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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 accuracy 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%, 17%, 49%, and 19% in the predictability of PM2.5 over South Korea in terms of IOA (index of agreement), R (correlation coefficient), MB (mean biases), and HR (hit rate), respectively, compared to PM2.5 prediction systems using only LEO satellite-derived observations.

Coarse particulate matter (PM) is a serious air pollution problem in East Asia. Analysis of air quality network observations in the North China Plain and the Seoul Metropolitan Area shows that it is mainly anthropogenic and has decreased by 21% over 2015-2019. This anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate (PM2.5) nitrate, a major contributor to PM2.5 pollution. Including it in the GEOS-Chem model decreases simulated PM2.5 nitrate to improve agreement with observations. Decreasing anthropogenic coarse PM over 2015-2019 directly increases PM2.5 nitrate in summer, offsetting the effect of other emission controls, while in winter it increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Our work implies the need for stronger ammonia and nitrogen oxides emission controls to improve PM2.5 air quality as coarse PM continues to decrease., We have revised this work considerably and want to avoid the confusion

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.

With the increasing importance of monitoring and verifying urban CO2 concentrations to mitigate carbon emissions from cities, a high-resolution ground networks of low-cost CO2 sensors are emerging that have a price advantage over existing high-cost sensors. This study develops a low-cost CO2 instrument called the Seoul National University CO2 Measurement (SNUCO2M) to monitor and analyze intra-city CO2 concentrations over Seoul, Korea. The first step of establishing this low-cost CO2 sensor network involved installing the SNUCO2M at the Yongsan Building (YSB; 113 m MASL) and Namsan Seoul Tower-High (NSTH; 385 m MASL) on October 18, 2018 and July 8, 2019, respectively. For comparison with the SNUCO2M, we utilized CO2 concentrations measured by the Picarro instrument (high-cost CO2 sensor) at Gwanak Mountain (GWA) background measurement site and the lower part of the NST (NSTL). The initial CO2 measurements from the SNUCO2M, show that 1) the SNUCO2M has a 0.71% maximum error range and is sufficient to measure urban atmospheric CO2 concentrations; and 2) the SNUCO2M captures 26.92 and 20.30 ppm of Seoul’s summer and winter time CO2 enhancement compared to the GWA background site. Our results suggest that the low-cost sensors such as SNUCO2M successfully detect urban CO2 characteristics over the megacity and has great potential to replace high-cost sensors with cost and management limitations.

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).

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.

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. In the surface level, the model underestimates campaign average sulfate aerosol by −64 % but overestimates nitrate aerosol by 36 %. The largest underestimate in sulfate occurs during the pollution event in conditions of high relative humidity, where models typically struggle to generate the high concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally-produced sulfate increased from 1 % to 46 % of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.

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.

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.

We use the CAMx (Comprehensive Air Quality Model with Extensions) chemical transport model (CTM) with 4-km horizontal resolution over the Korean Peninsula to investigate source contributions to PM2.5 in Korea from domestic and upwind sources. We modeled 2015 and 2016 to account for meteorological variation with Korean emissions from the Clean Air Policy Supporting System (CAPSS), meteorology from WRF (Weather, Research, and Forecasting) model, and regional boundary concentrations from the GEOS-Chem global CTM. The CAMx particulate source apportionment technology (PSAT) provided PM2.5 source contributions from 5 source sectors and 6 geographic regions within Korea, international sources, and boundary concentrations. PM2.5 contributions from outside Korea are important with boundary concentrations plus the “other” emissions sector (includes marine shipping, agricultural ammonia, and international emissions from North Korea and Japan within the CAMx domain) contributing 67% of annual average PM2.5 in Seoul in 2016 and 71% in 2015. The boundary concentrations contributed between 30% and 50% of PM2.5 at different Korean cities with contributions generally lower in 2016 than in 2015. For Korean sources, PM2.5 contributions from Electric Generating Unit (EGU) emissions were smaller than contributions from mobile and industrial emissions sources although there is considerable day-to-day variation in contributions. On an annual basis in 2016, the “other” category contributed 25% followed by mobile sources at 23%, industrial sources at 6%, and EGU sources at 3%. For 2015, the contributions were similar. Focusing on March when PM2.5 concentrations were higher than other months, the contributions from other, mobile, industrial, and EGUs were 21%, 18%, 4%, and 4%, respectively in 2016. For 2015, contributions from these four categories were 18%, 15%, 3%, and 3%, respectively.

The emission of pollution from Chinese point sources, and its migration to Korea, downwind of China, is an important issue in terms of Korean air quality management. Therefore, this study intended to improve the Asian Emission Inventory, NIER/KU-CREATE, by improving information about the point source emissions, their location, and discharge conditions, in China. By using the Global dataset, we can establish point source location information for Coal Power Plants and Non-Coal Power Plants in the Chinese power sector, and calculate and allocate emissions in the inventory. In addition, the emission inventory of NH3, as a by-product of NOx abatement processing, was regarded as being insufficiently characterized in the previous emission inventory, and has been re-estimated. As a result, 3798 LPSs in China were identified, and NH3 emissions from those power plants have increased significantly. In addition, the vertical distribution of emissions through the allocation stack height parameters showed atmospheric injection heights of between 250 m and 1000 m. Using this information, HY-SPLIT trajectory modeling found that during periods of active westerly from China to Korea, emissions from the higher injection height were more prone to move towards Korea, than those from the lower height.

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.

Nonmethane volatile organic compounds (NMVOCs) result in ozone and aerosol production that adversely affects the environment and human health. For modeling purposes, anthropogenic NMVOC emissions have been typically compiled using the “bottom-up” approach. To minimize uncertainties of the bottom-up emission inventory, “top-down” NMVOC emissions can be estimated using formaldehyde (HCHO) observations. In this study, HCHO vertical column densities (VCDs) obtained from the Geostationary Trace gas and Aerosol Sensor Optimization spectrometer during the Korea–United States Air Quality campaign were used to constrain anthropogenic volatile organic compound (AVOC) emissions in South Korea. Estimated top-down AVOC emissions differed from those of the up-to-date bottom-up inventory over major anthropogenic source regions by factors of 1.0 ± 0.4 to 6.9 ± 3.9. Our evaluation using a 3D chemical transport model indicates that simulated HCHO mixing ratios using the top-down estimates were in better agreement with observations onboard the DC-8 aircraft during the campaign relative to those with the bottom-up emission, showing a decrease in model bias from –25% to –13%. The top-down analysis used in this study, however, has some limitations related to the use of HCHO yields, background HCHO columns, and AVOC speciation in the bottom-up inventory, resulting in uncertainties in the AVOC emission estimates. Our attempt to constrain diurnal variations of the AVOC emissions using the aircraft HCHO VCDs was compromised by infrequent aircraft observations over the same source regions. These limitations can be overcome with geostationary satellite observations by providing hourly HCHO VCDs.

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.

Substantial mitigation of air pollutants emissions has been performed since 2013 around Beijing, and changes in the atmospheric characteristics have been expected over the downstream area of Beijing. In this study, both WRF-Chem simulation and on-site measurements were utilized for the Baengnyeong (island) supersite, one of the representative regional background sites located in the Yellow Sea, the entrance area of the long-range transport process in Korea. The changes in the chemical compositions of inorganic aerosols were examined for spring-time during the Chinese emission mitigation period from 2014 to 2016. The measured ratio of ionic species to PM2.5 at the Baengnyeong supersite showed changes in aerosol inorganic chemical compositions from sulfate in 2014 to nitrate in 2015–2016. The modeling results also showed that nitrate was low in 2014 and significantly increased in 2015 and 2016, and the acidic aerosol condition had also changed toward a more neutralized status in both the simulation and the observations. The WRF-Chem modeling study further indicated that the sulfur was not neutralized in 2014. However, in 2015 and 2016, SO2 was more sufficiently neutralized as sulfur emissions were substantially reduced in China, while at the same time nitrate had begun to increase in such a ‘SO2–poor’ condition in Beijing area in China, and thus approaching more enhanced neutralization over the Yellow Sea area. The causes of the higher nitrate based on the modeled characteristics of the ammonia-sulfate-nitrate aerosol formation in response to the SO2 emissions reduction in China are also discussed in this paper.

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.

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&ndash, 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.

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.

Understanding how ozone (O3) and fine particulate matter (PM) formation respond to the precursor concentrations in the presence of biogenic emissions (BEs) and thereby changes in health effects can be a key step to design effective air quality management plans. This is particularly true in the Seoul Metropolitan Area (SMA), where future significant controls of anthropogenic sources of O3 and PM2.5 precursors are expected. In this paper, we investigate the effects of BEs on O3 and fine PM (PM2.5) concentrations during a strong photochemical air pollution season in the SMA in Korea. O3 and PM2.5 levels are modeled with and without BEs in June 2008. Further, we perform the health impact assessments (HIA) of O3 and PM2.5 concentration changes due to BEs to seek useful implications for air quality management by utilizing the adjusted exposure concentration fields for O3 and PM2.5 with an observation fusing (OBF) method. With BEs, daily maximum 8-h average O3 (maximum 8-h O3) and secondary organic aerosol (SOA) concentrations in the SMA increase by 17 and 474%, respectively. These increments are associated with significant consumption of photochemical oxidants (Ox), such as a ~ 60% reduction in OH∙ radicals. The reduction in Ox, conversely, lowers the production of secondary inorganic aerosols (SIOAs) by 2.7%. Adjusted O3 and PM2.5 exposure metrics and the subsequent HIA reveal that large mean increments of O3, about 8.43 ppb, due to BEs are responsible for approximately 62 all-cause premature mortalities in the SMA in June. However, mean increment of PM2.5 due to BEs is approximately 0.3 μg m−3 and results in negligible impacts on the all-cause mortality. Significant correlations of O3 and mortality rates (MR) with the VOC/NOx ratios across the SMA suggest that controlling volatile organic compounds (VOCs) from anthropogenic sources can be a priority to reduce O3 levels and population health risks in the SMA. Specifically, linear relationships of log [O3] and log [MR] to log [VOC/NOx] ensure that a 10% decrease in the VOC/NOx ratios through the VOC abatements would lead to a 1.5% decrease in the O3 levels and a 4.3% decrease in the MR on average across the SMA.

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.

Recent regulatory policies in East Asia reduce ozone precursors, but these changes are spatially and temporally nonuniform. This study investigates variations in the long-term trends of tropospheric NO2, HCHO, and HCHO/NO2 ratios to diagnose ozone sensitivity to changes in NOx and volatile organic compound using the Ozone Monitoring Instrument (OMI). Using an adaptive-degree polynomial filter, we identify extremums of time series of NO2 to determine when and how NO2 change. Due to the regulations in China, trends which were predominantly upward turned downward. The years undergoing these changes primarily happened in 2011 and 2012. OMI column densities, however, suggest that NOx sources in South Korea, the Pearl River Delta (PRD), Taiwan, and Japan have not consistently decreased. Specifically, as Chinese exports of NO2 started subsiding, increasing trends in NO2 columns over several Korean cities, including Seoul, become evident. To quantify the changes in NOx emissions from summertime 2010 to 2014, we conduct a 3D-Var inverse modeling using a regional model with MIX-Asia inventory and estimate NOx emissions (in 2010 and 2014) for the PRD (1.6 and 1.5 Gg/d), the Yangtze River Delta (3.9 and 3.0 Gg/d), north China (15.6 and 14.3 Gg/d), South Korea (1.6 and 1.5 Gg/d), and Japan (2.7 and 2.6 Gg/d). OMI HCHO shows upward trends in East Asia resulting from anthropogenic effects; however, the magnitudes are negative in the PRD, Japan, North Korea, and Taiwan. OMI HCHO/NO2 ratios reveal that while South Korea, Japan, and the south of China have undergone toward more NOx-sensitive regime, areas around the Bohai Sea have become more NOx saturated.

The MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO2, 52.1 Tg NOx, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH3, 31.7 Tg PM10, 22.7 Tg PM2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO2. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: −8.1 % for SO2, +19.2 % for NOx, +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH3, −3.4 % for PM10, −1.6 % for PM2.5, +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO2. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25° × 0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.

Author(s): Tang, Wenfu; Emmons, Louisa K; Jr, Arellano Avelino F; Gaubert, Benjamin; Knote, Christoph; Tilmes, Simone; Buchholz, Rebecca R; Pfister, Gabriele G; Diskin, Glenn S; Blake, Donald R; Blake, Nicola J; Meinardi, Simone; DiGangi, Joshua P; Choi, Yonghoon; Woo, Jung-Hun; He, Cenlin; Schroeder, Jason R; Suh, Inseon; Lee, Hyo-Jung; Jo, Hyun-Young; Kanaya, Yugo; Jung, Jinsang; Lee, Youngjae; Kim, Danbi

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.

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.

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.

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.

Significant differences were found between two particulate sulfate size-distributions measured using a MOUDI impactor at Gosan, Jeju Island, Korea, and simulated via the Lagrangian photochemical model under a condition of aerosol internal mixing between mineral dust and urban pollution particles. It was suspected that these differences might have resulted from: (1) the assumption of aerosol internal mixing and (2) the uses of identical reaction probabilities (γ) of the gaseous sulfate precursors (SO2 and H2SO4) onto both urban pollution particles and mineral dust in the Lagrangian photochemical model simulations. In this study; therefore, some cases of aerosol external mixing between urban-derived pollution aerosols and mineral dust were investigated, with different magnitudes of γ for the gas-phase sulfate precursors onto the two different condensing media. The model simulations under the external mixing condition, with different magnitudes of the reaction probabilities (γi,urban and γi,dust) onto urban pollution particles and mineral dust, successfully reproduced the size-dependent particulate sulfate formation measured at the Gosan station. Further attempts were made to approximate the magnitudes of γSO2,urban and γH2SO4,dust under external mixing state conditions with the fixed γSO2,dust and γH2SO2,urban values of 10−4 and 1.0. The best-estimates of γSO2,urban and γH2SO4,dust found in this study were in the orders of 10−4–10−5 and 10−2–10−3, respectively.

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.

We examine the meteorological responses due to the probable eruption of Mt. Baekdu using an off-line Climate-Chemistry model that is composed of the National Center for Atmospheric Research (NCAR) Climate Atmosphere Model version 3 (CAM3) and a global chemistry transport model (GEOS-Chem). Using the aerosol dataset from the GEOS-Chem driven by GEOS-5 meteorology, experiment and control simulations of the climate model are performed and their meteorological differences between the two simulations are analyzed. The magnitudes of volcanic eruption and column injection height were presumably set to 1/200 of the Mt. Pinatubo eruption and 9 km, respectively. Significant temperature drop in the lower troposphere (850 hPa), which is mainly due to a direct effect of prescribed volcanic aerosols from Mt. Baekdu, has been simulated up to about −4 K. The upper atmosphere (150 hPa) right above the volcano, however, shows significant warming due to the absorption of the infrared radiation by volcanic aerosols. As a result of the volcanic eruption in the climate model, wave-like patterns are shown in both the geopotential height and horizontal wind. The changes in the lower atmospheric temperature are well associated with the modification of the atmospheric circulation through the hydrostatic balance. In spite of limitations in our current simulations due to several underlying assumptions, our results could give a clue to understanding the meteorological impacts from Mt. Baekdu eruptions that are currently attracting considerable public attention.

We examine the impacts of aerosols on regional meteorology due to intense Siberian forest fires occurred in May 2003 using both reanalysis data and global model simulations. Our analysis of the NCEP-DOE reanalysis data shows 99% statistical significant changes in meteorological variables over East Asia in May 2003 relative to the 30 years climatology. In particular a significant surface cooling was observed up to −3.5 K over Siberia and extended to the North Pacific region with the surface pressure increases up to 5.6 hPa. Whereas, smoke aerosols affected the large-scale circulations and resulted in the increases in rainfall rates of 2.9 mm day −1 averaged over the NW Pacific (10–35°N, 130–170°E). We use the climate model simulations with and without biomass burning emissions over Siberia to examine the effects of smoke aerosols on the regional meteorology. The simulated results show consistent changes in meteorological variables including surface temperature, surface pressure and precipitation rates with the observations over East Asia and the NW Pacific, which support that the observed changes are likely due to smoke aerosols from the Siberian forest fires. The implication is that smoke aerosols from the forest fires should be properly considered to correctly simulate both regional climate and synoptic scale weather patterns.

We estimated the source contributions to carbonaceous aerosol concentration in Korea on the basis of Intercontinental Chemical Transport Experiment Phase B (INTEX-B) anthropogenic emissions and satellite-derived biomass burning emissions by using a nested version of GEOS-Chem with a spatial resolution of 0.5 � � 0.667 � for the period March 2006eFebruary 2007. First, we evaluated the model by comparing the simulated and observed aerosol concentrations at East Asia Network (EANET) sites and at a site in Korea. The results indicate that the model reproduces the variability and magnitudes of the observed SO4 2� ,N O 3 � , and NH 4 þ concentrations in Korea and those of the observed PM 10 concentrations in East Asia. However, the organic carbon (OC) and black carbon (BC) aerosol concentrations estimated by the model are lower than those observed in Korea by a factor of 2, especially in winter. This underestimation is likely due to extremely low domestic anthropogenic emissions and lack in seasonal variation. Source adjustments using a simple fitting and the Emission Database for Global Atmospheric Research (EDGAR) monthly allocation factors for seasonal variation yield significantly improved model results (R 2

Elevated levels of formaldehyde (HCHO) along the ship corridors have been observed by satellite sensors, such as ESA/ERS-2 GOME (Global Ozone Monitoring Experiment), and were also simulated by global 3-D chemistry-transport models. In this study, three likely sources of the elevated HCHO levels in the ship plumes as well as their contributions to the elevated HCHO levels (budget) were investigated using a newly-developed ship-plume photochemical/dynamic model: (1) primary HCHO emission from ships; (2) secondary HCHO production via the atmospheric oxidation of non-methane volatile organic compounds (NMVOCs) emitted from ships; and (3) atmospheric oxidation of CH4 within the ship plumes. For this ship-plume modelling study, the ITCT 2K2 (Intercontinental Transport and Chemical Transformation 2002) ship-plume experiment, which was carried out about 100 km off the coast of California on 8 May 2002 (11:00 local standard time), was chosen as a base study case because it is the best defined in terms of (1) meteorological data, (2) in-plume chemical composition, and (3) background chemical composition. From multiple ship-plume model simulations for the ITCT 2K2 ship-plume experiment case, CH4 oxidation by elevated levels of in-plume OH radicals was found to be the main factor responsible for the elevated levels of HCHO in the ITCT 2K2 ship-plume. More than ~88% of the HCHO for the ITCT 2K2 ship-plume is produced by this atmospheric chemical process, except in the areas close to the ship stacks where the main source of the elevated HCHO levels would be primary HCHO from the ships (due to the deactivation of CH4 oxidation from the depletion of in-plume OH radicals). Because of active CH4 oxidation by OH radicals, the instantaneous chemical lifetime of CH4 (τCH4) decreased to ~0.45 yr inside the ship plume, which is in contrast to τCH4 of ~1.1 yr in the background (up to ~41% decrease) for the ITCT 2K2 ship-plume case. A variety of likely ship-plume situations at three different latitudinal locations within the global ship corridors was also studied to determine the enhancements in the HCHO levels in the marine boundary layer (MBL) influenced by ship emissions. It was found that the ship-plume HCHO levels could be 19.9–424.9 pptv higher than the background HCHO levels depending on the latitudinal locations of the ship plumes (i.e., intensity of solar radiation and temperature), MBL stability and NOx emission rates. On the other hand, NMVOC emissions from ships were not found to be a primary source of photochemical HCHO production inside ship plumes due to their rapid and individual dilution. However, the diluted NMVOCs would contribute to the HCHO productions in the background air.

Household fuel use in developing countries, particularly as biomass and coal, is a major source of carbonaceous aerosols and other air pollutants affecting health and climate. Using state-of-the-art emission inventories, a global three-dimensional photochemical tracer/transport model of the troposphere, and a global radiative transfer model based on methods presented in the latest IPCC Assessment Report (2007-AR4), we estimate the radiative forcing (RF) attributable to household fuel combustion in Asia in terms of current global annual-mean RF and future global integrated RF for a one-year pulse of emissions (2000) over two time horizons (100 and 20 years). Despite the significant emissions of black carbon (BC) aerosols, these estimates indicate that shorter-lived (non-Kyoto) air pollutants from household fuel use in the region overall seem to exert a small net negative RF because of the strong influence of reflective aerosols. There are, however, major uncertainties in emission estimates for solid fuel burning, and about the sustainability of household fuel wood harvesting in Asia (the carbon neutrality of harvesting). In addition, there is still substantial uncertainty associated with the BC radiative forcing. As a result we find that the sign of the RF from household biomass burning in the region cannot be established. While recognizing the value of integrating climate change and air pollution policies, we are concerned that for a ‘Kyoto style’ post-Kyoto treaty (with global cap-and-trade and the Global Warming Potential as the metric) expanding the basket of components with a selection of short-lived species without also including the wider range of co-emitted species may lead to unintended consequences for global-scale climate. Additional measurement, modelling, and policy research is urgently needed to reduce the uncertainties so that the net impact on climate of emissions and mitigation measures in this sector can be accurately assessed.

In this study, background concentration sites of Deokjeok and Gosan, which were deemed suitable for monitoring the impact of long-range transported air pollutants, were selected. An investigation of the source types of pollutants, their locations, and relative quantitative contributions to the particulate concentrations at both sites using appropriate methodologies to make initial estimations was conducted. Episodic measurements of PM2.5, PM10, and size distribution, along with its ion and carbon components were performed from 2005 to 2007, and a comprehensive analysis of the results was conducted utilizing back trajectory analysis. As for frequency of wind direction, it was quite apparent that the two sites are heavily influenced by air masses originating from the eastern and northern regions of China. For PM2.5 and PM10, the mass concentrations from north and east China were higher than other cases, originating from the ocean. In the northerly-wind case, meteorological properties for Deokjeok and Gosan and the influence of carbon emissions from northwest Korea resulted in a changing of air mass properties during transport. As was the case with mass concentration, the highest contribution for ionic and carbon components of PM2.5 and PM10 for both sites appeared for the westerly wind case. A specially high relative contribution, greater than 1.4 times, was apparent in the secondary aerosol case because of a large influence of long-range transported pollutants from east China. Carbon components exhibited different behaviors for the northerly and westerly wind cases compared with secondary aerosol. The major reason for this discrepancy appears to be the carbon emissions from northwest Korea.

In this study, NO2 columns from the US EPA Models-3/CMAQ model simulations carried out using the 2001 ACE-ASIA (Asia Pacific Regional Aerosol Characterization Experiment) emission inventory over East Asia were compared with the GOME-derived NO2 columns. There were large discrepancies between the CMAQ-predicted and GOME-derived NO2 columns in the fall and winter seasons. In particular, while the CMAQ-predicted NO2 columns produced larger values than the GOME-derived NO2 columns over South Korea for all four seasons, the CMAQ-predicted NO2 columns produced smaller values than the GOME-derived NO2 columns over North China for all seasons with the exception of summer (summer anomaly). It is believed that there might be some error in the NOx emission estimates as well as uncertainty in the NOx chemical loss rates over North China and South Korea. Regarding the latter, this study further focused on the biogenic VOC (BVOC) emissions that were strongly coupled with NOx chemistry during summer in East Asia. This study also investigated whether the CMAQ-modeled NO2/NOx ratios with the possibly overestimated isoprene emissions were higher than those with reduced isoprene emissions. Although changes in both the NOx chemical loss rates and NO2/NOx ratios from CMAQ-modeling with the different isoprene emissions affected the CMAQ-modeled NO2 levels, the effects were found to be limited, mainly due to the low absolute levels of NO2 in summer. Seasonal variations of the NOx emission fluxes over East Asia were further investigated by a set of sensitivity runs of the CMAQ model. Although the results still exhibited the summer anomaly possibly due to the uncertainties in both NOx-related chemistry in the CMAQ model and the GOME measurements, it is believed that consideration of both the seasonal variations in NOx emissions and the correct BVOC emissions in East Asia are critical. Overall, it is estimated that the NOx emissions are underestimated by ~57.3% in North China and overestimated by ~46.1% in South Korea over an entire year. In order to confirm the uncertainty in NOx emissions, the NOx emissions over South Korea and China were further investigated using the ACE-ASIA, REAS (Regional Emission inventory in ASia), and CAPSS (Clean Air Policy Support System) emission inventories. The comparison between the CMAQ-calculated and GOME-derived NO2 columns indicated that both the ACE-ASIA and REAS inventories have some uncertainty in NOx emissions over North China and South Korea, which can also lead to some errors in modeling the formation of ozone and secondary aerosols in South Korea and North China.