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Nitrogen oxide radicals (NOx≡NO+NO2) emitted by fuel combustion are important precursors of ozone and particulate matter pollution, and NO 2 itself is harmful to public health. The Geostationary Environment Monitoring Spectrometer (GEMS), launched in space in 2020, now provides hourly daytime observations of NO 2 columns over East Asia. This diurnal variation offers unique information on the emission and chemistry of NOx , but it needs to be carefully interpreted. Here we investigate the drivers of the diurnal variation in NO 2 observed by GEMS during winter and summer over Beijing and Seoul. We place the GEMS observations in the context of ground-based column observations (Pandora instruments) and GEOS-Chem chemical transport model simulations. We find good agreement between the diurnal variations in NO 2 columns in GEMS, Pandora, and GEOS-Chem, and we use GEOS-Chem to interpret these variations. NOx emissions are 4 times higher in the daytime than at night, driving an accumulation of NO 2 over the course of the day, offset by losses from chemistry and transport (horizontal flux divergence). For the urban core, where the Pandora instruments are located, we find that NO 2 in winter increases throughout the day due to high daytime emissions and increasing NO2/NOx ratio from entrainment of ozone, partly balanced by loss from transport and with a negligible role of chemistry. In summer, by contrast, chemical loss combined with transport drives a minimum in the NO 2 column at 13:00–14:00 local time (LT). Segregation of the GEMS data by wind speed further demonstrates the effect of transport, with NO 2 in winter accumulating throughout the day at low winds but flat at high winds. The effect of transport can be minimized in summer by spatially averaging observations over the broader metropolitan scale, under which conditions the diurnal variation in NO 2 reflects a dynamic balance between emission and chemical loss. [ABSTRACT FROM AUTHOR]

Anthropogenic emissions of aerosols and precursor gases have changed significantly in the past few decades around the world. In this study, the Explicit Aerosol Source Tagging (EAST) system is merged into the Energy Exascale Earth System Model version 1 (E3SMv1) to quantify the variations in anthropogenic aerosol concentrations, source contributions, and their subsequent radiative impact in four major emission regions across the globe during 1850–1980, 1980–2010, and 2010–2017. In North America and Europe, changes in anthropogenic PM2.5 were mainly caused by changes in emissions from local energy and industrial sectors. The local industrial sector caused the largest increase in PM2.5 in East Asia during 1980–2010 and decrease during 2010–2017. In South Asia, the increase in energy-related emissions dominated the rise in PM2.5 levels during 1980–2017. During 1850–1980, the increases in emissions from North America contributed to the increase in the European PM2.5 burden by 1.7 mgm-2 and the sources from the Europe were also responsible for the PM2.5 burden increase in East Asia and South Asia by about 1.0 mgm-2. During 1980–2010, East Asia contributed to an increase of 0.4–0.6 mgm-2 in the PM2.5 burden in North America and Europe, while South Asia contributed about 0.3 mgm-2. During 2010–2017, the contributions from East Asia to the PM2.5 burdens in the North America, Europe, and South Asia declined by 0.3–0.6 mgm-2 due to the clean air actions in China, while the contributions from South Asia still increased due to the continuous increase in emissions in South Asia. The historical changes in aerosols had an impact on effective radiative forcing through aerosol–radiation interactions (ERFari). During 1980–2010, a decline in North American aerosols resulted in a positive ERFari change (warming effect) in Europe and a decline in aerosols in Europe caused a warming effect in Russia and northern China. The changes in ERFari from the increase and decrease in aerosols in China during 1980–2010 and 2010–2017, respectively, are comparable in magnitude. The continuous aerosol increases in South Asia from 1980 to 2017 resulted in negative ERFari (cooling) changes in South Asia, Southeast Asia, and southern China. [ABSTRACT FROM AUTHOR]

The interactions between the terrestrial biosphere, atmospheric chemistry, and climate involve complex feedbacks that have traditionally been modeled separately. We present a new framework that couples the Yale Interactive terrestrial Biosphere (YIBs) model, a dynamic plant-chemistry model, with the RegCM-Chem model. RegCM-Chem–YIBs integrates meteorological variables and atmospheric chemical composition from RegCM-Chem with land surface parameters from YIBs. The terrestrial carbon flux calculated by YIBs is fed back into RegCM-Chem interactively, thereby representing the interactions between fine particulate matter (PM 2.5), ozone (O 3), and carbon dioxide (CO 2). For testing purposes, we carry out a 1-year simulation (2016) at a 30 km horizontal resolution over East Asia with RegCM-Chem–YIBs. The model accurately captures the spatio-temporal distribution of climate, chemical composition, and ecological parameters. In particular, the estimated O 3 and PM 2.5 are consistent with ground observations, with correlation coefficients (R) of 0.74 and 0.65, respectively. The simulated CO 2 concentration is consistent with observations from six sites (R ranged from 0.89 to 0.97) and exhibits a similar spatial pattern when compared with carbon assimilation products. RegCM-Chem–YIBs produces reasonably good gross primary productivity (GPP) and net primary productivity (NPP), showing seasonal and spatial distributions consistent with satellite observations, and mean biases (MBs) of 0.13 and 0.05 kg C m -2 yr -1. This study illustrates that RegCM-Chem–YIBs is a valuable tool to investigate coupled interactions between the terrestrial carbon cycle, atmospheric chemistry, and climate change at a higher resolution on a regional scale. [ABSTRACT FROM AUTHOR]

The interactions between the terrestrial biosphere, atmospheric chemistry, and climate involve complex feedbacks that have traditionally been modeled separately. We present a new framework that couples the Yale Interactive terrestrial Biosphere (YIBs), a dynamic plant-chemistry model, with the RegCM-Chem model. RegCM-Chem-YIBs integrates meteorological variables and atmospheric chemical composition from RegCM-Chem with land surface parameters from YIBs. The terrestrial carbon flux calculated by YIBs, are fed back into RegCM-Chem interactively, thereby representing the interactions between fine particulate matter (PM2.5), ozone (O3), and carbon dioxide (CO2). For testing purposes, we carry out a one-year simulation (2016) at a 30 km horizontal resolution over East Asia with RegCM-Chem-YIBs. The model accurately captures the spa-tio-temporal distribution of climate, chemical composition, and ecological parameters. In particular, the estimated O3 and PM2.5 are consistent with ground observations, with correlation coefficients (R) of 0.74 and 0.65, respec-tively. The simulated CO2 concentration is consistent with observations from six sites (R ranged from 0.89 to 0.97) and exhibits a similar spatial pattern when compared to carbon assimilation products. RegCM-Chem-YIBs produces reasonably good gross primary productivity (GPP) and net primary productivity (NPP), showing seasonal and spatial distributions consistent with satellite observations, and mean biases (MBs) of 0.13 and 0.05 kg C m-2 year-1. This study illustrates that the RegCM-Chem-YIBs is a valuable tool to investigate coupled interactions between the terrestrial carbon cycle, atmospheric chemistry, and climate change at a higher resolution in regional scale. [ABSTRACT FROM AUTHOR]

A new approach to more accurately monitor and evaluate transboundary particulate matter (PM) pollution is introduced based on aerosol optical products from Korea's Geostationary Ocean Color Imager (GOCI). The area studied is Northeast Asia (including eastern parts of China, the Korean peninsula and Japan), where GOCI has been monitoring since June 2010. The hourly multi-spectral aerosol optical data that were retrieved from GOCI sensor onboard geostationary satellite COMS (Communication, Ocean, and Meteorology Satellite) through the Yonsei aerosol retrieval algorithm were first presented and used in this study. The GOCI-retrieved aerosol optical data are integrated with estimated aerosol distributions from US EPA Models-3/CMAQ (Community Multi-scale Air Quality) v4.5.1 model simulations via data assimilation technique, thereby making the aerosol data spatially continuous and available even for cloud contamination cells. The assimilated aerosol optical data are utilized to provide quantitative estimates of transboundary PM pollution from China to the Korean peninsula and Japan. For the period of 1 April to 31 May, 2011 this analysis yields estimates that AOD as a proxy for PM2.5 or PM10 during long-range transport events increased by 117-265% compared to background average AOD (aerosol optical depth) at the four AERONET sites in Korea, and average AOD increases of 121% were found when averaged over the entire Korean peninsula. This paper demonstrates that the use of multi-spectral AOD retrievals from geostationary satellites can improve estimates of transboundary PM pollution. Such data will become more widely available later this decade when new sensors such as the GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI-2 are scheduled to be launched. [ABSTRACT FROM AUTHOR]

Trace metals in aerosol particles impact Earth's radiative budget, human health, and ocean biogeochemistry. Semi-continuous measurements of the elemental composition of fine-mode (PM 2.5) aerosols were conducted using an automated X-ray fluorescence analyzer on a remote island of Japan during the spring of 2018. Temporal variations in mass concentrations of geochemically important elements for this period, such as Pb, Cu, Si, Fe, and Mn, and their relationships with the emission tracers, carbon monoxide (CO) and black carbon (BC), were reported. The Integrated Massively Parallel Atmospheric Chemical Transport (IMPACT) model was used to evaluate the source apportionment of these components and was evaluated in terms of emissions and wet removal processes. Pb and Cu originated mainly from anthropogenic sources (98 % and 93 % on average, respectively) over the East Asian continent. Positive correlations of Pb and Cu with BC and CO and the similarity of their concentration-weighted trajectories indicated that the emission sources of these metals share the region where the large CO (and BC) emission sources are located and that CO can be regarded as a tracer of continental anthropogenic emissions. The air masses with minimized impacts of the wet removal during transport were extracted to elucidate the "top-down" emission ratio of Pb and Cu to CO, which were, for the first time, evaluated as 152.7 and 63.1 µg g -1 , respectively, during the spring of 2018 in the East Asian outflow. The analysis of the tagged tracer simulations by the IMPACT model confirmed that BC and Si could be used as tracers for anthropogenic and dust emissions, respectively, during the observation period. The source apportionment of Fe and Mn in PM 2.5 aerosols was conducted using Si and BC tracers, which revealed that the anthropogenic contribution was 17 % and 44 % on average, respectively. Based on the air mass origins of Fe and Mn, their anthropogenic fraction varied from 2 % to 29 % and 9 % to 68 %, respectively, during the high-PM 2.5 -concentration periods. However, despite the non-dominant anthropogenic contributions of Fe, they could adversely affect human health and ocean biogeochemistry, owing to their higher water solubility. The modeled BC, Pb, Cu, and Fe were evaluated by separately diagnosing their emission and transport. Ratios of modeled to observed concentrations for these components were analyzed in terms of the accumulated precipitation along the transport from the East Asian continent. The current model simulations were found to overestimate the emissions (based on the Community Emissions Data System, CEDS v2021-02-05) of BC by 44 % and underestimate Cu by 45 %, anthropogenic Fe by 28 % in East Asia, and the wet deposition rates for BC and Pb. Overall, Cu in East Asia exhibited a different nature from BC and Pb in terms of emission sources and wet removal. [ABSTRACT FROM AUTHOR]

Shipping contributes significantly to air pollutant emissions and atmospheric particulate matter (PM) concentrations. At the same time, worldwide maritime transport volumes are expected to continue to rise in the future. The Mediterranean Sea is a major short-sea shipping route within Europe and is the main shipping route between Europe and East Asia. As a result, it is a heavily trafficked shipping area, and air quality monitoring stations in numerous cities along the Mediterranean coast have detected high levels of air pollutants originating from shipping emissions. The current study is a part of the EU Horizon 2020 project SCIPPER (Shipping Contributions to Inland Pollution – Push for the Enforcement of Regulations), which intends to investigate how existing restrictions on shipping-related emissions to the atmosphere ensure compliance with legislation. To demonstrate the impact of ships on relatively large scales, the potential shipping impacts on various air pollutants can be simulated with chemical transport models. To determine the formation, transport, chemical transformation, and fate of particulate matter < 2.5 µ m (PM 2.5) in the Mediterranean Sea in 2015, five different regional chemical transport models (CAMx – Comprehensive Air Quality Model with Extensions, CHIMERE, CMAQ – Community Multiscale Air Quality model, EMEP – European Monitoring and Evaluation Programme model, and LOTOS-EUROS) were applied. Furthermore, PM 2.5 precursors (ammonia (NH 3), sulfur dioxide (SO 2), nitric acid (HNO 3)) and inorganic particle species (sulfate (SO 42-), ammonia (NH 4+), nitrate (NO 3-)) were studied, as they are important for explaining differences among the models. STEAM (see "List of abbreviations" in Appendix A) version 3.3.0 was used to compute shipping emissions, and the CAMS-REG version 2.2.1 dataset was used to calculate land-based emissions for an area encompassing the Mediterranean Sea at a resolution of 12 × 12 km 2 (or 0.1 ∘ × 0.1 ∘). For additional input, like meteorological fields and boundary conditions, all models utilized their regular configuration. The zero-out approach was used to quantify the potential impact of ship emissions on PM 2.5 concentrations. The model results were compared with observed background data from monitoring sites. Four of the five models underestimated the actual measured PM 2.5 concentrations. These underestimations are linked to model-specific mechanisms or underpredictions of particle precursors. The potential impact of ships on the PM 2.5 concentration is between 15 % and 25 % at the main shipping routes. Regarding particle species, SO 42- is the main contributor to the absolute ship-related PM 2.5 and to total PM 2.5 concentrations. In the ship-related PM 2.5 , a higher share of inorganic particle species can be found when compared with the total PM 2.5. The seasonal variabilities in particle species show that NO 3- is higher in winter and spring, while the NH 4+ concentrations displayed no clear seasonal pattern in any models. In most cases with high concentrations of both NH 4+ and NO 3- , lower SO 42- concentrations are simulated. Differences among the simulated particle species distributions might be traced back to the aerosol size distribution and how models distribute emissions between the coarse and fine modes (PM 2.5 and PM 10). The seasonality of wet deposition follows the seasonality of the precipitation, showing that precipitation predominates wet deposition. [ABSTRACT FROM AUTHOR]

In response to the need for an up-to-date emissions inventory and the recent achievement of geostationary observations afforded by the Geostationary Environment Monitoring Spectrometer (GEMS) and its sister instruments, this study aims to establish a top-down approach for adjusting aerosol precursor emissions over East Asia. This study involves a series of the TROPOspheric Monitoring Instrument (TROPOMI) NO 2 product, the GEMS aerosol optical depth (AOD) data fusion product and its proxy product, and chemical transport model (CTM)-based inverse modeling techniques. We begin by sequentially adjusting bottom-up estimates of nitrogen oxides (NOx) and primary particulate matter (PM) emissions, both of which significantly contribute to aerosol loadings over East Asia to reduce model biases in AOD simulations during the year 2019. While the model initially underestimates AOD by 50.73 % on average, the sequential emissions adjustments that led to overall increases in the amounts of NOx emissions by 122.79 % and of primary PM emissions by 76.68 % and 114.63 % (single- and multiple-instrument-derived emissions adjustments, respectively) reduce the extents of AOD underestimation to 33.84 % and 19.60 %, respectively. We consider the outperformance of the model using the emissions constrained by the data fusion product to be the result of the improvement in the quantity of available data. Taking advantage of the data fusion product, we perform sequential emissions adjustments during the spring of 2022, the period during which the substantial reductions in anthropogenic emissions took place accompanied by the COVID-19 pandemic lockdowns over highly industrialized and urbanized regions in China. While the model initially overestimates surface PM 2.5 concentrations by 47.58 % and 20.60 % in the North China Plain (NCP) region and South Korea (hereafter referred to as Korea), the sequential emissions adjustments that led to overall decreases in NOx and primary PM emissions by 7.84 % and 9.03 %, respectively, substantially reduce the extents of PM 2.5 underestimation to 19.58 % and 6.81 %, respectively. These findings indicate that the series of emissions adjustments, supported by the TROPOMI and GEMS-involved data fusion products, performed in this study are generally effective at reducing model biases in simulations of aerosol loading over East Asia; in particular, the model performance tends to improve to a greater extent on the condition that spatiotemporally more continuous and frequent observational references are used to capture variations in bottom-up estimates of emissions. In addition to reconfirming the close association between aerosol precursor emissions and AOD as well as surface PM 2.5 concentrations, the findings of this study could provide a useful basis for how to most effectively exploit multisource top-down information for capturing highly varying anthropogenic emissions. [ABSTRACT FROM AUTHOR]

Shipping contributes significantly to air pollutant emissions and atmospheric particulate matter (PM) concentrations. At the same time worldwide maritime transport volumes are expected to continue to rise in the future. The Mediterranean Sea is a major short-sea shipping route within Europe, as well as the main shipping route between Europe and East Asia. As a result, it is a heavily trafficked shipping area, and air quality monitoring stations in numerous cities along the Mediterranean coast have detected high levels of air pollutants originating from shipping emissions. The current study is a part of the EU Horizon 2020 project SCIPPER (Shipping contribution to Inland Pollution - Push for the Enforcement of Regulations) which intends to investigate how existing restrictions on shipping-related emissions to the atmosphere ensure compliance with legislation. To demonstrate the impact of ships on relatively large scales, the potential shipping impacts on various air pollutants can be simulated with chemistry transport models. To determine formation, transport, chemical transformation and fate of PM2.5 in the Mediterranean Sea in 2015, five different regional chemistry transport models (CAMx – Comprehensive Air Quality Model with Extensions, CHIMERE, CMAQ – Community Multiscale Air Quality model, EMEP – European Monitoring and Evaluation Programme model, LOTOS-EUROS) were applied. Furthermore, PM2.5 precursors (NH3, SO2, HNO3) and inorganic particle species (SO42−, NH4+, NO3−) were studied, as they are important for explaining differences among the models. STEAM version 3.3.0 was used to compute shipping emissions, and the CAMS-REG v2.2.1 dataset was used to calculate land-based emissions for an area encompassing the Mediterranean Sea at a resolution of 12 × 12 km2 (or 0.1° × 0.1°). For additional input, like meteorological fields and boundary conditions, all models utilized their regular configuration. The zero-out approach was used to quantify the potential impact of ship emissions on PM2.5 concentrations. The model results were compared to observed background data from monitoring sites. Four of the five models underestimated the actual measured PM2.5 concentrations. These underestimations are linked to model-specific mechanisms or underpredictions of particle precursors. The potential impact of ships on the PM2.5 concentration is between 15 % and 25 % at the main shipping routes. Regarding particle species, SO42− is main contributor to the absolute ship-related PM2.5 and also to total PM2.5 concentrations. In the ship-related PM2.5, a higher share of inorganic particle species can be found when compared to the total PM2.5. The seasonal variabilities in particle species show that NO3− is higher in winter and spring, while the NH4+ concentrations displayed no clear seasonal pattern in any models. In most cases with high concentrations of both NH4+ and NO3−, lower SO42− concentrations are simulated. Differences among the simulated particle species distributions might be traced back to the aerosol size distribution and how models distribute among the coarse and fine mode (PM2.5 and PM10). The seasonality of wet deposition follows the seasonality of the precipitation, displaying that precipitation predominates the wet deposition. [ABSTRACT FROM AUTHOR]

Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM 10 and PM 2.5. Coarse PM concentrations in 2015 averaged 52 µ g m -3 in the North China Plain (NCP) and 23 µ g m -3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM 10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM 2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM 2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM 2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM 2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM 2.5 nitrate. [ABSTRACT FROM AUTHOR]

Shipping has a significant share in the emissions of air pollutants such as NO x and particulate matter (PM), and the global maritime transport volumes are projected to increase further in the future. The major route for short sea shipping within Europe and the main shipping route between Europe and East Asia are found in the Mediterranean Sea. Thus, it is a highly frequented shipping area, and high levels of air pollutants with significant potential impacts from shipping emissions are observed at monitoring stations in many cities along the Mediterranean coast. The present study is part of the EU H2020 project SCIPPER (Shipping contribution to Inland Pollution Push for the Enforcement of Regulations). Five different regional chemistry transport models (CAMx – Comprehensive Air Quality Model with Extensions, CHIMERE, CMAQ, EMEP – European Monitoring and Evaluation Programme, LOTOS-EUROS) were used to simulate the transport, chemical transformation and fate of atmospheric pollutants in the Mediterranean Sea for 2015. Shipping emissions were calculated with the Ship Traffic Emission Assessment Model (STEAM) version 3.3.0, and land-based emissions were taken from the CAMS-REG v2.2.1 dataset for a domain covering the Mediterranean Sea at a resolution of 12 km × 12 km (or 0.1∘×0.1∘). All models used their standard setup for further input. The potential impact of ships was calculated with the zero-out method. The model results were compared to each other and to measured background data at monitoring stations. The model results differ regarding the time series and pattern but are similar concerning the overall underestimation of NO 2 and overestimation of O 3. The potential impact from ships on the total NO 2 concentration was especially high on the main shipping routes and in coastal regions (25 % to 85 %). The potential impact from ships on the total O 3 concentration was lowest in regions with the highest NO 2 impact (down to -20 %). CAMx and CHIMERE simulated the highest potential impacts of ships on the NO 2 and O 3 air concentrations. Additionally, the strongest correlation was found between CAMx and CHIMERE, which can be traced back to the use of the same meteorological input data. The other models used different meteorological input due to their standard setup. The CMAQ-, EMEP- and LOTOS-EUROS-simulated values were within one range for the NO 2 and O 3 air concentrations. Regarding simulated deposition, larger differences between the models were found when compared to air concentration. These uncertainties and deviations between models are caused by deposition mechanisms, which are unique within each model. A reliable output from models simulating ships' potential impacts can be expected for air concentrations of NO 2 and O 3. [ABSTRACT FROM AUTHOR]

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea–United States Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by - 64 % but overestimates nitrate by + 36 %. The largest underestimate in sulfate occurs during the pollution event, for which models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by + 100 % against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of 5 increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape, resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model's inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model, which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation, implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally produced sulfate increased from 1 % to 25 % of locally produced PM2.5 , implying that local emissions controls could have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction, which affects the aerosol liquid water abundance and chemistry driving sulfate–nitrate–ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and this results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate + nitrate + ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements. [ABSTRACT FROM AUTHOR]

Long-range transport of anthropogenic air pollutants from East Asia can affect the downwind marine air quality during spring and winter. Long-range transport of continental air pollutants and their interaction with sea salt aerosol (SSA) significantly modify the radiative forcing of marine aerosols and influence ocean biogeochemical cycling. Previous studies poorly characterize variations of aerosol particles along with air mass transport from the continental edge to the remote ocean. Here, the research ship R/V Dongfanghong 2 traveled from the eastern China seas (ECS) to the northwestern Pacific Ocean (NWPO) to understand what and how air pollutants were transported from the highly polluted continental air to clean marine air in spring. A transmission electron microscope (TEM) was used to find the long-range transported anthropogenic particles and the possible Cl-depletion phenomenon of SSA in marine air. Anthropogenic aerosols (e.g., sulfur (S)-rich, S-soot, S-metal/fly ash, organic matter (OM)-S, and OM coating particles) were identified and dramatically declined from 87 % to 8 % by number from the ECS to remote NWPO. For the SSA aging, 87 % of SSA particles in the ECS were identified as fully aged, while the proportion of fully aged SSA particles in the NWPO decreased to 29 %. Our results highlight that anthropogenic acidic gases in the troposphere (e.g., SO 2 , NO x , and volatile organic compounds) could be transported to remote marine air and exert a significant impact on aging of SSA particles in the NWPO. The study shows that anthropogenic particles and gases from East Asia significantly perturb different aerosol chemistry from coastal to remote marine air. More attention should be given to the modification of SSA particles in remote marine areas due to the influence of anthropogenic gaseous pollutants. [ABSTRACT FROM AUTHOR]

Geostationary satellite measurements of aerosol optical depth (AOD) over East Asia from the Geostationary Ocean Color Imager (GOCI) and Advanced Himawari Imager (AHI) instruments can augment surface monitoring of fine particulate matter (PM 2.5) air quality, but this requires better understanding of the AOD–PM 2.5 relationship. Here we use the GEOS-Chem chemical transport model to analyze the critical variables determining the AOD–PM 2.5 relationship over East Asia by simulation of observations from satellite, aircraft, and ground-based datasets. This includes the detailed vertical aerosol profiling over South Korea from the KORUS-AQ aircraft campaign (May–June 2016) with concurrent ground-based PM 2.5 composition, PM 10 , and AERONET AOD measurements. The KORUS-AQ data show that 550 nm AOD is mainly contributed by sulfate–nitrate–ammonium (SNA) and organic aerosols in the planetary boundary layer (PBL), despite large dust concentrations in the free troposphere, reflecting the optically effective size and high hygroscopicity of the PBL aerosols. We updated SNA and organic aerosol size distributions in GEOS-Chem to represent aerosol optical properties over East Asia by using in situ measurements of particle size distributions from KORUS-AQ. We find that SNA and organic aerosols over East Asia have larger size (number median radius of 0.11 µ m with geometric standard deviation of 1.4) and 20 % larger mass extinction efficiency as compared to aerosols over North America (default setting in GEOS-Chem). Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM 2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM 2.5 nitrate. The GOCI–AHI AOD data over East Asia in different seasons show agreement with AERONET AODs and a spatial distribution consistent with surface PM 2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM 2.5. This is due to low PBL depths compounded by high residential coal emissions in winter and high relative humidity (RH) in summer. Seasonality of AOD and PM 2.5 over South Korea is much weaker, reflecting weaker variation in PBL depth and lack of residential coal emissions. [ABSTRACT FROM AUTHOR]

Ocean-going ships emit large amounts of air pollutants such as nitrogen oxide (NO x) and particulate matter. NO x emitted from ships can be converted to nitrous acid (HONO) and nitryl chloride (ClNO 2), which produce hydroxyl (OH) and chlorine (Cl) radicals and recycle NO x , thereby affecting the oxidative capacity and production of secondary pollutants. However, these effects have not been quantified in previous investigations of the impacts of ship emissions. In this study, a regional transport model (WRF-Chem) revised to incorporate the latest HONO and ClNO 2 processes was used to investigate their effects on the concentrations of RO x (RO 2 + HO 2 + OH) radicals, ozone (O 3), and fine particulate matter (PM 2.5) in Asia during summer. The results show that the ship-derived HONO and ClNO 2 increased the concentration of RO x radicals by approximately 2–3 times in the marine boundary layer. The enhanced radicals then increased the O 3 and PM 2.5 concentrations in marine areas, with the ship contributions increasing from 9 % to 21 % and from 7 % to 10 % respectively. The largest RO x enhancement was simulated over the remote ocean with the ship contribution increasing from 29 % to 50 %, which led to increases in ship-contributed O 3 and PM 2.5 from 21 % to 38 % and from 13 % to 19 % respectively. In coastal cities, the enhanced levels of radicals also increased the maximum O 3 and averaged PM 2.5 concentrations from 5 % to 11 % and from 4 %–8 % to 4 %–12 % respectively. These findings indicate that modelling studies that do not consider HONO and ClNO 2 can significantly underestimate the impact of ship emissions on radicals and secondary pollutants. Therefore, it is important that these nitrogen compounds be included in future models of the impact of ship emissions on air quality. [ABSTRACT FROM AUTHOR]

The Taklamakan desert is an important dust source for the global atmospheric dust budget and a cause of the dust weather in East Asia. The characterization of Taklamakan dust in the source region is still very limited. To fill this gap, the DAO (dust aerosol observation) was conducted in April 2019 in Kashi, China. The Kashi site is about 150 km from the western rim of the Taklamakan desert and is strongly impacted by desert dust aerosols, especially in spring time, i.e., April and May. According to sun–sky photometer measurements, the aerosol optical depth (at 500 nm) varied in the range of 0.07–4.70, and the Ångström exponent (between 440 and 870 nm) in the range of 0.0–0.8 in April 2019. In this study, we provide the first profiling of the 2α+3β+3δ parameters of Taklamakan dust based on a multiwavelength Mie–Raman polarization lidar. For Taklamakan dust, the Ångström exponent related to the extinction coefficient (EAE, between 355 and 532 nm) is about 0.01 ± 0.30, and the lidar ratio is found to be 45 ± 7 sr (51 ± 8–56 ± 8 sr) at 532 (355) nm. The particle linear depolarization ratios (PLDRs) are about 0.28–0.32 ± 0.07 at 355 nm, 0.36 ± 0.05 at 532 nm and 0.31 ± 0.05 at 1064 nm. Both lidar ratios and depolarization ratios are higher than the typical values of Central Asian dust in the literature. The difference is probably linked to the fact that observations in the DAO campaign were collected close to the dust source; therefore, there is a large fraction of coarse-mode and giant particles (radius >20 µ m) in the Taklamakan dust. Apart from dust, fine particles coming from local anthropogenic emissions and long-range transported aerosols are also non-negligible aerosol components. The signatures of pollution emerge when dust concentration decreases. The polluted dust (defined by PLDR 532≤0.30 and EAE 355-532≥0.20) is featured with reduced PLDRs and enhanced EAE 355-532 compared to Taklamakan dust. The mean PLDRs of polluted dust generally distributed in the range of 0.20–0.30. Due to the complexity of the nature of the involved pollutants and their mixing state with dust, the lidar ratios exhibit larger variabilities compared to those of dust. The study provides the first reference of novel characteristics of Taklamakan dust measured by Mie–Raman polarization lidar. The data could contribute to complementing the dust model and improving the accuracy of climate modeling. [ABSTRACT FROM AUTHOR]

This study compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM 10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM 10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to -20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s -1 differences over inland regions). [ABSTRACT FROM AUTHOR]

To improve poor air quality in Asia and inform effective emission-reduction strategies, it is vital to understand the contributions of different pollution sources and their associated human health burdens. In this study, we use the WRF-Chem regional atmospheric model to explore the air quality and human health benefits of eliminating emissions from six different anthropogenic sectors (transport, industry, shipping, electricity generation, residential combustion, and open biomass burning) over South and East Asia in 2014. We evaluate WRF-Chem against measurements from air quality monitoring stations across the region and find the model captures the spatial distribution and magnitude of PM 2.5 (particulate matter with an aerodynamic diameter of no greater than 2.5 µ m). We find that eliminating emissions from residential energy use, industry, or open biomass burning yields the largest reductions in population-weighted PM 2.5 concentrations across the region. The largest human health benefit is achieved by eliminating either residential or industrial emissions, averting 467 000 (95 % uncertainty interval (95UI): 409 000–542 000) or 283 000 (95UI: 226 000–358 000) annual premature mortalities, respectively, in India, China, and South-east Asia, with fire prevention averting 28 000 (95UI: 24 000–32 000) annual premature mortalities across the region. We compare our results to previous sector-specific emission studies. Across these studies, residential emissions are the dominant cause of particulate pollution in India, with a multi-model mean contribution of 42 % to population-weighted annual mean PM 2.5. Residential and industrial emissions cause the dominant contributions in China, with multi-model mean contributions of 29 % for both sectors to population-weighted annual mean PM 2.5. Future work should focus on identifying the most effective options within the residential, industrial, and open biomass-burning emission sectors to improve air quality across South and East Asia. [ABSTRACT FROM AUTHOR]

This study proposes an aerosol-type classification based on the particle linear depolarization ratio (PLDR) and single-scattering albedo (SSA) provided in the AErosol RObotic NETwork (AERONET) version 3 level 2.0 inversion product. We compare our aerosol-type classification with an earlier method that uses fine-mode fraction (FMF) and SSA. Our new method allows for a refined classification of mineral dust that occurs as a mixture with other absorbing aerosols: pure dust (PD), dust-dominated mixed plume (DDM), and pollutant-dominated mixed plume (PDM). We test the aerosol classification at AERONET sites in East Asia that are frequently affected by mixtures of Asian dust and biomass-burning smoke or anthropogenic pollution. We find that East Asia is strongly affected by pollution particles with high occurrence frequencies of 50 % to 67 %. The distribution and types of pollution particles vary with location and season. The frequency of PD and dusty aerosol mixture (DDM+PDM) is slightly lower (34 % to 49 %) than pollution-dominated mixtures. Pure dust particles have been detected in only 1 % of observations. This suggests that East Asian dust plumes generally exist in a mixture with pollution aerosols rather than in pure form. In this study, we have also considered data from selected AERONET sites that are representative of anthropogenic pollution, biomass-burning smoke, and mineral dust. We find that average aerosol properties obtained for aerosol types in our PLDR–SSA-based classification agree reasonably well with those obtained at AERONET sites representative for different aerosol types. [ABSTRACT FROM AUTHOR]

To more accurately estimate direct radiative forcing (DRF) by aerosols, and better investigate particulate pollution over East Asia, precise calculations of the optical properties of aerosols, such as aerosol optical depth (AOD), single scattering albedo (SSA) and aerosol extinction coefficient (σext), are of primary importance. The aerosol optical properties over East Asia were investigated in this study, based on US EPA Models-3/CMAQ v4.5.1 model simulations. The CMAQ model simulations in this study were improved in several ways compared to those in a previous study (Song et al., 2008). Although the details of the improvements were described in the manuscript, the following points should be emphasized: (1) two data assimilation techniques were employed for producing more accurate AOD products and meteorological fields over East Asia; (2) updated/ upgraded emission inventories were used in the CMAQ model simulations with a fine grid resolution of 30x30 km²; and (3) the 4-D particulate composition calculated from the CMAQ model simulations was converted into 3-D or 4-D aerosol optical products, using the Malm and Hand (2007) algorithm with significant further modifications. The results from the CMAQ model simulations (without assimilation) showed great improvements compared to those from a previous study. For example, in terms of the regression coefficients (R), R values were increased from 0.48-0.68 (previous study) to 0.62-0.79 (this study). The monthly-averaged CMAQ-simulated single scattering albedo (SSA) also agreed well with the AERONET SSA, with the exceptions of the Hong Kong and Taipei sites, where the air qualities were strongly influenced by active biomass burning events from January to April. There were also excellent matches between the vertical profiles of the CMAQ-simulated σext and LIDAR-retrieved σext. It was also found that the contributions of (NH4)2SO4 during summer, NH4NO3 during winter, sea-salt particles during winter and dust particles during spring to the total AOD were large over East Asia. In particular, the largest contribution of NH4NO3 to the total AOD was found over East Asia during winter. Therefore, it was suggested that this contribution of NH4NO3 should not be neglected. In order to produce more accurate AOD products, the CMAQ-simulated AODs were further assimilated with the MODIS-retrieved AODs. Both of the assimilated and AERONET AODs were better correlated with each other than the CMAQ-simulated and AERONET AODs. The obvious benefits from this study would be that with these improved aerosol optical properties, the particulate pollution (e.g. AOD can be served as a proxy to PM2.5 or PM10) and DRF by aerosols over East Asia can be more satisfactorily investigated in future. [ABSTRACT FROM AUTHOR]