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For the first time, mobile campaign and building monitoring experiments were conducted in downtown Seoul, Korea during the 2018/2019 winter period to assess the possibility of the co-benefit of CO2 emission reduction and air quality improvement. Given that CO2 and air pollutants in cities both originate from fossil fuel combustion, monitoring urban CO2 concentrations using a mobile vehicle and from the top of tall buildings can be a potentially effective approach for diagnosing the air quality. The local enhancement values (△species) related to urban emission sources were estimated by eliminating baseline concentrations. The results obtained showed high correlation coefficients between △CO2 and △air pollutants (i.e., 0.753, 0.505, and 0.525 for △CO, △NOX, and △NO2), confirming the applicability of CO2 as an indicator of air pollutant sources in downtown Seoul. The evaluation of the air quality in the study area using air pollutant ratios, including the ratios of CO and NOX/NO2, relative to CO2 showed that the ratios of △CO, △NOX, and △NO2 relative to △CO2 were 5.76, 1.89, and 0.21 ppb ppm−1. The estimated △NO2/△NOX ratio (11%) and a comparison of the △NOX/△CO2 ratios obtained with those reported for other cities in different countries suggested the possibility of a relationship between the current air quality in downtown Seoul and the use of diesel vehicles. Results suggest that the development of municipal policies aimed at mitigating climate change should consider the co-benefit of air quality improvement so as to ensure the effective reduction of CO2 and air pollutant emissions.

The absence of up-to-date emissions has been a major impediment to accurately simulating aspects of atmospheric chemistry and to precisely quantifying the impact of changes in emissions on air pollution. Hence, a nonlinear joint analytical inversion (Gauss–Newton method) of both volatile organic compounds (VOCs) and nitrogen oxide ( NOx ) emissions is made by exploiting the Smithsonian Astrophysical Observatory (SAO) Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) formaldehyde (HCHO) and the National Aeronautics and Space Administration (NASA) Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide ( NO2 ) columns during the Korea–United States Air Quality (KORUS-AQ) campaign over East Asia in May–June 2016. Effects of the chemical feedback of NOx and VOCs on both NO2 and HCHO are implicitly included by iteratively optimizing the inversion. Emission uncertainties are greatly narrowed (averaging kernels > 0.8 , which is the mathematical presentation of the partition of information gained from the satellite observations with respect to the prior knowledge) over medium- to high-emitting areas such as cities and dense vegetation. The prior amount of total NOx emissions is mainly dictated by values reported in the MIX-Asia 2010 inventory. After the inversion we conclude that there is a decline in emissions (before, after, change) for China ( 87.94±44.09 Gg d −1 , 68.00±15.94 Gg d −1 , −23 %), North China Plain (NCP) ( 27.96±13.49 Gg d −1 , 19.05±2.50 Gg d −1 , −32 %), Pearl River Delta (PRD) ( 4.23±1.78 Gg d −1 , 2.70±0.32 Gg d −1 , −36 %), Yangtze River Delta (YRD) ( 9.84±4.68 Gg d −1 , 5.77±0.51 Gg d −1 , −41 %), Taiwan ( 1.26±0.57 Gg d −1 , 0.97±0.33 Gg d −1 , −23 %), and Malaysia ( 2.89±2.77 Gg d −1 , 2.25±1.34 Gg d −1 , −22 %), all of which have effectively implemented various stringent regulations. In contrast, South Korea ( 2.71±1.34 Gg d −1 , 2.95±0.58 Gg d −1 , + 9 %) and Japan ( 3.53±1.71 Gg d −1 , 3.96±1.04 Gg d −1 , +12 %) are experiencing an increase in NOx emissions, potentially due to an increased number of diesel vehicles and new thermal power plants. We revisit the well-documented positive bias (by a factor of 2 to 3) of MEGAN v2.1 (Model of Emissions of Gases and Aerosols from Nature) in terms of biogenic VOC emissions in the tropics. The inversion, however, suggests a larger growth of VOCs (mainly anthropogenic) over NCP (25 %) than previously reported (6 %) relative to 2010. The spatial variation in both the magnitude and sign of NOx and VOC emissions results in nonlinear responses of ozone production and loss. Due to a simultaneous decrease and increase in NOx∕VOC over NCP and YRD, we observe a ∼53 % reduction in the ratio of the chemical loss of NOx ( LNOx ) to the chemical loss of ROx ( RO2+HO2 ) over the surface transitioning toward NOx -sensitive regimes, which in turn reduces and increases the afternoon chemical loss and production of ozone through NO2+OH ( −0.42 ppbv h −1 ) ∕HO2 (and RO2 ) +NO ( +0.31 ppbv h −1 ). Conversely, a combined decrease in NOx and VOC emissions in Taiwan, Malaysia, and southern China suppresses the formation of ozone. Simulations using the updated emissions indicate increases in maximum daily 8 h average (MDA8) surface ozone over China (0.62 ppbv), NCP (4.56 ppbv), and YRD (5.25 ppbv), suggesting that emission control strategies on VOCs should be prioritized to curb ozone production rates in these regions. Taiwan, Malaysia, and PRD stand out as regions undergoing lower MDA8 ozone levels resulting from the NOx reductions occurring predominantly in NOx -sensitive regimes.

The Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in February 2020 to monitor air quality (AQ) at an unprecedented spatial and temporal resolution from a geostationary Earth orbit (GEO) for the first time. With the development of UV–visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO, and aerosols) can be obtained. To date, all the UV–visible satellite missions monitoring air quality have been in low Earth orbit (LEO), allowing one to two observations per day. With UV–visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be on board the Geostationary Korea Multi-Purpose Satellite 2 (GEO-KOMPSAT-2) satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager 2 (GOCI-2). These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA’s Tropospheric Emissions: Monitoring of Pollution (TEMPO) and ESA’s Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS).

The air quality in Republic of Korea, especially in cities such as Seoul, has been a serious public health concern over the years. The key pollutant in the atmosphere leading to poor air quality in Korea is fine particulate matter (PM2.5). Here, we use a 3-D global chemistry model (GEOS-Chem) to conduct source attribution to PM2.5 in Korea from international and domestic emissions. The modeling was done for 2015 and 2016 to account for different meteorological conditions. We ran the GEOS-Chem model for both years, conducted model evaluation using ground and aloft observations, and then conducted sensitivity simulations without domestic anthropogenic emissions and Chinese anthropogenic emissions, respectively. Results show that the Chinese influence on PM2.5 in Korea varies from month to month with the highest contribution during spring when observed concentrations are also the highest. Chinese contributions to PM2.5 concentrations in South Korea reach a maximum of up to ~60% in January and February and gradually decrease until August when they reach a minimum at about 20%. On an annual basis, our analysis estimated that in 2016, Chinese anthropogenic emissions contributed 45% to PM2.5 in South Korea. The 2016 contribution from China was generally 3–5% lower than in 2015 because of emissions reductions in China. Compared to the Chinese contribution, the rest of the world contributions (which also include contributions from natural emissions worldwide) were minor except for summer in the South Sea.

The Comprehensive Automobile Research System (CARS) is an open-source python-based automobile emissions inventory model designed to efficiently estimate high quality emissions from motor-vehicle emission sources. It can estimate the criteria air pollutants, greenhouse gases, and air toxics in various temporal resolutions at the national, state, county, and any spatial resolution based on the spatiotemporal resolutions of input datasets. The CARS is designed to utilize the local vehicle activity database, such as vehicle travel distance, road link-level network Geographic Information System (GIS) information, and vehicle-specific average speed by road type, to generate a temporally and spatially enhanced automobile emissions inventory for policymakers, stakeholders, and the air quality modeling community. The CARS model adopted the European Environment Agency's (EEA) onroad automobile emissions calculation methodologies to estimate the hot exhaust, cold start, and evaporative emissions from onroad automobile sources. It can optionally utilize road link-specific average speed distribution (ASD) inputs to reflect more realistic vehicle speed variations by road type than a road-specific single averaged speed approach. Also, utilizing high-resolution road GIS data allows the CARS to estimate the road link-level emissions to improve the inventory's spatial resolution. When we compared the official 2015 national mobile emissions from Korea's Clean Air Policy Support System (CAPSS) against the ones estimated by the CARS, there is a moderate increase of VOC (33 %), CO (52 %), and fine particulate matter (PM2.5) (15 %) emissions while NOx and SOx are reduced by 24 % and 17 % in the CARS estimates. The main differences are driven by the usage of different vehicle activities and the incorporation of road-specific ASD, which plays a critical role in hot exhaust emission estimates but wasn’t implemented in Korea’s CAPSS mobile emissions inventory. While 52% of vehicles use gasoline fuel and 35 % use diesel, gasoline vehicles only contribute 7.7 % of total NOx emissions while diesel vehicles contribute 85.3 %. But for VOC emissions, gasoline vehicles contribute 52.1 % while diesel vehicles are limited to 23 %. While diesel buses are only 0.3 % of vehicles, each vehicle has the largest contribution to NOx emissions (8.51 % of NOx total) due to its longest daily VKT. For VOC, CNG buses are the largest contributor with 19.5 % of total VOC emissions. It indicates that the CNG bus is better for the rural area while the diesel bus is better applicable for the urban area for a better ozone control strategy because the rural area is usually NOx limited for ozone formation and urban area is VOC limited region. For primary PM2.5, more than 98.5 % is from diesel vehicles. The CARS model's in-depth analysis feature can assist government policymakers and stakeholders develop the best emission abatement strategies.

Geostationary satellite sensors over East Asia (GOCI and AHI) are now providing continuous mapping of aerosol optical depth (AOD) at 550 nm to improve monitoring of fine particulate matter (PM2.5) air quality. Here we evaluate our understanding of the physical relationships between AOD and PM2.5 over East Asia by using the GEOS-Chem atmospheric chemistry model to simulate observations from multiple sources: 1) the joint NASA-NIER Korea – United States Air Quality aircraft campaign over South Korea (KORUS-AQ; May–June 2016); 2) AODs from the AERONET ground-based network; 3) AOD from a new GOCI/AHI fused product; and 4) surface PM2.5 networks in South Korea and China. 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 the high hygroscopicity of the PBL aerosols. Although GEOS-Chem is successful in reproducing the KORUS-AQ vertical profiles of aerosol mass, its ability to link AOD to PM2.5 is limited by under-accounting of coarse PM and by a large overestimate of nighttime PM2.5 nitrate. A broader analysis of the GOCI/AHI AOD data over East Asia in different seasons shows agreement with AERONET AODs and a spatial distribution consistent with surface PM2.5 network data. The AOD observations over North China show a summer maximum and winter minimum, opposite in phase to surface PM2.5. 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 PM2.5 over South Korea is much weaker, reflecting weaker variation of PBL depth and lack of residential coal emissions. Physical interpretation of the satellite AOD data in terms of surface PM2.5 is sensitive to accurate information on aerosol size distributions, PBL depths, RH, the role of coarse particles, and diurnal variation of PM2.5.

High concentrations of PM2.5 have become a serious environmental issue in South Korea, which ranked 1st or 2nd among OECD countries in terms of population exposure to PM2.5. Quantitative understanding of PM2.5 source attribution is thus crucial for developing efficient air quality mitigation strategies. Here we use a suite of extensive observations of PM2.5 and its precursors concentrations during the international KORea-US cooperative Air Quality field study in Korea (KORUS-AQ) in May–June 2016 to investigate source contributions to PM2.5 in South Korea under various meteorological conditions. For the quantitative analysis, we updated a 3-D chemical transport model, GEOS-Chem, and its adjoint with the latest regional emission inventory and other recent findings. The updated model is evaluated by comparing against observed daily PM2.5 and its component concentrations from six ground sites (Bangnyung, Bulkwang, Olympic park, Gwangju, Ulsan, and Jeju). Overall, simulated concentrations of daily PM2.5 and its components are in a good agreement with observations over the peninsula. We conduct an adjoint sensitivity analysis for simulated surface level PM2.5 concentrations at five ground sites (except for Bangnyung because of its small population) under four different meteorological conditions: dynamic weather, stagnant, extreme pollution, and blocking periods. Source contributions by regions vary greatly depending on synoptic meteorological conditions. Chinese contribution accounts for almost 68% of PM2.5 in surface air in South Korea during the extreme pollution period of the campaign, whereas an enhanced contribution from domestic sources (57%) occurs for the blocking period. Results from our sensitivity analysis suggest that the reduction of domestic anthropogenic NH3 emissions could be most effective in reducing population exposure to PM2.5 in South Korea (effectiveness = 14%) followed by anthropogenic SO2 emissions from Shandong region (effectiveness = 11%), domestic anthropogenic NOx emissions (effectiveness = 10%), anthropogenic NH3 emissions from Shandong region (effectiveness = 8%), anthropogenic NOx emissions from Shandong region (effectiveness = 7%), domestic anthropogenic OC emissions (effectiveness = 7%), and domestic anthropogenic BC emissions (effectiveness = 5%).

In this work, we investigate the NOx emissions inventory in Seoul, South Korea, using a regional ozone monitoring instrument (OMI) NO2 product derived from the standard NASA product. We first develop a regional OMI NO2 product by recalculating the air mass factors using a high-resolution (4 km × 4 km) WRF-Chem model simulation, which better captures the NO2 profile shapes in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the subpixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 times larger in the Seoul metropolitan region and >2 times larger near substantial point sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the South Korea–United States Air Quality (KORUS-AQ) field campaign. NOx emissions are then derived for the Seoul metropolitan area during the KORUS-AQ field campaign using a top-down approach with the standard and regional NASA OMI NO2 products. We first apply the top-down approach to a model simulation to ensure that the method is appropriate: the WRF-Chem simulation utilizing the bottom-up emissions inventory yields a NOx emissions rate of 227±94 kt yr −1 , while the bottom-up inventory itself within a 40 km radius of Seoul yields a NOx emissions rate of 198 kt yr −1 . Using the top-down approach on the regional OMI NO2 product, we derive the NOx emissions rate from Seoul to be 484±201 kt yr −1 , and a 353±146 kt yr −1 NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53 % and 36 % in the bottom-up inventory using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 and NOy simulated by WRF-Chem to observations of the same quantity acquired by aircraft and find a model underestimate. When NOx emissions in the WRF-Chem model are increased by a factor of 2.13 in the Seoul metropolitan area, there is better agreement with KORUS-AQ aircraft observations and the recalculated OMI NO2 tropospheric columns. Finally, we show that by using a WRF-Chem simulation with an updated emissions inventory to recalculate the air mass factor (AMF), there are small differences ( ∼8 %) in OMI NO2 compared to using the original WRF-Chem simulation to derive the AMF. This suggests that changes in model resolution have a larger effect on the AMF calculation than modifications to the South Korean emissions inventory. Although the current work is focused on South Korea using OMI, the methodology developed in this work can be applied to other world regions using TROPOMI and future satellite datasets (e.g., GEMS and TEMPO) to produce high-quality region-specific top-down NOx emissions estimates.

The Korea-United States Air Quality (KORUS-AQ) field study was conducted during May–June 2016 to understand the factors controlling air quality in South Korea. Extensive aircraft and ground network observations from the campaign offer an opportunity to address issues in current air quality models and reduce model-observation disagreements. This study examines these issues using model evaluation against the KORUS-AQ observations and intercomparisons between models. Six regional and two global chemistry transport models using identical anthropogenic emissions participated in the model intercomparison study and were used to conduct air quality simulations focusing on ozone (O3), aerosols, and their precursors for the campaign. Using the KORUSv5 emissions inventory, which has been updated from KORUSv1, the models successfully reproduced observed nitrogen oxides (NOx) and volatile organic compounds mixing ratios in surface air, especially in the Seoul Metropolitan Area, but showed systematic low biases for carbon monoxide (CO), implying possible missing CO sources in the inventory in East Asia. Although the DC-8 aircraft-observed O3 precursor mixing ratios were well captured by the models, simulated O3 levels were lower than the observations in the free troposphere in part due to too low stratospheric O3 influxes, especially in regional models. During the campaign, the synoptic meteorology played an important role in determining the observed variability of PM2.5 (PM diameter ≤ 2.5 μm) concentrations in South Korea. The models successfully simulated the observed PM2.5 variability with significant inorganic sulfate-nitrate-ammonium aerosols contribution, but failed to reproduce that of organic aerosols, causing a large inter-model variability. From the model evaluation, we find that an ensemble of model results, incorporating individual models with differing strengths and weaknesses, performs better than most individual models at representing observed atmospheric compositions for the campaign. Ongoing model development and evaluation, in close collaboration with emissions inventory development, are needed to improve air quality forecasting.

The Korea–United States Air Quality (KORUS-AQ) field study was conducted during May–June 2016. The effort was jointly sponsored by the National Institute of Environmental Research of South Korea and the National Aeronautics and Space Administration of the United States. KORUS-AQ offered an unprecedented, multi-perspective view of air quality conditions in South Korea by employing observations from three aircraft, an extensive ground-based network, and three ships along with an array of air quality forecast models. Information gathered during the study is contributing to an improved understanding of the factors controlling air quality in South Korea. The study also provided a valuable test bed for future air quality–observing strategies involving geostationary satellite instruments being launched by both countries to examine air quality throughout the day over Asia and North America. This article presents details on the KORUS-AQ observational assets, study execution, data products, and air quality conditions observed during the study. High-level findings from companion papers in this special issue are also summarized and discussed in relation to the factors controlling fine particle and ozone pollution, current emissions and source apportionment, and expectations for the role of satellite observations in the future. Resulting policy recommendations and advice regarding plans going forward are summarized. These results provide an important update to early feedback previously provided in a Rapid Science Synthesis Report produced for South Korean policy makers in 2017 and form the basis for the Final Science Synthesis Report delivered in 2020.

The U.S. National Aeronautics and Space Administration in partnership with Korea’s National Institute of Environmental Research embarked on the Korea-United States Air Quality (KORUS-AQ) study to address air quality issues over the Korean peninsula. Underestimation of volatile organic compound (VOC) emissions from various large facilities on South Korea’s northwest coast may contribute to this problem, and this study focuses on quantifying top-down emissions of formaldehyde (CH2O) and VOCs from the largest of these facilities, the Daesan petrochemical complex, and comparisons with the latest emission inventories. To accomplish this and additional goals discussed herein, this study employed a number of measurements acquired during KORUS-AQ onboard the NASA DC-8 aircraft during three Daesan overflights on June 2, 3, and 5, 2016, in conjunction with a mass balance approach. The measurements included fast airborne measurements of CH2O and ethane from an infrared spectrometer, additional fast measurements from other instruments, and a suite of 33 VOC measurements acquired by the whole air sampler. The mass balance approach resulted in consistent top-down yearly Daesan VOC emission flux estimates, which averaged (61 ± 14) × 103 MT/year for the 33 VOC compounds, a factor of 2.9 ± 0.6 (±1.0) higher than the bottom-up inventory value. The top-down Daesan emission estimate for CH2O and its four primary precursors averaged a factor of 4.3 ± 1.5 (± 1.9) times higher than the bottom-up inventory value. The uncertainty values in parentheses reflect upper limits for total uncertainty estimates. The resulting averaged top-down Daesan emission estimate for sulfur dioxide (SO2) yielded a ratio of 0.81–1.0 times the bottom-up SO2 inventory, and this provides an important cross-check on the accuracy of our mass balance analysis.

We present trace gas vertical profiles observed by instruments on the NASA DC-8 and at a ground site during the Korea-US air quality study (KORUS) field campaign in May to June 2016. We focus on the region near the Seoul metropolitan area and its surroundings where both anthropogenic and natural emission sources play an important role in local photochemistry. Integrating ground and airborne observations is the major research goal of many atmospheric chemistry field campaigns. Although airborne platforms typically aim to sample from near surface to the free troposphere, it is difficult to fly very close to the surface especially in environments with complex terrain or a populated area. A detailed analysis integrating ground and airborne observations associated with specific concentration footprints indicates that reactive trace gases are quickly oxidized below an altitude of 700 m. The total OH reactivity profile has a rapid decay in the lower part of troposphere from surface to the lowest altitude (700 m) sampled by the NASA DC-8. The decay rate is close to that of very reactive biogenic volatile organic compounds such as monoterpenes. Therefore, we argue that photochemical processes in the bottom of the boundary layer, below the typical altitude of aircraft sampling, should be thoroughly investigated to properly assess ozone and secondary aerosol formation.

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.

For the purpose of improving PM prediction skills in East Asia, we estimated a new background error covariance matrix (BEC) for aerosol data assimilation using surface PM2.5 observations that accounts for the uncertainties in anthropogenic emissions. In contrast to the conventional method to estimate the BEC that uses perturbations in meteorological data, this method additionally considered the perturbations using two different emission inventories. The impacts of the new BEC were then tested for the prediction of surface PM2.5 over East Asia using Community Multi-scale Air Quality (CMAQ) initialized by three-dimensional variational method (3D-VAR). The surface PM2.5 data measured at 154 sites in South Korea and 1,535 sites in China were assimilated every six hours during the Korea-United States Air Quality Study (KORUS-AQ) campaign period (1 May–14 June 2016). Data assimilation with our new BEC showed better agreement with the surface PM2.5 observations than that with the conventional method. Our method also showed closer agreement with the observations in 24-hour PM2.5 predictions with ~ 44 % fewer negative biases than the conventional method. We conclude that increased standard deviations, together with horizontal and vertical length scales in the new BEC, tend to improve the data assimilation and short-term predictions for the surface PM2.5. This paper also suggests further research efforts devoted to estimating the BEC to improve PM2.5 predictions.

The absence of up-to-date emissions has been a major impediment to accurately simulate aspects of atmospheric chemistry, and to precisely quantify the impact of changes of emissions on air pollution. Hence, a non-linear joint analytical inversion (Gauss–Newton method) of both volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions is made by exploiting the Smithsonian Astrophysical Observatory (SAO) Ozone Mapping and Profile Suite Nadir Mapper (OMPS-NM) formaldehyde (HCHO) and the National Aeronautics and Space Administration (NASA) Ozone Monitoring Instrument (OMI) tropospheric nitrogen dioxide (NO2) retrievals during the Korea-United States Air Quality (KORUS-AQ) campaign over East Asia in May–June 2016. Effects of the chemical feedback of NOx and VOCs on both NO2 and HCHO are implicitly included through iteratively optimizing the inversion. Emissions estimates are greatly improved (averaging kernels > 0.8) over medium- to high-emitting areas such as cities and dense vegetation. The amount of total NOx emissions is mainly dictated by values reported in the MIX-Asia 2010 inventory. After the inversion we conclude a decline in the emissions (before, after, change) for China (87.94 ± 44.09 Gg/day, 68.00 ± 15.94 Gg/day, −23 %), North China Plain (NCP) (27.96 ± 13.49 Gg/day, 19.05 ± 2.50 Gg/day, −32 %), Pearl River Delta (PRD) (4.23 ± 1.78 Gg/day, 2.70 ± 0.32 Gg/day, −36 %), Yangtze River Delta (YRD) (9.84 ± 4.68 Gg/day, 5.77 ± 0.51 Gg/day, −41 %), Taiwan (1.26 ± 0.57 Gg/day, 0.97 ± 0.33 Gg/day, −23 %), and Malaysia (2.89 ± 2.77 Gg/day, 2.25 ± 1.34 Gg/day, −22 %), all of which have effectively implemented various stringent regulations. In contrast, South Korea (2.71 ± 1.34 Gg/day, 2.95 ± 0.58 Gg/day, +9 %) and Japan (3.53 ± 1.71 Gg/day, 3.96 ± 1.04 Gg/day, +12 %) experience an increase in NOx emissions potentially due to risen number of diesel vehicles and new thermal power plants. We revisit the well-documented positive bias of the model in terms of biogenic VOC emissions in the tropics. The inversion, however, suggests a larger growth of VOC (mainly anthropogenic) over NCP (25 %) than previously reported (6 %) relative to 2010. The spatial variation in both magnitude and sign of NOx and VOC emissions results in non-linear responses of ozone production/loss. Due to simultaneous decrease/increase of NOx/VOC over NCP and YRD, we observe an ~ 53 % reduction in the ratio of the chemical loss of NOx (LNOx) to the chemical loss of ROx (RO2 + HO2) transitioning toward NOx-sensitive regimes, which in turn, reduces/increases the afternoon chemical loss/production of ozone through NO2 + OH (−0.42 ppbv hr−1)/HO2 (and RO2) + NO (+0.31 ppbv hr−1). Conversely, a combined decrease in NOx and VOC emissions in Taiwan, Malaysia, and the southern China suppresses the formation of ozone. Ultimately, model simulations indicate enhancements of maximum daily 8-hour average (MDA8) surface ozone over China (0.62 ppbv), NCP (4.56 ppbv), and YRD (5.25 ppbv) due to the non-linear ozone chemistry, suggesting that emissions standards should be extended to regulate VOCs to be able to curb ozone production rates. Taiwan, Malaysia, and PRD stand out as the regions undergoing lower MDA8 ozone levels resulting from the NOx reductions occurring predominantly in NOx-sensitive regimes.

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.

Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO2 analyses as well as two higher-resolution forecasts (16 and 9 km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO2 with a mean bias against airborne CO2 measurements of 2.2, 0.7, and 0.3 ppmv for 16 and 9 km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the 16 km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of − 19.2 (16 km), − 16.7 (9 km), and − 20.7 ppbv (analysis). This negative CO mean bias is mostly seen below 750 hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul ( d CO / d CO 2 = 9 ppbv ppmv −1 ) compared to the West Sea ( d CO / d CO 2 = 28 ppbv ppmv −1 ). This “combustion signature contrast” is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8–12 ppbv ppmv −1 , the West Sea: ∼30 ppbv ppmv −1 ) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64–0.90, the West Sea: ∼0.80 ) suggesting that the contrast captured by CAMS may be dominated by anthropogenic emission ratios used in CAMS. However, CAMS shows poorer performance in terms of capturing local-to-urban CO and CO2 variability. Along with measurements at ground sites over the Korean Peninsula, CAMS produces too high CO and CO2 concentrations at the surface with steeper vertical gradients ( ∼0.4 ppmv hPa −1 for CO2 and 3.5 ppbv hPa −1 for CO) in the morning samples than observed ( ∼0.25 ppmv hPa −1 for CO2 and 1.7 ppbv hPa −1 for CO), suggesting weaker boundary layer mixing in the model. Lastly, we find that the combination of CO analyses (i.e., improved initial condition) and use of finer resolution (9 km vs. 16 km) generally produces better forecasts.

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.

Enforcement of an air quality standard for PM2.5 in the Seoul metropolitan area (SMA) was enacted in 2015. From May to June of 2016, an international airborne and surface measurement campaign took place to investigate air pollution mechanisms in the SMA. The total and speciated PM2.5 concentrations since 2008 have been measured at an intensive monitoring site for the SMA operated by the National Institute of Environmental Research (NIER). To gain insight on the trends and sources of PM2.5 in the SMA in May, we analyze PM2.5 concentrations from 2009 to 2013 using the measurements and simulations from a 3-dimensional global chemical transport model, GEOS-Chem and its adjoint. The model is updated here with the latest regional emission inventory and diurnally varying NH3 emissions. Monthly average PM2.5 concentration measured by β-ray attenuation ranges from 28 (2010) to 45 (2013) μg/m3, decreased from 2009 to 2010, and then continuously increased until 2013. The model shows good agreement with the measurements for the daily average PM2.5 concentrations (R ≥ 0.5), and reproduces 10 out of 17 measured episodes exceeding the daily air quality standard (50 μg/m3). Using the GEOS-Chem adjoint model, we find that anthropogenic emissions from the Shandong region have the largest modeled influence on PM2.5 in Seoul in May. Average contributions to the high PM2.5 episodes simulated by the model are 39% from the Shandong region, 16% from the Shanghai region, 14% from the Beijing region, and 15% from South Korea. Anthropogenic SO2 emissions from South Korea are negligible with 90% of the total contribution originating from China. Findings from this study may guide interpretation of observations obtained in the KORUS-AQ measurement campaign.

This study examines the effects of different foreign anthropogenic emissions inventories on predicted ozone concentrations in the Seoul Metropolitan Area (SMA), South Korea, and estimates changes in ozone due to emissions reductions. We ran the Community Multi-Scale Air Quality (CMAQ) model using the High-Order Decoupled Direct Method with three inventories of foreign anthropogenic emissions: (1) the Intercontinental Chemical Transport Experiment, Phase B (INTEX-B) 2006; (2) the Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE) 2010; and (3) the Model Inter-Comparison Study (MICS)-Asia 2010. All three inventories have different spatial distributions of emissions, yielding different modeled ozone concentrations. However, the ozone concentrations modeled for the SMA differ less than those modeled for large, foreign cities in the modeling domain. The simulations using INTEX-B 2006 and CREATE 2010 suggested greater reduction in ozone with NOx control than with VOCs control. All simulations show that (1) simultaneous reduction in NOx and VOCs leads to less ozone reduction than the sum of ozone reductions for individual NOx and VOCs controls and (2) ozone reductions are stronger for high ozone days than for low ozone days. Comparing the modeled reductions in the relative sense yields smaller differences between high and low ozone days than comparing the modeled reductions in the absolute sense. With a 20% reduction in only NOx emissions, the differences in MDA1O3 among the three inventories were between 0.3 and 0.7 ppb. Because air-quality planning often leads to defined tonnage reductions, we examined the model’s response to such a defined emissions reduction. Using the NOx reduction in China estimated by Zhao et al. (2013), we estimated that the differences in MDA1O3 among the three inventories were between 1.50 and 1.78 ppb. Based on these results, we recommend using different foreign anthropogenic emissions inventories to test future scenarios for air-quality control

For the purpose of providing reliable and robust air quality predictions, an operational air quality prediction system was developed for the main air quality criteria species in South Korea (PM10, PM2.5, CO, O3, and SO2). The main caveat of the system is to prepare the initial conditions (ICs) of the Community Multi-scale Air Quality (CMAQ) model simulations using observations from the Geostationary Ocean Color Imager (GOCI) and ground-based monitoring networks in northeast Asia. The performance of the air quality prediction system was evaluated during the Korea-United States Air Quality Study (KORUS-AQ) campaign period (1 May–12 June 2016). Data assimilation (DA) of optimal interpolation (OI) with Kalman filter was used in this study. One major advantage of the system is that it can predict not only particulate matter (PM) concentrations but also PM chemical composition including five main constituents: sulfate, nitrate, ammonium, organic aerosols (OAs), and elemental carbon (EC). In addition, it is also capable of predicting the concentrations of gaseous pollutants (CO, O3 and SO2). In this sense, this new operational air quality prediction system is comprehensive. The results with the ICs (DA RUN) were compared with those of the CMAQ simulations without ICs (BASE RUN). For almost all of the species, the application of ICs led to improved performance in terms of correlation, errors, and biases over the entire campaign period. The DA RUN agreed reasonably well with the observations for PM10 (IOA = 0.60; MB = −13.54) and PM2.5 (IOA = 0.71; MB = −2.43) as compared to the BASE RUN for PM10 (IOA = 0.51; MB = −27.18) and PM2.5 (IOA = 0.67; MB = −9.9). A significant improvement was also found with the DA RUN in terms of bias. For example, for CO, the MB of −0.27 (BASE RUN) was greatly enhanced to −0.036 (DA RUN). In the cases of O3 and SO2, the DA RUN also showed better performance than the BASE RUN. Further, several more practical issues frequently encountered in the operational air quality prediction system were also discussed. In order to attain more accurate ozone predictions, the DA of NO2 mixing ratios should be implemented with careful consideration of the measurement artifacts (i.e., inclusion of alkyl nitrates, HNO3, and PANs in the ground-observed NO2 mixing ratios). It was also discussed that, in order to ensure accurate nocturnal predictions of the concentrations of the ambient species, accurate predictions of the mixing layer heights (MLH) should be achieved from the meteorological modeling. Several advantages of the current air quality prediction system, such as its non-static free parameter scheme, dust episode prediction, and possible multiple implementations of DA prior to actual predictions, were also discussed. These configurations are all possible because the current DA system is not computationally expensive. In the ongoing and future works, more advanced DA techniques such as the three-dimensional variational (3DVAR) method and ensemble Kalman filter (EnK) are being tested and will be introduced to the Korean operational air quality forecasting system.

A bottom-up emissions inventory is one of the most important data sets needed to understand air quality (AQ) and climate change (CC). Several emission inventories have been developed for Asia, including Transport and Chemical Evolution over the Pacific (TRACE-P), Regional Emission Inventory in Asia (REAS), and Inter-Continental Chemical Transport Experiment (INTEX) and, while these have been used successfully for many international studies, they have limitations including restricted amounts of information on pollutant types and low levels of transparency with respect to the polluting sectors or fuel types involved. To address these shortcomings, we developed: 1) a base-year, bottom-up anthropogenic emissions inventory for Asia, using the most current parameters and international frameworks (i.e., the Greenhouse gas—Air pollution INteractions and Synergies (GAINS) model); and 2) a base-year, natural emissions inventory for biogenic and biomass burning. For 1), we focused mainly on China, South Korea, and Japan; however, we also covered emission inventories for other regions in Asia using data covering recent energy/industry statistics, emission factors, and control technology penetration. The emissions inventory (Comprehensive Regional Emissions inventory for Atmospheric Transport Experiment (CREATE)) covers 54 fuel classes, 201 subsectors, and 13 pollutants, namely SO2, NOx, CO, non-methane volatile organic compounds (NMVOC), NH3, OC, BC, PM10, PM2.5, CO2, CH4, N2O, and Hg. For the base-year natural emissions inventory, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and BlueSky-Asia frameworks were used to estimate biogenic and biomass burning emissions, respectively. Since the CREATE emission inventory was designed/developed using international climate change/air quality (CC/AQ) assessment frameworks, such as GAINS, and has been fully connected with the most comprehensive emissions modeling systems—such as the US Environmental Protection Agency (EPA) Chemical Manufacturing Area Source (CMAS) system—it can be used to support various climate and AQ integrated modeling studies, both now and in the future.

Anthropogenic emissions in East Asia have changed dramatically in recent years. To measure these changing emissions in support of air-quality modeling, we developed a top-down emission update system using surface observations and a geographical information system spatial-allocation technique. We deploy a data-processing system to construct adjustment factors to prefecture-level SO2 emissions by comparing surface and modeled observations. A case study is conducted over East Asia for 2016 in which we update Chinese SO2 emissions using measurements from around 1500 surface monitoring sites. Model simulations using updated SO2 emissions are improved relative to the existing simulation system (e.g., R = 0.23 to R = 0.8), suggesting that the newly designed system provides an efficient, practical forecast solution. Finally, estimated SO2 emissions are compared with existing emission inventories, agreeing well with recent reports of reduced SO2 emissions from Chinese anthropogenic sources.

We have developed the Integrated Climate and Air Quality Modeling System (ICAMS) through the one-way nesting of global–regional models to examine the changes in the surface ozone concentrations over East Asia under future climate scenarios. Model simulations have been conducted for the present period of 1996–2005 to evaluate the performance of ICAMS. The simulated surface ozone concentrations reproduced the observed monthly mean concentrations at sites in East Asia with high R2 values (0.4–0.9), indicating a successful simulation to capture both spatial and temporal variability. We then performed several model simulations with the six IPCC SRES scenarios (A2, A1B, A1FI, A1T, B1, and B2) for the next three periods, 2016–2025 (the 2020s), 2046–2055 (the 2050s), and 2091–2100 (the 2090s). The model results show that the projected changes of the annual daily mean maximum eight-hour (DM8H) surface ozone concentrations in summertime for East Asia are in the range of 2–8 ppb, −3 to 8 ppb, and −7 to 9 ppb for the 2020s, the 2050s, and the 2090s, respectively, and are primarily determined based on the emission changes of NOx and NMVOC. The maximum increases in the annual DM8H surface ozone and high-ozone events occur in the 2020s for all scenarios except for A2, implying that the air quality over East Asia is likely to get worse in the near future period (the 2020s) than in the far future periods (the 2050s and the 2090s). The changes in the future environment based on IPCC SRES scenarios would also influence the change in the occurrences of high-concentrations events more greatly than that of the annual DM8H surface ozone concentrations. Sensitivity simulations show that the emissions increase is the key factor in determining future regional surface ozone concentrations in the case of a developing country, China, whereas a developed country, Japan would be influenced more greatly by effects of the regional climate change than the increase in emissions.

We investigate ozone air quality changes in 2050 caused by global changes in climate and anthropogenic emissions of ozone precursors by using a global chemical transport model driven by meteorological fields from a general circulation model. We use projected emissions based on the Representative Concentration Pathway (RCP) scenarios and conduct model simulations to quantify the effects of climate and emission changes on future air quality, focusing on ozone in surface air. Our model results show that annual mean concentrations of surface ozone will be lower in 2050 relative to 2000 by −3.3, −3.7, and −4.2 ppbv under RCP6.0, RCP4.5, and RCP2.6, respectively. In contrast, the RCP8.5 projection results in a slight increase of 2.1 ppbv caused by a methane increase. The ozone reductions are driven primarily by decreases in NOx emission, which dominate the climate penalty on ozone driven by temperature increases. We also estimate the effect of 21st century climate change on ozone air quality, assuming no changes in anthropogenic emissions of ozone precursors in the future. We further use a statistical method to analyze the results in order to quantify the effect of each meteorological variable change on ozone concentration in summer. Temperature increase is found to result in ozone increases of up to 2.2 ppbv over land. Ozone over the oceans, however, is largely reduced with specific humidity increase, particularly in the Northern Hemisphere, where the ozone concentration decreases by 0.8 ppbv. We find that future increases in natural NOx emissions from lightning and soil make an important contribution to the formation of nitric acid and might seriously offset future decreases in nitrogen deposition caused by anthropogenic NOx emission reduction.

We use a 3-D regional atmospheric chemistry transport model (WRF-Chem) to examine ozone dry deposition in East Asia, which is an important but uncertain research area because of insufficient observation and numerical studies focusing on East Asia. Here we compare two widely used dry deposition parameterization schemes, the Wesely and M3DRY schemes, which are used in the WRF-Chem and Community Multiscale Air Quality (CMAQ) models, respectively. Simulated ozone dry deposition velocities with the two schemes under identical meteorological conditions show considerable differences (a factor of 2) owing to surface resistance parameterization discrepancies. Resulting ozone concentrations differ by up to 10 ppbv for a monthly mean in May when the peak ozone typically occurs in East Asia. An evaluation of the simulated dry deposition velocities shows that the Wesely scheme calculates values with more pronounced diurnal variation than the M3DRY and results in a good agreement with the observations. However, we find significant changes in simulated ozone concentrations using the Wesely scheme but with different surface type data sets, indicating the high sensitivity of ozone deposition calculations to the input data. The need is high for observations to constrain the dry deposition parameterization and its input data to improve the use of air quality models for East Asia.

A major obstacle of the interdisciplinary communications for decision-making is that each participant prefers the solution from their own area because current collaboration systems cannot effectively mediate among many alternatives. If a visual collaboration system could display multiple alternatives in a single visual presentation, users would be able to compare alternatives with only a few variables, where all other parameters are fixed, at least from a visual perspective. In this study, we developed a visualization tool to support a microscale air quality (MSAQ) management group, the members of which often need to compare the effects of many alternative control methods. The main achievements of this study are: (1) three-dimensional (3D) visualization of the MSAQ using a 3D city model and (2) development of a geospatial spreadsheet (GS) to facilitate visual comparisons, thereby improving decision-making by making it easy to compare differences based on realistic visual display items. A questionnaire-bas...

Ozone concentrations in East Asia were simulated using the Community Multi-scale Air Quality (CMAQ) model, and its source contributions were estimated by multiple source–receptor modeling techniques. To study relationships between ozone concentrations and precursor emission sources, three approaches were applied to four months (January, April, July, and October 2009) to represent seasonal characteristics and compare results, with a particular focus on South Korea. Brute force (BF) is a traditional sensitivity analysis method used to estimate model output response to an input change. The high-order decoupled direct method (HDDM), a computational method, is an efficient and accurate alternative to the BF method for sensitivity. The Ozone and Particulate Precursor Tagging Methodology (OPTM) provides contribution information quantified by tracking emissions from selected sources throughout the simulation period. The approaches generally show that most of the receptor regions were substantially influenced by emissions from central China, which is the largest anthropogenic emissions source region in East Asia. Local emissions were still major contributors, especially South Korea and Japan during July 2009. On the other hand, a case study of maximum 8-h ozone concentrations derived from CMAQ–OPTM on April 9 in South Korea shows that the NOx and VOCs emissions from China contributed approximately 82% and 91%, respectively, to maximum 8-h ozone in Region 4 (South Korea) without boundary inflow, which indicates that Chinese emissions are the dominant contributor in this episode. A comparison study of the three approaches shows that HDDM tends to estimate biogenic source contributions lower than that from OPTM in China but similar to OPTM in South Korea and Japan. When comparing the BF method and HDDM, the sensitivity results show a reasonably good agreement during a given period. The location- and time-dependent maximum 8-h ozone isopleths over South Korea as a receptor region created by HDDM suggest that most ozone was being transported from central China, whereas almost no ozone was formed locally during April 2009, and local conditions were heavily VOC limited. On the other hand, local emissions were the dominant contributor during July 2009, and every source region showed a NOx-limited regime, which indicates that ozone concentrations in South Korea strongly depend on NOx emissions during this month.

Plant functional type (PFT) distributions affect the results of biogenic emission modeling as well as O3 and particulate matter (PM) simulations using chemistry-transport models (CTMs). This paper analyzes the variations of both surface biogenic volatile organic compound (BVOC) emissions and O3 concentrations due to changes in the PFT distributions in the Seoul Metropolitan Areas, Korea. The Fifth-Generation NCAR/Pennsylvania State Meso-scale Model (MM5)/the Model of Emissions of Gases and Aerosols from Nature (MEGAN)/the Sparse Matrix Operator Kernel Emissions (SMOKE)/the Community Multiscale Air Quality (CMAQ) model simulations were implemented over the Seoul Metropolitan Areas in Korea to predict surface O3 concentrations for the period of 1 May to 31 June 2008. Starting from a performance check of CTM predictions, we consecutively assessed the effects of PFT area deviations on the MEGAN BVOC and CTM O3 predictions, and we further considered the basis of geospatial and statistical analyses. The three PFT data sets considered were (1) the Korean PFT, developed with Korea-specific vegetation database; (2) the CDP PFT, adopted from the community data portal (CDP) of US National Center for Atmospheric Research in the United States (NCAR); (3) MODIS PFT, reclassified from the NASA Terra and Aqua combined land cover products. Although the CMAQ performance check reveals that all of the three different PFT data sets are applicable choices for regulatory modeling practice, noticeable primary data (i.e., PFT and Leaf Area Index (LAI)) was observed to be missing in many geographic locations. Based on the assessed effect of such missing data on CMAQ O3 predictions, we found that this missing data can cause spatially increased bias in CMAQ O3. Thus, it must be resolved in the near future to obtain more accurate biogenic emission and chemistry transport modeling results. Comparisons of MEGAN biogenic emission results with the three different PFT data showed that broadleaf trees (BTs) are the most significant contributor, followed by needleleaf trees (NTs), shrub (SB), and herbaceous plants (HBs) to the total BVOCs. In addition, isoprene from BTs and terpene from NTs were recognized as significant primary and secondary BVOC species in terms of BVOC emissions distributions and O3-forming potentials in the study domain. A geographically weighted regression analysis with locally compensated ridge (LCR-GWR) with the different PFT data (δO3 vs. δPFTs) suggests that addition of BT, SB, and NT areas can contribute to O3 increase, whereas addition of an HB area contributes to O3 decrease in the domain. Assessment results of the simulated spatial and temporal changes of O3 distributions with the different PFT scenarios reveal that hourly and local impacts from the different PFT distributions on occasional inter-deviations of O3 are quite noticeable, reaching up to 13 ppb. The simulated maximum 1 h O3 inter-deviations between different PFT scenarios have an asymmetric diurnal distribution pattern (low in the early morning, rising during the day, peaking at 05:00 p.m., and decreasing during the night) in the study domain. Exponentially diverging hourly BVOC emissions and O3 concentrations with increasing ambient temperature suggest that the use of different PFT distribution data requires much caution when modeling (or forecasting) O3 air quality in complicated urban atmospheric conditions in terms of whether uncertainties in O3 prediction results are expected to be mild or severe.

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.

The main aim of this paper is to examine ways to integrate urban climate information into urban planning using spatially distributed information. To achieve this, the structures of urban planning in the study area and their contents concerning climate issues were examined. Spatially distributed information on ventilation, air quality and thermal situation in the study area was generated using the CAMPUS framework, which is a set of climate analysis and evaluation tools suitable for planning purposes. Finally, urban planning strategies concerning ventilation, air quality and thermal situation were suggested, and planning measures for implementing the planning strategies were recommended. This study will contribute to a discussion on how urban climate information can be more efficiently considered in urban spatial planning. Furthermore, the information generated in this study can support the development of an evaluative framework for the integration of the climate information into the environmental assessment process, e.g. the implementation of strategic environmental assessment (SEA) in urban planning.

Current status and future direction of air quality modeling for monitoring and forecasting air quality in East Asia were discussed in this paper. An integrated air quality modeling system, combining (1) emission processing and modeling, (2) meteorological model simulation, (3) chemistry-transport model (CTM) simulation, (4) ground-based and satellite-retrieved observations, and (5) data assimilation, was introduced. Also, the strategies for future development of the integrated air quality modeling system in East Asia was discussed in this paper. In particular, it was emphasized that the successful use and development of the air quality modeling system should depend on the active applications of the data sets from incumbent and upcoming LEO/GEO (Low Earth Orbit/Geostationary Earth Orbit) satellites. This is particularly true, since Korea government successfully launched Geostationary Ocean Color Imager (GOCI) in June, 2010 and has another plan to launch Geostationary Environmental Monitoring Spectrometer (GEMS) in 2018, in order to monitor the air quality and emissions in/around the Korean peninsula as well as over East Asia.

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.

Air quality modeling is a useful methodology to investigate air quality degradation in various locations and to analyze effectiveness of emission reduction plans. A comprehensive air quality model usually requires a coordinated set of emissions input of all necessary chemical species. We have developed an anthropogenic emissions processing system for Asia in support of air quality modeling and analysis over Asia (named SMOKE-Asia). The SMOKE (Sparse Matrix Operator kernel Emissions) system, which was developed by U.S. EPA and has been maintained by the Carolina Environmental Program (CEP) of the University of North Carolina, was used to develop our emissions processing system. A merged version of INTEX 2006 and TRACE-P 2000 inventories was used as an initial Asian emissions inventory. The IDA (Inventory Data Analyzer) format was used to create SMOKE-ready emissions. Source Classification Codes (SCCs) and country/state/county (FIPS) code, which are the two key data fields of SMOKE IDA data structure, were created for Asia. The 38 SCCs and 2752 FIPS codes were allocated to our SMOKE-ready emissions for more comprehensive processing. US EPA’s MIMS (Multimedia Integrated Modeling System) Spatial Allocator software, along with many global and regional GIS shapes, were used to create spatial allocation profiles for Asia. Temporal allocation and chemical speciation profiles were partly regionalized using Asia-based studies. Initial data production using the developed SMOKE-Asia system was successfully performed. NOx and VOC emissions for the year 2009 were projected to be increased by 50% from those of 1997. The emission hotspots, such as large cities and large point sources, are distinguished in the domain due to spatial allocation. Regional emission peaks were distinguished due to temporally resolved emission information. The PAR (Paraffin carbon bond) and XYL (Xylene and other polyalkyl aromatics) showed the first and second largest emission rate among VOC species. Most of point source emissions are located in layers 3 to 4, which the altitude range reaches 310–550 m AGL. Qualitative inter-comparison between model output and ground/satellite measurement showed good agreements in terms of spatial and temporal patterns. We expect that the result of this study will provide better air quality modeling inputs, which will act as a major step to improve our understanding of Asian air quality.

We examine the effects of below-cloud scavenging on regional aerosol simulations over East Asia using wet deposition fluxes observed at Acid Deposition Monitoring Network in East Asia (EANET) sites and the Community Multiscale Air Quality (CMAQ) model together with a new below-cloud-scavenging scheme. Typical air quality models, including CMAQ, assume below-cloud scavenging as a simple first-order process with a constant or simple form depending on rain intensity. The scheme used here accounts for the collection efficiency, terminal velocity of raindrops, raindrop-size distributions, and particle-size distributions, which are important factors affecting below-cloud scavenging. We conduct model simulations for spring 2001, including baseline and sensitivity simulations. Our analysis mainly focuses on May 2001 to rule out the effect of dust aerosols. Simulated wet deposition fluxes of SO42−, NO3−, and NH4+ by the new scheme are increased by 103, 16, and 108%, respectively, relative to the baseline simulation and show better agreement with observations. The effect of below-cloud scavenging on coarse particles is even greater, producing wet deposition fluxes two orders of magnitude higher than the baseline. The resulting changes in the model indicate the considerable impacts of below-cloud scavenging on regional aerosol simulations over East Asia, where both anthropogenic emissions and natural sources of aerosols are present throughout the year. An accurate wet scavenging simulation is critical to simulate the atmospheric burden and wet deposition fluxes of both fine-mode and coarse-mode aerosols over East Asia.

South Korea has recently achieved developed country status with the second largest megacity in the world, the Seoul Metropolitan Area (SMA). This study provides insights into future changes in air quality for rapidly emerging megacities in the East Asian region. We present total OH reactivity observations in the SMA conducted at an urban Seoul site (May–June, 2015) and a suburban forest site (Sep, 2015). The total OH reactivity in an urban site during the daytime was observed at similar levels (∼15 s−1) to those previously reported from other East Asian megacity studies. Trace gas observations indicate that OH reactivity is largely accounted for by NOX (∼50%) followed by volatile organic compounds (VOCs) (∼35%). Isoprene accounts for a substantial fraction of OH reactivity among the comprehensive VOC observational dataset (25–47%). In general, observed total OH reactivity can be accounted for by the observed trace gas dataset. However, observed total OH reactivity in the suburban forest area cannot be largely accounted for (∼70%) by the trace gas measurements. The importance of biogenic VOC (BVOCs) emissions and oxidations used to evaluate the impacts of East Asian megacity outflows for the regional air quality and climate contexts are highlighted in this study.

AirScope is a micro-scale modeling system as well as a micro-scale air quality monitoring system, which comprises as a micro-scale air quality management system. Importance of micro-scale air monitoring is rising due to the concern about environment near residential places. Traditional monitoring methods are providing overall air quality indexes. However, these methods have limited functionalities to provide air quality of near my house or where I am now. In this paper, we are trying to overcome the limitation of traditional methods by using ubiquitous sensor network (USN). AirScope consists of computational fluid dynamics based air quality modeling, USN-based sensor monitoring, and multi-modal interaction platform. We present a brief overview of AirScope and several aspects of constructed initial indoor test environment with a few validity tests. The proposed system will be extended to an outdoor real-world testbed with most of modern urban elements. Copyright © 2011 John Wiley & Sons, Ltd.

Climate change has been predicted to adversely impact regional air quality with resulting health effects. Here a regional air quality model and a technology analysis tool are used to assess the additional emission reductions required and associated costs to offset impacts of climate change on air quality. Analysis is done for six regions and five major cities in the continental United States. Future climate is taken from a global climate model simulation for 2049-2051 using the Intergovernmental Panel on Climate Change (IPCC) A1B emission scenario, and emission inventories are the same as current ones to assess impacts of climate change alone on air quality and control expenses. On the basis of the IPCC A1B emission scenario and current control technologies, least-cost sets of emission reductions for simultaneously offsetting impacts of climate change on regionally averaged 4th highest daily maximum 8-hr average ozone and yearly averaged PM2.5 (particulate matter [PM] with an aerodynamic diameter less than 2.5 microm) for the six regions examined are predicted to range from $36 million (1999$) yr(-1) in the Southeast to $5.5 billion yr(-1) in the Northeast. However, control costs to offset climate-related pollutant increases in urban areas can be greater than the regional costs because of the locally exacerbated ozone levels. An annual cost of $4.1 billion is required for offsetting climate-induced air quality impairment in 2049-2051 in the five cities alone. Overall, an annual cost of $9.3 billion is estimated for offsetting climate change impacts on air quality for the six regions and five cities examined. Much of the additional expense is to reduce increased levels of ozone. Additional control costs for offsetting the impacts everywhere in the United States could be larger than the estimates in this study. This study shows that additional emission controls and associated costs for offsetting climate impacts could significantly increase currently estimated control requirements and should be considered in developing control strategies for achieving air quality targets in the future.

Several fine particle-related policies in Northeast United States were investigated in support of the execution of special measures to improve air quality of Seoul Metropolitan Area (SMA). The definition of particulate matter (PM) in the Clean Air Act (CAA), components and procedures of Regional Haze Rule (RHR), and Air Quality Management (AQM) were reviewed. Several State Implementation Plans (SIPs) were also reviewed as the way to attain required air quality under the Clean Air Act. attainment SIP of Maryland, 8-hr Ozone attainment SIP of New Jersey, and Regional Haze Rule attainment SIP of MANE-VU were analyzed in detail as case studies. We realized that "Special Measures for Air Quality Improvement in the Seoul Metropolitan Area" has many similarities with its US counterparts in terms of purpose, components, procedures, and implementation methods. US policies, however, have more advanced features, such as standardized procedures and methods, transparent guidelines, and stable relationship among federal/state/local governments and stakeholders, which would be helpful to improve air quality in SMA.

An assessment of how future climate change will impact regional air quality requires projecting emissions many decades into the future in a consistent manner. An approach that integrates the impact of both the current regulations and the longer-term national and global trends is developed to construct an emissions inventory (EI) for North America for the mid-century in support of a regional modeling study of ozone and particulate matter (PM) less than or equal to 2.5 microm (PM2.5). Because the time horizon of such a distant projection is beyond that of EIs used in typical modeling studies, it is necessary to identify a practical approach that allows the emission projections to account for emission controls and climatic and energy-use changes. However, a technical challenge arises because this requires integration of various different types of information with which emissions from human activities are associated. Often, emission information in global models has less detail and uses coarser spatiotemporal resolution. The method developed here is based on data availability, spatiotemporal coverage and resolution, and future-scenario consistency (i.e., Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios [IPCC SRES] A1B), and consists of two major steps: (1) near-future EI projection (to the year 2020), and (2) longer-term EI projection (to mid-century). The first step is based closely on the U.S. Environmental Protection Agency Clean Air Interstate Rule EI, the Environment Canada EI, as well estimates of Mexico's EI; whereas the second step follows approaches proposed by the EI from the Integrated Model to Assess the Global Environment (IMAGE), developed by Netherlands's National Institute for Public Health and the Environment (RIVM). For the United States, the year-2050 emissions for nitrogen oxides (NOx), sulfur dioxide (SO2), PM2.5, anthropogenic volatile organic compounds (VOCs), and ammonia are projected to change by -55, -55, -30, -40, and +20%, respectively, compared with 2001. NOx and SO2 emission changes are very similar in total amount but different in sectoral contribution. The projected emission trends for Canada and Mexico differ considerably. After taking into account the modeled climate changes, biogenic VOC emission increases from three countries overwhelm the decreases in anthropogenic VOC emissions, leading to a net small increase (approximately 2%) in overall VOC emissions.

Potential impacts of global climate and emissions changes on regional air quality over southern (western and eastern) Canada and northern Mexico are examined by comparing future summers' (i.e., 2049–2051) average regional O3 and PM2.5 concentrations with historic concentrations (i.e., 2000–2002 summers). Air quality modeling was conducted using CMAQ and meteorology downscaled from the GISS-GCM using MM5. Emissions for North America are found using US EPA, Mexican and Canadian inventories and projected emissions following CAIR and IPCC A1B emissions scenario. Higher temperatures for all sub-regions and regional changes in mixing height, insolation and precipitation are forecast in the 2049-2051 period. Future emissions are calculated to be lower over both Canadian sub-regions, but higher over northern Mexico. Global climate change, alone, is predicted to affect PM2.5 concentrations more than O3 for the projections used in this study: average daily maximum eight (8) hour O3 (M8hO3) concentrations are estimated to be slightly different in all examined sub-regions while average PM2.5 concentrations are estimated to be higher over both Canadian sub-regions (8% over western and 3% over eastern) but 11% lower over northern Mexico. More days are forecast where M8hO3 concentrations are over 75 ppb in all examined sub-regions but the number of days where PM2.5 concentration will be over 15 μg/m3 is projected higher only over western Canada. Climate change combined with the projected emissions lead to greater change in pollutant concentrations: average M8hO3 concentrations are simulated to be 6% lower over western Canada and 8% lower over eastern Canada while average PM2.5 concentrations are simulated to be 5% lower over western Canada and 11% lower over eastern Canada. Although future emissions over northern Mexico are projected higher, pollutant concentrations are simulated to be lower due to US emissions reductions. Global climate change combined with the projected emissions will decrease average M8hO3 4% and PM2.5 17% over northern Mexico. Significant reductions in the number of days where M8hO3 concentrations are over 75 ppb and PM2.5 concentration over 15 μg/m3 are also projected with a significant reduction in peak values.

A numerical simulation study to quantify the effect of upstream transport and fossil-fuel and biomass-burning emissions from East Asia on the surface ozone near Taiwan has been performed based on data taken April 8-13, 2001, when a cold air outbreak occurred. The TAQM (Taiwan Air Quality Model) is employed in this study. Results show that, without considering emissions in East Asia, upstream transport of chemical species associated with the movement of the cold air mass increased the levels of CO and ozone near Taiwan from 75 to 180ppbv, and 35 to 55ppbv, respectively. Fossil-fuel and biomass-burning emissions can thus result in a significant increase of CO and ozone levels (70-150% and 50-100%, respectively) from the emissionless background. The most noteworthy phenomenon is that biomass burning in Eastern China alone can contribute up to 20% of the increase for these species, while the biomass burning in Southeast Asia has negligible influence.

In this study, the accuracy of NH3 emissions in East Asia is evaluated by a comparison of measured and predicted NH4NO3 concentrations. For the prediction of particulate NH4NO3 concentrations, this study uses the USEPA Models-3/Community Multi-scale Air Quality (Models-3/CMAQ) model. The measurement data are collected from 4 ground-based stations (Beijing, Shanghai, Qingdao, and Kangwha) and ACE-ASIA C130 Flights #6, #7, and #10. The four ground-based stations and air flight tracks are located in and around the Yellow Sea in East Asia. According to the results, the predicted fine-mode NH4+concentrations are 1.2–3.8 times overestimated compared to those measured on the mass basis, and fine-mode NO3− concentrations are 1.9–7.6 times overestimated on the mass basis. It is also revealed in this study that aberrantly high predicted fine-mode NO3− concentrations in East Asia can be attributed to the overestimated NH3 emissions. The predicted gas-phase NH3 concentrations and estimated NH3 emissions are likely to be 1.2–3.8 times overestimated in East Asia on the mass basis. Therefore, it is recommended that approximately 20–75% reduced NH3 emission fields should be used in future modeling studies for East Asia.

An intercomparison study involving eight long-range transport models for sulfur deposition in East Asia has been initiated. The participating models included Eulerian and Lagrangian frameworks, with a wide variety of vertical resolutions and numerical approaches. Results from this study, in which models used common data sets for emissions, meteorology, and dry, wet and chemical conversion rates, are reported and discussed. Model results for sulfur dioxide and sulfate concentrations, wet deposition amounts, for the period January and May 1993, are compared with observed quantities at 18 surface sites in East Asia. At many sites the ensemble of models is found to have high skill in predicting observed quantities. At other sites all models show poor predictive capabilities. Source–receptor relationships estimated by the models are also compared. The models show a high degree of consistency in identifying the main source–receptor relationships, as well as in the relative contributions of wet/dry pathways for removal. But at some locations estimated deposition amounts can vary by a factor or 5. The influence of model structure and parameters on model performance is discussed. The main factors determining the deposition fields are the emissions and underlying meteorological fields. Model structure in terms of vertical resolution is found to be more important than the parameterizations used for chemical conversion and removal, as these processes are highly coupled and often work in compensating directions.

Monitoring air quality for daily life gets more and more attention Especially in modern urban environment with high skylines and unexpected pollution events, it is important to have micro-scale monitoring in addition to traditional monitoring methods We propose a micro-scale modeling system as well as a micro-scale air quality monitoring system, which comprises as a micro-scale air quality management system, named AirScope AirScope consists of CFD-based air quality modeling, USN-based sensor monitoring, and multi-modal interaction platform In this paper, we present a brief overview of AirScope and several aspects of constructed initial indoor test environment with a few validity tests The proposed system will be extended to an outdoor real-world testbed with most of modern urban elements.

This paper provides a synthesis of results that have emerged from recent modeling studies of the potential sensitivity of U.S. regional ozone (O3) concentrations to global climate change (ca. 2050). This research has been carried out under the auspices of an ongoing U.S. Environmental Protection Agency (EPA) assessment effort to increase scientific understanding of the multiple complex interactions among climate, emissions, atmospheric chemistry, and air quality. The ultimate goal is to enhance the ability of air quality managers to consider global change in their decisions through improved characterization of the potential effects of global change on air quality, including O3 The results discussed here are interim, representing the first phase of the EPA assessment. The aim in this first phase was to consider the effects of climate change alone on air quality, without accompanying changes in anthropogenic emissions of precursor pollutants. Across all of the modeling experiments carried out by the different groups, simulated global climate change causes increases of a few to several parts per billion (ppb) in summertime mean maximum daily 8-h average O3 concentrations over substantial regions of the country. The different modeling experiments in general do not, however, simulate the same regional patterns of change. These differences seem to result largely from variations in the simulated patterns of changes in key meteorological drivers, such as temperature and surface insolation. How isoprene nitrate chemistry is represented in the different modeling systems is an additional critical factor in the simulated O3 response to climate change.

Nowadays, air quality problems are getting more serious. Without having a good outdoor air quality, indoor air quality also could be a serious problem. The Seoul Metro of Korea always wants to reduce air pollution in the subway stations for people using subway as daily transportation. Fine particles (such as, PM10, PM2.5) are well known pollutants that can cause many diseases. In this paper we discuss framework design of the Integrated Air Quality Management System for Subway (IUMS) in support of subway stations' air quality improvement. By using this system the Metro subway office clerks can automatically monitoring and controlling the status of air quality in a subway station. To make this IT-based air quality system more efficient and realistic, PM10 mass and ion had been measured at the four subway stations in Seoul. The measurements were conducted in four different compartments in a station so that we can find sources and processes of particle pollution. From these joint effort of IT-ET, we are expecting to get cleaner-but-greener air quality management system.