Transpacific Transport of Asian Peroxyacetyl Nitrate (PAN) Observed from Satellite: Implications for Ozone

Peroxyacetyl nitrate (PAN) is produced in the atmosphere by photochemical oxidation of non-methane volatile organic compounds in the presence of nitrogen oxides (NOx), and it can be transported over long distances at cold temperatures before decomposing thermally to release NOx in the remote troposphere. It is both a tracer and a precursor for transpacific ozone pollution transported from East Asia to North America. Here, we directly demonstrate this transport with PAN satellite observations from the infrared atmospheric sounding interferometer (IASI). We reprocess the IASI PAN retrievals by replacing the constant prior vertical profile with vertical shape factors from the GEOS-Chem model that capture the contrasting shapes observed from aircraft over South Korea (KORUS-AQ) and the North Pacific (ATom). The reprocessed IASI PAN observations show maximum transpacific transport of East Asian pollution in spring, with events over the Northeast Pacific offshore from the Western US associated in GEOS-Chem with elevated ozone in the lower free troposphere. However, these events increase surface ozone in the US by less than 1 ppbv because the East Asian pollution mainly remains offshore as it circulates the Pacific High.

Interannual changes in atmospheric oxidation over forests determined from space

The hydroxyl radical (OH) is the central oxidant in Earth's troposphere, but its temporal variability is poorly understood. We combine 2012-2020 satellite-based isoprene and formaldehyde measurements to identify coherent OH changes over temperate and tropical forests with attribution to emission trends, biotic stressors, and climate. We identify a multiyear OH decrease over the Southeast United States and show that with increasingly hot/dry summers the regional chemistry could become even less oxidizing depending on competing temperature/drought impacts on isoprene. Furthermore, while global mean OH decreases during El Niño, we show that near-field effects over tropical rainforests can alternate between high/low OH anomalies due to opposing fire and biogenic emission impacts. Results provide insights into how atmospheric oxidation will evolve with changing emissions and climate.

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.

Impacts of anthropogenic emissions and meteorology on spring ozone differences in San Antonio, Texas between 2017 and 2021

San Antonio has been designated as ozone nonattainment under the current National Ambient Air Quality Standards (NAAQS). Ozone events in the city typically occur in two peaks, characterized by a pronounced spring peak followed by a late summer peak. Despite higher ozone levels, the spring peak has received less attention than the summer peak. To address this research gap, we used the Weather Research and Forecasting (WRF)-driven GEOS-Chem (WRF-GC) model to simulate San Antonio's ozone changes in the spring month of May from 2017 to 2021 and quantified the respective contributions from changes in anthropogenic emissions and meteorology. In addition to modeling, observations from the San Antonio Field Studies (SAFS), the Texas Commission on Environmental Quality (TCEQ) Continuous Ambient Monitoring Stations (CAMS), and the spaceborne TROPOspheric Monitoring Instrument (TROPOMI) are used to examine and validate changes in ozone and precursors. Results show that the simulated daytime mean surface ozone in May 2021 is 3.8 ± 0.6 ppbv lower than in May 2017, which is slightly less than the observed average differences of -5.3 ppbv at CAMS sites. The model predicted that the anthropogenic emission-induced changes contribute to a 1.4 ± 0.5 ppbv reduction in daytime ozone levels, while the meteorology-induced changes account for a 2.4 ± 0.6 ppbv reduction over 2017-2021. This suggests that meteorology plays a relatively more important role than anthropogenic emissions in explaining the spring ozone differences between the two years. We additionally identified (1) reduced NO2 and HCHO concentrations as chemical reasons, and (2) lower temperature, higher humidity, increased wind speed, and a stronger Bermuda High as meteorological reasons for lower ozone levels in 2021 compared to 2017. The quantification of the different roles of meteorology and ozone precursor concentrations helps understand the cause and variation of ozone changes in San Antonio over recent years.

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.

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.

Elucidating the mechanisms of rapid O3 increase in North China Plain during COVID-19 lockdown period

Ozone (O3) levels in North China Plain (NCP) suffered from rapid increases during the COVID-19 period. Many previous studies have confirmed more rapid NOx reduction compared with VOCs might be responsible for the O3 increase during this period, while the comprehensive impacts of each VOC species and NOx on ambient O3 and their interactions with meteorology were not revealed clearly. To clarify the detailed reasons for the O3 increase, a continuous campaign was performed in a typical industrial city of NCP. Meanwhile, the machine-learning technique and the box model were employed to reveal the mechanisms of O3 increase from the perspective of meteorology and photochemical process, respectively. The result suggested that the ambient O3 level in Tangshan increased from 18.7 ± 4.63 to 45.6 ± 8.52 μg/m3 (143%) during COVID-19 lockdown, and the emission reduction and meteorology contributed to 54 % and 46 % of this increment, respectively. The lower wind speed (WS) coupled with regional transport played a significant role on O3 increase (30.8 kg/s). The O3 sensitivity verified that O3 production was highly volatile organic compounds (VOC)-sensitive (Relative incremental reactivity (RIR): 0.75), while the NOx showed the negative impact on O3 production in Tangshan (RIR: -0.59). It suggested that the control of VOCs rather than NOx might be more effective in reducing O3 level in Tangshan because it was located on the VOC-limited regime. Besides, both of ozone formation potential (OFP) analysis and observation-based model (OBM) demonstrated that the alkenes (36.3 ppb) and anthropogenic oxygenated volatile organic compounds (OVOCs) (15.2 ppb) showed the higher OFP compared with other species, and their reactions released a large number of HO2 and RO2 radicals. Moreover, the concentrations of these species did not experience marked decreases during COVID-19 lockdown, which were major contributors to O3 increase during this period. This study also underlined the necessity of priority controlling alkenes and OVOCs across the NCP.

Synthesizing evidence for the external cycling of NOx in high- to low-NOx atmospheres

External cycling regenerating nitrogen oxides (NOx ≡ NO + NO2) from their oxidative reservoir, NOz, is proposed to reshape the temporal-spatial distribution of NOx and consequently hydroxyl radical (OH), the most important oxidant in the atmosphere. Here we verify the in situ external cycling of NOx in various environments with nitrous acid (HONO) as an intermediate based on synthesized field evidence collected onboard aircraft platform at daytime. External cycling helps to reconcile stubborn underestimation on observed ratios of HONO/NO2 and NO2/NOz by current chemical model schemes and rationalize atypical diurnal concentration profiles of HONO and NO2 lacking noontime valleys specially observed in low-NOx atmospheres. Perturbation on the budget of HONO and NOx by external cycling is also found to increase as NOx concentration decreases. Consequently, model underestimation of OH observations by up to 41% in low NOx atmospheres is attributed to the omission of external cycling in models.

Impact of Legislated and Best Available Emission Control Measures on UK Particulate Matter Pollution, Premature Mortality, and Nitrogen-Sensitive Habitats

Past emission controls in the UK have substantially reduced precursor emissions of health-hazardous fine particles (PM2.5) and nitrogen pollution detrimental to ecosystems. Still, 79% of the UK exceeds the World Health Organization (WHO) guideline for annual mean PM2.5 of 5 μg m-3 and there is no enforcement of controls on agricultural sources of ammonia (NH3). NH3 is a phytotoxin and an increasingly large contributor to PM2.5 and nitrogen deposited to sensitive habitats. Here we use emissions projections, the GEOS-Chem model, high-resolution data sets, and contemporary exposure-risk relationships to assess potential human and ecosystem health co-benefits in 2030 relative to the present day of adopting legislated or best available emission control measures. We estimate that present-day annual adult premature mortality attributable to exposure to PM2.5 is 48,625 (95% confidence interval: 45,188-52,595), that harmful amounts of reactive nitrogen deposit to almost all (95%) sensitive habitat areas, and that 75% of ambient NH3 exceeds levels safe for bryophytes and lichens. Legal measures decrease the extent of the UK above the WHO guideline to 58% and avoid 6,800 premature deaths by 2030. This improves with best available measures to 36% of the UK and 13,300 avoided deaths. Both legal and best available measures are insufficient at reducing the extent of damage of nitrogen pollution to sensitive habitats. Far more ambitious reductions in nitrogen emissions (>80%) than is achievable with best available measures (34%) are required to halve the amount of excess nitrogen deposited to sensitive habitats.

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.

Advances in Simulating the Global Spatial Heterogeneity of Air Quality and Source Sector Contributions: Insights into the Global South

High-resolution simulations are essential to resolve fine-scale air pollution patterns due to localized emissions, nonlinear chemical feedbacks, and complex meteorology. However, high-resolution global simulations of air quality remain rare, especially of the Global South. Here, we exploit recent developments to the GEOS-Chem model in its high-performance implementation to conduct 1-year simulations in 2015 at cubed-sphere C360 (∼25 km) and C48 (∼200 km) resolutions. We investigate the resolution dependence of population exposure and sectoral contributions to surface fine particulate matter (PM2.5) and nitrogen dioxide (NO2), focusing on understudied regions. Our results indicate pronounced spatial heterogeneity at high resolution (C360) with large global population-weighted normalized root-mean-square difference (PW-NRMSD) across resolutions for primary (62-126%) and secondary (26-35%) PM2.5 species. Developing regions are more sensitive to spatial resolution resulting from sparse pollution hotspots, with PW-NRMSD for PM2.5 in the Global South (33%), 1.3 times higher than globally. The PW-NRMSD for PM2.5 for discrete southern cities (49%) is substantially higher than for more clustered northern cities (28%). We find that the relative order of sectoral contributions to population exposure depends on simulation resolution, with implications for location-specific air pollution control strategies.

Satellite-Based Long-Term Spatiotemporal Trends in Ambient NO2 Concentrations and Attributable Health Burdens in China From 2005 to 2020

Despite the recent development of using satellite remote sensing to predict surface NO₂ levels in China, methods for estimating reliable historical NO₂ exposure, especially before the establishment of NO₂ monitoring network in 2013, are still rare. A gap-filling model was first adopted to impute the missing NO₂ column densities from satellite, then an ensemble machine learning model incorporating three base learners was developed to estimate the spatiotemporal pattern of monthly mean NO₂ concentrations at 0.05° spatial resolution from 2005 to 2020 in China. Further, we applied the exposure data set with epidemiologically derived exposure response relations to estimate the annual NO₂ associated mortality burdens in China. The coverage of satellite NO₂ column densities increased from 46.9% to 100% after gap-filling. The ensemble model predictions had good agreement with observations, and the sample-based, temporal and spatial cross-validation (CV) R ² were 0.88, 0.82, and 0.73, respectively. In addition, our model can provide accurate historical NO₂ concentrations, with both by-year CV R ² and external separate year validation R ² achieving 0.80. The estimated national NO₂ levels showed a increasing trend during 2005-2011, then decreased gradually until 2020, especially in 2012-2015. The estimated annual mortality burden attributable to long-term NO₂ exposure ranged from 305 thousand to 416 thousand, and varied considerably across provinces in China. This satellite-based ensemble model could provide reliable long-term NO₂ predictions at a high spatial resolution with complete coverage for environmental and epidemiological studies in China. Our results also highlighted the heavy disease burden by NO₂ and call for more targeted policies to reduce the emission of nitrogen oxides in China.

The importance of ammonia for springtime atmospheric new particle formation and aerosol number abundance over the United States

New particle formation (NPF) and subsequent growth can contribute upwards of 50 % of the global cloud condensation nuclei (CCN) budget. It is also a significant source of ultrafine aerosols (PM_0.1) with health implications. Ammonia (NH₃) can play a significant role in enhancing NPF and contributing to the growth of nucleated particles. Understanding these processes are vital for air quality and climate. Here, we examine the role of NH₃ in NPF and consequent effects on aerosol number concentrations (including CCN) and size distributions during springtime over the United States (US). We use the GEOS-Chem chemistry transport model coupled with the size-resolved Advanced Particle Microphysics (APM) Model. We also employ measurements of particle number size distributions, CN10 (condensation nuclei > 10 nm), CCN0.4 (CCN at 0.4 % supersaturation), and aerosol composition (SO₄, NO₃, NH₄, Organics) at the Southern Great Plains site (SGP). The impact of NH₃ in ion-mediated nucleation is the improved capturing of the occurrence of almost all springtime (March-April) NPF events observed at SGP during 2015-2020. Furthermore, this brings the magnitude and temporal variations of particle number concentrations in stronger agreement with observations; mean fractional bias for modeled CN10(CCN0.4) reducing from -1.26 to -0.27 (-0.75 to -0.54) and overall good-agreement (∣FractionalBias ∣ < 0.6) improving from 8.5 to 54 % (31 to 42 %). The contribution of NH₃ in new particle formation is important for springtime abundance of ultrafine aerosols (explaining 63 ± 15 % of CN10) and CCN (16 ± 10 % of CCN0.4) over the US. Our analysis shows that the deviation of CCN0.4 is strongly correlated with PM₁-NH₄⁺ deviations, suggesting the importance of improved model representation of ammonium for more accurate quantification of potential cloud forming particles.

Variation of lightning-ignited wildfire patterns under climate change

Lightning is the main precursor of natural wildfires and Long-Continuing-Current (LCC) lightning flashes are proposed to be the main igniters of lightning-ignited wildfires (LIW). Previous studies predict a change of the global occurrence rate and spatial pattern of total lightning. Nevertheless, the sensitivity of lightning-ignited wildfire occurrence to climate change is uncertain. Here, we investigate space-based measurements of LCC lightning associated with lightning ignitions and present LCC lightning projections under the Representative Concentration Pathway RCP6.0 for the 2090s by applying a recent LCC lightning parameterization based on the updraft strength in thunderstorms. We find a 41% global increase of the LCC lightning flash rate. Increases are largest in South America, the western coast of North America, Central America, Australia, Southern and Eastern Asia, and Europe, while only regional variations are found in northern polar forests, where fire risk can affect permafrost soil carbon release. These results show that lightning schemes including LCC lightning are needed to project the occurrence of lightning-ignited wildfires under climate change.

Nitrogen deposition from aviation emissions

Excess nitrogen deposition from anthropogenic sources of atmospheric emissions, such as agriculture and transportation, can have negative effects on natural environments. Designing effective conservation efforts requires knowledge of the contribution of individual sectors. This study utilizes a global atmospheric chemistry-transport model to quantify, for the first time, the contribution of global aviation NO_x emissions to nitrogen deposition for 2005 and 2019. We find that aviation led to an additional 1.39 Tg of nitrogen deposited globally in 2019, up 72 % from 2005, with 67 % of each year's total occurring through wet deposition. In 2019, aviation was responsible for an average of 0.66 %, 1.13 %, and 1.61 % of modeled nitrogen deposition from all sources over Asia, Europe, and North America, respectively. These impacts are spatially widespread, with 56 % of deposition occurring over water. Emissions during the landing, taxi and takeoff (LTO) phases of flight are responsible for 8 % of aviation's nitrogen deposition impacts on average globally, and between 16 and 32 % over most land in regions with high aviation activity. Despite currently representing less than 1.2 % of nitrogen deposition globally, further growth of aviation emissions would result in increases in aviation's contribution to nitrogen deposition and associated critical loads.

Using machine learning approach to reproduce the measured feature and understand the model-to-measurement discrepancy of atmospheric formaldehyde

The solar absorption spectrometry in the infrared spectral region, using high-resolution Fourier transform infrared (FTIR) spectrometer, has been established as a powerful tool in atmospheric science. These observations cannot be performed continuously, for example, clouds prevent observations. On the other hand, chemical transport models give continuously data. Their results depend on the knowledge of emission inventories, the chemistry involved, and the meteorological fields, yielding to potential biases between measurements and simulations. In our study we concentrated on Formaldehyde (HCHO) and used machine learning approach to fill the gap between the observations, performed on an irregular time scale and having their measurement lacks, and model data, giving continuous data, but having potential variable biases. The proposed machine learning approach is based on the Light Gradient Boosting Machine (LightGBM) algorithm and created by using GEOS-Chem simulations, meteorological fields, emission inventory, and is referred to as the GEOS-Chem-LightGBM model. The results of established GEOS-Chem-LightGBM model have generated consistent HCHO predictions with the ground-based FTIR and satellite (OMI and TROPOMI) observations. In order to understand the GEOS-Chem model to measurement discrepancy, we have investigated the contribution of each input variable to GEOS-Chem-LightGBM model HCHO predictions through the SHapely Additive exPlanations (SHAP) approach. We found that the GEOS-Chem model underestimates the sensitivities of HCHO total column to most photochemical variables, contributing to lower amplitudes of diurnal cycle and seasonal cycle by the GEOS-Chem model. By correcting the model-to-measurement discrepancy, the sensitivities of HCHO total column to all variables by the GEOS-Chem-LightGBM became to be in good agreement with the FTIR observations. As a result, GEOS-Chem-LightGBM model has significantly improved the performance of HCHO predictions compared to the GEOS-Chem alone. The proposed GEOS-Chem-LightGBM model can be extendible to other atmospheric constituents obtained by various measurement techniques and platforms, and is expected to have wide applications.

Diagnosing the Model Bias in Simulating Daily Surface Ozone Variability Using a Machine Learning Method: The Effects of Dry Deposition and Cloud Optical Depth

Machine learning methods are increasingly used in air quality studies to predict air pollution levels, while few applied them to diagnose and improve the underlying mechanisms controlling air pollution represented in chemical transport models (CTMs). Here, we use the random forest (RF) method to diagnose high biases of surface daily maximum 8 h average (MDA8) ozone concentrations in the GEOS-Chem CTM evaluated against measurements from the nationwide monitoring network in summer 2018 over China. The feature importance results show that cloud optical depth (COD), relative humidity, and precipitation are the top three factors affecting CTM high biases. Such results indicate that the high ozone biases in summer over China mainly occur on wet/cloudy days (∼40% biased high), while biases on dry/clear days are small (within 5%). We link the important features with model parameterizations and variables, identifying model underestimates in the dry deposition velocity and COD on wet/cloudy days. By accounting for the enhanced dry deposition on wet plant cuticles and using satellite observation constrained COD, we find that CTM high ozone biases can be halved with an improved agreement in the temporal variability, highlighting the effects of dry deposition and COD on ozone, as suggested by the RF outcomes.

Compositional Constraints are Vital for Atmospheric PM2.5 Source Attribution over India

India experiences some of the highest levels of ambient PM_2.5 aerosol pollution in the world. However, due to the historical dearth of in situ measurements, chemical transport models that are often used to estimate PM_2.5 exposure over the region are rarely evaluated. Here, we conduct a novel model comparison with speciated airborne measurements of fine aerosol, revealing large biases in the ammonium and nitrate simulations. To address this, we incorporate process-level changes to the model and use satellite observations from the Cross-track Infrared Sounder (CrIS) and the TROPOspheric Monitoring Instrument (TROPOMI) to constrain ammonia and nitrogen oxide emissions. The resulting simulation demonstrates significantly lower bias (NMB_Modified: 0.19; NMB_Base: 0.61) when validated against the airborne aerosol measurements, particularly for the nitrate (NMB_Modified: 0.08; NMB_Base: 1.64) and ammonium simulation (NMB_Modified: 0.49; NMB_Base: 0.90). We use this validated simulation to estimate a population-weighted annual PM_2.5 exposure of 61.4 μg m^-3, with the RCO (residential, commercial, and other) and energy sectors contributing 21% and 19%, respectively, resulting in an estimated 961,000 annual PM_2.5-attributable deaths. Regional exposure and sectoral source contributions differ meaningfully in the improved simulation (compared to the baseline simulation). Our work highlights the critical role of speciated observational constraints in developing accurate model-based PM_2.5 aerosol source attribution for health assessments and air quality management in India.

Atmospheric transport drives regional interactions of ozone pollution in China

In recent years, ozone pollution becomes a serious environmental issue in China. A good understanding of source-receptor relationships of ozone transport from aboard and inside China is beneficial to mitigating ozone pollution there. To date, these issues have not been comprehensively assessed, especially for highly polluted regions in the central and eastern China (CEC), including the North China Plain (NCP), Twain-Hu region (THR), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SCB). Here, based on simulations over 2013-2020 from a well-validated chemical transport model, GEOS-Chem, we show that foreign ozone accounts for a large portion of surface ozone over CEC, ranging from 25.0% in THR to 39.4% in NCP. Focusing on transport of domestic ozone between the five regions in CEC, we find that atmospheric transport can largely modulate regional interactions of ozone pollution in China. At the surface, THR receives the largest amount of ozone from the other four regions (54.2% of domestic ozone in the receptor region, the same in below), followed by PRD (32.3%), SCB (26.7%), YRD (21.1%), and NCP (18.0%). Meanwhile, YRD exports largest amount of ozone to the other regions, ranging from 8.9% in SCB to 28.4% in THR. Although SCB is relatively isolated and thus impacts NCP, YRD, and PRD weakly (< 2.2%), export of SCB ozone to THR reaches 9.3%. The regional ozone transport over CEC, occurring mostly in the lower troposphere, is mainly modulated by the East Asian monsoon circulations, proximity between source and receptor regions, seasonal changes of ozone production, and topography.

Source Sector Mitigation of Solar Energy Generation Losses Attributable to Particulate Matter Pollution

Particulate matter (PM) in the atmosphere and deposited on solar photovoltaic (PV) panels reduce PV energy generation. Reducing anthropogenic PM sources will therefore increase carbon-free energy generation and as a cobenefit will improve surface air quality. However, we lack a global understanding of the sectors that would be the most effective at achieving the necessary reductions in PM sources. Here we combine well-evaluated models of solar PV performance and atmospheric composition to show that deep cuts in air pollutant emissions from the residential, on-road, and energy sectors are the most effective approaches to mitigate PM-induced PV energy losses over East and South Asia, and the Tibetan Plateau, Central Asia, and the Arabian Peninsula, and Western Siberia, respectively. Using 2019 PV capacities as a baseline, we find that a 50% reduction in residential emissions would lead to an additional 10.3 TWh yr^-1 (US$878 million yr^-1) and 2.5 TWh yr^-1 (US$196 million yr^-1) produced in China and India, respectively.

Impact of Rocket Launch and Space Debris Air Pollutant Emissions on Stratospheric Ozone and Global Climate

Detailed examination of the impact of modern space launches on the Earth's atmosphere is crucial, given booming investment in the space industry and an anticipated space tourism era. We develop air pollutant emissions inventories for rocket launches and re-entry of reusable components and debris in 2019 and for a speculative space tourism scenario based on the recent billionaire space race. This we include in the global GEOS-Chem model coupled to a radiative transfer model to determine the influence on stratospheric ozone (O₃) and climate. Due to recent surge in re-entering debris and reusable components, nitrogen oxides from re-entry heating and chlorine from solid fuels contribute equally to all stratospheric O₃ depletion by contemporary rockets. Decline in global stratospheric O₃ is small (0.01%), but reaches 0.15% in the upper stratosphere (∼5 hPa, 40 km) in spring at 60-90°N after a decade of sustained 5.6% a^-1 growth in 2019 launches and re-entries. This increases to 0.24% with a decade of emissions from space tourism rockets, undermining O₃ recovery achieved with the Montreal Protocol. Rocket emissions of black carbon (BC) produce substantial global mean radiative forcing of 8 mW m^-2 after just 3 years of routine space tourism launches. This is a much greater contribution to global radiative forcing (6%) than emissions (0.02%) of all other BC sources, as radiative forcing per unit mass emitted is ∼500 times more than surface and aviation sources. The O₃ damage and climate effect we estimate should motivate regulation of an industry poised for rapid growth.

NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0: Stratospheric Composition

The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS-CF) provides recent estimates and 5-day forecasts of atmospheric composition to the public in near-real time. To do this, the GEOS Earth system model is coupled with the GEOS-Chem tropospheric-stratospheric unified chemistry extension (UCX) to represent composition from the surface to the top of the GEOS atmosphere (0.01 hPa). The GEOS-CF system is described, including updates made to the GEOS-Chem UCX mechanism within GEOS-CF for improved representation of stratospheric chemistry. Comparisons are made against balloon, lidar, and satellite observations for stratospheric composition, including measurements of ozone (O3) and important nitrogen and chlorine species related to stratospheric O3 recovery. The GEOS-CF nudges the stratospheric O3 toward the GEOS Forward Processing (GEOS FP) assimilated O3 product; as a result the stratospheric O3 in the GEOS-CF historical estimate agrees well with observations. During abnormal dynamical and chemical environments such as the 2020 polar vortexes, the GEOS-CF O3 forecasts are more realistic than GEOS FP O3 forecasts because of the inclusion of the complex GEOS-Chem UCX stratospheric chemistry. Overall, the spatial patterns of the GEOS-CF simulated concentrations of stratospheric composition agree well with satellite observations. However, there are notable biases-such as low NO x and HNO3 in the polar regions and generally low HCl throughout the stratosphere-and future improvements to the chemistry mechanism and emissions are discussed. GEOS-CF is a new tool for the research community and instrument teams observing trace gases in the stratosphere and troposphere, providing near-real-time three-dimensional gridded information on atmospheric composition.

Nocturnal survival of isoprene linked to formation of upper tropospheric organic aerosol

Isoprene is emitted mainly by terrestrial vegetation and is the dominant volatile organic compound (VOC) in Earth's atmosphere. It plays key roles in determining the oxidizing capacity of the troposphere and the formation of organic aerosol. Daytime infrared satellite observations of isoprene reported here broadly agree with emission inventories, but we found substantial differences in the locations and magnitudes of isoprene hotspots, consistent with a recent study. The corresponding nighttime infrared observations reveal unexpected hotspots over tropical South America, the Congo basin, and Southeast Asia. We used an atmospheric chemistry model to link these nighttime isoprene measurements to low-NO_x regions with high biogenic VOC emissions; at sunrise the remaining isoprene can lead to the production of epoxydiols and subsequently to the widespread seasonal production of organic aerosol in the tropical upper troposphere.

Satellite-Based Long-Term Spatiotemporal Patterns of Surface Ozone Concentrations in China: 2005-2019

BACKGROUND

Although short-term ozone (O3) exposure has been associated with a series of adverse health outcomes, research on the health effects of chronic O3 exposure is still limited, especially in developing countries because of the lack of long-term exposure estimates.

OBJECTIVES

The present study aimed to estimate the spatiotemporal distribution of monthly mean daily maximum 8-h average O3 concentrations in China from 2005 to 2019 at a 0.05° spatial resolution.

METHODS

We developed a machine learning model with a satellite-derived boundary-layer O3 column, O3 precursors, meteorological conditions, land-use information, and proxies of anthropogenic emissions as predictors.

RESULTS

The random, spatial, and temporal cross-validation R2 of our model were 0.87, 0.86, and 0.76, respectively. Model-predicted spatial distribution of ground-level O3 concentrations showed significant differences across seasons. The highest summer peak of O3 occurred in the North China Plain, whereas southern regions were the most polluted in winter. Most large urban centers showed elevated O3 levels, but their surrounding suburban areas may have even higher O3 concentrations owing to nitrogen oxides titration. The annual trend of O3 concentrations fluctuated over 2005-2013, but a significant nationwide increase was observed afterward.

DISCUSSION

The present model had enhanced performance in predicting ground-level O3 concentrations in China. This national data set of O3 concentrations would facilitate epidemiological studies to investigate the long-term health effect of O3 in China. Our results also highlight the importance of controlling O3 in China's next round of the Air Pollution Prevention and Control Action Plan. https://doi.org/10.1289/EHP9406.

Abating ammonia is more cost-effective than nitrogen oxides for mitigating PM2.5 air pollution

[Figure: see text].

The underappreciated role of agricultural soil nitrogen oxide emissions in ozone pollution regulation in North China

Intensive agricultural activities in the North China Plain (NCP) lead to substantial emissions of nitrogen oxides (NOx) from soil, while the role of this source on local severe ozone pollution is unknown. Here we use a mechanistic parameterization of soil NOx emissions combined with two atmospheric chemistry models to investigate the issue. We find that the presence of soil NOx emissions in the NCP significantly reduces the sensitivity of ozone to anthropogenic emissions. The maximum ozone air quality improvements in July 2017, as can be achieved by controlling all domestic anthropogenic emissions of air pollutants, decrease by 30% due to the presence of soil NOx. This effect causes an emission control penalty such that large additional emission reductions are required to achieve ozone regulation targets. As NOx emissions from fuel combustion are being controlled, the soil emission penalty would become increasingly prominent and shall be considered in emission control strategies.

Predicting Spatial Variations in Multiple Measures of Oxidative Burden for Outdoor Fine Particulate Air Pollution across Canada

Fine particulate air pollution (PM_2.5) is a leading contributor to the overall global burden of disease. Traditionally, outdoor PM_2.5 has been characterized using mass concentrations which treat all particles as equally harmful. Oxidative potential (OP) (per μg) and oxidative burden (OB) (per m³) are complementary metrics that estimate the ability of PM_2.5 to cause oxidative stress, which is an important mechanism in air pollution health effects. Here, we provide the first national estimates of spatial variations in multiple measures (glutathione, ascorbate, and dithiothreitol depletion) of annual median outdoor PM_2.5 OB across Canada. To do this, we combined a large database of ground-level OB measurements collected monthly prospectively across Canada for 2 years (2016-2018) with PM_2.5 components estimated using a chemical transport model (GEOS-Chem) and satellite aerosol observations. Our predicted ground-level OB values of all three methods were consistent with ground-level observations (cross-validation R² = 0.63-0.74). We found that forested regions and urban areas had the highest OB, predicted primarily by black carbon and organic carbon from wildfires and transportation sources. Importantly, the dominant components associated with OB were different than those contributing to PM_2.5 mass concentrations (secondary inorganic aerosol); thus, OB metrics may better indicate harmful components and sources on health than the bulk PM_2.5 mass, reinforcing that OB estimates can complement the existing PM_2.5 data in future national-level epidemiological studies.

Extreme oxidant amounts produced by lightning in storm clouds

Lightning increases the atmosphere's ability to cleanse itself by producing nitric oxide (NO), leading to atmospheric chemistry that forms ozone (O₃) and the atmosphere's primary oxidant, the hydroxyl radical (OH). Our analysis of a 2012 airborne study of deep convection and chemistry demonstrates that lightning also directly generates the oxidants OH and the hydroperoxyl radical (HO₂). Extreme amounts of OH and HO₂ were discovered and linked to visible flashes occurring in front of the aircraft and to subvisible discharges in electrified anvil regions. This enhanced OH and HO₂ is orders of magnitude greater than any previous atmospheric observation. Lightning-generated OH in all storms happening at the same time globally can be responsible for a highly uncertain, but substantial, 2 to 16% of global atmospheric OH oxidation.

Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0

The Goddard Earth Observing System composition forecast (GEOS-CF) system is a high-resolution (0.25°) global constituent prediction system from NASA's Global Modeling and Assimilation Office (GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA's broad range of space-based and in-situ observations. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide hindcasts and 5-days forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community. Evaluation of GEOS-CF against satellite, ozonesonde and surface observations for years 2018-2019 show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to 0.3, normalized root mean square errors between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants in many regions of the world and during all seasons, yet also highlight current limitations, such as a global high bias in SO2 and an overprediction of summertime O3 over the Southeast United States. GEOS-CF v1.0 generally overestimates aerosols by 20%-50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions. The 5-days forecasts have skill scores comparable to the 1-day hindcast. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

Substantial nitrogen oxides emission reduction from China due to COVID-19 and its impact on surface ozone and aerosol pollution

A top-down approach was employed to estimate the influence of lockdown measures implemented during the COVID-19 pandemic on NOx emissions and subsequent influence on surface PM2.5 and ozone in China. The nation-wide NOx emission reduction of 53.4% due to the lockdown in 2020 quarter one in China may represent the current upper limit of China's NOx emission control. During the Chinese New Year Holiday (P2), NOx emission intensity in China declined by 44.7% compared to the preceding 3 weeks (P1). NOx emission intensity increased by 20.3% during the 4 weeks after P2 (P3), despite the unchanged NO2 column. It recovered to 2019 level at the end of March (P4). The East China (22°N - 42°N, 102°E - 122°E) received greater influence from COVID-19. Overall NOx emission from East China for 2020 first quarter is 40.5% lower than 2019, and in P4 it is still 22.9% below the same period in 2019. The 40.5% decrease of NOx emission in 2020 first quarter in East China lead to 36.5% increase of surface O3 and 12.5% decrease of surface PM2.5. The elevated O3 promotes the secondary aerosol formation through heterogeneous pathways. We recommend that the complicated interaction between PM2.5 and O3 should be considered in the emission control strategy making process in the future.

Impacts of COVID-19 lockdown, Spring Festival and meteorology on the NO2 variations in early 2020 over China based on in-situ observations, satellite retrievals and model simulations

The lockdown measures due to COVID-19 affected the industry, transportation and other human activities within China in early 2020, and subsequently the emissions of air pollutants. The decrease of atmospheric NO2 due to the COVID-19 lockdown and other factors were quantitively analyzed based on the surface concentrations by in-situ observations, the tropospheric vertical column densities (VCDs) by different satellite retrievals including OMI and TROPOMI, and the model simulations by GEOS-Chem. The results indicated that due to the COVID-19 lockdown, the surface NO2 concentrations decreased by 42% ± 8% and 26% ± 9% over China in February and March 2020, respectively. The tropospheric NO2 VCDs based on both OMI and high quality (quality assurance value (QA) ≥ 0.75) TROPOMI showed similar results as the surface NO2 concentrations. The daily variations of atmospheric NO2 during the first quarter (Q1) of 2020 were not only affected by the COVID-19 lockdown, but also by the Spring Festival (SF) holiday (January 24-30, 2020) as well as the meteorology changes due to seasonal transition. The SF holiday effect resulted in a NO2 reduction from 8 days before SF to 21 days after it (i.e. January 17 - February 15), with a maximum of 37%. From the 6 days after SF (January 31) to the end of March, the COVID-19 lockdown played an important role in the NO2 reduction, with a maximum of 51%. The meteorology changes due to seasonal transition resulted in a nearly linear decreasing trend of 25% and 40% reduction over the 90 days for the NO2 concentrations and VCDs, respectively. Comparisons between different datasets indicated that medium quality (QA ≥ 0.5) TROPOMI retrievals might suffer large biases in some periods, and thus attention must be paid when they are used for analyses, data assimilations and emission inversions.

Satellite-based estimates of decline and rebound in China's CO2 emissions during COVID-19 pandemic

Changes in CO₂ emissions during the COVID-19 pandemic have been estimated from indicators on activities like transportation and electricity generation. Here, we instead use satellite observations together with bottom-up information to track the daily dynamics of CO₂ emissions during the pandemic. Unlike activity data, our observation-based analysis deploys independent measurement of pollutant concentrations in the atmosphere to correct misrepresentation in the bottom-up data and can provide more detailed insights into spatially explicit changes. Specifically, we use TROPOMI observations of NO₂ to deduce 10-day moving averages of NO _x and CO₂ emissions over China, differentiating emissions by sector and province. Between January and April 2020, China's CO₂ emissions fell by 11.5% compared to the same period in 2019, but emissions have since rebounded to pre-pandemic levels before the coronavirus outbreak at the beginning of January 2020 owing to the fast economic recovery in provinces where industrial activity is concentrated.

Satellite isoprene retrievals constrain emissions and atmospheric oxidation

Isoprene is the dominant non-methane organic compound emitted to the atmosphere1-3. It drives ozone and aerosol production, modulates atmospheric oxidation and interacts with the global nitrogen cycle4-8. Isoprene emissions are highly uncertain1,9, as is the nonlinear chemistry coupling isoprene and the hydroxyl radical, OH-its primary sink10-13. Here we present global isoprene measurements taken from space using the Cross-track Infrared Sounder. Together with observations of formaldehyde, an isoprene oxidation product, these measurements provide constraints on isoprene emissions and atmospheric oxidation. We find that the isoprene-formaldehyde relationships measured from space are broadly consistent with the current understanding of isoprene-OH chemistry, with no indication of missing OH recycling at low nitrogen oxide concentrations. We analyse these datasets over four global isoprene hotspots in relation to model predictions, and present a quantification of isoprene emissions based directly on satellite measurements of isoprene itself. A major discrepancy emerges over Amazonia, where current underestimates of natural nitrogen oxide emissions bias modelled OH and hence isoprene. Over southern Africa, we find that a prominent isoprene hotspot is missing from bottom-up predictions. A multi-year analysis sheds light on interannual isoprene variability, and suggests the influence of the El Niño/Southern Oscillation.

Constraining remote oxidation capacity with ATom observations

The global oxidation capacity, defined as the tropospheric mean concentration of the hydroxyl radical (OH), controls the lifetime of reactive trace gases in the atmosphere such as methane and carbon monoxide (CO). Models tend to underestimate the methane lifetime and CO concentrations throughout the troposphere, which is consistent with excessive OH. Approximately half of the oxidation of methane and non-methane volatile organic compounds (VOCs) is thought to occur over the oceans where oxidant chemistry has received little validation due to a lack of observational constraints. We use observations from the first two deployments of the NASA ATom aircraft campaign during July-August 2016 and January-February 2017 to evaluate the oxidation capacity over the remote oceans and its representation by the GEOS-Chem chemical transport model. The model successfully simulates the magnitude and vertical profile of remote OH within the measurement uncertainties. Comparisons against the drivers of OH production (water vapor, ozone, and NO y concentrations, ozone photolysis frequencies) also show minimal bias, with the exception of wintertime NO y . The severe model overestimate of NO y during this period may indicate insufficient wet scavenging and/or missing loss on sea-salt aerosols. Large uncertainties in these processes require further study to improve simulated NO y partitioning and removal in the troposphere, but preliminary tests suggest that their overall impact could marginally reduce the model bias in tropospheric OH. During the ATom-1 deployment, OH reactivity (OHR) below 3 km is significantly enhanced, and this is not captured by the sum of its measured components (cOHRobs) or by the model (cOHRmod). This enhancement could suggest missing reactive VOCs but cannot be explained by a comprehensive simulation of both biotic and abiotic ocean sources of VOCs. Additional sources of VOC reactivity in this region are difficult to reconcile with the full suite of ATom measurement constraints. The model generally reproduces the magnitude and seasonality of cOHRobs but underestimates the contribution of oxygenated VOCs, mainly acetaldehyde, which is severely underestimated throughout the troposphere despite its calculated lifetime of less than a day. Missing model acetaldehyde in previous studies was attributed to measurement uncertainties that have been largely resolved. Observations of peroxyacetic acid (PAA) provide new support for remote levels of acetaldehyde. The underestimate in both model acetaldehyde and PAA is present throughout the year in both hemispheres and peaks during Northern Hemisphere summer. The addition of ocean sources of VOCs in the model increases cOHRmod by 3% to 9% and improves model-measurement agreement for acetaldehyde, particularly in winter, but cannot resolve the model summertime bias. Doing so would require 100 Tg yr-1 of a long-lived unknown precursor throughout the year with significant additional emissions in the Northern Hemisphere summer. Improving the model bias for remote acetaldehyde and PAA is unlikely to fully resolve previously reported model global biases in OH and methane lifetime, suggesting that future work should examine the sources and sinks of OH over land.

Assessment of NO2 observations during DISCOVER-AQ and KORUS-AQ field campaigns

NASA's Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ, conducted in 2011-2014) campaign in the United States and the joint NASA and National Institute of Environmental Research (NIER) Korea-United States Air Quality Study (KORUS-AQ, conducted in 2016) in South Korea were two field study programs that provided comprehensive, integrated datasets of airborne and surface observations of atmospheric constituents, including nitrogen dioxide (NO2), with the goal of improving the interpretation of spaceborne remote sensing data. Various types of NO2 measurements were made, including in situ concentrations and column amounts of NO2 using ground- and aircraft-based instruments, while NO2 column amounts were being derived from the Ozone Monitoring Instrument (OMI) on the Aura satellite. This study takes advantage of these unique datasets by first evaluating in situ data taken from two different instruments on the same aircraft platform, comparing coincidently sampled profile-integrated columns from aircraft spirals with remotely sensed column observations from ground-based Pandora spectrometers, intercomparing column observations from the ground (Pandora), aircraft (in situ vertical spirals), and space (OMI), and evaluating NO2 simulations from coarse Global Modeling Initiative (GMI) and high-resolution regional models. We then use these data to interpret observed discrepancies due to differences in sampling and deficiencies in the data reduction process. Finally, we assess satellite retrieval sensitivity to observed and modeled a priori NO2 profiles. Contemporaneous measurements from two aircraft instruments that likely sample similar air masses generally agree very well but are also found to differ in integrated columns by up to 31.9 %. These show even larger differences with Pandora, reaching up to 53.9 %, potentially due to a combination of strong gradients in NO2 fields that could be missed by aircraft spirals and errors in the Pandora retrievals. OMI NO2 values are about a factor of 2 lower in these highly polluted environments due in part to inaccurate retrieval assumptions (e.g., a priori profiles) but mostly to OMI's large footprint (> 312 km2).

Premature mortality related to United States cross-state air pollution

Outdoor air pollution adversely affects human health and is estimated to be responsible for five to ten per cent of the total annual premature mortality in the contiguous United States^1-3. Combustion emissions from a variety of sources, such as power generation or road traffic, make a large contribution to harmful air pollutants such as ozone and fine particulate matter (PM_2.5)⁴. Efforts to mitigate air pollution have focused mainly on the relationship between local emission sources and local air quality². Air quality can also be affected by distant emission sources, however, including emissions from neighbouring federal states^5,6. This cross-state exchange of pollution poses additional regulatory challenges. Here we quantify the exchange of air pollution among the contiguous United States, and assess its impact on premature mortality that is linked to increased human exposure to PM_2.5 and ozone from seven emission sectors for 2005 to 2018. On average, we find that 41 to 53 per cent of air-quality-related premature mortality resulting from a state's emissions occurs outside that state. We also find variations in the cross-state contributions of different emission sectors and chemical species to premature mortality, and changes in these variations over time. Emissions from electric power generation have the greatest cross-state impacts as a fraction of their total impacts, whereas commercial/residential emissions have the smallest. However, reductions in emissions from electric power generation since 2005 have meant that, by 2018, cross-state premature mortality associated with the commercial/residential sector was twice that associated with power generation. In terms of the chemical species emitted, nitrogen oxides and sulfur dioxide emissions caused the most cross-state premature deaths in 2005, but by 2018 primary PM_2.5 emissions led to cross-state premature deaths equal to three times those associated with sulfur dioxide emissions. These reported shifts in emission sectors and emission species that contribute to premature mortality may help to guide improvements to air quality in the contiguous United States.

Air Quality and Health Impact of Future Fossil Fuel Use for Electricity Generation and Transport in Africa

Africa has ambitious plans to address energy deficits and sustain economic growth with fossil fueled power plants. The continent is also experiencing faster population growth than anywhere else in the world that will lead to proliferation of vehicles. Here, we estimate air pollutant emissions in Africa from future (2030) electricity generation and transport. We find that annual emissions of two precursors of fine particles (PM_2.5) hazardous to health, sulfur dioxide (SO₂) and nitrogen oxides (NO_x), approximately double by 2030 relative to 2012, increasing from 2.5 to 5.5 Tg SO₂ and 1.5 to 2.8 Tg NO_x. We embed these emissions in the GEOS-Chem model nested over the African continent to simulate ambient concentrations of PM_2.5 and determine the burden of disease (excess deaths) attributable to exposure to future fossil fuel use. We calculate 48000 avoidable deaths in 2030 (95% confidence interval: 6000-88000), mostly in South Africa (10400), Nigeria (7500), and Malawi (2400), with 3-times higher mortality rates from power plants than transport. Sensitivity of the burden of disease to either population growth or air quality varies regionally and suggests that emission mitigation strategies would be most effective in Southern Africa, whereas population growth is the main driver everywhere else.

Carbon and health implications of trade restrictions

In a globalized economy, production of goods can be disrupted by trade disputes. Yet the resulting impacts on carbon dioxide emissions and ambient particulate matter (PM2.5) related premature mortality are unclear. Here we show that in contrast to a free trade world, with the emission intensity in each sector unchanged, an extremely anti-trade scenario with current tariffs plus an additional 25% tariff on each traded product would reduce the global export volume by 32.5%, gross domestic product by 9.0%, carbon dioxide by 6.3%, and PM2.5-related mortality by 4.1%. The respective impacts would be substantial for the United States, Western Europe and China. A freer trade scenario would increase global carbon dioxide emission and air pollution due to higher levels of production, especially in developing regions with relatively high emission intensities. Global collaborative actions to reduce emission intensities in developing regions could help achieve an economic-environmental win-win state through globalization.

Constraining Emissions of Volatile Organic Compounds Over the Indian Subcontinent Using Space-Based Formaldehyde Measurements

India is an air pollution mortality hot spot, but regional emissions are poorly understood. We present a high-resolution nested chemical transport model (GEOS-Chem) simulation for the Indian subcontinent and use it to interpret formaldehyde (HCHO) observations from two satellite sensors (OMI and GOME-2A) in terms of constraints on regional volatile organic compound (VOC) emissions. We find modeled biogenic VOC emissions to be overestimated by ~30-60% for most locations and seasons, and derive a best estimate biogenic flux of 16 Tg C/year subcontinent-wide for year 2009. Terrestrial vegetation provides approximately half the total VOC flux in our base-case inversions (full uncertainty range: 44-65%). This differs from prior understanding, in which biogenic emissions represent >70% of the total. Our derived anthropogenic VOC emissions increase slightly (13-16% in the base case, for a subcontinent total of 15 Tg C/year in 2009) over RETRO year 2000 values, with some larger regional discrepancies. The optimized anthropogenic emissions agree well with the more recent CEDS inventory, both subcontinent-wide (within 2%) and regionally. An exception is the Indo-Gangetic Plain, where we find an underestimate for both RETRO and CEDS. Anthropogenic emissions thus constitute 37-50% of the annual regional VOC source in our base-case inversions and exceed biogenic emissions over the Indo-Gangetic Plain, West India, and South India, and over the entire subcontinent during winter and post-monsoon. Fires are a minor fraction (<7%) of the total regional VOC source in the prior and optimized model. However, evidence suggests that VOC emissions in the fire inventory used here (GFEDv4) are too low over the Indian subcontinent.

Simulation of airborne trace metals in fine particulate matter over North America

Trace metal distributions are of relevance to understand sources of fine particulate matter (PM2.5), PM2.5-related health effects, and atmospheric chemistry. However, knowledge of trace metal distributions is lacking due to limited ground-based measurements and model simulations. This study develops a simulation of 12 trace metal concentrations (Si, Ca, Al, Fe, Ti, Mn, K, Mg, As, Cd, Ni and Pb) over continental North America for 2013 using the GEOS-Chem chemical transport model. Evaluation of modeled trace metal concentrations with observations indicates a spatial consistency within a factor of 2, an improvement over previous studies that were within a factor of 3-6. The spatial distribution of trace metal concentrations reflects their primary emission sources. Crustal element (Si, Ca, Al, Fe, Ti, Mn, K) concentrations are enhanced over the central US from anthropogenic fugitive dust and over the southwestern U.S. due to natural mineral dust. Heavy metal (As, Cd, Ni and Pb) concentrations are high over the eastern U.S. from industry. K is abundance in the southeast from biomass burning and high concentrations of Mg is observed along the coast from sea spray. The spatial pattern of PM2.5 mass is most strongly correlated with Pb, Ni, As and K due to their signature emission sources. Challenges remain in accurately simulating observed trace metal concentrations. Halving anthropogenic fugitive dust emissions in the 2011 National Air Toxic Assessment (NATA) inventory and doubling natural dust emissions in the default GEOS-Chem simulation was necessary to reduce biases in crustal element concentrations. A fivefold increase of anthropogenic emissions of As and Pb was necessary in the NATA inventory to reduce the national-scale bias versus observations by more than 80 %, potentially reflecting missing sources.

Source Contributions to Ambient Fine Particulate Matter for Canada

Understanding the sectoral contribution of emissions to fine particulate matter (PM_2.5) offers information for air quality management, and for investigation of association with health outcomes. This study evaluates the contribution of different emission sectors to PM_2.5 in 2013 for Canada using the GEOS-Chem chemical transport model, downscaled with satellite-based PM_2.5. Despite the low population-weighted PM_2.5 concentrations of 5.5 μg m^-3 across Canada, we find that over 70% of population-weighted PM_2.5 originates from Canadian sources followed by 30% from the contiguous United States. The three leading sectoral contributors to population-weighted PM_2.5 over Canada are wildfires with 1.0 μg m^-3 (17%), transportation with 0.96 μg m^-3 (16%), and residential combustion with 0.91 μg m^-3 (15%). The relative contribution to population-weighted PM_2.5 of different sectors varies regionally with residential combustion as the leading contributor in Central Canada (19%), while wildfires dominate over Northern Canada (59%), Atlantic Canada (34%), and Western Canada (18%). The contribution from U.S. sources is larger over Central Canada (33%) than over Western Canada (17%), Atlantic Canada (17%), and Northern Canada (<2%). Sectoral trend analysis showed that the contribution from anthropogenic sources to population-weighted PM_2.5 decreased from 7.1 μg m^-3 to 3.4 μg m^-3 over the past two decades.

FTIR time series of stratospheric NO2 over Hefei, China, and comparisons with OMI and GEOS-Chem model data

We present the trend and seasonal variability of stratospheric NO₂ column for the first time over the polluted atmosphere at Hefei, China, retrieved using Fourier transform infrared spectroscopy (FTIR) between 2015 and 2018. The FTIR observed stratospheric NO₂ columns over Hefei show a peak in June and reach a minimum in January. The mean stratospheric NO₂ column concentration in June is (3.49 ± 0.25) × 10¹⁵ molecules*cm^-2, and is 39.20% ± 8.95% higher than that in January with a mean value of (2.51 ± 0.21) × 10¹⁵ molecules*cm^-2. We find a negative trend of (-0.34 ± 0.05) %/yr in the FTIR observations of stratospheric NO₂ column. The FTIR data are compared to the satellite OMI observations to assess the new data set quality and also applied to evaluate the GEOS-Chem model simulations. We find in general the OMI observations and GEOS-Chem model results are in good agreement with the coincident FTIR data, and they all show similar seasonal cycles with strong correlation coefficients of 0.84-0.86. The annual average OMI minus FTIR difference is (1.48 ± 5.33) × 10¹⁴ molecules*cm^-2 (4.82% ± 17.37%), and average GEOS-Chem minus FTIR difference is (2.36 ± 2.33) × 10¹⁴ molecules*cm ^-2 (7.66% ± 7.49%). Their maximum differences occur in April and May with mean differences of 12-16%. We also found negative trends in the stratospheric NO₂ column over Hefei for 2015-2018 with both OMI observations (-0.91 ± 0.09%/yr) and GEOS-Chem model results (-0.31 ± 0.05%/yr), demonstrating some consistency among them.

Hybrid Mass Balance/4D-Var Joint Inversion of NO x and SO2 Emissions in East Asia

Accurate estimates of NO x and SO2 emissions are important for air quality modeling and management. To incorporate chemical interactions of the two species in emission estimates, we develop a joint hybrid inversion framework to estimate their emissions in China and India (2005-2012). Pseudo observation tests and posterior evaluation with surface measurements demonstrate that joint assimilation of SO2 and NO2 can provide more accurate constraints on emissions than single-species inversions. This occurs through synergistic change of O3 and OH concentrations, particularly in conditions where satellite retrievals of the species being optimized have large uncertainties. The percentage changes of joint posterior emissions from the single-species posterior emissions go up to 242% at grid scales, although the national average of monthly emissions, seasonality, and interannual variations are similar. In China and India, the annual budget of joint posterior SO2 emissions is lower, but joint NO x posterior emissions are higher, because NO x emissions increase to increase SO2 concentration and better match Ozone Monitoring Instrument SO2 observations in high-NO x regions. Joint SO2 posterior emissions decrease by 16.5% from 2008 to 2012, while NO x posterior emissions increase by 24.9% from 2005 to 2011 in China-trends which are consistent with the MEIC inventory. Joint NO x and SO2 posterior emissions in India increase by 15.9% and 19.2% from 2005 to 2012, smaller than the 59.9% and 76.2% growth rate using anthropogenic emissions from EDGARv4.3.2. This work shows the benefit and limitation of joint assimilation in emission estimates and provides an efficient framework to perform the inversion.

Global tropospheric effects of aromatic chemistry with the SAPRC-11 mechanism implemented in GEOS-Chem version 9-02

The Goddard Earth Observing System with chemistry (GEOS-Chem) model has been updated with the Statewide Air Pollution Research Center version 11 (SAPRC-11) aromatics chemical mechanism, with the purpose of evaluating global and regional effects of the most abundant aromatics (benzene, toluene, xylenes) on the chemical species important for tropospheric oxidation capacity. The model evaluation based on surface and aircraft observations indicates good agreement for aromatics and ozone. A comparison between scenarios in GEOS-Chem with simplified aromatic chemistry (as in the standard setup, with no ozone formation from related peroxy radicals or recycling of NOx) and with the SAPRC-11 scheme reveals relatively slight changes in ozone, the hydroxyl radical, and nitrogen oxides on a global mean basis (1 %-4 %), although remarkable regional differences (5 %-20 %) exist near the source regions. NO x decreases over the source regions and increases in the remote troposphere, due mainly to more efficient transport of peroxyacetyl nitrate (PAN), which is increased with the SAPRC aromatic chemistry. Model ozone mixing ratios with the updated aromatic chemistry increase by up to 5 ppb (more than 10 %), especially in industrially polluted regions. The ozone change is partly due to the direct influence of aromatic oxidation products on ozone production rates, and in part to the altered spatial distribution of NOx that enhances the tropospheric ozone production efficiency. Improved representation of aromatics is important to simulate the tropospheric oxidation.

Effects of halogens on European air-quality

Halogens (Cl, Br) have a profound influence on stratospheric ozone (O₃). They (Cl, Br and I) have recently also been shown to impact the troposphere, notably by reducing the mixing ratios of O₃ and OH. Their potential for impacting regional air-quality is less well understood. We explore the impact of halogens on regional pollutants (focussing on O₃) with the European grid of the GEOS-Chem model (0.25° × 0.3125°). It has recently been updated to include a representation of halogen chemistry. We focus on the summer of 2015 during the ICOZA campaign at the Weybourne Atmospheric Observatory on the North Sea coast of the UK. Comparisons between these observations together with those from the UK air-quality network show that the model has some skill in representing the mixing ratios/concentration of pollutants during this period. Although the model has some success in simulating the Weybourne ClNO₂ observations, it significantly underestimates ClNO₂ observations reported at inland locations. It also underestimates mixing ratios of IO, OIO, I₂ and BrO, but this may reflect the coastal nature of these observations. Model simulations, with and without halogens, highlight the processes by which halogens can impact O₃. Throughout the domain O₃ mixing ratios are reduced by halogens. In northern Europe this is due to a change in the background O₃ advected into the region, whereas in southern Europe this is due to local chemistry driven by Mediterranean emissions. The proportion of hourly O₃ above 50 nmol mol^-1 in Europe is reduced from 46% to 18% by halogens. ClNO₂ from N₂O₅ uptake onto sea-salt leads to increases in O₃ mixing ratio, but these are smaller than the decreases caused by the bromine and iodine. 12% of ethane and 16% of acetone within the boundary layer is oxidised by Cl. Aerosol response to halogens is complex with small (∼10%) reductions in PM_2.5 in most locations. A lack of observational constraints coupled to large uncertainties in emissions and chemical processing of halogens make these conclusions tentative at best. However, the results here point to the potential for halogen chemistry to influence air quality policy in Europe and other parts of the world.

Alpine ice evidence of a three-fold increase in atmospheric iodine deposition since 1950 in Europe due to increasing oceanic emissions

Our measurements show a tripling of iodine in Alpine ice between 1950 and 1990. A 20th century increase in global iodine emissions has been previously found from model simulations, based on laboratory studies, but, up to now, long-term iodine records exist only in polar regions. These polar records are influenced by sea ice processes, which may obscure global iodine trends. Our results suggest that the increased iodine deposition over the Alps is consistent with increased oceanic iodine emissions coupled with a change in the iodine speciation, both driven by increasing anthropogenic NO_x emissions. In turn, the recent increase of iodine emissions implies that iodine-related ozone loss in the troposphere is more active now than in the preindustrial period.

Iodine is an important nutrient and a significant sink of tropospheric ozone, a climate-forcing gas and air pollutant. Ozone interacts with seawater iodide, leading to volatile inorganic iodine release that likely represents the largest source of atmospheric iodine. Increasing ozone concentrations since the preindustrial period imply that iodine chemistry and its associated ozone destruction is now substantially more active. However, the lack of historical observations of ozone and iodine means that such estimates rely primarily on model calculations. Here we use seasonally resolved records from an Alpine ice core to investigate 20th century changes in atmospheric iodine. After carefully considering possible postdepositional changes in the ice core record, we conclude that iodine deposition over the Alps increased by at least a factor of 3 from 1950 to the 1990s in the summer months, with smaller increases during the winter months. We reproduce these general trends using a chemical transport model and show that they are due to increased oceanic iodine emissions, coupled to a change in iodine speciation over Europe from enhanced nitrogen oxide emissions. The model underestimates the increase in iodine deposition by a factor of 2, however, which may be due to an underestimate in the 20th century ozone increase. Our results suggest that iodine’s impact on the Northern Hemisphere atmosphere accelerated over the 20th century and show a coupling between anthropogenic pollution and the availability of iodine as an essential nutrient to the terrestrial biosphere.

Bidirectional Ecosystem-Atmosphere Fluxes of Volatile Organic Compounds Across the Mass Spectrum: How Many Matter?

Terrestrial ecosystems are simultaneously the largest source and a major sink of volatile organic compounds (VOCs) to the global atmosphere, and these two-way fluxes are an important source of uncertainty in current models. Here, we apply high-resolution mass spectrometry (proton transfer reaction-quadrupole interface time-of-flight; PTR-QiTOF) to measure ecosystem-atmosphere VOC fluxes across the entire detected mass range (m/z 0-335) over a mixed temperate forest and use the results to test how well a state-of-science chemical transport model (GEOS-Chem CTM) is able to represent the observed reactive carbon exchange. We show that ambient humidity fluctuations can give rise to spurious VOC fluxes with PTR-based techniques and present a method to screen for such effects. After doing so, 377 of the 636 detected ions exhibited detectable gross fluxes during the study, implying a large number of species with active ecosystem-atmosphere exchange. We introduce the reactivity flux as a measure of how Earth-atmosphere fluxes influence ambient OH reactivity and show that the upward total VOC (∑VOC) carbon and reactivity fluxes are carried by a far smaller number of species than the downward fluxes. The model underpredicts the ∑VOC carbon and reactivity fluxes by 40-60% on average. However, the observed net fluxes are dominated (90% on a carbon basis, 95% on a reactivity basis) by known VOCs explicitly included in the CTM. As a result, the largest CTM uncertainties in simulating VOC carbon and reactivity exchange for this environment are associated with known rather than unrepresented species. This conclusion pertains to the set of species detectable by PTR-TOF techniques, which likely represents the majority in terms of carbon mass and OH reactivity, but not necessarily in terms of aerosol formation potential. In the case of oxygenated VOCs, the model severely underpredicts the gross fluxes and the net exchange. Here, unrepresented VOCs play a larger role, accounting for ~30% of the carbon flux and ~50% of the reactivity flux. The resulting CTM biases, however, are still smaller than those that arise from uncertainties for known and represented compounds.

Long-Term Trend of Gaseous Ammonia Over the United States: Modeling and Comparison With Observations

The concentrations of atmospheric ammonia ([NH3]) have been observed to be increasing over the United States in the last decade, especially in Eastern United States. It is important to understand this temporal trend and variation due to the role of NH3 in particle formation and its ecological effects. Here the long-term trend of [NH3] over the United States is investigated using GEOS-Chem, a global 3-D tropospheric chemistry model, and is corroborated with empirical evidence from the Ammonia Monitoring Network. Model simulations, consistent with observations, show increase in [NH3] over the United States from 2001 to 2016, with magnitude largest in the East (~5% to 12%/year) and smallest in the West (~0% to 5%/year). Reasons for this are examined, and evidence for the role of decreasing SO2 and NOx emissions in increasing [NH3] is provided. The contributions of meteorology and NH3 emission changes to the [NH3] increase appear to be small during the period. Our sensitivity study suggests that decreasing SO2 and NOx emissions over the United States owing to stringent regulations explain about 2/3 and 1/3 of the increase in [NH3], respectively. This effect is different for various NH3 and SO2 and NOx regimes. Given the continued reduction of SO2 and NOx emissions due to U.S. regulations mainly aimed at PM2.5 reduction, the present results are important towards better assessing the environmental impact of emission controlling policies.

Modeling emissions for three-dimensional atmospheric chemistry transport models

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scales and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed, and new methods to improve the spatiotemporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions such as national totals on appropriate grids. The wide area of natural emissions is also summarized, and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example, by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date.

IMPLICATIONS

Emission data are probably the most important input for chemistry transport model (CTM) systems. They need to be provided in high spatial and temporal resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g., for ammonia emissions, provide grid cell-dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.