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.

Sensitivity of air quality to vehicle ammonia emissions in the United States

The US Environmental Protection Agency (EPA) estimates on-road vehicles emissions using the Motor Vehicle Emission Simulator (MOVES). We developed updated ammonia emission rates for MOVES based on road-side exhaust emission measurements of light-duty gasoline and heavy-duty diesel vehicles. The resulting nationwide on-road vehicle ammonia emissions are 1.8, 2.1, 1.8, and 1.6 times higher than the MOVES3 estimates for calendar years 2010, 2017, 2024, and 2035, respectively, primarily due to an increase in light-duty gasoline vehicle NH3 emission rates. We conducted an air quality simulation using the Community Multi-Scale Air Quality (CMAQv5.3.2) model to evaluate the sensitivity of modeled ammonia and fine particulate matter (PM2.5) concentrations in calendar year 2017 using the updated on-road vehicle ammonia emissions. The average monthly urban ammonia ambient concentrations increased by up to 2.3 ppbv in January and 3.0 ppbv in July. The updated on-road NH3 emission rates resulted in better agreement of modeled ammonia concentrations with 2017 annual average ambient ammonia measurements, reducing model bias by 5.8 % in the Northeast region. Modeled average winter PM2.5 concentrations increased in urban areas, including enhancements of up to 0.5 μg/m3 in the northeast United States. The updated ammonia emission rates have been incorporated in MOVES4 and will be used in future versions of the NEI and EPA's modeling platforms.

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.

Characteristics of aerosol aminiums over a coastal city in North China: Insights from the divergent impacts of marine and terrestrial influences

Aminium ions, as crucial alkaline components within fine atmospheric particles, have a notable influence on new particle formation and haze occurrence. Their concentrations within coastal atmosphere depict considerable variation due to the interplay of distinctive marine and terrestrial sources, further complicated by dynamic meteorological conditions. This study conducted a comprehensive examination of aminiums ions concentrations, with a particular focus on methylaminium (MMAH+), dimethylaminium (DMAH+), trimethylaminium (TMAH+), and triethylaminium (TEAH+) within PM2.5, over varying seasons (summer, autumn, and winter of 2019 and summer of 2021), at an urban site in the coastal megacity of Qingdao, Northern China. The investigations revealed that the total concentration of particulate aminium ions (∑Aminium) was 21.6 ± 23.6 ng/m3, exhibiting higher values in the autumn and winter compared to the two summer periods. Considering diurnal variations during autumn and winter, concentrations of particulate aminium ions (excluding TEAH+) exhibited a slight increase during the day compared to night, with a notable peak during the morning hours. However, it was not the case for TEAH+, which was argued to be readily oxidized by ambient oxidants in the afternoon. Additionally, the ∑Aminium within the summer demonstrated markedly elevated levels during the day compared to night, potentially attributed to daytime sea fog associated with sea-land breeze interactions. Positive matrix factorization results indicate terrestrial anthropogenic emissions, including vehicle emission mixed with road dust and primary pollution, as the primary sources of MMAH+ and DMAH+. Conversely, TMAH+ was predominantly emitted from agricultural and marine sources. With the dominance of sea breeze in summer, TMAH+ was identified as a primary marine emission correlated with sea salt, while MMAH+, DMAH+, and TEAH+ were postulated to undergo secondary formation. Furthermore, a notable inverse correlation was observed between TMAH+ and methanesulfonate in PM2.5, consistent with dynamic emissions of sulfur-content and nitrogen-content gases reported in the literature.

Temporal and spatial shifts in the chemical composition of urban coastal rainwaters of Kuwait: The role of air mass trajectory and meteorological variables

The rainwater chemistry encompasses the signatures of geogenic and anthropogenic processes along the regional air mass movement apart from the local sources. The predominance of dust events and anthropogenic emissions in arid regions facilitate new particle formation. Further, rain events of different seasons depict moisture sources from diverse regions reflecting variation in the regional geochemistry with respect to seasons. Hence, to characterize the geochemical composition of rainwater, the study has focused on an integrated approach by considering regional transport, meteorological components and possible local sources. A total of 74 rainwater samples were collected from 27 rain events in 2018, 2019, and 2022, representing urban coastal areas of Kuwait predominantly of Ca-SO4-HCO3 type. The average pH and electrical conductivity of the rainwater were 7.18 and 140 μS/cm, respectively. The sea salt fractions calculated relative to Kuwait seawater ranged from 25.6 to >100 %, with higher values attributed to anthropogenic sources. Sea salt fraction, ion ratios, principal component analysis and factor scores revealed the terrestrial and anthropogenic sources apart from marine contributions. In addition, new particle formation and aerosols contributed to the rainwater chemistry involving SOx, NOx, and photochemical reactions during higher relative humidity and lesser wind speed. The HYSPLIT reflected that the moisture sources were largely from western regions of the study area, and those of December and January events had long-distance travel across the Azores high originating from northeast America. The trajectories of the November events are observed to originate from the Caspian/Black Sea region in the northeastern part of Kuwait with a relatively shorter distance of travel. The rainfall samples had higher ionic concentrations, and saturated with aragonite and calcite minerals in a few locations specifically after the dust events, while the subsequent rain events were less polluted.

Sources of PM2.5-Associated Health Risks in Europe and Corresponding Emission-Induced Changes During 2005-2015

We present a newly developed approach to characterize the sources of fine particulate matter (PM_2.5)-related premature deaths in Europe using the chemical transport model GEOS-Chem and its adjoint. The contributions of emissions from each individual country, species, and sector are quantified and mapped out at km scale. In 2015, total PM_2.5-related premature death is estimated to be 449,813 (257,846-722,138) in Europe, 59.0% of which were contributed by domestic anthropogenic emissions. The anthropogenic emissions of nitrogen oxides, ammonia, and organic carbon contributed most to the PM_2.5-related health damages, making up 29.6%, 23.2%, and 16.8%, respectively of all domestic anthropogenic contributions. Residential, agricultural, and ground transport emissions are calculated to be the largest three sectoral sources of PM_2.5-related health risks, accounting for 23.5%, 23.0%, and 19.4%, respectively, of total anthropogenic contributions within Europe. After excluding the influence of extra-regional sources, we find eastern European countries suffered from more premature deaths than their emissions caused; in contrast, the emissions from some central and western European regions contributed premature deaths exceeding three times the number of deaths that occurred locally. During 2005-2015, the first decade of PM_2.5 regulation in Europe, emission controls reduced PM_2.5-related health damages in nearly all European countries, resulting in 63,538 (46,092-91,082) fewer PM_2.5-related premature deaths. However, our calculation suggests that efforts to reduce air pollution from key sectors in some countries can be offset by the lag in control of emissions in others. International cooperation is therefore vitally important for tackling air pollution and reducing corresponding detrimental effects on public health.

Air pollution mitigation assessment to inform Cambodia's first clean air plan

Cambodia's 16.5 million people are exposed to air pollution in excess of World Health Organisation guidelines. The Royal Government of Cambodia has regulated air pollutant emissions and concentrations since 2000, but rapid economic growth and energy consumption means air pollution continues to impact human health. In December 2021, the Ministry of Environment of Cambodia published Cambodia's first Clean Air Plan that outlines actions to reduce air pollutant emissions over the next decade. This work presents the quantitative air pollution mitigation assessment underpinning the identification and evaluation of measures included in Cambodia's Clean Air Plan. Historic emissions of particulate matter (PM_2.5, black carbon, organic carbon) and gaseous (nitrogen oxides, volatile organic compounds, sulphur dioxide, ammonia, and carbon monoxide) air pollutants are quantified between 2010 and 2015, and projected to 2030 for a baseline scenario. Mitigation scenarios reflecting implementation of 14 measures included in Cambodia's Clean Air Plan were modelled, to quantify the national reduction in emissions, from which the reduction in ambient PM_2.5 exposure and attributable health burdens were estimated. In 2015, the residential, transport, and waste sectors contribute the largest fraction of national total air pollutant emissions. Without emission reduction measures, air pollutant emissions could increase by between 50 and 150% in 2030 compared to 2015 levels, predominantly due to increases in transport emissions. The implementation of the 14 mitigation measures could substantially reduce emissions of all air pollutants, by between 60 and 80% in 2030 compared to the baseline. This reduction in emissions was estimated to avoid approximately 900 (95% C.I.: 530-1200) premature deaths per year in 2030 compared to the baseline scenario. In addition to improving air pollution and public health, Cambodia's Clean Air Plan could also to lead to additional benefits, including a 19% reduction in carbon dioxide emissions, simultaneously contributing to Cambodia's climate change goals.

Assessing the ecological risk induced by PM2.5 pollution in a fast developing urban agglomeration of southeastern China

High PM_2.5 concentration threats ecosystem functions but limited quantitative studies have recognized PM_2.5 pollution as an individual stressor in evaluating ecological risk. In this study, we applied a machine-learning-based simulation model incorporating full-coverage satellite-driven PM_2.5 dataset to estimate high-resolution ground PM_2.5 concentration for the Golden Triangle of Southern Fujian Province, China (GTSF) in 2030 under two Representative Concentration Pathways (RCPs). Based on the simulation output, the ecological risk's spatiotemporal change and the risk for different land cover types, which were caused by PM_2.5 pollution, were assessed. We found that the PM_2.5 levels and ecological risk in the GTSF under RCP 4.5 would be reduced while those under RCP 8.5 would continue to increase. The regions with the highest ecological risk under RCP 4.5 are the most urbanized and industrialized districts, while those with the highest ecological risk under RCP 8.5 are of the highest rate in urbanization and the greatest decrease in planetary potential layer height. For both base years and 2030 under two RCPs, the ecological risk on developed land is the highest, while that on the forest is the lowest. Our study can provide useful information for environmental policy risk assessment.

Remote Aerosol Simulated During the Atmospheric Tomography (ATom) Campaign and Implications for Aerosol Lifetime

We investigate and assess how well a global chemical transport model (GEOS-Chem) simulates submicron aerosol mass concentrations in the remote troposphere. The simulated speciated aerosol (organic aerosol (OA), black carbon, sulfate, nitrate, and ammonium) mass concentrations are evaluated against airborne observations made during all four seasons of the NASA Atmospheric Tomography Mission (ATom) deployments over the remote Pacific and Atlantic Oceans. Such measurements over pristine environments offer fresh insights into the spatial (Northern [NH] and Southern Hemispheres [SH], Atlantic, and Pacific Oceans) and temporal (all seasons) variability in aerosol composition and lifetime, away from continental sources. The model captures the dominance of fine OA and sulfate aerosol mass concentrations in all seasons. There is a high bias across all species in the ATom-2 (NH winter) simulations; implementing recent updates to the wet scavenging parameterization improves our simulations, eliminating the large ATom-2 (NH winter) bias, improving the ATom-1 (NH summer) and ATom-3 (NH fall) simulations, but producing a model underestimate in aerosol mass concentrations for the ATom-4 (NH spring) simulations. Following the wet scavenging updates, simulated global annual mean aerosol lifetimes vary from 1.9 to 4.0 days, depending on species. Aerosol lifetimes in each hemisphere vary by season, and are longest for carbonaceous aerosol during the southern hemispheric fire season. The updated wet scavenging parameterization brings simulated concentrations closer to observations and reduces global aerosol lifetime for all species, indicating the sensitivity of global aerosol lifetime and burden to wet removal processes.

Summer ozone pollution in China affected by the intensity of Asian monsoon systems

Ozone in the troposphere is harmful to human health and ecosystems. It has become the most severe air pollutant in China. Here, based on global atmospheric chemistry model simulations during 1981-2019 and nation-wide surface observations, the impacts of interannual variations in Asian summer monsoon (ASM), including East Asian summer monsoon (EASM) and South Asian summer monsoon (SASM), on surface O₃ concentrations during June-July-August (JJA) in China are investigated. EASM intensity has a significant positive correlation with the surface O₃ concentration in south-central China (97.5°-117.5°E, 20°-35°N) with a correlation coefficient of 0.6. Relative to the weak EASM years, O₃ concentrations in strong EASM years increased by up to 5 ppb (10 % relative to the average) due to the weakened transboundary transport of O₃ resulting from the decrease in prevailing southwesterlies. SASM can be divided into two components. The one near East Asia has a similar relation with O₃ in southern China (100°-117.5°E, 22°-32°N) as that of EASM. The other component of SASM is negatively correlated with surface O₃ concentration in eastern China (110°-117.5°E, 22°-34°N) and the maximum difference in O₃ concentrations exceeded 5 ppb (10 %) between the strong and weak monsoon years, which can be explained by the O₃ divergence caused by the anomalous southerlies blowing pollutants away from the northern boundary of eastern China. This study shows that the ASM has an important impact on the O₃ concentrations in China, primarily through changing transboundary transport related to the variability of large-scale circulations, which has great implications for air pollution prevention and mitigation in China. Future projections of ASM suggests that the sustainable and medium development scenarios are the perfect pathways that can help to mitigate O₃ pollution, while high social vulnerability and radiative forcing scenarios could enhance future O₃ pollution in China.

Stringent Emission Controls Are Needed to Reach Clean Air Targets for Cities in China under a Warming Climate

Quantifying the threat that climate change poses to fine particle (PM_2.5) pollution is hampered by large uncertainties in the relationship between PM_2.5 and meteorology. To constrain the impact of climate change on PM_2.5, statistical models are often employed in a different manner than physical-chemical models to reduce the requirement of input data. A majority of statistical models predict PM_2.5 concentration (often log-transformed) as a simple function of meteorology, which could be biased due to the conversion of precursor gases to PM_2.5. We reduced this bias by developing a unique statistic model where the sum of PM_2.5 and the weighted precursor gases, rather than the PM_2.5 alone, was predicted as a function of meteorology and a proxy of primary emissions, where the input data of PM₁₀, CO, O₃, NO_x, and SO₂ were obtained from routine measurements. This modification, without losing the simplicity of statistical models, reduced the mean-square error from 27 to 17% and increased the coefficient of determination from 47 to 67% in the model cross-validation using daily PM_2.5 observations during 2013-2018 for 74 cities over China. We found a previously unrecognized mechanism that synoptic climate change in the past half-century might have increased low quantiles of PM_2.5 more strenuously than the upper quantiles in large cities over China. Climate change during 1971-2018 was projected to increase the annual mean concentration of PM_2.5 at a degree that could be comparable with the toughest-ever clean air policy during 2013-2018 had counteracted it, as inferred from the decline in the daily concentration of carbon monoxide as an inert gas. Our estimate of the impact of climate change on PM_2.5 is higher than previous statistical models, suggesting that aerosol chemistry might play a more important role than previously thought in the interaction between climate change and air pollution. Our result indicated that air quality might degrade if the future synoptic climate change could continue interacting with aerosol chemistry as it had occurred in the past half-century.

Simulating indoor inorganic aerosols of outdoor origin with the inorganic aerosol thermodynamic equilibrium model ISORROPIA

Outdoor aerosols can transform and have their composition altered upon transport indoors. Herein, IMAGES, a platform that simulates indoor organic aerosol with the 2-dimensional volatility basis set (2D-VBS), was extended to incorporate the inorganic aerosol thermodynamic equilibrium model, ISORROPIA. The model performance was evaluated by comparing aerosol component predictions to indoor measurements from an aerosol mass spectrometer taken during the summer and winter seasons. Since ammonia was not measured in the validation dataset, outdoor ammonia was estimated from aerosol measurements using a novel pH-based algorithm, while nitric acid was held constant. Modeled indoor ammonia sources included temperature-based occupant and surface emissions. Sensitivity to the nitric acid indoor surface deposition rate β g , HNO 3 , g was explored by varying it in model runs, which did not affect modeled sulfate due to its non-volatile nature, though the fitting of a filter efficiency was required for good correlations of modeled sulfate with measurements in both seasons. Modeled summertime nitrate well-matched measured observations when β g , HNO 3 , g = 2.75 h - 1 , but wintertime comparisons were poor, possibly due to missing thermodynamic processes within the heating, ventilating, and air-conditioning (HVAC) system. Ammonium was consistently overpredicted, potentially due to neglecting thirdhand smoke impacts observed in the field campaign, as well as HVAC impacts.

Aerosol-Radiation Interactions in China in Winter: Competing Effects of Reduced Shortwave Radiation and Cloud-Snowfall-Albedo Feedbacks Under Rapidly Changing Emissions

Since 2013, Chinese policies have dramatically reduced emissions of particulates and their gas-phase precursors, but the implications of these reductions for aerosol-radiation interactions are unknown. Using a global, coupled chemistry-climate model, we examine how the radiative impacts of Chinese air pollution in the winter months of 2012 and 2013 affect local meteorology and how these changes may, in turn, influence surface concentrations of PM_2.5, particulate matter with diameter <2.5 μm. We then investigate how decreasing emissions through 2016 and 2017 alter this impact. We find that absorbing aerosols aloft in winter 2012 and 2013 heat the middle- and lower troposphere by ∼0.5-1 K, reducing cloud liquid water, snowfall, and snow cover. The subsequent decline in surface albedo appears to counteract the ∼15-20 W m^-2 decrease in shortwave radiation reaching the surface due to attenuation by aerosols overhead. The net result of this novel cloud-snowfall-albedo feedback in winters 2012-2013 is a slight increase in surface temperature of ∼0.5-1 K in some regions and little change elsewhere. The aerosol heating aloft, however, stabilizes the atmosphere and decreases the seasonal mean planetary boundary layer (PBL) height by ∼50 m. In winter 2016 and 2017, the ∼20% decrease in mean PM_2.5 weakens the cloud-snowfall-albedo feedback, though it is still evident in western China, where the feedback again warms the surface by ∼0.5-1 K. Regardless of emissions, we find that aerosol-radiation interactions enhance mean surface PM_2.5 pollution by 10%-20% across much of China during all four winters examined, mainly though suppression of PBL heights.

Projected Aerosol Changes Driven by Emissions and Climate Change Using a Machine Learning Method

Projection of future aerosols and understanding the driver of the aerosol changes are of great importance in improving the atmospheric environment and climate change mitigation. The latest Coupled Model Intercomparison Project Phase 6 (CMIP6) provides various climate projections but limited aerosol output. In this study, future near-surface aerosol concentrations from 2015 to 2100 are predicted based on a machine learning method. The machine learning model is trained with global atmospheric chemistry model results and projects aerosols with CMIP6 multi-model simulations, creatively estimating future aerosols with all important species considered. PM_2.5 (particulate matter less than 2.5 μm in diameter) concentrations in 2095 (2091-2100 mean) are projected to decrease by 40% in East Asia, 20-35% in South Asia, and 15-25% in Europe and North America, compared to those in 2020 (2015-2024 mean), under low-emission scenarios (SSP1-2.6 and SSP2-4.5), which are mainly due to the presumed emission reductions. Driven by the climate change alone, PM_2.5 concentrations would increase by 10-25% in northern China and western U.S. and decrease by 0-25% in southern China, South Asia, and Europe under the high forcing scenario (SSP5-8.5). A warmer climate exerts a stronger modulation on global aerosols. Climate-driven global future aerosol changes are found to be comparable to those contributed by changes in anthropogenic emissions over many regions of the world in high forcing scenarios, highlighting the importance of climate change in regulating future air quality.

Improving surface PM2.5 forecasts in the United States using an ensemble of chemical transport model outputs: 2. bias correction with satellite data for rural areas

This work serves as the second of a two-part study to improve surface PM2.5 forecasts in the continental U.S. through the integrated use of multi-satellite aerosol optical depth (AOD) products (MODIS Terra/Aqua and VIIRS DT/DB), multi chemical transport model (CTM) (GEOS-Chem, WRF-Chem and CMAQ) outputs and ground observations. In part I of the study, a multi-model ensemble Kalman filter (KF) technique using three CTM outputs and ground observations was developed to correct forecast bias and generate a single best forecast of PM2.5 for next day over non-rural areas that have surface PM2.5 measurements in the proximity of 125 km. Here, with AOD data, we extended the bias correction into rural areas where the closest air quality monitoring station is at least 125 - 300 km away. First, we ensembled all of satellite AOD products to yield the single best AOD. Second, we corrected daily PM2.5 in rural areas from multiple models through the AOD spatial pattern between these areas and non-rural areas, referred to as "extended ground truth" or EGT, for today. Lastly, we applied the KF technique to update the bias in the forecast for next day using the EGT. Our results find that the ensemble of bias-corrected daily PM2.5 from three models for both today and next day show the best performance. Together, the two-part study develops a multi-model and multi-AOD bias correction technique that has the potential to improve PM2.5 forecasts in both rural and non-rural areas in near real time, and be readily implemented at state levels.

Air Quality in Africa: Public Health Implications

This review highlights the importance of air quality in the African urban development process. We address connections between air pollution and (a) rapid urbanization, (b) social problems, (c) health impacts, (d) climate change, (e) policies, and (f) new innovations. We acknowledge that air pollution levels in Africa can be extremely high and a serious health threat. The toxic content of the pollution could relate to region-specific sources such as low standards for vehicles and fuels, cooking with solid fuels, and burning household waste. We implore the pursuit of interdisciplinary research to create new approaches with relevant stakeholders. Moreover, successful air pollution research must regard conflicts, tensions, and synergies inherent to development processes in African municipalities, regions, and countries. This includes global relationships regarding climate change, trade, urban planning, and transportation. Incorporating aspects of local political situations (e.g., democracy) can also enhance greater political accountability and awareness about air pollution.

On the impact of the COVID-19 pandemic on air quality in Florida

Since early 2020, the world has faced an unprecedented pandemic caused by the novel COVID-19 virus. In this study, we characterize the impact of the lockdown associated with the pandemic on air quality in six major cities across the state of Florida, namely: Jacksonville, Tallahassee, Gainesville, Orlando, Tampa, and Miami. Hourly measurements of PM_2.5, ozone, NO₂, SO₂, and CO were provided by the US EPA at thirty sites operated by the Florida Department of Environmental Protection during mid-February to mid-April from 2015 through 2020. To analyze the effect of the pandemic, atmospheric pollutant concentrations in 2020 were compared to historic data at these cities during the same period from 2015 to 2019. Reductions in NO₂ and CO levels were observed across the state in most cities and were attributed to restrictions in mobility and the decrease in vehicle usage amid the lockdown. Likewise, decreases in O₃ concentrations were observed and were related to the prevailing NO_x-limited regime during this time period. Changes in concentrations of SO₂ exhibited spatial variations, concentrations decreased in northern cities, however an increase was observed in central and southern cities, likely due to increased power generation at facilities primarily in the central and southern regions of the state. PM_2.5 levels varied temporally during the study and were positively correlated with SO₂ concentrations during the lockdown. In March, reductions in PM_2.5 levels were observed, however elevations in PM_2.5 concentrations in April were attributed to long-range transport of pollutants rather than local emissions. This study provides further insight into the impacts of the COVID-19 pandemic on anthropogenic sources from vehicular emissions and power generation in Florida. This work has implications for policies and regulations of vehicular emissions as well as consequences on the use of sustainable energy sources in the state.

Future air pollution related health burdens associated with RCP emission changes in the UK

Three Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) are used to simulate future ozone (O₃), nitrogen dioxide (NO₂), and fine particulate matter (PM_2.5) in the United Kingdom (UK) for the 2050s relative to the 2000s with an air quality model (AQUM) at a 12 km horizontal resolution. The present-day and future attributable fractions (AF) of mortality associated with long-term exposure to annual mean O₃, NO₂ and PM_2.5 have accordingly been estimated for the first time for regions across England, Scotland and Wales. Across the three RCPs (RCP2.6, RCP6.0 and RCP8.5), simulated annual mean of the daily maximum 8-h mean (MDA8) O₃ concentrations increase compared to present-day, likely due to decreases in NO_x (nitrogen oxides) emissions, leading to less titration of O₃ by NO. Annual mean NO₂ and PM_2.5 concentrations decrease under all RCPs for the 2050s, mostly driven by decreases in NO_x and sulphur dioxide (SO₂) emissions, respectively. The AF of mortality associated with long-term exposure to annual mean MDA8 O₃ is estimated to increase in the future across all the regions and for all RCPs. Reductions in NO₂ and PM_2.5 concentrations lead to reductions in the AF estimated for future periods under all RCPs, for both pollutants. Total mortality burdens are also highly sensitive to future population projections. Accounting for population projections exacerbates differences in total UK-wide MDA8 O₃-health burdens between present-day and future by up to a factor of ~3 but diminishes differences in NO₂-health burdens. For PM_2.5, accounting for future population projections results in additional UK-wide deaths brought forward compared to present-day under RCP2.6 and RCP6.0, even though the simulated PM_2.5 concentrations for the 2050s are estimated to decrease. Thus, these results highlight the sensitivity of future health burdens in the UK to future trends in atmospheric emissions over the UK as well as future population projections.

Effects of COVID-19 lockdowns on fine particulate matter concentrations

Lockdowns during the COVID-19 pandemic provide an unprecedented opportunity to examine the effects of human activity on air quality. The effects on fine particulate matter (PM2.5) are of particular interest, as PM2.5 is the leading environmental risk factor for mortality globally. We map global PM2.5 concentrations for January to April 2020 with a focus on China, Europe, and North America using a combination of satellite data, simulation, and ground-based observations. We examine PM2.5 concentrations during lockdown periods in 2020 compared to the same periods in 2018 to 2019. We find changes in population-weighted mean PM2.5 concentrations during the lockdowns of -11 to -15 μg/m3 across China, +1 to -2 μg/m3 across Europe, and 0 to -2 μg/m3 across North America. We explain these changes through a combination of meteorology and emission reductions, mostly due to transportation. This work demonstrates regional differences in the sensitivity of PM2.5 to emission sources.

Open fire exposure increases the risk of pregnancy loss in South Asia

Interactions between climate change and anthropogenic activities result in increasing numbers of open fires, which have been shown to harm maternal health. However, few studies have examined the association between open fire and pregnancy loss. We conduct a self-comparison case-control study including 24,876 mothers from South Asia, the region with the heaviest pregnancy-loss burden in the world. Exposure is assessed using a chemical transport model as the concentrations of fire-sourced PM_2.5 (i.e., fire PM_2.5). The adjusted odds ratio (OR) of pregnancy loss for a 1-μg/m³ increment in averaged concentration of fire PM_2.5 during pregnancy is estimated as 1.051 (95% confidence intervals [CI]: 1.035, 1.067). Because fire PM_2.5 is more strongly linked with pregnancy loss than non-fire PM_2.5 (OR: 1.014; 95% CI: 1.011, 1.016), it contributes to a non-neglectable fraction (13%) of PM_2.5-associated pregnancy loss. Here, we show maternal health is threaten by gestational exposure to fire smoke in South Asia.

Isotopic evidence for acidity-driven enhancement of sulfate formation after SO2 emission control

After the 1980s, atmospheric sulfate reduction is slower than the dramatic reductions in sulfur dioxide (SO₂) emissions. However, a lack of observational evidence has hindered the identification of causal feedback mechanisms. Here, we report an increase in the oxygen isotopic composition of sulfate ([Formula: see text]) in a Greenland ice core, implying an enhanced role of acidity-dependent in-cloud oxidation by ozone (up to 17 to 27%) in sulfate production since the 1960s. A global chemical transport model reproduces the magnitude of the increase in observed [Formula: see text] with a 10 to 15% enhancement in the conversion efficiency from SO₂ to sulfate in Eastern North America and Western Europe. With an expected continued decrease in atmospheric acidity, this feedback will continue in the future and partially hinder air quality improvements.

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.

Development and Evaluation of Chemistry-Aerosol-Climate Model CAM5-Chem-MAM7-MOSAIC: Global Atmospheric Distribution and Radiative Effects of Nitrate Aerosol

An advanced aerosol treatment, with a focus on semivolatile nitrate formation, is introduced into the Community Atmosphere Model version 5 with interactive chemistry (CAM5-chem) by coupling the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) with the 7-mode Modal Aerosol Module (MAM7). An important feature of MOSAIC is dynamic partitioning of all condensable gases to the different fine and coarse mode aerosols, as governed by mode-resolved thermodynamics and heterogeneous chemical reactions. Applied in the free-running mode from 1995 to 2005 with prescribed historical climatological conditions, the model simulates global distributions of sulfate, nitrate, and ammonium in good agreement with observations and previous studies. Inclusion of nitrate resulted in ∼10% higher global average accumulation mode number concentrations, indicating enhanced growth of Aitken mode aerosols from nitrate formation. While the simulated accumulation mode nitrate burdens are high over the anthropogenic source regions, the sea-salt and dust modes respectively constitute about 74% and 17% of the annual global average nitrate burden. Regional clear-sky shortwave radiative cooling of up to -5 W m-2 due to nitrate is seen, with a much smaller global average cooling of -0.05 W m-2. Significant enhancements in regional cloud condensation nuclei (at 0.1% supersaturation) and cloud droplet number concentrations are also attributed to nitrate, causing an additional global average shortwave cooling of -0.8 W m-2. Taking into consideration of changes in both longwave and shortwave radiation under all-sky conditions, the net change in the top of the atmosphere radiative fluxes induced by including nitrate aerosol is -0.7 W m-2.

Effect of emission control measures on ozone concentrations in Hangzhou during G20 meeting in 2016

The effect of emission control measures on ozone (O₃) concentrations in Hangzhou during G20 (The Group of Twenty Finance Ministers and Central Bank Governors) meeting during 24 August to 6 September of 2016 was evaluated using the nested version of a global chemical transport model. During G20, observed concentrations of PM₁₀, PM_2.5, SO₂, NO₂, and CO were all below national air quality standards, whereas those of MDA8 O₃ were above national standard (with an averaged value of 160.2 μg m^-3) but had a decreasing trend. Model sensitivity studies show that, MDA8 O₃ concentrations in Hangzhou during G20 were reduced by 11.3 μg m^-3 (6.8%), 14.8 μg m^-3 (8.9%), and 19.5 μg m^-3 (11.7%) with emission control measures in the core area, Zhejiang province, and the Yangtze River Delta (YRD) region, respectively, indicating that control measures were the most effective when carried out jointly in YRD. Considering the ratios of NO_x to VOCs during G20, Hangzhou and most areas of Zhejiang province were in transitional regime; reductions in either NO_x or VOCs could reduce O₃ concentrations. We also quantified how sensitive O₃ concentrations respond to emission reductions in sectors of industry, power, residential and transportation in the whole of YRD during G20. The removal of emissions in industry and transportation sectors would lead to the largest reductions of 17.6 μg m^-3 (10.5%) and 12.3 μg m^-3 (7.4%) in MDA8 O₃ concentrations in Hangzhou during G20, respectively. This study has important implications for the control of high O₃ levels in eastern China.

Quantification of Atmospheric Ammonia Concentrations: A Review of Its Measurement and Modeling

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing the current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions, such as the Midwest US and the North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ a few tens of pptv, variations of which can affect aerosol formation. Satellite remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at the surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, which is of concern from the standpoint of human health and the ecosystem.

Persistent ozone pollution episodes in North China exacerbated by regional transport

Summertime ozone (O₃) concentrations over China continue to increase although the governmental Clear Air Actions have been carried out since 2013. The worst O₃ pollution is confronted over North China Plain. Ozone polluted days (with observed regionally-averaged maximum daily 8-h average (MDA8) O₃ concentrations exceeding 80 ppbv) in May-July in North China increased from 35 days in year 2014 to 56 days in year 2018, and persistent O₃ pollution episodes that lasted for 5 days or longer (OPEs5) contributed 14.3% and 66.1% to those O₃ polluted days in 2014 and 2018, respectively. Model simulations suggest that O₃ transport from central eastern China (including Shandong, Henan, Jiangsu and Anhui Provinces) contributes 36% of the enhanced O₃ concentrations in North China during OPEs5 relative to the seasonal mean. We find that emission control of volatile organic compounds in central eastern China is most effective to alleviate intensity of OPEs5 in North China.

Global Importance of Hydroxymethanesulfonate in Ambient Particulate Matter: Implications for Air Quality

Sulfur compounds are an important constituent of particulate matter, with impacts on climate and public health. While most sulfur observed in particulate matter has been assumed to be sulfate, laboratory experiments reveal that hydroxymethanesulfonate (HMS), an adduct formed by aqueous phase chemical reaction of dissolved HCHO and SO2, may be easily misinterpreted in measurements as sulfate. Here we present observational and modeling evidence for a ubiquitous global presence of HMS. We find that filter samples collected in Shijiazhuang, China, and examined with ion chromatography within 9 days show as much as 7.6 μg m-3 of HMS, while samples from Singapore examined 9-18 months after collection reveal ~0.6 μg m-3 of HMS. The Shijiazhuang samples show only minor traces of HMS 4 months later, suggesting that HMS had decomposed over time during sample storage. In contrast, the Singapore samples do not clearly show a decline in HMS concentration over 2 months of monitoring. Measurements from over 150 sites, primarily derived from the IMPROVE network across the United States, suggest the ubiquitous presence of HMS in at least trace amounts as much as 60 days after collection. The degree of possible HMS decomposition in the IMPROVE observations is unknown. Using the GEOS-Chem chemical transport model, we estimate that HMS may account for 10% of global particulate sulfur in continental surface air and over 25% in many polluted regions. Our results suggest that reducing emissions of HCHO and other volatile organic compounds may have a co-benefit of decreasing particulate sulfur.

Global estimates of dry ammonia deposition inferred from space-measurements

Ammonia (NH₃), as an alkaline gas, contributes substantially to atmospheric nitrogen deposition, which can cause biodiversity loss, water eutrophication and soil acidification. Advances in the application of satellite observations allow us to gain deeper insights into atmospheric NH₃ concentrations at large spatial scales. A new satellite-based methodology is proposed for estimating dry NH₃ deposition with consideration of bi-directional NH₃ exchange. We estimate the global dry NH₃ deposition for nine years (2008-2016) by using the Infrared Atmospheric Sounding Interferometer Instrument (IASI) NH₃ retrievals. Satellite-based dry NH₃ deposition is in general consistent with measured dry NH₃ deposition over the monitoring sites (R² = 0.65). Global dry NH₃ deposition over 8 kg N ha^-1 is mainly distributed in the Eastern China, Northern and Central Pakistan, and Northern India. An annual increase rate of 0.27 and 0.13 kg N ha^-1 y^-1 in dry NH₃ deposition during 2008-2016 occurs in Eastern China and Sichuan Basin, which are the major Chinese agricultural regions. The NH₃ compensation point is high during warm months, and can be above 1 μg m^-3 such as in Eastern China, implying the importance of considering the NH₃ compensation points for estimating dry NH₃ deposition. We find, if the upward NH₃ flux was ignored, it will cause 11%, 17%, 5% and 3% overestimation in dry NH₃ deposition in Eastern China, Northern India, Eastern United States and Western Europe, respectively. This study presents the potential of using the satellite retrievals to estimate the large-scale dry NH₃ deposition, and the methodology is able to provide temporally continuous and spatially complete fine-resolution datasets.

Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 1. Bias Correction With Surface Observations in Nonrural Areas

This work is the first of a two-part study that aims to develop a computationally efficient bias correction framework to improve surface PM_2.5 forecasts in the United States. Here, an ensemble-based Kalman filter (KF) technique is developed primarily for nonrural areas with approximately 500 surface observation sites for PM_2.5 and applied to three (GEOS-Chem, WRF-Chem, and WRF-CMAQ) chemical transport model (CTM) hindcast outputs for June 2012. While all CTMs underestimate daily surface PM_2.5 mass concentration by 20-50%, KF correction is effective for improving each CTM forecast. Subsequently, two ensemble methods are formulated: (1) the arithmetic mean ensemble (AME) that equally weights each model and (2) the optimized ensemble (OPE) that calculates the individual model weights by minimizing the least-square errors. While the OPE shows superior performance than the AME, the combination of either the AME or the OPE with a KF performs better than the OPE alone, indicating the effectiveness of the KF technique. Overall, the combination of a KF with the OPE shows the best results. Lastly, the Successive Correction Method (SCM) was applied to spread the bias correction from model grids with surface PM_2.5 observations to the grids lacking ground observations by using a radius of influence of 125 km derived from surface observations, which further improves the forecast of surface PM_2.5 at the national scale. Our findings provide the foundation for the second part of this study that uses satellite-based aerosol optical depth (AOD) products to further improve the forecast of surface PM_2.5 in rural areas by performing statistical analysis of model output.

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.

Assessing the spatiotemporal characteristics of dry deposition flux in forests and wetlands

Forests and wetlands, as two important ecosystems, play a crucial role in reducing the concentration of particulate matters. The main purpose of this study is to reveal the contribution of forest and wetland ecosystems to the reduction of particulate matter. We collected the concentration and meteorological data during the daytime in a forest and a wetland in the Olympic Park in Beijing. The main results are as follows: daily variation in the PM₁₀ and PM_2.5 concentration had the similar trend with the lowest value at midday and relatively high values in the morning and at nightfall. In the forest ecosystem, the trend of PM₁₀ concentration at three heights followed the order: 6 m > 10 m > 1.5 m, while that of the PM_2.5 followed the order 1.5 m > 10 m > 6 m. In the wetland, PM₁₀ and PM_2.5 concentrations at the three heights exhibited the same trend: 10 m > 1.5 m > 6 m. It is a comprehensive impact on concentration which may include vegetation collection rate, meteorological conditions and some kind of human activities. The PM deposition velocity of wetland was higher than that of forest, and showed the highest values in winter both in PM_2.5 and PM₁₀. The PM deposition flux in wetland was lower than forest only in autumn, and the value of deposition flux was higher than forest in other seasons. PM concentrations was positively correlated with relative humidity but negatively correlated with temperature and wind velocity.

The Acidity of Atmospheric Particles and Clouds

Acidity, defined as pH, is a central component of aqueous chemistry. In the atmosphere, the acidity of condensed phases (aerosol particles, cloud water, and fog droplets) governs the phase partitioning of semi-volatile gases such as HNO3, NH3, HCl, and organic acids and bases as well as chemical reaction rates. It has implications for the atmospheric lifetime of pollutants, deposition, and human health. Despite its fundamental role in atmospheric processes, only recently has this field seen a growth in the number of studies on particle acidity. Even with this growth, many fine particle pH estimates must be based on thermodynamic model calculations since no operational techniques exist for direct measurements. Current information indicates acidic fine particles are ubiquitous, but observationally-constrained pH estimates are limited in spatial and temporal coverage. Clouds and fogs are also generally acidic, but to a lesser degree than particles, and have a range of pH that is quite sensitive to anthropogenic emissions of sulfur and nitrogen oxides, as well as ambient ammonia. Historical measurements indicate that cloud and fog droplet pH has changed in recent decades in response to controls on anthropogenic emissions, while the limited trend data for aerosol particles indicates acidity may be relatively constant due to the semi-volatile nature of the key acids and bases and buffering in particles. This paper reviews and synthesizes the current state of knowledge on the acidity of atmospheric condensed phases, specifically particles and cloud droplets. It includes recommendations for estimating acidity and pH, standard nomenclature, a synthesis of current pH estimates based on observations, and new model calculations on the local and global scale.

Causes of Large Increases in Atmospheric Ammonia in the Last Decade across North America

Decadal trends of atmospheric ammonia (NH₃) and their potential causes were explored through the analysis of monitored data collected at 15 sites in the United States and 7 sites in Canada. Large percentage increases in the annual average concentration of atmospheric NH₃, for example, >100% at 6 sites and 40-100% at 10 sites, were observed over the most recent 8-13 year period. In contrast, a decrease or a narrow variation in NH₃ emissions was reported at the state or provincial level in both countries during the same period. Decreased emissions of SO₂ and NO _x across North America in the past decade would have reduced the chemical loss of atmospheric NH₃ to form particulate NH₄ ⁺. Such a chemical mechanism was verified through regression analysis at about half of the monitored sites, where the increasing trends in atmospheric NH₃ were partially explained by the reduced NH₄ ⁺. Excluding the reduced contribution from this chemical loss to generate the adjusted annual NH₃ concentration through two approaches, no decreasing trends can be obtained to align those in emissions at most sites, implying that other factors also contributed to the increase in the annual NH₃ concentration. Correlation analysis results implied that enhanced drought conditions and increased ambient temperatures also likely contributed to the increasing trend in the annual NH₃ concentration at some sites. The large percentage increases in the annual NH₃ concentration cannot be fully explained by all the identified causes, leading to oppugning the reality of the decrease in NH₃ emissions reported across North America in the recent decade.

Climate impact on ambient PM2.5 elemental concentration in the United States: A trend analysis over the last 30 years

Weather impacts on the chemical composition of PM_2.5 varies significantly over space and time given the diversity of particle components and the complex mechanisms governing particle formation and removal. In this study, we employed generalized additive models (GAMs) to estimate weather-associated changes in PM_2.5 composition in the US during 1988-2017. We considered seven components of ambient PM_2.5, which included elemental carbon (EC), organic carbon (OC), nitrate, sulfate, sodium, ammonium, and silicon. The impact of long-term weather changes on each PM_2.5 component was defined in our study as "weather penalty". During our study period, temperature increased in four regions, including the Industrial Midwest and Northeast during the warm and cold season; and Upper Midwest and West in the cold season. Wind speed decreased in the both seasons. Relative humidity increased in the warm season and decreased in the cold season. The weather changes between 1988 and 2017 were associated with most PM_2.5 components during both warm and cold seasons. The direction and the magnitude of the weather penalty varied considerably over the space and season. In the warm season, our findings suggest a nationwide weather penalty for EC, OC, nitrate, sulfate, sodium, ammonium, and silicon of 0.04, 0.21, 0.04, 0.35, -0.01, 0.05, and 0.01 μg/m³, respectively. In the cold season, the estimated total penalty was 0.04, 0.21, 0.06, 0.04, -0.01, -0.02, and 0.02 μg/m³, respectively.

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.

Current and Future Responses of Aerosol pH and Composition in the U.S. to Declining SO2 Emissions and Increasing NH3 Emissions

Aerosol pH can affect gas-particle partitioning of semivolatile species, secondary aerosol formation, aerosol water uptake and growth, acid deposition, and, potentially, aerosol toxicity. Despite its importance, aerosol pH projected in the near future has not been addressed explicitly while investigating the response of aerosol concentrations to emission regulations. In this study, we apply CMAQ to simulate aerosol pH in 2011 and 2050 across the continental U.S. We also assess the influence of two major emission trends, declining SO₂ emissions and rising NH₃ emissions, with a set of sensitivity simulations. Our results show that the aerosols will remain acidic with average pH typically ranging from 0.5 to 3.5 in 2050. Further reducing domestic SO₂ emissions does not significantly decrease aerosol acidity, even if SO₂ emissions were reduced to preindustrial levels because of the nonlinear response of SO₄^2- concentration to SO₂ emissions, and the semivolatile NH₃-NH₄⁺ buffering effect. Aerosol pH response to NH₃ emission increase will remain minor. Consequently, future fine particulate matter control efficiency will not be undercut by additional nitrate aerosol formation even if SO₂ emissions from industry and electricity generation are aggressively controlled, although areas will see some substitution leading to nitrate increases if NO_x emissions are not reduced.

Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors

An accurate fine-resolution surface of the chemical composition of fine particulate matter (PM_2.5) would offer valuable information for epidemiological studies and health impact assessments. We develop geoscience-derived estimates of PM_2.5 composition from a chemical transport model (GEOS-Chem) and satellite observations of aerosol optical depth, and statistically fuse these estimates with ground-based observations using a geographically weighted regression over North America to produce a spatially complete representation of sulfate, nitrate, ammonium, black carbon, organic matter, mineral dust, and sea-salt over 2000-2016. Significant long-term agreement is found with cross-validation sites over North America (R² = 0.57-0.96), with the strongest agreement for sulfate (R² = 0.96), nitrate (R² = 0.90), and ammonium (R² = 0.86). We find that North American decreases in population-weighted fine particulate matter (PM_2.5) concentrations since 2000 have been most heavily influenced by regional changes in sulfate and organic matter. Regionally, the relative importance of several chemical components are found to change with PM_2.5 concentration, such as higher PM_2.5 concentrations having a larger proportion of nitrate and a smaller proportion of sulfate. This data set offers information for research into the health effects of PM_2.5 chemical components.

Contribution of Wildland-Fire Smoke to US PM2.5 and Its Influence on Recent Trends

Seasonal-mean concentrations of particulate matter with diameters smaller than 2.5 μm (PM_2.5) have been decreasing across the United States (US) for several decades, with large reductions in spring and summer in the eastern US. In contrast, summertime-mean PM_2.5 in the western US has not significantly decreased. Wildfires, a large source of summertime PM_2.5 in the western US, have been increasing in frequency and burned area in recent decades. Increases in extreme PM_2.5 events attributable to wildland fires have been observed in wildfire-prone regions, but it is unclear how these increases impact trends in seasonal-mean PM_2.5. Using two distinct methods, (1) interpolated surface observations combined with satellite-based smoke plume estimates and (2) the GEOS-Chem chemical transport model (CTM), we identify recent trends (2006-2016) in summer smoke, nonsmoke, and total PM_2.5 across the US. We observe significant decreases in nonsmoke influenced PM_2.5 in the western US and find increases in summer-mean smoke PM_2.5 in fire-prone regions, although these are not statistically significant due to large interannual variability in the abundance of smoke. These results indicate that without the influence of wildland fires, we would expect to have observed improvements in summer fine particle pollution in the western US but likely weaker improvements than those observed in the eastern US.

Strengthened scientific support for the Endangerment Finding for atmospheric greenhouse gases

We assess scientific evidence that has emerged since the U.S. Environmental Protection Agency’s 2009 Endangerment Finding for six well-mixed greenhouse gases and find that this new evidence lends increased support to the conclusion that these gases pose a danger to public health and welfare. Newly available evidence about a wide range of observed and projected impacts strengthens the association between the risk of some of these impacts and anthropogenic climate change, indicates that some impacts or combinations of impacts have the potential to be more severe than previously understood, and identifies substantial risk of additional impacts through processes and pathways not considered in the Endangerment Finding.

Impact of air pollution control policies on future PM2.5 concentrations and their source contributions in China

To investigate the impact of air pollutant control policies on future PM_2.5 concentrations and their source contributions in China, we developed four future scenarios for 2030 based on a 2013 emission inventory, and conducted air quality simulations for each scenario using the chemical transport model GEOS-Chem (version 9.1.3). Two energy scenarios i.e., current legislation (CLE) and with additional measures (WAM), were developed to project future energy consumption, reflecting, respectively, existing legislation and implementation status as of the end of 2012, and new energy-saving policies that would be released and enforced more stringently. Two end-of-pipe control strategies, i.e., current control technologies (until 2017) and more stringent control technologies (until 2030), were also developed. The combinations of energy scenarios and end-of-pipe control strategies constitute four emission scenarios (2017-CLE, 2030-CLE, 2017-WAM, and 2030-WAM) evaluated in simulations. PM_2.5 concentrations at national level were estimated to be 57 μg/m³ in the base year 2013, and 58 μg/m³, 42 μg/m³, 42 μg/m³, and 30 μg/m³ under the 2017-CLE, 2030-CLE, 2017-WAM, and 2030-WAM scenarios in 2030, respectively. Large PM_2.5 reductions between 2013 and 2030 were estimated for heavily polluted regions (Sichuan Basin, Middle Yangtze River, North China). The energy-saving policies show similar effects to the end-of-pipe emission control measures, but the relative importance of these two groups of policies varies in different regions. Absolute contributions to PM_2.5 concentrations from most major sources declined from 2017-CLE to 2030-WAM. With respect to fractional contributions, most coal-burning sectors (including power plant, industrial and residential coal burning) increased from 2017-CLE to 2030-WAM, due to larger reductions from non-coal sources, including transportation and biomass open burning. Residential combustion and open burning had much lower fractional contribution to ambient PM_2.5 concentrations in the 2017-WAM/2030-WAM compared to the 2017-CLE/2030-CLE scenarios. Fractional contributions from transportation were reduced dramatically in 2030-CLE and 2030-WAM compared to 2017-CLE/2017-WAM, due to the enforcement of stringent end-of-pipe emission controls. Across all scenarios, coal combustion remained the single largest contributor to PM_2.5 concentrations in 2030. Reducing PM_2.5 emissions from coal combustion remains a strategic priority for air quality management in China.

Implications of RCP emissions on future concentration and direct radiative forcing of secondary organic aerosol over China

This study applies the nested-grid version of Goddard Earth Observing System (GEOS) chemical transport model (GEOS-Chem) to examine future changes (2000-2050) in SOA concentration and associated direct radiative forcing (DRF) over China under the Representative Concentration Pathways (RCPs). The projected changes in SOA concentrations over 2010-2050 generally follow future changes in emissions of toluene and xylene. On an annual mean basis, the largest increase in SOA over eastern China is simulated to be 25.1% in 2020 under RCP2.6, 20.4% in 2020 under RCP4.5, 56.3% in 2050 under RCP6.0, and 44.6% in 2030 under RCP8.5. The role of SOA in PM_2.5 increases with each decade in 2010-2050 under RCP2.6, RCP4.5, and RCP8.5, with a maximum ratio of concentration of SOA to that of PM_2.5 of 16.3% in 2050 under RCP4.5 as averaged over eastern China (20°-45°N, 100°-125°E). Concentrations of SOA are projected to be able to exceed those of sulfate, ammonium, and black carbon (BC) in the future. The future changes in SOA levels over eastern China are simulated to lead to domain-averaged (20°-45°N, 100°-125°E) DRFs of +0.19 W m^-2, +0.12 W m^-2, - 0.28 W m^-2, and -0.17 W m^-2 in 2050 relative to 2000 under RCP2.6, RCP4.5, RCP6.0, and RCP8.5, respectively. Model results indicate that future changes in SOA owing to future changes in anthropogenic precursor emissions are important for future air quality planning and climate mitigation measures.

Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation

Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system. By 2046-2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NO_x), volatile organic compounds (VOCs), ammonia (NH₃), and sulfur dioxide (SO₂) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively large increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NO_x, VOC, and NH₃, while emissions from both the on-road and non-road modes have strong contributions to PM and SO₂ emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations.

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

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

POPULATION

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

Source influence on emission pathways and ambient PM2.5 pollution over India (2015-2050)

India is currently experiencing degraded air quality, and future economic development will lead to challenges for air quality management. Scenarios of sectoral emissions of fine particulate matter and its precursors were developed and evaluated for 2015-2050, under specific pathways of diffusion of cleaner and more energy-efficient technologies. The impacts of individual source sectors on PM_2.5 concentrations were assessed through systematic simulations of spatially and temporally resolved particulate matter concentrations, using the GEOS-Chem model, followed by population-weighted aggregation to national and state levels. We find that PM_2.5 pollution is a pan-India problem, with a regional character, and is not limited to urban areas or megacities. Under present-day emissions, levels in most states exceeded the national PM_2.5 annual standard (40 μg m^-3). Sources related to human activities were responsible for the largest proportion of the present-day population exposure to PM_2.5 in India. About 60 % of India's mean population-weighted PM_2.5 concentrations come from anthropogenic source sectors, while the remainder are from "other" sources, windblown dust and extra-regional sources. Leading contributors are residential biomass combustion, power plant and industrial coal combustion and anthropogenic dust (including coal fly ash, fugitive road dust and waste burning). Transportation, brick production and distributed diesel were other contributors to PM_2.5. Future evolution of emissions under regulations set at current levels and promulgated levels caused further deterioration of air quality in 2030 and 2050. Under an ambitious prospective policy scenario, promoting very large shifts away from traditional biomass technologies and coal-based electricity generation, significant reductions in PM_2.5 levels are achievable in 2030 and 2050. Effective mitigation of future air pollution in India requires adoption of aggressive prospective regulation, currently not formulated, for a three-pronged switch away from (i) biomass-fuelled traditional technologies, (ii) industrial coal-burning and (iii) open burning of agricultural residue. Future air pollution is dominated by industrial process emissions, reflecting larger expansion in industrial, rather than residential energy demand. However, even under the most active reductions envisioned, the 2050 mean exposure, excluding any impact from windblown mineral dust, is estimated to be nearly 3 times higher than the WHO Air Quality Guideline.

Air pollution at Rochester, NY: Long-term trends and multivariate analysis of upwind SO2 source impacts

There have been many changes in the air pollutant sources in the northeastern United States since 2001. To assess the effect of these changes, trend analyses of the monthly average values were performed on PM_2.5 and its components including major ions, elemental carbon (EC), organic carbon (OC), and gaseous pollutant concentrations measured between 2001 (in some cases 1999) and 2015 at the NYS Department of Environmental Conservation sites in Rochester, NY. Mann-Kendall regression with Sen's slope was applied to estimate the trends and seasonality. Using piecewise regression, significant reductions in the air pollution of Rochester area were observed between 2008 and 2010 when a 260MW coal-fired power plant was decommissioned, new heavy-duty diesel trucks had to be equipped with catalytic regenerator traps, and the economic recession that began in 2008 reduced traffic and other activities. The monthly average PM_2.5 mass showed a downward trend (-5μg/m³; -41%) in Rochester between 2001 and 2015. This change is largely due to reductions in particulate sulfate that showed a 65% decrease. The sulfate concentrations were compared to changes in SO₂ emissions in seventeen upwind source domains, and other systematic changes by multivariate linear regression. Selectivity ratio obtained from target projection discriminated the most important source domains that are SO₂ emissions from Georgia for winter, North Carolina for transition (spring and fall) and Ohio along with other influences for summer. North Carolina and Michigan were identified as the main sources for entire period. These observations suggest that any further reductions in the specified regional SO₂ emissions would result in a proportional decrease in sulfate in Rochester.

The potential effects of climate change on air quality across the conterminous U.S. at 2030 under three Representative Concentration Pathways

The potential impacts of climate change on regional ozone (O3) and fine particulate (PM2.5) air quality in the United States are investigated by linking global climate simulations with regional scale meteorological and chemical transport models. Regional climate at 2000 and at 2030 under three Representative Concentration Pathways (RCPs) is simulated by using the Weather Research and Forecasting (WRF) model to downscale 11-year time slices from the Community Earth System Model (CESM). The downscaled meteorology is then used with the Community Multiscale Air Quality (CMAQ) model to simulate air quality during each of these 11-year periods. The analysis isolates the future air quality differences arising from climate-driven changes in meteorological parameters and specific natural emissions sources that are strongly influenced by meteorology. Other factors that will affect future air quality, such as anthropogenic air pollutant emissions and chemical boundary conditions, are unchanged across the simulations. The regional climate fields represent historical daily maximum and daily minimum temperatures well, with mean biases less than 2 K for most regions of the U.S. and most seasons of the year and good representation of variability. Precipitation in the central and eastern U.S. is well simulated for the historical period, with seasonal and annual biases generally less than 25%, with positive biases exceeding 25% in the western U.S. throughout the year and in part of the eastern U.S. during summer. Maximum daily 8-h ozone (MDA8 O3) is projected to increase during summer and autumn in the central and eastern U.S. The increase in summer mean MDA8 O3 is largest under RCP8.5, exceeding 4 ppb in some locations, with smaller seasonal mean increases of up to 2 ppb simulated during autumn and changes during spring generally less than 1 ppb. Increases are magnified at the upper end of the O3 distribution, particularly where projected increases in temperature are greater. Annual average PM2.5 concentration changes range from -1.0 to 1.0 μg m-3. Organic PM2.5 concentrations increase during summer and autumn due to increased biogenic emissions. Aerosol nitrate decreases during winter, accompanied by lesser decreases in ammonium and sulfate, due to warmer temperatures causing increased partitioning to the gas phase. Among meteorological factors examined to account for modeled changes in pollution, temperature and isoprene emissions are found to have the largest changes and the greatest impact on O3 concentrations.

Developing and diagnosing climate change indicators of regional aerosol optical properties

Given the importance of aerosol particles to radiative transfer via aerosol-radiation interactions, a methodology for tracking and diagnosing causes of temporal changes in regional-scale aerosol populations is illustrated. The aerosol optical properties tracked include estimates of total columnar burden (aerosol optical depth, AOD), dominant size mode (Ångström exponent, AE), and relative magnitude of radiation scattering versus absorption (single scattering albedo, SSA), along with metrics of the structure of the spatial field of these properties. Over well-defined regions of North America, there are generally negative temporal trends in mean and extreme AOD, and SSA. These are consistent with lower aerosol burdens and transition towards a relatively absorbing aerosol, driven primarily by declining sulfur dioxide emissions. Conversely, more remote regions are characterized by increasing mean and extreme AOD that is attributed to increased local wildfire emissions and long-range (transcontinental) transport. Regional and national reductions in anthropogenic emissions of aerosol precursors are leading to declining spatial autocorrelation in the aerosol fields and increased importance of local anthropogenic emissions in dictating aerosol burdens. However, synoptic types associated with high aerosol burdens are intensifying (becoming more warm and humid), and thus changes in synoptic meteorology may be offsetting aerosol burden reductions associated with emissions legislation.

Climate change impacts on human health over Europe through its effect on air quality

This review examines the current literature on the effects of future emissions and climate change on particulate matter (PM) and O₃ air quality and on the consequent health impacts, with a focus on Europe. There is considerable literature on the effects of climate change on O₃ but fewer studies on the effects of climate change on PM concentrations. Under the latest Intergovernmental Panel on Climate Change (IPCC) 5th assessment report (AR5) Representative Concentration Pathways (RCPs), background O₃ entering Europe is expected to decrease under most scenarios due to higher water vapour concentrations in a warmer climate. However, under the extreme pathway RCP8.5 higher (more than double) methane (CH₄) abundances lead to increases in background O₃ that offset the O₃ decrease due to climate change especially for the 2100 period. Regionally, in polluted areas with high levels of nitrogen oxides (NO_x), elevated surface temperatures and humidities yield increases in surface O₃ - termed the O₃ climate penalty - especially in southern Europe. The O₃ response is larger for metrics that represent the higher end of the O₃ distribution, such as daily maximum O₃. Future changes in PM concentrations due to climate change are much less certain, although several recent studies also suggest a PM climate penalty due to high temperatures and humidity and reduced precipitation in northern mid-latitude land regions in 2100.A larger number of studies have examined both future climate and emissions changes under the RCP scenarios. Under these pathways the impact of emission changes on air quality out to the 2050s will be larger than that due to climate change, because of large reductions in emissions of O₃ and PM pollutant precursor emissions and the more limited climate change response itself. Climate change will also affect climate extreme events such as heatwaves. Air pollution episodes are associated with stagnation events and sometimes heat waves. Air quality during the 2003 heatwave over Europe has been examined in numerous studies and mechanisms for enhancing O₃ have been identified.There are few studies on health effects associated with climate change impacts alone on air quality, but these report higher O₃-related health burdens in polluted populated regions and greater PM_2.5 health burdens in these emission regions. Studies that examine the combined impacts of climate change and anthropogenic emissions change under the RCP scenarios report reductions in global and European premature O₃-respiratory related and PM mortalities arising from the large decreases in precursor emissions. Under RCP 8.5 the large increase in CH₄ leads to global and European excess O₃-respiratory related mortalities in 2100. For future health effects, besides uncertainty in future O₃ and particularly PM concentrations, there is also uncertainty in risk estimates such as effect modification by temperature on pollutant-response relationships and potential future adaptation that would alter exposure risk.