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

Abstract Using updated emission inventories can enhance the accuracy of air quality forecast models. Given China’s rapid economic growth and Korea’s geographical and meteorological position on the windward side of China, updating China’s emission inventory has become particularly crucial for Korea’s air quality modeling. This study aimed to develop an updated version of China’s Emission Inventory in Comprehensive Regional Emissions for Atmospheric Transport Experiments version 3 for the base year of 2019 (CREATEv3 (YR 2019)). To achieve this goal, we utilized the Chinese emission inventory of CREATEv3 for the base year of 2015 (CREATEv3 (YR 2015)) as a framework to incorporate the latest Chinese emission data from the Multi-resolution Emission Inventory Model for Climate and Air Pollution Research for the base year of 2019 (MEIC COVID-19 (YR 2019)) and update the inventory. The updated China’s annual emissions are now reflected in CREATEv3 (YR 2019), and the amounts are as follows: 132 Tg for CO, 21 Tg for NO x , 8 Tg for SO2, 7 Tg for PM2.5, 9 Tg for NH3, and 28 Tg for volatile organic compound (VOC). By comparing previous Chinese emission inventories with the updated inventory developed in this study, it was found that SO2, NO x , VOC, and NH3 emissions were decreased. Therefore, using the updated inventory seemingly reduces the impact of China’s fine dust on Korea. By comparing emissions by pollutant and region in China using CREATEv3 (YR 2019), it was found that regions with high emissions of targeted pollutants strongly correlated with major industries operating in those areas. This study is expected to provide insights into China’s emission changes in 2019 and support air quality forecasting.

Abstract This study aims to understand the impact of previous air quality improvement policies on historical emission changes by examining long-term emission trends in Korea. Annual emissions from 2000 to 2018 were estimated using Korea’s official emissions inventory, the Clean Air Policy Support System (CAPSS). To ensure a consistent comparison, standardization of the method for calculating emissions and unification of the reported emission sectors were conducted each year. Furthermore, Korea’s emissions history was compared with that of neighboring countries, such as China and Japan. The annual emissions of these countries were acquired from the HTAPv3 emissions inventory, an international long-term emission trend study. For comparison, the emission source classification of Korea was matched with that of HTAPv3. As a result of the analysis, NOx and SOx emissions in Korea have shown decreasing trends, whereas VOCs (volatile organic compounds) have indicated a gradual increasing trend since 2000. Compared to the previous period of implementing South Korea’s air quality improvement policy, changes in NOx and SOx emissions, which are combustion-related pollutants, showed a relationship with the policy’s timeline. However, non-combustion-related pollutants such as VOCs did not exhibit such a relationship. It was concluded that the related policies were not as effective in reducing VOCs as planned in the policy. By comparing the emission trends of Japan, Korea, and China, it was confirmed that Japan was the first country to experience a decrease in combustion-related pollutants emissions, followed by Korea and China. Additionally, combustion-related pollutants decreased in all three countries, whereas VOCs decreased only in Japan. VOC is a precursor material generating secondary PM2.5 and Ozone; considering that, if relevant policies are additionally implemented to control future PM2.5 concentrations, and to reduce emissions efficiently and effectively, Japan’s VOC reduction policies can be applied to Korea’s emission reduction policies. These results are expected to serve as important references when establishing future air quality improvement policies in Korea.

This study proposes the use of light detection and ranging (LiDAR) remote sensing (RS) to support morphometric research for estimating the aerodynamic roughness length (z0 ) of building placement on various scales. A LiDAR three-dimensional point cloud (3DPC) data processing graphical user interface (GUI) was developed to explore the z0 and related urban canopy parameters (UCPs) in the Incheon metropolitan area in South Korea. The results show that multi-scale urban aerodynamic roughness exploration is viable and can address differences in urban building data at various spatial resolutions. Although validating morphological multi-scale UCPs using dense tall towers is challenging, emerging low-cost and efficient methods can serve as substitutes. However, further efforts are required to link the measured z0 to building form regulations, such as floor area ratio, and expand RS research to obtain more quantitative and qualitative knowledge.

Abstract Concentrations of ambient particulate matter (such as PM2.5 and PM10) have come to represent a serious environmental problem worldwide, causing many deaths and economic losses. Because of the detrimental effects of PM2.5 on human health, many countries and international organizations have developed and operated regional and global short-term PM2.5 prediction systems. The short-term predictability of PM2.5 (and PM10) is determined by two main factors: the performance of the air quality model and the precision of the initial states. While specifically focusing on the latter factor, this study attempts to demonstrate how information from classical ground observation networks, a state-of-the-art geostationary (GEO) satellite sensor, and an advanced air quality modeling system can be synergistically combined to improve short-term PM2.5 predictability over South Korea. Such a synergistic combination of information can effectively overcome the major obstacle of scarcity of information, which frequently occurs in PM2.5 prediction systems using low Earth orbit (LEO) satellite-borne observations. This study first presents that the scarcity of information is mainly associated with cloud masking, sun-glint effect, and ill-location of satellite-borne data, and it then demonstrates that an advanced air quality modeling system equipped with synergistically-combined information can achieve substantially improved performances, producing enhancements of approximately 10%, 19%, 29%, and 10% in the predictability of PM2.5 over South Korea in terms of index of agreement (IOA), correlation coefficient (R), mean biases (MB), and hit rate (HR), respectively, compared to PM2.5 prediction systems using only LEO satellite-derived observations.

Abstract Model intercomparison studies often report a large spread in simulation results, but quantifying the causes of these differences is hindered by the fact that several processes contribute to the model spread simultaneously. Here we use the Multi‐Scale Infrastructure for Chemistry and Aerosols (MUSICA) version 0 to investigate the model resolution dependencies of simulated chemical species, with a focus on the differences between global uniform grid and regional refinement grid simulations with the same modeling framework. We construct two global (ne30 [∼112 km] and ne60 [∼56 km]) and two regional refinement grids over Korea (ne30x8 [∼14 km] and ne30x16 [∼7 km]). The grid resolution can change chemical concentrations by an order of magnitude in the boundary layer, and the importance increases as the species' reactivity increases (e.g., up to 50% and 1,000% changes for ethane and xylenes, respectively). The diurnal cycle of oxidants (OH, O3, and NO3) also varies with the grid resolution, which leads to different oxidation pathways of volatile organic compounds (e.g., the fraction of monoterpenes reacting with NO3 in Seoul around midnight is 90% for ne30, but 65% for ne30x16). The models with high‐resolution grids usually do a better job at reproducing aircraft observations during the KORUS‐AQ campaign, but not always, implying compensating errors in the coarse grid simulations. For example, ozone is better reproduced by the coarse grid due to the artificial mixing of NOx. When developing new chemical mechanisms and evaluating models over urban areas, the uncertainties associated with model resolution should be considered.

North Korea’s air quality is poorly understood due to a lack of reliable data. Here, we analyzed urban- to national-scale air quality changes in North Korea using multi-year satellite observations. Pyongyang, Nampo, Pukchang, and Munchon were identified as pollution hotspots. On a national scale, we found that North Korea experienced 6.7, 17.8, and 20.6 times greater amounts of nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO) per unit primary energy supply (PES) than South Korea from 2005 to 2018. Besides, North Korea had a 24.3 times larger aerosol optical depth (AOD) per PES than South Korea from 2011 to 2018. Severe CO and aerosol pollution is aligned with extensive biofuel combustion. High SO2 pollution corresponds with the strong coal dependence of the industry. The change rates of the national average columns for NO2, SO2, and CO were + 3.6, –4.4, and –0.4 % yr−1, respectively. The AOD change rate was –4.8 % yr−1. Overall decreasing trends, except for NO2, are likely due to a decline in coal-fired PES. Positive NO2 trends are consistent with increasing industrial activities. Each pollutant showed consistent patterns of linear trends, even after correcting the influence of transboundary pollution. Flue gas control and biofuel consumption reduction seem necessary to improve North Korea’s air quality.

Efforts to reduce greenhouse gas emissions are ongoing in many East Asian countries; however, their influences on future drought remain unknown. We analyzed future changes in drought intensity over East Asia using the Representative Concentration Pathway (RCP) 8.5 and the new two limiting local greenhouse gas emission scenarios in East Asia: National Institute of Environmental Research (NIER)-H scenario for high emission and NIER-L scenario for low emission. The two scenarios were made by a fully coupled global climate model with prescribed gas boundaries of high and low greenhouse gas emissions from an atmospheric chemistry model reflecting the up-to-date environmental policies of South Korea, China, and Japan. The application of a clustering analysis to the calculated drought index time series identified four zonally distributed drought regions in the present-day period (1951 - 2016). Among these regions, higher latitude regions showed a more rapidly increasing trend in drought intensity than other regions for the present-day period. All future scenarios projected the continuation of this meridional intensification trend of drought until 2100; however, the intensification rates in the NIER-L were much smaller than those in the RCP8.5 and NIER-H scenarios. Our results suggest that reducing greenhouse gas emissions is critical for East Asian countries to alleviate the potential damages of future droughts.

The Korea-United States Air Quality Study (KORUS-AQ) took place in spring 2016 to better understand air pollution in Korea. In support of KORUS-AQ, 2554 whole air samples (WAS) were collected aboard the NASA DC-8 research aircraft and analyzed for 82 C1–C10 volatile organic compounds (VOCs) using multi-column gas chromatography. Together with fast-response measurements from other groups, the air samples were used to characterize the VOC composition in Seoul and surrounding regions, determine which VOCs are major ozone precursors in Seoul, and identify the sources of these reactive VOCs. (1) The WAS VOCs showed distinct signatures depending on their source origins. Air collected over Seoul had abundant ethane, propane, toluene and 'n'-butane while plumes from the Daesan petrochemical complex were rich in ethene, C2–C6 alkanes and benzene. Carbonyl sulfide (COS), CFC-113, CFC-114, carbon tetrachloride (CCl4) and 1,2-dichloroethane were good tracers of air originating from China. CFC-11 was also elevated in air from China but was surprisingly more elevated in air over Seoul. (2) Methanol, isoprene, toluene, xylenes and ethene were strong individual contributors to OH reactivity in Seoul. However methanol contributed less to ozone formation based on photochemical box modeling, which better accounts for radical chemistry. (3) Positive Matrix Factorization (PMF) and other techniques indicated a mix of VOC source influences in Seoul, including solvents, traffic, biogenic, and long-range transport. The solvent and traffic sources were roughly equal using PMF, and the solvents source was stronger in the KORUS-AQ emission inventory. Based on PMF, ethene and propene were primarily associated with traffic, and toluene, ethylbenzene and xylenes with solvents, especially non-paint solvents for toluene and paint solvents for ethylbenzene and xylenes. This suggests that VOC control strategies in Seoul could continue to target vehicle exhaust and paint solvents, with additional regulations to limit the VOC content in a variety of non-paint solvents.

We examine O3 production and its sensitivity to precursor gases and boundary layer mixing in Korea by using a 3-D global chemistry transport model and extensive observations during the KORea-US cooperative Air Quality field study in Korea, which occurred in May–June 2016. During the campaign, observed aromatic species onboard the NASA DC-8 aircraft, especially toluene, showed high mixing ratios of up to 10 ppbv, emphasizing the importance of aromatic chemistry in O3 production. To examine the role of VOCs and NOx in O3 chemistry, we first implement a detailed aromatic chemistry scheme in the model, which reduces the normalized mean bias of simulated O3 mixing ratios from –26% to –13%. Aromatic chemistry also increases the average net O3 production in Korea by 37%. Corrections of daytime PBL heights, which are overestimated in the model compared to lidar observations, increase the net O3 production rate by ~10%. In addition, increasing NOx emissions by 50% in the model shows best performance in reproducing O3 production characteristics, which implies that NOx emissions are underestimated in the current emissions inventory. Sensitivity tests show that a 30% decrease in anthropogenic NOx emissions in Korea increases the O3 production efficiency throughout the country, making rural regions ~2 times more efficient in producing O3 per NOx consumed. Simulated O3 levels overall decrease in the peninsula except for urban and other industrial areas, with the largest increase (~6 ppbv) in the Seoul Metropolitan Area (SMA). However, with simultaneous reductions in both NOx and VOCs emissions by 30%, O3 decreases in most of the country, including the SMA. This implies the importance of concurrent emission reductions for both NOx and VOCs in order to effectively reduce O3 levels in Korea.

Atmospheric ammonia is a significant pollutant throughout the year, necessitating standardized measurement and identification of emission factors. We performed a quantized evaluation of ammonia concentrations at various locations in and around Seoul, South Korea. The established testing methods of the Radiello Passive Sampler were used for ammonia sampling, and the method was validated using annular denuder sampling. Urban and suburban areas were studied to gain a deeper understanding of the factors responsible for ammonia pollution. This study aimed to establish the fluctuations in concentration over one year, by analyzing the seasonal and regional variation in ammonia concentration. Livestock and agricultural areas recorded the highest concentration of ammonia among all sites, with the highest concentration recorded in autumn. However, at most of the other studied sites, the highest and lowest ammonia concentrations were recorded during summer and winter, respectively. This study attempted to establish a correlation between ammonia concentration and temperature, as well as ammonia concentration and altitude.

Climate change is an important issue, with many researches examining not only future climatic conditions, but also the interaction of climate and air quality. In this study, a new version of the emissions processing software tool - Python-based PRocessing Operator for Climate and Emission Scenarios (PROCES) - was developed to support climate and atmospheric chemistry modeling studies. PROCES was designed to cover global and regional scale modeling domains, which correspond to GEOS-Chem and CMAQ/CAMx models, respectively. This tool comprises of one main system and two units of external software. One of the external software units for this processing system was developed using the GIS commercial program, which was used to create spatial allocation profiles as an auxiliary database. The SMOKE-Asia emissions modeling system was linked to the main system as an external software, to create model-ready emissions for regional scale air quality modeling. The main system was coded in Python version 2.7, which includes several functions allowing general emissions processing steps, such as emissions interpolation, spatial allocation and chemical speciation, to create model-ready emissions and auxiliary inputs of SMOKE-Asia, as well as user-friendly functions related to emissions analysis, such as verification and visualization. Due to its flexible software architecture, PROCES can be applied to any pre-gridded emission data, as well as regional inventories. The application results of our new tool for global and regional (East Asia) scale modeling domain under RCP scenario for the years 1995-2006, 2015-2025, and 2040-2055 was quantitatively in good agreement with the reference data of RCPs.

We report the results of year-long PM2.5 (particulate matter less than 2.5 µm in diameter) simulations over Northeast Asia for the base year of 2013 under the framework of the Long-range Transboundary Air Pollutants in Northeast Asia (LTP) project. LTP is a tripartite project launched by China, Japan, and Korea for cooperative monitoring and modeling of the long-range transport (LRT) of air pollutants. In the modeling aspect in the LTP project, each country’s modeling group employs its own original air quality model and options. The three regional air quality models employed by the modeling groups are WRF-CAMx, NHM-RAQM2, and WRF-CMAQ. PM2.5 concentrations were simulated in remote exit-and-entrance areas associated with the LRT process over China, Japan, and Korea. The results showed apparent bias that remains unexplored due to a series of uncertainties from emission estimates and inherent model limitations. The simulated PM10 levels at seven remote exit-and-entrance sites were underestimated with the normalized mean bias of 0.4 ± 0.2. Among the four chemical components of PM2.5 (SO42−, NO3−, organic carbon (OC), and elemental carbon (EC)), the largest inter-model variability was in OC, with the second largest discrepancy in NO3−. Our simulation results also indicated that under considerable SO42− levels, favorable environments for ammonium nitrate formation were found in exit-and-entrance areas between China and Korea, and gas-aerosol partitioning for semi-volatile species of ammonium nitrate could be fully achieved prior to arrival at the entrance areas. Other chemical characteristics, including NO3−/SO42− and OC/EC ratios, are discussed to diagnose the LRT characteristics of PM2.5 in exit-and-entrance areas associated with transboundary transport over China, Japan, and Korea.

Spatial and temporal variations of mercury, including dry and wet deposition fluxes, were assessed over Northeast Asia, targeting the Yellow Sea, using meteorology and chemistry models. Four modeling periods, each representative of one of the four seasons, were selected. Modeling results captured general patterns and behaviors, and fell within similar ranges with respect to observations. However, temporal variations of mercury were not closely matched, possibly owing to the effects of localized emissions. Modeling results indicated that dry deposition is correlated with wind speed, while wet deposition is correlated with precipitation amount. Overall, the wet deposition flux of 66 ng/m2-day was about twice as large as the dry deposition flux of 32 ng/m2-day, when averaged over the four modeling periods. Dry deposition occurred predominantly in the form of reactive gaseous mercury (RGM). In contrast, RGM accounted for only about two-thirds of wet deposition, while particulate mercury accounted for the remainder.

With global anthropogenic black carbon (BC) emissions increasing, automobiles are significantly contributing as the major source of emissions. However, the appropriate regulations of BC emissions from vehicles are not in place. This study examined BC emissions following fuel types (gasoline, liquefied petroleum gas (LPG), and diesel) and engine combustion (gasoline direct injection (GDI) and multi-port injection (MPI) for gasoline vehicles) with emission regulations. To this end, chassis dynamometer and aethalometer (AE33) were used. Driving modes created by the National Institute of Environmental Research (NIER) and emission certification modes (CVS-75 and NEDC) for vehicles in Korea were used to determine BC emissions for various vehicle speeds. In addition, the contributions of biomass and coal combustion to the data of AE33 were analyzed to determine the possibility of tracking the BC sources. MPI, LPG, and EURO 6 with diesel particulate filter (DPF) vehicles emitted the lowest BC emissions in NIER modes. Among gasoline vehicles, MPI vehicles showed the lower BC content in PM emissions. Also, older vehicles in MPI vehicles emitted the high PM and BC emissions. The BC emissions of EURO 3 vehicles without DPF were the highest as the results of previous studies, and it was found that as emissions regulations were tightened, the level of BC results of diesel vehicles became similar with MPI vehicles. The average absorption Ångström exponent (AAE) from difference emissions sources were biomass combustion (oak wood) > coal combustion (the power plant stack) > automobile emissions (gasoline, LPG, diesel).

Biogenic volatile organic compound (BVOCs) emissions are the largest VOC emission source globally, and are precursors to ozone and secondary organic aerosols, both of which are strong, short-lived climate pollutants. BVOC emissions are usually estimated using the Model of Emissions of Gases and Aerosols from Nature (MEGAN), which requires Plant Functional Types (PFTs) and Leaf Area Indexes (LAIs) as inputs. Herein, the effects of refined input data on regional BVOC emission estimates are analyzed. For LAIs, lower resolution MODerate-resolution Imaging Spectroradiometer (MODIS), and higher spatio-temporal resolution Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) LAI were generated. For PFTs, local land cover maps were developed, in addition to MODIS PFT. In South Korea, annual emissions of isoprene and monoterpenes in 2015 were estimated as 384 and 160 Gg/year, respectively, using STARFM LAI and Local PFT (Case 4). For North Korea, 340 Gg/year isoprene and 72 Gg/year monoterpenes emissions were estimated using STARFM LAI and MODIS PFT. These estimates were 14–110% higher than when using MODIS LAI and MODIS PFT (Case 1). Inter-comparison with satellite-based inverse isoprene emission estimates from GlobEmission shows 32% (North Korea) to 34% (South Korea) overestimation in bottom-up data. Our new vegetation inputs improve MEGAN performance and resulting BVOC emission estimations. Performance of Weather Research and Forecasting (WRF) meteorological modeling requires improvement, especially for solar radiation, to avoid overestimation of isoprene emissions.

Gaseous emissions from vehicles contribute substantially to air pollution and climate change. Vehicular emissions also contain secondary pollutants produced via chemical reactions that occur between the emitted gases and atmospheric air. This study aims at understanding patterns concerning emission of regulated, greenhouse, and precursor gases, which demonstrate potential for secondary aerosol (SA) formation, from vehicles incorporating different engine technologies—multi-point injection (MPI) and gasoline direct injection (GDI)—and using different fuels—gasoline, liquefied petroleum gas (LPG), and diesel. Drive cycles from the National Institute of Environmental Research (NIER) were used in this study. Results obtained from drive cycle tests demonstrate a decline in aggregate gas emissions corresponding to an increase in average vehicle speed. CO2 accounts for more than 99% of aggregate gaseous emissions. In terms of concentration, CO and NH3 form predominantly non-CO2 emissions from gasoline and LPG vehicles, whereas nitrogen oxides (NOx) and non-methane hydrocarbons (NMHC) dominate diesel-vehicle emissions. A higher percentage of SO2 is emitted from diesel vehicles compared to their gasoline- and LPG-powered counterparts. EURO-5- and EURO-6-compliant vehicles equipped with diesel particulate filters (DPFs) tend to emit higher amounts of NO2 compared to EURO-3-compliant vehicles, which are not equipped with DPFs. Vehicles incorporating GDI tend to emit less CO2 compared to those incorporating MPI, albeit at the expense of increased CO emissions. The authors believe that results reported in this paper concerning regulated and unregulated pollutant-emission monitoring can contribute towards an accurate evaluation of both primary and secondary air-pollution scenarios in Korea.

Open biomass burning (excluding biofuels) is an important contributor to air pollution in the Asian region. Estimation of emissions from fires, however, has been problematic, primarily because of uncertainty in the size and location of sources and in their temporal and spatial variability. Hence, more comprehensive tools to estimate wildfire emissions and that can characterize their temporal and spatial variability are needed. Furthermore, an emission processing system that can generate speciated, gridded, and temporally allocated emissions is needed to support air-quality modeling studies over Asia. For these reasons, a biomass-burning emissions modeling system based on satellite imagery was developed to better account for the spatial and temporal distributions of emissions. The BlueSky Framework, which was developed by the USDA Forest Service and US EPA, was used to develop the Asian biomass-burning emissions modeling system. The sub-models used for this study were the Fuel Characteristic Classification System (FCCS), CONSUME, and the Emissions Production Model (EPM). Our domain covers not only Asia but also Siberia and part of central Asia to assess the large boreal fires in the region. The MODIS fire products and vegetation map were used in this study. Using the developed modeling system, biomass-burning emissions were estimated during April and July 2008, and the results were compared with previous studies. Our results show good to fair agreement with those of GFEDv3 for most regions, ranging from 9.7 % in East Asia to 52% in Siberia. The SMOKE modeling system was combined with this system to generate three-dimensional model-ready emissions employing the fire-plume rise algorithm. This study suggests a practicable and maintainable methodology for supporting Asian air-quality modeling studies and to help understand the impact of air-pollutant emissions on Asian air quality.

Nitrous acid (HONO) is a main precursor of hydroxyl radicals (OH), which contribute to the formation of numerous secondary air pollutants in the troposphere. Despite its importance in atmospheric chemistry, HONO chemistry has not been fully incorporated into many chemical transport models (CTMs). Due to the lack of atmospheric HONO processes, CTM simulations often tend to underestimate atmospheric mixing ratios of HONO. This study was undertaken because simulations with current Community Multiscale Air Quality (CMAQ) model have a strong tendency to underestimate the HONO mixing ratio. In search of missing sources of atmospheric HONO, we attempted to sequentially incorporate the following potential HONO sources and processes into the CMAQ modeling framework: (i) gas-phase HONO reactions; (ii) traffic HONO emissions; (iii) soil HONO emissions; (iv) heterogeneous HONO production on the surfaces of aerosols; (v) heterogeneous HONO formation on tree leaf and building surfaces; (vi) photolysis reactions of particulates and deposited HNO3/nitrates called 'renoxification'. The simulation performances of the modified CMAQ models were then evaluated by comparing the modeled HONO mixing ratios with the HONO mixing ratios observed at the Olympic Park station in Seoul, South Korea. When HONO processes were fully added to the CMAQ model, average daily HONO mixing ratios increased from 0.06 ppb to 1.18 ppb. The daytime HONO mixing ratios produced from the CMAQ model run with a full account of atmospheric HONO processes were found to be in better agreement with observations than those from the original CMAQ model (CMAQv5.2.1) runs with improved statistical metrics (e.g., IOA increased from 0.59 to 0.68, while MB decreased dramatically from -0.57 ppb to -0.34 ppb). In addition, we investigated the contributions of individual atmospheric HONO processes to HONO mixing ratios, as well as the impacts of HONO atmospheric processes on the concentrations of other atmospheric species in South Korea. All these issues are also discussed in this manuscript. [ABSTRACT FROM AUTHOR]

The MIXv2 Asian emission inventory is developed under the framework of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase IV, and produced from a mosaic of up-to-date regional emission inventories. We estimated the emissions for anthropogenic and biomass burning sources covering 23 countries and regions in East, Southeast and South Asia, and aggregated emissions to a uniform spatial and temporal resolution for seven sectors: power, industry, residential, transportation, agriculture, open biomass burning and shipping. Compared to MIXv1, we extended the dataset to 2010 - 2017, included emissions of open biomass burning and shipping, and provided model-ready emissions of SAPRC99, SAPRC07, and CB05. A series of unit-based point source information was incorporated covering power plants in China and India. A consistent speciation framework for Non-Methane Volatile Organic Compounds (NMVOCs) was applied to develop emissions by three chemical mechanisms. The total Asian emissions for anthropogenic | open biomass sectors in 2017 are estimated as follows: 41.6 | 1.1 Tg NOx, 33.2 | 0.1 Tg SO2, 258.2 | 20.6 Tg CO, 61.8 | 8.2 Tg NMVOC, 28.3 | 0.3 Tg NH3, 24.0 | 2.6 Tg PM10, 16.7 | 2.0 Tg PM2.5, 2.7 | 0.1 Tg BC, 5.3 | 0.9 Tg OC, and 18.0 | 0.4 Pg CO2. The contributions of India and Southeast Asia have been emerging in Asia during 2010-2017, especially for SO2, NH3 and particulate matters. Gridded emissions at a spatial resolution of 0.1 degree with monthly variations are now publicly available at. [ABSTRACT FROM AUTHOR]

In this study, the WRF-Chem v4.4 model was utilized to evaluate three bottom-up emission inventories (EDGAR-HTAP v2, v3, and KORUS v5) using surface and aircraft data in East Asia during the Korea-United States Air Quality (KORUS-AQ) campaign period in 2016. All emission inventories were found to reproduce the diurnal variations of O3 and NO2 as compared to the surface monitor data. However, the spatial distributions of the daily maximum 8-hour average (MDA8) O3 in the model do not completely align with the observations. The model MDA8 O3 had a negative (positive) bias north (south) of 30°N over China. All simulations underestimated the observed CO by 50-60% over China and South Korea. In the Seoul Metropolitan Area (SMA), EDGAR-HTAP v2, v3, and KORUS v5 simulated the vertical shapes and diurnal patterns of O3 and other precursors effectively, but the model underestimated the observed O3, CO and HCHO concentrations. Notably, the model aromatic VOCs were significantly underestimated with the three bottom-up emission inventories, although the KORUS v5 shows improvements. The model isoprene estimations had a positive bias relative to the observations, suggesting that the Model of Emissions of Gases and Aerosols from Nature (MEGAN) version 2.04 overestimated isoprene emissions. Additional model simulations were conducted by doubling CO and VOC emissions over China and South Korea to investigate the causes of the model O3 biases and the effects of the long-range transport on the O3 over South Korea. The doubled CO and VOC emission simulations improved the model O3 simulations for the local emission dominant case, but led to the model O3 overestimations for the transport dominant case, which emphasizes the need for accurate representations of the local VOC emissions over South Korea. [ABSTRACT FROM AUTHOR]

Styrene, Benzene, Toluene, Ethylbenzene, and Xylenes (SBTEX) are established neurotoxicants. These SBTEX are hazardous air pollutants (HAPs) and released from the petrochemical industry, combustion process, transport emission, and solvent usage sources. Although several SBTEX toxic assessment studies have been conducted, they have mainly relied on ambient measurements to estimate exposure and limiting their scope to specific locations and observational periods. To overcome these spatiotemporal limitations, an air quality modeling system over the U.S. Gulf region was created predicting the the spatially and temporally enhanced SBTEX modeling concentrations from May to September 2012. Due to the incompleteness of SBTEX in the official US EPA National Emission Inventory (NEI), Hazardous Air Pollutions Imputation (HAPI) program was used to identify and estimate the missing HAPs emissions. The improved emission data was processed to generate the chemically-speciated hourly gridded emission inputs for the Comprehensive Air Quality Model with Extensions (CAMx) chemical transport model to simulate the SBTEX concentrations over the Gulf modeling region. SBTEX pollutants were modeled using a "Reactive Tracer" feature in CAMx that accounts for their chemical and physical processes in the atmosphere. The data shows that the major SBTEX emissions in this region are contributed by mobile emission (45%), wildfire (30%), and industry (26%). Most SBTEX emissions are emitted during daytime hours (local time 14:00 -17:00), and the emission rate in the model domain is about 20 - 40 t hr-1, which is about 4 times higher than that in the night-time (local time 24:00 - 4:00, about 4 - 10 t hr-1). High concentrations of SBTEX (above 1 ppb) occurred near the cities close to the I-10 interstate highway (Houston, Beaumont, Lake Charles, Lafayette, Baton Rouge, New Orleans, and Mobile) and other metropolitan cities (Shreveport and Dallas). High Styrene concentrations were co-located with industrial sources, which contribute the most to the Styrene emissions. The HAPI program successfully estimated missing emissions of Styrene from the chemical industry. The change increased total Styrene emissions was increased by 22% resulting in maximum ambient concentrations increasing from 0.035 ppb to 1.75 ppb across the model domain. The predicted SBTEX concentrations with imputed emissions present good agreement with observational data, with a correlation coefficient (R) of 0.75 (0.46 to 0.77 for individual SBTEX species) and normalized mean bias (NMB) of -5.6% (-24.9% to 32.1% for individual SBTEX species), suggesting their value for supporting any SBTEX-related human health studies in the Gulf region. [ABSTRACT FROM AUTHOR]

The main focus of this study is to develop a dynamic-coupling 'inline' air quality modeling system for the meteorology-induced emissions with simulated meteorological data. To improve the spatiotemporal representations and accuracy of onroad vehicle emissions, which are largely sensitive to local meteorology, we developed the 'inline' coupler module called 'MetEmis' for Meteorology-Induced Emission sources within the Community Multiscale Air Quality (CMAQ) version 5.3.2 modeling system. It can dynamically estimate meteorology-induced hourly gridded emissions within the CMAQ modeling system using modeled meteorology. The CMAQ air quality modeling system is applied over the continental U.S. for two months (January and July 2019) for two emissions scenarios: a) current 'offline' based onroad vehicle emissions, and b) 'inline' CMAQ-MetEmis onroad vehicle emissions. Overall, the 'MetEmis' coupler allows us to dynamically simulate onroad vehicle emissions from the MOVES onroad emission model for CMAQ with a better spatio-temporal representation compared to the 'offline' scenario based on static temporal profiles. With an instance interpolation calculation approach, the new 'inline' approach significantly enhances the computational efficiency and accuracy of estimating mobile source emissions, compared to the existing 'offline' approach that yields almost identical hourly emission estimation. The domain total of daily VOC emissions from the 'inline' scenario shows the largest impacts from the local meteorology, which is approximately 10% lower than the ones from the 'offline' scenario. Especially, the major difference of VOC estimates was shown over the California region. These local meteorology impacts on onroad vehicle emissions via CMAQ-MetEmis revealed an improvement in hourly NO2, daily maximum ozone, and daily average PM2.5 patterns with a higher agreement and correlation with daily ground observations. [ABSTRACT FROM AUTHOR]