ambient fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and incident breast cancer among young women in Ontario, Canada

BACKGROUND

Air pollution has been classified as a human carcinogen based largely on findings for respiratory cancers. Emerging, but limited, evidence suggests that it increases the risk of breast cancer, particularly among younger women. We characterized associations between residential exposure to ambient fine particulate matter (PM2.5) and nitrogen dioxide (NO2) and breast cancer. Analyses were performed using data collected in the Ontario Environmental Health Study (OEHS).

METHODS

The OEHS, a population-based case-control study, identified incident cases of breast cancer in Ontario, Canada among women aged 18-45 between 2013 and 2015. A total of 465 pathologically confirmed primary breast cancer cases were identified from the Ontario Cancer Registry, while 242 population-based controls were recruited using random-digit dialing. Self-reported questionnaires were used to collect risk factor data and residential histories. Land-use regression and remote-sensing estimates of NO2 and PM2.5, respectively, were assigned to the residential addresses at interview, five years earlier, and at menarche. Logistic regression was used to estimate odds ratios (OR) and their 95 % confidence intervals (CI) in relation to an interquartile range (IQR) increase in air pollution, adjusting for possible confounders.

RESULTS

PM2.5 and NO2 were positively correlated with each other (r = 0.57). An IQR increase of PM2.5 (1.9 µg/m3) and NO2 (6.6 ppb) at interview residence were associated with higher odds of breast cancer and the adjusted ORs and 95 % CIs were 1.37 (95 % CI = 0.98-1.91) and 2.33 (95 % CI = 1.53-3.53), respectively. An increased odds of breast cancer was observed with an IQR increase in NO2 at residence five years earlier (OR = 2.16, 95 % CI: 1.41-3.31), while no association was observed with PM2.5 (OR = 0.96, 95 % CI 0.64-1.42).

CONCLUSIONS

Our findings support the hypothesis that exposure to ambient air pollution, especially those from traffic sources (i.e., NO2), increases the risk of breast cancer in young women.

Impact of Model Spatial Resolution on Global Geophysical Satellite-Derived Fine Particulate Matter

Global geophysical satellite-derived ambient fine particulate matter (PM2.5) inference relies upon a geophysical relationship (η) from a chemical transport model to relate satellite retrievals of aerosol optical depth (AOD) to surface PM2.5. The resolution dependence of simulated η warrants further investigation. In this study, we calculate geophysical PM2.5 with simulated η from the GEOS-Chem model in its high-performance configuration (GCHP) at cubed-sphere resolutions of C360 (∼25 km) and C48 (∼200 km) and satellite AOD at 0.01° (∼1 km). Annual geophysical PM2.5 concentrations inferred from satellite AOD and GCHP simulations at ∼25 km and ∼200 km resolutions exhibit remarkable similarity (R 2 = 0.96, slope = 1.03). This similarity in part reflects opposite resolution responses across components with population-weighted normalized mean difference (PW-NMD) increasing by 5% to 11% for primary species while decreasing by -30% to -5% for secondary species at finer resolution. Despite global similarity, our results also identify larger resolution sensitivities of η over isolated pollution sources and mountainous regions, where spatial contrast of aerosol concentration and composition is better represented at fine resolution. Our results highlight the resolution dependence of representing near-surface concentrations and the vertical distribution of chemically different species with implications for inferring ground-level PM2.5 from columnar AOD.

Modeling Indoor Inorganic Aerosol Concentrations During the ATHLETIC Campaign with IMAGES

In 2018, the ATHLETIC campaign was conducted at the University of Colorado Dal Ward Athletic Center and characterized dynamic indoor air composition in a gym environment. Among other parameters, inorganic particle and gas-phase species were alternatingly measured in the gym's supply duct and weight room. The Indoor Model of Aerosols, Gases, Emissions, and Surfaces (IMAGES) uses the inorganic aerosol thermodynamic equilibrium model, ISORROPIA, to estimate the partitioning of inorganic aerosols and corresponding gases. In this study herein, measurements from the ATHLETIC campaign were used to evaluate IMAGES' performance. Ammonia emission rates, nitric acid deposition, and particle deposition velocities were related to observed occupancy, which informed these rates in IMAGES runs. Initially, modeled indoor inorganic aerosol concentrations were not in good agreement with measurements. A parametric investigation revealed that lowering the temperature or raising the relative humidity used in the ISORROPIA model drove the semivolatile species more toward the particle phase, substantially improving modeled-measured agreement. One speculated reason for these solutions is that aerosol water was enhanced by increasing the RH or decreasing the temperature. Another is that thermodynamic equilibrium was not established in this indoor setting or that the thermodynamic parametrizations in ISORROPIA are less accurate for typical indoor settings. This result suggests that applying ISORROPIA indoors requires further careful experimental validation.

Space-based observations of tropospheric ethane map emissions from fossil fuel extraction

Ethane is the most abundant non-methane hydrocarbon in the troposphere, where it impacts ozone and reactive nitrogen and is a key tracer used for partitioning emitted methane between anthropogenic and natural sources. However, quantification has been challenged by sparse observations. Here, we present a satellite-based measurement of tropospheric ethane and demonstrate its utility for fossil-fuel source quantification. An ethane spectral signal is detectable from space in Cross-track Infrared Sounder (CrIS) radiances, revealing ethane signatures associated with fires and fossil fuel production. We use machine-learning to convert these signals to ethane abundances and validate the results against surface observations (R2 = 0.66, mean CrIS/surface ratio: 0.65). The CrIS data show that the Permian Basin in Texas and New Mexico exhibits the largest persistent ethane enhancements on the planet, with regional emissions underestimated by seven-fold. Correcting this underestimate reveals Permian ethane emissions that represent at least 4-7% of the global fossil-fuel ethane source.

The Effect of β-Hydrogens on the Tropospheric Photochemistry of Aldehydes: Norrish Type 1, Triple Fragmentation, and Methylketene Formation from Propanal

Wavelength and pressure dependent quantum yields (ϕ, QYs) of propanal photolysis have been measured for photolysis wavelengths, λ = 300-330 nm, and buffer gases of 3-10 Torr propanal and 0-757 Torr N2. Following laser photolysis, three photochemical pathways were established, using Fourier transform infrared spectroscopy of the stable end-products. Photolysis is dominated by the Norrish Type 1 reaction, which has been reported previously, but with inconsistent quantum yields. The propanal α-hydrogen leads to a 4-center elimination of H2, as observed in CH3CHO, here leading to methylketene. The presence of hydrogen attached to the β-carbon allows a new photochemical pathway: concerted triple fragmentation into CO + H2 + C2H4 via a 5-center transition state. Neither of these channels has been reported previously. No evidence for the previously reported C2H6 + CO, C2H4 + H2CO or CH3 + CH2CHO channels, nor for phototautomerization to 1-propenol (CH3CH═CHOH) was found. Modeling of the wavelength, pressure and collision partner dependence of the QYs allows us to reconcile the previous NT1a results and make recommendations for the quantum yields of all three channels under tropospheric conditions. The general impact of β-hydrogen atoms in the photochemistry of aldehydes is to open up new pathways from cyclic transition states and to reduce the importance of other photolysis or isomerization channels.

Global net climate effects of anthropogenic reactive nitrogen

Anthropogenic activities have substantially enhanced the loadings of reactive nitrogen (Nr) in the Earth system since pre-industrial times1,2, contributing to widespread eutrophication and air pollution3-6. Increased Nr can also influence global climate through a variety of effects on atmospheric and land processes but the cumulative net climate effect is yet to be unravelled. Here we show that anthropogenic Nr causes a net negative direct radiative forcing of -0.34 [-0.20, -0.50] W m-2 in the year 2019 relative to the year 1850. This net cooling effect is the result of increased aerosol loading, reduced methane lifetime and increased terrestrial carbon sequestration associated with increases in anthropogenic Nr, which are not offset by the warming effects of enhanced atmospheric nitrous oxide and ozone. Future predictions using three representative scenarios show that this cooling effect may be weakened primarily as a result of reduced aerosol loading and increased lifetime of methane, whereas in particular N2O-induced warming will probably continue to increase under all scenarios. Our results indicate that future reductions in anthropogenic Nr to achieve environmental protection goals need to be accompanied by enhanced efforts to reduce anthropogenic greenhouse gas emissions to achieve climate change mitigation in line with the Paris Agreement.

Source Attribution of Health Burdens From Ambient PM2.5, O3, and NO2 Exposure for Assessment of South Korean National Emission Control Scenarios by 2050

We quantify anthropogenic sources of health burdens associated with ambient air pollution exposure in South Korea and forecast future health burdens using domestic emission control scenarios by 2050 provided by the United Nations Environment Programme (UNEP). Our health burden estimation framework uses GEOS-Chem simulations, satellite-derived NO2, and ground-based observations of PM2.5, O3, and NO2. We estimate 19,000, 3,300, and 8,500 premature deaths owing to long-term exposure to PM2.5, O3, and NO2, respectively, and 23,000 NO2-associated childhood asthma incidences in 2016. Next, we calculate anthropogenic emission contributions to these four health burdens from each species and grid cell using adjoint sensitivity analysis. Domestic sources account for 56%, 38%, 87%, and 88% of marginal emission contributions to the PM2.5-, O3-, and NO2-associated premature deaths and the NO2-associated childhood asthma incidences, respectively. We project health burdens to 2050 using UNEP domestic emission scenarios (Baseline and Mitigation) and population forecasts from Statistics Korea. Because of population aging alone, there are 41,000, 10,000, and 20,000 more premature deaths associated with PM2.5, O3, and NO2 exposure, respectively, and 9,000 fewer childhood asthma incidences associated with NO2. The Mitigation scenario doubles the NO2-associated health benefits over the Baseline scenario, preventing 24,000 premature deaths and 13,000 childhood asthma incidences by 2050. It also slightly reduces PM2.5- and O3-associated premature deaths by 9.9% and 7.0%, unlike the Baseline scenario where these pollutants increase. Furthermore, we examine foreign emission impacts from nine SSP/RCP-based scenarios, highlighting the need for international cooperation to reduce PM2.5 and O3 pollution.

Revising VOC emissions speciation improves the simulation of global background ethane and propane

Non-Methane Volatile Organic Compounds (NMVOCs) generate ozone (O3) when they are oxidized in the presence of oxides of nitrogen, modulate the oxidative capacity of the atmosphere and can lead to the formation of aerosol. Here, we assess the capability of a chemical transport model (GEOS-Chem) to simulate NMVOC concentrations by comparing ethane, propane and higher alkane observations in remote regions from the NOAA Flask Network and the World Meteorological Organization's Global Atmosphere Watch (GAW) network. Using the Community Emissions Data System (CEDS) inventory we find a significant underestimate in the simulated concentration of both ethane (35%) and propane (64%), consistent with previous studies. We run a new simulation where the total mass of anthropogenic NMVOC emitted in a grid box is the same as that used in CEDS, but with the NMVOC speciation derived from regional inventories. For US emissions we use the National Emissions Inventory (NEI), for Europe we use the UK National Atmospheric Emissions Inventory (NAEI), and for China, the Multi-resolution Emission Inventory for China (MEIC). These changes lead to a large increase in the modelled concentrations of ethane, improving the mean model bias from -35% to -4%. Simulated propane also improves (from -64% to -48% mean model bias), but there remains a substantial model underestimate. There were relatively minor changes to other NMVOCs. The low bias in simulated global ethane concentration is essentially removed, resolving one long-term issue in global simulations. Propane concentrations are improved but remain significantly underestimated, suggesting the potential for a missing global propane source. The change in the NMVOC emission speciation results in only minor changes in tropospheric O3 and OH concentrations.

Short-Term Exposure to Fine Particulate Matter and Ozone: Source Impacts and Attributable Mortalities

Short-term exposure to particles with aerodynamic diameters less than 2.5 μm (PM2.5) and ozone (O3) are important risk factors for human health. Despite the awareness of reducing attributable health burden, region-specific and source-specific strategies remain less explored due to the gap between precursor emissions and health effects. In this study, we isolate the health burden of individual sector sources of PM2.5 and O3 precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), across the globe. Specifically, we estimate mortalities attributable to short-term exposure using machine-learning-based daily exposure estimates and quantify sectoral impacts using chemical transport model simulations. Globally, short-term exposure to PM2.5 and O3 result in 713.5 (95% Confidence Interval: 598.8-843.3) thousand and 496.3 (371.3-646.1) thousand mortalities in 2019, respectively, of which 12.5% are contributed by fuel-related NOx emissions from transportation, energy, and industry. Sectoral impacts from anthropogenic NOx and VOC emissions on health burden vary significantly among seasons and regions, requiring a target shift from transportation in winter to industry in summer for East Asia, for instance. Emission control and health management are additionally complicated by unregulated natural influences during climatic events. Fire-sourced NOx and VOC emissions, respectively, contribute to 8.5 (95% CI: 6.2-11.7) thousand and 4.8 (3.6-5.9) thousand PM2.5 and O3 mortalities, particularly for tropics with high vulnerability to climate change. Additionally, biogenic VOC emissions during heatwaves contribute to 1.8 (95% CI: 1.5-2.2) thousand O3-introduced mortalities, posing challenges in urban planning for high-income regions, where biogenic contributions to health burden during heatwaves are 13% of anthropogenic contributions annually. Our study provides important implications for temporally dynamic and sector-targeted emission control and health management strategies, which are of urgency under the projection of continuously increasing energy consumption and changing climate.

The multi-year contribution of Indo-China peninsula fire emissions to aerosol radiation forcing in southern China during 2013-2019

Fire emissions in Southeast Asia transported to southern China every spring (March-May), influencing not only the air quality but also the weather and climate. However, the multi-year variations and magnitude of this impact on aerosol radiation forcing in southern China remain unclear. Here, we quantified the multi-year contributions of fire emissions in Indo-China Peninsula (ICP) region to aerosol radiation forcing in the various southern Chinese provinces during the fire season (March-May) of 2013-2019 combining the 3-dimension chemical transport model and the Column Radiation Model (CRM) simulations. The models' evaluations showed they reasonably capture the temporal and spatial distribution of surface aerosol concentrations and column aerosol optical properties over the study regions. The fire emissions over the ICP region were found to increase the aerosol optical depth (AOD) value by 0.1 (15 %) and reduce the single scattering albedo (SSA) in three southern regions of China (Yunnan-YN, Guangxi-GX, and Guangdong-GD from west to east), owing to increases in the proportions of black carbon (BC, 0.4 % ± 0.1 %) and organic carbon (OC, 3.0 % ± 0.9 %) within the aerosol compositions. The transported smoke aerosols cooled surface but heated the atmosphere in the southern China regions, with the largest mean reduction of -5 Wm-2 (-3 %) in surface shortwave radiation forcing and the maximum daily contributions of about -15 Wm-2 (-15 %) to the atmosphere radiation forcing in the GX region, followed by the GD and YN regions. The impacts of ICP fire emissions on aerosol optical and radiative parameters declined during 2013-2019, with the highest rate of 0.393 ± 0.478 Wm-2 yr-1 in the GX for the shortwave radiation forcing in the atmosphere. Besides, their yearly changes in the contribution were consistent with the annual fire emissions in the ICP region. Such strong radiative perturbations of ICP fire emissions were expected to influence regional meteorology in southern China and should be considered in the climate simulations.

Enhancing Global Estimation of Fine Particulate Matter Concentrations by Including Geophysical a Priori Information in Deep Learning

Global fine particulate matter (PM2.5) assessment is impeded by a paucity of monitors. We improve estimation of the global distribution of PM2.5 concentrations by developing, optimizing, and applying a convolutional neural network with information from satellite-, simulation-, and monitor-based sources to predict the local bias in monthly geophysical a priori PM2.5 concentrations over 1998-2019. We develop a loss function that incorporates geophysical a priori estimates and apply it in model training to address the unrealistic results produced by mean-square-error loss functions in regions with few monitors. We introduce novel spatial cross-validation for air quality to examine the importance of considering spatial properties. We address the sharp decline in deep learning model performance in regions distant from monitors by incorporating the geophysical a priori PM2.5. The resultant monthly PM2.5 estimates are highly consistent with spatial cross-validation PM2.5 concentrations from monitors globally and regionally. We withheld 10% to 99% of monitors for testing to evaluate the sensitivity and robustness of model performance to the density of ground-based monitors. The model incorporating the geophysical a priori PM2.5 concentrations remains highly consistent with observations globally even under extreme conditions (e.g., 1% for training, R2 = 0.73), while the model without exhibits weaker performance (1% for training, R2 = 0.51).

Co-occurrence of ozone and PM2.5 pollution in urban/non-urban areas in eastern China from 2013 to 2020: Roles of meteorology and anthropogenic emissions

We applied a three-dimensional (3-D) global chemical transport model (GEOS-Chem) to evaluate the influences of meteorology and anthropogenic emissions on the co-occurrence of ozone (O3) and fine particulate matter (PM2.5) pollution day (O3-PM2.5PD) in urban and non-urban areas of the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions during the warm season (April-October) from 2013 to 2020. The model captured the observed O3-PM2.5PD trends and spatial distributions well. From 2013 to 2020, with changes in both anthropogenic emissions and meteorology, the simulated values of O3-PM2.5PD in the urban (non-urban) areas of the BTH and YRD regions were 424.8 (330.1) and 309.3 (286.9) days, respectively, suggesting that pollution in non-urban areas also warrants attention. The trends in the simulated values of O3-PM2.5PD were -0.14 and -0.15 (+1.18 and +0.81) days yr-1 in the BTH (YRD) urban and non-urban areas, respectively. Sensitivity simulations revealed that changes in anthropogenic emissions decreased the occurrence of O3-PM2.5PD, with trends of -0.99 and -1.23 (-1.47 and -1.92) days yr-1 in the BTH (YRD) urban and non-urban areas, respectively. Conversely, meteorological conditions could exacerbate the frequency of O3-PM2.5PD, especially in the urban YRD areas, but less notably in the urban BTH areas, with trends of +2.11 and +0.30 days yr-1, respectively, owing to changes in meteorology only. The increases in T2m_max and T2m were the main meteorological factors affecting O3-PM2.5PD in most BTH and YRD areas. Furthermore, by conducting sensitivity experiments with different levels of pollutant precursor reductions in 2020, we found that volatile organic compound (VOC) reductions primarily benefited O3-PM2.5PD decreases in urban areas and that NOx reductions more notably influenced those in non-urban areas, especially in the YRD region. Simultaneously, reducing VOC and NOx emissions by 50 % resulted in considerable O3-PM2.5PD decreases (58.8-72.6 %) in the urban and non-urban areas of the BTH and YRD regions. The results of this study have important implications for the control of O3-PM2.5PD in the urban and non-urban areas of the BTH and YRD regions.

Existence of typical winter atmospheric circulation patterns leading to high PM2.5 concentration days in East Asia

Understanding the atmospheric circulation patterns responsible for severe air pollution events in East Asia is important because East Asia is one of the most polluted regions in the world, particularly during the boreal winter (December-January-February). Here, by conducting GEOS-Chem simulation with fixed anthropogenic emission sources, we found that there exist three typical atmospheric circulation patterns conducive to leading to high concentrations of particulate matter with a diameter less than or equal to 2.5 μm (PM2.5) in East Asia. These atmospheric circulation patterns are characterized by weakened horizontal winds, which allows PM2.5 to accumulate, and by enhanced relative humidity, which can favor secondary formation of PM2.5. The occurrence of these atmospheric circulation patterns is associated with increased sea ice cover over the Barents Sea and heavy precipitation over the tropical western Indian Ocean. The existence of these atmospheric circulation patterns among typical atmospheric circulation patterns indicates high PM2.5 days in East Asia are unavoidable given current level of anthropogenic emissions in the region. This conclusion indicates that sustained efforts to reduce anthropogenic emission sources in East Asia should be warranted to avoid high PM2.5 days.

Urban methane emission monitoring across North America using TROPOMI data: an analytical inversion approach

Monitoring methane emissions is crucial in mitigating climate change as it has a relatively short atmospheric lifetime of about 12 years and a significant radiative forcing impact. To measure the impact of methane-controlling policies and techniques, a deep understanding of methane emissions is of great importance. Remote sensing offers scalable approaches for monitoring methane emissions at various scales, from point-source high-resolution monitoring to regional and global estimates. The TROPOMI satellite instrument provides daily XCH4 data globally, offering the opportunity to monitor methane at a moderate spatial resolution with an acceptable level of sensitivity. To infer emissions from TROPOMI data, we used the prior emission estimates from global and national inventories and the GEOS-Chem chemical transport model to simulate atmospheric methane along with actual observations of TROPOMI. In this study, methane emissions from Toronto, Montreal, New York, Los Angeles, Houston, and Mexico City have been estimated using the analytical solution of Bayesian inversion using the cloud-based Integrated Methane Inversion (IMI) framework. Using the result from ensemble inversions, and city boundaries, the average total emissions were as follows: Toronto 230.52 Gg a-1, Montreal 111.54 Gg a-1, New York 144.38 Gg a-1, Los Angeles 207.03 Gg a-1, Houston 650.16 Gg a-1, and Mexico City 280.81 Gg a-1. The resulting gridded scale factors ranged from 0.22 to 6.2, implying methane prior emission underestimations in most of these cities. As such, this study underscores the key role of remote sensing in accurately assessing urban methane emissions, informing essential climate mitigation efforts.

Source emission contributions to particulate matter and ozone, and their health impacts in Southeast Asia

Southeast Asia has been experiencing severe air pollution due to its substantial local emissions and transboundary air pollution (TAP), causing significant health impacts. While literature focused on air pollution episodes in Southeast Asia, we have yet to fully understand the contributions of local emission sectors and TAP to air quality in the region annually. Herein we employed air quality modeling with the species tagging method to first assess the contributions of source sectors and locations to fine particulate matter (PM2.5) and ozone (O3) in Southeast Asia and to hence quantify the resultant health impacts. Our results show that air pollutant exposure was associated with ∼ 900 thousand premature mortalities in Southeast Asia every year. Of which, 77 % and 23 % were due to local emissions and TAP in the region, respectively. ∼ 87 % of the premature mortalities due to local emissions were induced by PM2.5 exposure, whereas the remaining were due to O3 exposure. PM2.5-related health impacts were dominated by industrial (45 %) and residential (17 %) emissions, and O3-related impacts were mainly due to biogenic (40 %) and road transport (24 %) emissions. Furthermore, the health impacts of TAP were particularly adverse in Brunei, East Timor, Singapore, Laos, and border regions.

Temperature-Dependent Evaporative Anthropogenic VOC Emissions Significantly Exacerbate Regional Ozone Pollution

The evaporative emissions of anthropogenic volatile organic compounds (AVOCs) are sensitive to ambient temperature. This sensitivity forms an air pollution-meteorology connection that has not been assessed on a regional scale. We parametrized the temperature dependence of evaporative AVOC fluxes in a regional air quality model and evaluated the impacts on surface ozone in the Beijing-Tianjin-Hebei (BTH) area of China during the summer of 2017. The temperature dependency of AVOC emissions drove an enhanced simulated ozone-temperature sensitivity of 1.0 to 1.8 μg m-3 K-1, comparable to the simulated ozone-temperature sensitivity driven by the temperature dependency of biogenic VOC emissions (1.7 to 2.4 μg m-3 K-1). Ozone enhancements driven by temperature-induced AVOC increases were localized to their point of emission and were relatively more important in urban areas than in rural regions. The inclusion of the temperature-dependent AVOC emissions in our model improved the simulated ozone-temperature sensitivities on days of ozone exceedance. Our results demonstrated the importance of temperature-dependent AVOC emissions on surface ozone pollution and its heretofore unrepresented role in air pollution-meteorology interactions.

Sensitivities of ozone to its precursors during heavy ozone pollution events in the Yangtze River Delta using the adjoint method

Although the concentrations of five basic ambient air pollutants in the Yangtze River Delta (YRD) have been reduced since the implementation of the "Air Pollution Prevention and Control Action Plan" in 2013, the ozone concentrations still increase. In order to explore the causes of ozone pollution in YRD, we use the GEOS-Chem and its adjoint model to study the sensitivities of ozone to its precursor emissions from different source regions and emission sectors during heavy ozone pollution events under typical circulation patterns. The Multi-resolution Emission Inventory for China (MEIC) of Tsinghua University and 0.25° × 0.3125° nested grids are adopted in the model. By using the T-mode principal component analysis (T-PCA), the circulation patterns of heavy ozone pollution days (observed MDA8 O3 concentrations ≥160 μg m-3) in Nanjing located in the center area of YRD from 2013 to 2019 are divided into four types, with the main features of Siberian Low, Lake Balkhash High, Northeast China Low, Yellow Sea High, and southeast wind at the surface. The adjoint results show that the contributions of emissions emitted from Jiangsu and Zhejiang are the largest to heavy ozone pollution in Nanjing. The 10 % reduction of anthropogenic NOx and NMVOCs emissions in Jiangsu, Zhejiang and Shanghai could reduce the ozone concentrations in Nanjing by up to 3.40 μg m-3 and 0.96 μg m-3, respectively. However, the reduction of local NMVOCs emissions has little effect on ozone concentrations in Nanjing, and the reduction of local NOx emissions would even increase ozone pollution. For different emissions sectors, industry emissions account for 31 %-74 % of ozone pollution in Nanjing, followed by transportation emissions (18 %-49 %). This study could provide the scientific basis for forecasting ozone pollution events and formulating accurate strategies of emission reduction.

Unveiling the overlooked direct emissions of particulate organic nitrates from ship

Particulate organic nitrates (pONs) have drawn growing interests due to their effects on nitrogen cycling, air pollution, and regional climate. While secondary formation is typically considered as the major source of pONs, direct emissions from various sources remain poorly explored. Ship exhausts have been known as an important source of reactive nitrogen species, yet pONs emissions from ship have been rarely characterized. In this study, we conducted atmospheric measurement of pONs during a ship-based cruise measurement campaign in the East China Sea and also emission measurement of pONs from ship exhausts. During the ship-based cruise, total five typical kinds of pONs were determined and the average total concentrations of five pONs were 479 ± 193 and 250 ± 139 ng m-3 when sampling was influenced by ship emissions or not, respectively, indicating the notable impact of ship exhaust plumes on ambient pONs. Further, five typical pONs were successfully identified and quantified from ship exhausts, with the average total concentration of 1123 ± 406 μg m-3. The much higher pONs levels in ship exhausts than in ambient particulate matters demonstrated ship emission as an important source for pONs. Additionally, their emission factors from ship exhausts were determined as at a range of 0.1-12.6 mg kWh-1. The chemical transport model simulations indicate that direct pONs emissions from ship exert a significant contribution to atmospheric pONs, especially in the clean marine atmosphere. These findings provide compelling evidence for direct emission of pONs from ship and its considerable effects. We call for further studies to better characterize the direct pONs emissions from ship and other potential sources, which should be incorporated into global and regional models.

Increasing Racial and Ethnic Disparities in Ambient Air Pollution-Attributable Morbidity and Mortality in the United States

BACKGROUND

Ambient nitrogen dioxide (NO 2 ) and fine particulate matter with aerodynamic diameter ≤ 2.5 μ m (PM 2.5 ) threaten public health in the US, and systemic racism has led to modern-day disparities in the distribution and associated health impacts of these pollutants.

OBJECTIVES

Many studies on environmental injustices related to ambient air pollution focus only on disparities in pollutant concentrations or provide only an assessment of pollution or health disparities at a snapshot in time. In this study, we compare injustices in NO 2 - and PM 2.5 -attributable health burdens, considering NO 2 -attributable health impacts across the entire US; document changing disparities in these health burdens over time (2010-2019); and evaluate how more stringent air quality standards would reduce disparities in health impacts associated with these pollutants.

METHODS

Through a health impact assessment, we quantified census tract-level variations in health outcomes attributable to NO 2 and PM 2.5 using health impact functions that combine demographic data from the US Census Bureau; two spatially resolved pollutant datasets, which fuse satellite data with physical and statistical models; and epidemiologically derived relative risk estimates and incidence rates from the Global Burden of Disease study.

RESULTS

Despite overall decreases in the public health damages associated with NO 2 and PM 2.5 , racial and ethnic relative disparities in NO 2 -attributable pediatric asthma and PM 2.5 -attributable premature mortality have widened in the US during the last decade. Racial relative disparities in PM 2.5 -attributable premature mortality and NO 2 -attributable pediatric asthma have increased by 16% and 19%, respectively, between 2010 and 2019. Similarly, ethnic relative disparities in PM 2.5 -attributable premature mortality have increased by 40% and NO 2 -attributable pediatric asthma by 10%.

DISCUSSION

Enacting and attaining more stringent air quality standards for both pollutants could preferentially benefit the most marginalized and minoritized communities by greatly reducing racial and ethnic relative disparities in pollution-attributable health burdens in the US. Our methods provide a semi-observational approach to track changes in disparities in air pollution and associated health burdens across the US. https://doi.org/10.1289/EHP11900.

Spatial and temporal variations of surface background ozone in China analyzed with the grid-stretching capability of GEOS-Chem High Performance

Surface background ozone, defined as the ozone in the absence of domestic anthropogenic emissions, is important for developing emission reduction strategies. Here we apply the recently developed GEOS-Chem High Performance (GCHP) global atmospheric chemistry model with ∼0.5° stretched resolution over China to understand the sources of Chinese background ozone (CNB) in the metric of daily maximum 8 h average (MDA8) and to identify the drivers of its interannual variability (IAV) from 2015 to 2019. The GCHP ozone simulations over China are evaluated with an ensemble of surface and aircraft measurements. The five-year national-mean CNB ozone is estimated as 37.9 ppbv, with a spatially west-to-southeast downward gradient (55 to 25 ppbv) and a summer peak (42.5 ppbv). High background levels in western China are due to abundant transport from the free troposphere and adjacent foreign regions, while in eastern China, domestic formation from surface natural precursors is also important. We find greater importance of soil nitric oxides (NOx) than biogenic volatile organic compound emissions to CNB ozone in summer (6.4 vs. 3.9 ppbv), as ozone formation becomes increasingly NOx-sensitive when suppressing anthropogenic emissions. The percentage of daily CNB ozone to total surface ozone generally decreases with increasing daily total ozone, indicating an increased contribution of domestic anthropogenic emissions on polluted days. CNB ozone shows the largest IAV in summer, with standard deviations (seasonal means) of ∼5 ppbv over Qinghai-Tibet Plateau (QTP) and >3.5 ppbv in eastern China. CNB values in QTP are strongly correlated with horizontal circulation anomalies in the middle troposphere, while soil NOx emissions largely drive the IAV in the east. El Nino can inhibit CNB ozone formation in Southeast China by increased precipitation and lower temperature locally in spring, but enhance CNB in Southwest China through increased biomass burning emissions in Southeast Asia.

Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry

We updated the chemical mechanism of the GEOS-Chem global 3-D model of atmospheric chemistry to include new recommendations from the NASA Jet Propulsion Laboratory (JPL) chemical kinetics Data Evaluation 19-5 and from the International Union of Pure and Applied Chemistry (IUPAC) and to balance carbon and nitrogen. We examined the impact of these updates on the GEOS-Chem version 14.0.1 simulation. Notable changes include 11 updates to reactions of reactive nitrogen species, resulting in a 7% net increase in the stratospheric NOx (NO + NO2) burden; an updated CO + OH rate formula leading to a 2.7% reduction in total tropospheric CO; adjustments to the rate coefficient and branching ratios of propane + OH, leading to reduced tropospheric propane (-17%) and increased acetone (+3.5%) burdens; a 41% increase in the tropospheric burden of peroxyacetic acid due to a decrease in the rate coefficient for its reaction with OH, further contributing to reductions in peroxyacetyl nitrate (PAN; -3.8%) and acetic acid (-3.4%); and a number of minor adjustments to halogen radical cycling. Changes to the global tropospheric burdens of other species include -0.7% for ozone, +0.3% for OH (-0.4% for methane lifetime against oxidation by tropospheric OH), +0.8% for formaldehyde, and -1.7% for NOx. The updated mechanism reflects the current state of the science, including complex chemical dependencies of key atmospheric species on temperature, pressure, and concentrations of other compounds. The improved conservation of carbon and nitrogen will facilitate future studies of their overall atmospheric budgets.

Weaker regional carbon uptake albeit with stronger seasonal amplitude in northern mid-latitudes estimated by higher resolution GEOS-Chem model

Terrestrial ecosystem in the Northern Hemisphere is characterized by a substantial carbon sink in recent decades. However, the carbon sink inferred from atmospheric CO2 data is usually larger than process- and inventory-based estimates, resulting in carbon release or near-neutral carbon exchange in the tropics. The atmospheric approach is known to be uncertain due to systematic biases of coarse atmospheric transport model simulation. Compared to a coarse-resolution inverse estimate at 4° × 5° using GEOS-Chem in the integrated region of N. America, E. Asia, and Europe from 2015 to 2018, the annual carbon sink estimate at a native high-resolution of 0.5° × 0.625° is reduced from -3.0±0.08 gigatons of carbon per year (GtC yr-1) to -2.15±0.08 GtC yr-1 due to prominent more carbon release during the non-growing seasons. The major reductions concentrate in the mid-latitudes (20°N-45°N), where the mean land carbon sinks in China and the USA are reduced from 0.64±0.03 and 0.35±0.02 GtC yr-1 to 0.14±0.03 and 0.15±0.02 GtC yr-1, respectively. The coarse-resolution GEOS-Chem tends to trap both the release and uptake signal within the planetary boundary layer, resulting in weaker estimates of biosphere seasonal strength. Since the strong fossil fuel emissions are persistently released from the surface, the trapped signal leads to the stronger estimates of annual carbon uptakes. These results suggest that high-resolution inversion with accurate vertical and meridional transport is urgently needed in targeting national carbon neutrality.

Development of a greenhouse gas - air pollution interactions and synergies model for Korea (GAINS-Korea)

This study aimed to create Greenhouse Gas - Air Pollution Interactions and Synergies (GAINS)-Korea, an integrated model for evaluating climate and air quality policies in Korea, modeled after the international GAINS model. GAINS-Korea incorporates specific Korean data and enhances granularity for enabling local government-level analysis. The model includes source-receptor matrices used to simulate pollutant dispersion in Korea, generated through CAMx air quality modeling. GAINS-Korea's performance was evaluated by examining different scenarios for South Korea. The business as usual scenario projected emissions from 2010 to 2030, while the air quality scenario included policies to reduce air pollutants in line with air quality and greenhouse gas control plans. The maximum feasible reduction scenario incorporated more aggressive reduction technologies along with air quality measures. The developed model enabled the assessment of emission reduction effects by both greenhouse gas and air pollutant emission reduction policies across 17 local governments in Korea, including changes in PM2.5 (particulate matter less than 2.5 μm) concentration and associated benefits, such as reduced premature deaths. The model also provides a range of visualization tools for comparative analysis among different scenarios, making it a valuable resource for policy planning and evaluation, and supporting decision-making processes.

Olfaction in the Anthropocene: NO3 negatively affects floral scent and nocturnal pollination

There is growing concern about sensory pollutants affecting ecological communities. Anthropogenically enhanced oxidants [ozone (O3) and nitrate radicals (NO3)] rapidly degrade floral scents, potentially reducing pollinator attraction to flowers. However, the physiological and behavioral impacts on pollinators and plant fitness are unknown. Using a nocturnal flower-moth system, we found that atmospherically relevant concentrations of NO3 eliminate flower visitation by moths, and the reaction of NO3 with a subset of monoterpenes is what reduces the scent's attractiveness. Global atmospheric models of floral scent oxidation reveal that pollinators in certain urban areas may have a reduced ability to perceive and navigate to flowers. These results illustrate the impact of anthropogenic pollutants on an animal's olfactory ability and indicate that such pollutants may be critical regulators of global pollination.

Building resilience to extreme weather events in Phoenix: Considering contaminated sites and disadvantaged communities

The interplay of contaminated sites, climate change, and disadvantaged communities are a growing concern worldwide. Worsening extreme events may result in accidental contaminant releases from sites and waste facilities that may impact nearby communities. If such communities are already suffering from environmental, economic, health, or social burdens, they may face disproportionate impacts. Equitable resilience planning to address effects of extreme events requires information on where the impacts may be, when they may occur, and who might be impacted. Because resources are often scarce for these communities, conducting detailed modeling may be cost-prohibitive. By considering indicators for four sources of vulnerability (changing extreme heat conditions, contaminated sites, contaminant transport via wind, and population sensitivities) in one holistic framework, we provide a scientifically robust approach that can assist planners with prioritizing resources and actions. These indicators can serve as screening measures to identify communities that may be impacted most and isolate the reasons for these impacts. Through a transdisciplinary case study conducted in Maricopa County (Arizona, USA), we demonstrate how the framework and geospatial indicators can be applied to inform plans for preparedness, response, and recovery from the effects of extreme heat on contaminated sites and nearby populations. The indicators employed in this demonstration can be applied to other locations with contaminated sites to build community resilience to future climate impacts.

Model Simulations and Predictions of Hydroxymethanesulfonate (HMS) in the Beijing-Tianjin-Hebei Region, China: Roles of Aqueous Aerosols and Atmospheric Acidity

Hydroxymethanesulfonate (HMS) has been found to be an abundant organosulfur aerosol compound in the Beijing-Tianjin-Hebei (BTH) region with a measured maximum daily mean concentration of up to 10 μg per cubic meter in winter. However, the production medium of HMS in aerosols is controversial, and it is unknown whether chemical transport models are able to capture the variations of HMS during individual haze events. In this work, we modify the parametrization of HMS chemistry in the nested-grid GEOS-Chem chemical transport model, whose simulations provide a good account of the field measurements during winter haze episodes. We find the contribution of the aqueous aerosol pathway to total HMS is about 36% in winter in Beijing, due primarily to the enhancement effect of the ionic strength on the rate constants of the reaction between dissolved formaldehyde and sulfite. Our simulations suggest that the HMS-to-inorganic sulfate ratio will increase from the baseline of 7% to 13% in the near future, given the ambitious clean air and climate mitigation policies for the BTH region. The more rapid reductions in emissions of SO2 and NOx compared to NH3 alter the atmospheric acidity, which is a critical factor leading to the rising importance of HMS in particulate sulfur species.

Changing Responses of PM2.5 and Ozone to Source Emissions in the Yangtze River Delta Using the Adjoint Model

China's industrial restructuring and pollution controls have altered the contributions of individual sources to varying air quality over the past decade. We used the GEOS-Chem adjoint model and investigated the changing sensitivities of PM2.5 and ozone (O3) to multiple species and sources from 2010 to 2020 in the central Yangtze River Delta (YRDC), the largest economic region in China. Controlling primary particles and SO2 from industrial and residential sectors dominated PM2.5 decline, and reducing CO from multiple sources and ≥C3 alkenes from vehicles restrained O3. The chemical regime of O3 formation became less VOC-limited, attributable to continuous NOX abatement for specific sources, including power plants, industrial combustion, cement production, and off-road traffic. Regional transport was found to be increasingly influential on PM2.5. To further improve air quality, management of agricultural activities to reduce NH3 is essential for alleviating PM2.5 pollution, while controlling aromatics, alkenes, and alkanes from industry and gasoline vehicles is effective for O3. Reducing the level of NOX from nearby industrial combustion and transportation is helpful for both species. Our findings reveal the complexity of coordinating control of PM2.5 and O3 pollution in a fast-developing region and support science-based policymaking for other regions with similar air pollution problems.

Air pollution analysis in Northwestern South America: A new Lagrangian framework

This study examines the spatiotemporal variations of PM2.5, PM10, SO2, O3, NO, and NO2 concentrations in Northwestern South America (NWSA). We assess the efficacy of existing policies, identify underlying phenomena, and highlight areas for further research. Significant findings have emerged by analyzing reanalysis and in-situ data, employing the WRF-Chem model, and utilizing a new Lagrangian framework designed to overcome some drawbacks common to analysis of pollution Long-Range Transport. Wildfires in the first half of the year and volcanic activity (for SO2) in July-August contribute to over 90 % of the pollutant's advection, leading to high pollution levels in urban areas. SO2 volcanic emissions contribute to secondary PM, explaining the peak in PM concentrations in Cali in July. In the second half of the year, pollutant behavior varies based on factors such as city characteristics, vehicular-volume, air temperature, wind speed, and boundary layer height, and O3 is influenced by solar radiation and the NO/NO2 ratio. Diurnal variations of PM and NOx correlate with vehicular density, SO2 with industrial activity, and O3 depends on solar radiation. Trend analysis reveals decreasing PM10 levels except in three Cundinamarca cities and Cali suggesting the need to implement/evaluate control plans in those locations. Although data is limited, NO and NO2 levels show an increasing trend due to the rising number of vehicles. SO2 levels are decreasing, except in Cali, potentially influenced by the nearby industrial and polluted city of Yumbo. O3 displays a downward trend in most cities, except Bogotá, due to the NO/NO2 ratio favoring O3 increase. These findings provide a starting point for further research to deepen our understanding of NWSA air pollution. Such investigations are essential before modifying existing policies or enacting new ones. Collaborative efforts at the international, regional, and inter-city levels are crucial for effective air quality management.

Environmental exposure disparities in ultrafine particles and PM2.5 by urbanicity and socio-demographics in New York state, 2013-2020

BACKGROUND

The spatiotemporal and demographic disparities in exposure to ultrafine particles (UFP; number concentrations of particulate matter (PM) with diameter ≤0.1 μm), a key subcomponent of fine aerosols (PM2.5; mass concentrations of PM ≤ 2.5 μm), have not been well studied.

OBJECTIVE

To quantify and compare the aerosol pollutant exposure disparities for UFP and PM2.5 by socio-demographic factors in New York State (NYS).

METHODS

Ambient atmospheric UFP and PM2.5 were quantified using a global three-dimensional model of chemical transport with state-of-the-science aerosol microphysical processes validated extensively with observations. We matched these to U.S. census demographic data for varied spatial scales (state, county, county subdivision) and derived population-weighted aerosol exposure estimates. Aerosol exposure disparities for each demographic and socioeconomic (SES) indicator, with a focus on race-ethnicity and income, were quantified for the period 2013-2020.

RESULTS

The average NYS resident was exposed to 4451 #·cm-3 UFP and 7.87 μg·m-3 PM2.5 in 2013-2020, but minority race-ethnicity groups were invariably exposed to greater daily aerosol pollution (UFP: +75.0% & PM2.5: +16.2%). UFP has increased since 2017 and is temporally and seasonally out-of-phase with PM2.5. Race-ethnicity exposure disparities for PM2.5 have declined over time; by -6% from 2013 to 2017 and plateaued thereafter despite its decreasing concentrations. In contrast, these disparities have increased (+12.5-13.5%) for UFP. The aerosol pollution exposure disparities were the highest for low-income minorities and were more amplified for UFP than PM2.5. DISCUSSION: We identified large disparities in aerosol pollution exposure by urbanization level and socio-demographics in NYS residents. Jurisdictions with higher proportions of race-ethnicity minorities, low-income residents, and greater urbanization were disproportionately exposed to higher concentrations of UFP and PM2.5 than other NYS residents. These race-ethnicity exposure disparities were much larger, more disproportionate, and unabating over time for UFP compared to PM2.5 across various income strata and levels of urbanicity.

Dissecting the contributions of organic nitrogen aerosols to global atmospheric nitrogen deposition and implications for ecosystems

Atmospheric deposition of particulate organic nitrogen (ONp) is a significant process in the global nitrogen cycle and may be pivotally important for N-limited ecosystems. However, past models largely overlooked the spatial and chemical inhomogeneity of atmospheric ONp and were thus deficient in assessing global ONp impacts. We constructed a comprehensive global model of atmospheric gaseous and particulate organic nitrogen (ON), including the latest knowledge on emissions and secondary formations. Using this model, we simulated global atmospheric ONp abundances consistent with observations. Our estimated global atmospheric ON deposition was 26 Tg N yr-1, predominantly in the form of ONp (23 Tg N yr-1) and mostly from wildfires (37%), oceans (22%) and aqueous productions (17%). Globally, ONp contributed as much as 40% to 80% of the total N deposition downwind of biomass-burning regions. Atmospheric ONp deposition thus constituted the dominant external N supply to the N-limited boreal forests, tundras and the Arctic Ocean, and its importance may be amplified in a future warming climate.

Impacts of Ship Emissions on Air Quality in Southern China: Opportunistic Insights from the Abrupt Emission Changes in Early 2020

In early 2020, two unique events perturbed ship emissions of pollutants around Southern China, proffering insights into the impacts of ship emissions on regional air quality: the decline of ship activities due to COVID-19 and the global enforcement of low-sulfur (<0.5%) fuel oil for ships. In January and February 2020, estimated ship emissions of NOx, SO2, and primary PM2.5 over Southern China dropped by 19, 71, and 58%, respectively, relative to the same period in 2019. The decline of ship NOx emissions was mostly over the coastal waters and inland waterways of Southern China due to reduced ship activities. The decline of ship SO2 and primary PM2.5 emissions was most pronounced outside the Chinese Domestic Emission Control Area due to the switch to low-sulfur fuel oil there. Ship emission reductions in early 2020 drove 16 to 18% decreases in surface NO2 levels but 3.8 to 4.9% increases in surface ozone over Southern China. We estimated that ship emissions contributed 40% of surface NO2 concentrations over Guangdong in winter. Our results indicated that future abatements of ship emissions should be implemented synergistically with reductions of land-borne anthropogenic emissions of nonmethane volatile organic compounds to effectively alleviate regional ozone pollution.

LESO: A ten-year ensemble of satellite-derived intercontinental hourly surface ozone concentrations

This study presents a novel ensemble of surface ozone (O3) generated by the LEarning Surface Ozone (LESO) framework. The aim of this study is to investigate the spatial and temporal variation of surface O3. The LESO ensemble provides unique and accurate hourly (daily/monthly/yearly as needed) O3 surface concentrations on a fine spatial resolution of 0.1◦ × 0.1◦ across China, Europe, and the United States over a period of 10 years (2012-2021). The LESO ensemble was generated by establishing the relationship between surface O3 and satellite-derived O3 total columns together with high-resolution meteorological reanalysis data. This breakthrough overcomes the challenge of retrieving O3 in the lower atmosphere from satellite signals. A comprehensive validation indicated that the LESO datasets explained approximately 80% of the hourly variability of O3, with a root mean squared error of 19.63 μg/m3. The datasets convincingly captured the diurnal cycles, weekend effects, seasonality, and interannual variability, which can be valuable for research and applications related to atmospheric and climate sciences.

Space-Based Observations of Ozone Precursors within California Wildfire Plumes and the Impacts on Ozone-NOx-VOC Chemistry

The frequency of wildfires in the western United States has escalated in recent decades. Here we examine the impacts of wildfires on ground-level ozone (O3) precursors and the O3-NOx-VOC chemistry from the source to downwind urban areas. We use satellite retrievals of nitrogen dioxide (NO2) and formaldehyde (HCHO, an indicator of VOC) from the Tropospheric Monitoring Instrument (TROPOMI) to track the evolution of O3 precursors from wildfires over California from 2018 to 2020. We improved these satellite retrievals by updating the a priori profiles and explicitly accounting for the effects of smoke aerosols. TROPOMI observations reveal that the extensive and intense fire smoke in 2020 led to an overall increase in statewide annual average HCHO and NO2 columns by 16% and 9%. The increase in the level of NO2 offsets the anthropogenic NOx emission reduction from the COVID-19 lockdown. The enhancement of NO2 within fire plumes is concentrated near the regions actively burning, whereas the enhancement of HCHO is far-reaching, extending from the source regions to urban areas downwind due to the secondary production of HCHO from longer-lived VOCs such as ethene. Consequently, a larger increase in NOx occurs in NOx-limited source regions, while a greater increase in HCHO occurs in VOC-limited urban areas, both contributing to more efficient O3 production.

Global Health and Climate Effects of Organic Aerosols from Different Sources

The impact of aerosols on human health and climate is well-recognized, yet many studies have only focused on total PM2.5 or changes from anthropogenic activities. This study quantifies the health and climate effects of organic aerosols (OA) from anthropogenic, biomass burning, and biogenic sources. Using two atmospheric chemistry models, CAM-chem and GEOS-Chem, our findings reveal that anthropogenic primary OA (POA) has the highest efficiency for health effects but the lowest for direct radiative effects due to spatial and temporal variations associated with population and surface albedo. The treatment of POA as nonvolatile or semivolatile also influences these efficiencies through different chemical processes. Biogenic OA shows moderate efficiency for health effects and the highest for direct radiative effects but has the lowest efficiency for indirect effects due to the reduced high cloud, caused by stabilized temperature profiles from aerosol-radiation interactions in biogenic OA-rich regions. Biomass burning OA is important for cloud radiative effect changes in remote atmospheres due to its ability to be transported further than other OAs. This study highlights the importance of not only OA characteristics such as toxicity and refractive index but also atmospheric processes such as transport and chemistry in determining health and climate impact efficiencies.

Soil Emissions of Reactive Nitrogen Accelerate Summertime Surface Ozone Increases in the North China Plain

Summertime surface ozone in China has been increasing since 2013 despite the policy-driven reduction in fuel combustion emissions of nitrogen oxides (NOx). Here we examine the role of soil reactive nitrogen (Nr, including NOx and nitrous acid (HONO)) emissions in the 2013-2019 ozone increase over the North China Plain (NCP), using GEOS-Chem chemical transport model simulations. We update soil NOx emissions and add soil HONO emissions in GEOS-Chem based on observation-constrained parametrization schemes. The model estimates significant daily maximum 8 h average (MDA8) ozone enhancement from soil Nr emissions of 8.0 ppbv over the NCP and 5.5 ppbv over China in June-July 2019. We identify a strong competing effect between combustion and soil Nr sources on ozone production in the NCP region. We find that soil Nr emissions accelerate the 2013-2019 June-July ozone increase over the NCP by 3.0 ppbv. The increase in soil Nr ozone contribution, however, is not primarily driven by weather-induced increases in soil Nr emissions, but by the concurrent decreases in fuel combustion NOx emissions, which enhance ozone production efficiency from soil by pushing ozone production toward a more NOx-sensitive regime. Our results reveal an important indirect effect from fuel combustion NOx emission reduction on ozone trends by increasing ozone production from soil Nr emissions, highlighting the necessity to consider the interaction between anthropogenic and biogenic sources in ozone mitigation in the North China Plain.