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

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

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

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

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

KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean Peninsula during May-June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (24 May). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but overpredicted surface particulate matter concentrations in South Korea, especially PM[sub 2.5], often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low-resolution size bin representation (four bins) underestimates the efficiency with which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins (8-16 bins), it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve better consistency with measured values of the mass extinction efficiency (6.7 m²2 g-1 observed average) and light-scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth (2.2 observed average). Furthermore, an evaluation of the optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF- Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an underestimate of organic aerosol density (1.0 g cm-3 in the model vs. observed average of 1.5 g cm-3) and an overprediction of the fractional contribution of submicron inorganic aerosols other than sulfate, ammonium, nitrate, chloride, and sodium corresponding to mostly dust (17 %-28 % modeled vs. 12 % estimated from observations). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health impact assessments, climate projections, solar power forecasts, and aerosol data assimilation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Atmospheric nitrogen deposition in China has attracted huge public attention in recently years due to the increasing anthropogenic emission of reactive nitrogen (Nr) and its impacts on the terrestrial and aquatic ecosystems. However, limited long-term and multi-site measurements have restrained the understanding on the mechanism of the Nr deposition as well as the chemical transport model (CTM) improvement. In this study, the performance of the simulated wet and dry deposition for different Nr species, i.e., particulate NO3− and NH4+, gaseous NOx, HNO3 and NH3, have been conducted using the framework of Model Inter-Comparison Study for Asia (MICS-Asia) phase III. Nine Models, including 5 WRF-CAMQ models, 2 self-developed regional models, a global model and a RAMS-CMAQ model, have been selected for the comparison. For wet depositions, observation data from 83 measurement sites of EANET, CREN, CAUDN, NADMN and DEE of China have been collected and normalized to compare with model results. In general, most models showed the consistent spatial and temporal variation of both oxidized N (Nox) and reduced N (Nrd) wet depositions in China with the NME around at 50 %, which is lower than the value of 70 % based on EANET observation over Asia. Both the ratio of wet or dry deposition to the total inorganic N deposition (TIN) and the ratios of TIN to their emissions have shown the consistent results with the NNDMN estimations. The performance of ensemble results (ENM) was further assessed with the measurement from satellite. In different regions of China, the results showed that the simulated Nox wet deposition was overestimated in North East China (NE) but underestimated in south of China (SE+SW), while the Nrd wet deposition was underpredicted in all regions by all models. The deposition of Nox have large uncertainties than the Nrd especially in North China (NC), indicating chemical reaction process is one of the most importance factors that affecting the model performance. Compared to Critical load (CL) value, the Nr deposition in NC, SE and SW reached or exceeded the reported CL value and exerted serious ecological impacts. The control of Nrd in NC and SW and Nox in SE would be effective to mitigate the TIN deposition in these regions. More interestingly, the Nr deposition in Tibet plateau with the high ratio of TIN/emission (~3.0), indicating a significant import from outside should be focused in the future due to its climatical influence to the sensitive ecosystem in whole China. [ABSTRACT FROM AUTHOR]

KORUS-AQ was an international cooperative air quality field study in South Korea that measured local and remote sources of air pollution affecting the Korean peninsula during May-June 2016. Some of the largest aerosol mass concentrations were measured during a Chinese haze transport event (May 24th). Air quality forecasts using the WRF-Chem model with aerosol optical depth (AOD) data assimilation captured AOD during this pollution episode but over-predicted surface particulate matter concentrations, especially PM2.5 often by a factor of 2 or larger. Analysis revealed multiple sources of model deficiency related to the calculation of optical properties from aerosol mass that explain these discrepancies. Using in-situ observations of aerosol size and composition as inputs to the optical properties calculations showed that using a low resolution size bin representation under-estimates the efficiency at which aerosols scatter and absorb light (mass extinction efficiency). Besides using finer-resolution size bins, it was also necessary to increase the refractive indices and hygroscopicity of select aerosol species within the range of values reported in the literature to achieve consistency with measured values of mass/volume extinction efficiencies and light scattering enhancement factor (f(RH)) due to aerosol hygroscopic growth. Furthermore, evaluation of optical properties obtained using modeled aerosol properties revealed the inability of sectional and modal aerosol representations in WRF-Chem to properly reproduce the observed size distribution, with the models displaying a much wider accumulation mode. Other model deficiencies included an under-estimate of organic aerosol density and an over-prediction of the fractional contribution of inorganic aerosols other than sulfate, ammonium, nitrate, chloride and sodium (mostly dust). These results illustrate the complexity of achieving an accurate model representation of optical properties and provide potential solutions that are relevant to multiple disciplines and applications such as air quality forecasts, health-effect assessments, climate projections, solar-power forecasts, and aerosol data assimilation. [ABSTRACT FROM AUTHOR]

Topic 3 of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase III examines how online coupled air quality models perform in simulating high aerosol pollution in the North China Plain region during wintertime haze events and evaluates the importance of aerosol radiative and microphysical feedbacks. This paper discusses the estimates of aerosol radiative forcing, aerosol feedbacks, and possible causes for the differences among the models. Over the Beijing-Tianjin-Hebei (BTH) region, the ensemble mean of aerosol direct radiative forcing (ADRF) at the top of atmosphere, inside the atmosphere and at the surface are -1.9, 8.4 and -10.3 W/m2, respectively. Subdivisions of direct and indirect aerosol radiative forcing confirm the dominant roles of direct forcing. During severe haze days (January 17-19, 2010), the averaged reduction in near surface temperature for the BTH region can reach 0.3-3.0 °C. The responses of wind speeds at 10 m (WS10) inferred from different models show consistent declines in eastern China. For the BTH region, aerosol-radiation feedback induced changes in PM2.5 range from 6.0 to 8.8 μg/m3 (< 6.6 %). Sensitivity simulations indicate the most sensitive parameter for aerosol radiative forcing and feedback is the aerosol mixing state, and BC exhibits large contribution to atmospheric heating although it accounts for a small share of mass concentration of PM2.5. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Long-term ozone (O3) and nitric oxide (NOx) from fourteen state-of-the-art chemical transport models are evaluated and intercompared to ozone observations in East Asia, within the framework of the Model Inter-Comparison Study for ASIA phase III (MICS-ASIA III), designed to evaluate the capabilities and uncertainties of current chemical transport models (CTMs) simulations in Asia and provide multi-model estimates of pollution distributions. These models were run by fourteen independent groups in China, Japan, Korea, United States of America and other countries/regions. Compared with MICS-ASIAII, the evaluation against observations were extended to be one-full year in China and the western Pacific Rim from four months and the western Pacific Rim. Potential causes of the discrepancies between model results and observation have also been investigated by assessing the PBL heights, emission fluxes, dry deposition, O3-NOx relationships and vertical profiles among models in this study. In general, the model skills for O3 varied largely with region and seasons. Most models captured the key pattern of monthly and diurnal surface O3 and its precursors in North China Plain, Yangtze River Delta and western Pacific rim, but failed in Peral River Delta of China. A significant overestimation of surface ozone was found in May-September/October and January-May over North China Plain, western Pacific rim and Peral River Delta of China, respectively. A large intermodel variability of O3 existed in all subregions over East Asia in this study, which was caused by the internal parameterizations of chemistry, dry deposition and vertical mixing of models, even though the native schemes in models are similar. Ensemble average of 13 models on O3 did not always exhibit a superior performance compared to certain individual model, in contrast to its superiority in Europe. This suggested that the spread of ensemble-model values hadn't represented all uncertainties of ozone or most models in MICS-ASIAIII missed key processes. Compared with the previous phase of MICS-ASIA(MICS-ASIAII, this study improved the performance of ozone in March at Japan sites. But it predicted too enhanced surface O3 concentrations at western Japan in July, which has not been found in MICS-ASIAII. Major challenges still remain with regards to recognizing the sources of bias in surface O3 over East Asia in CTMs. [ABSTRACT FROM AUTHOR]

In this work, we investigate the NOx emissions inventory in Seoul, South Korea using a regional NASA Ozone Monitoring Instrument (OMI) NO2 product. We first develop a regional OMI NO2 product by re-calculating the air mass factors using a high-resolution (4×4km2) WRF-Chem model simulation, which better captures the NO2 shape profiles in urban regions. We then apply a model-derived spatial averaging kernel to further downscale the retrieval and account for the sub-pixel variability. These two modifications yield OMI NO2 values in the regional product that are 1.37 larger in the Seoul metropolitan region and >2 times larger near large industrial sources. These two modifications also yield an OMI NO2 product that is in better agreement with the Pandora NO2 spectrometer measurements acquired during the Korea U.S.-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 emission inventory yields a NOx emission rate of 227±94kton/yr, while the bottom-up inventory itself yields a NOx emission rate of 198kton/yr. Using the top-down approach on the regional OM NO2 product, we derive the NOx emissions rate from Seoul to be 484±201kton/yr, and a 353±146kton/yr NOx emissions rate using the standard NASA OMI NO2 product. This suggests an underestimate of 53% and 36% using the regional and standard NASA OMI NO2 products respectively. To supplement this finding, we compare the NO2 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 doubled, there is better agreement with KORUS-AQ aircraft observations. 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 emission estimates. [ABSTRACT FROM AUTHOR]

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 plus two higher resolution forecasts (16-km 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-km and 9-km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the16-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 show a remarkable agreement with observed enhancement ratios of CO with CO2 over Seoul metropolitan and over the West Sea, where East Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (delta(CO)/delta(CO2) = 9 ppbv/ppmv) compared to the West Sea (delta(CO)/delta(CO2) = 28 ppbv/ppmv). 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, West Sea: ~30 ppbv/ppmv) 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, 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 for CO2 and 3.5 ppbv/hPa for CO) in the morning samples than observed (~0.25 ppmv/hPa for CO2 and 1.7 ppbv/hPa 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 produce better forecasts. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]