Improvement China Point Source for Improving Bottom-Up Emission Inventory

Jang, Yuyeon; Lee, Yungu; Kim, Jinseok; Kim, Youn H.; Woo, Jung‐Hun

doi:10.1007/s13143-019-00115-y

Cited by 33 publications

(25 citation statements)

References 13 publications

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“…The meteorology-chemistry interface processor (MCIP) [48] v3.6 and sparse matrix operator kernel emission (SMOKE) are used as a preprocessor and as an emission processing model, respectively. The AERO5 module and statewide air pollution research center version 99 (SAPRC99) [49] are used as the aerosol module and chemical mechanism, based on anthropogenic emissions, from CREATE 2015 (Asia) and [50] CAPSS 2016 (South Korea) [41], and biogenic emissions (Model of Emissions of Gases and Aerosols from Nature; MEGAN) [51]. Natural emissions from dust and fire are not included in the simulations due to their high uncertainty.…”

Section: Modelmentioning

confidence: 99%

Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory

Kim

Lee

et al. 2020

Atmosphere

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Fine-scale nitrogen oxide (NOx) concentrations over South Korea are examined using surface observations, satellite data and high-resolution model simulations based on the latest emission inventory. While accurate information on NOx emissions in South Korea is crucial to understanding regional air quality in the region, consensus on the validation of NOx emissions is lacking. We investigate the spatial and temporal variation in fine-scale NOx emission sources over South Korea. Surface observations and newly available fine-scale satellite data (TROPOspheric Monitoring Instrument; TROPOMI; 3.5 × 7 km2) are compared with the community multiscale air quality (CMAQ) model based on the clean air policy support system (CAPSS) 2016 emission inventory. The results show that the TROPOMI NO2 column densities agree well with the CMAQ simulations based on CAPSS emissions (e.g., R = 0.96 for June 2018). The surface observations, satellite data and model are consistent in terms of their spatial distribution, the overestimation over the Seoul Metropolitan Area and major point sources; however, the model tends to underestimate the surface concentrations during the cold season.

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Section: Modelmentioning

confidence: 99%

Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory

Kim

Lee

et al. 2020

Atmosphere

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“…We use anthropogenic emissions of CO, NO x , SO 2 , NH 3 , and VOCs for East Asia from the KORUS v2.0 inventory, developed by Konkuk University (Jang et al, 2019), who updated the inventory from its' previous version, using detailed regional segregation, GIS data, and 2015 control policies for Korea. Monthly emissions for South Korea were estimated by projecting the 2012 Korean national emissions inventory (Clean Air Policy Support System) with 3-year growth factors.…”

Section: Geos-chem Chemical Transport Modelmentioning

confidence: 99%

Evaluation of simulated O3 production efficiency during the KORUS-AQ campaign: Implications for anthropogenic NOx emissions in Korea

Oak

Park

Schroeder

et al. 2019

Elementa: Science of the Anthropocene

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We examine O 3 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 O 3 production. To examine the role of VOCs and NO x in O 3 chemistry, we first implement a detailed aromatic chemistry scheme in the model, which reduces the normalized mean bias of simulated O 3 mixing ratios from-26% to-13%. Aromatic chemistry also increases the average net O 3 production in Korea by 37%. Corrections of daytime PBL heights, which are overestimated in the model compared to lidar observations, increase the net O 3 production rate by ~10%. In addition, increasing NO x emissions by 50% in the model shows best performance in reproducing O 3 production characteristics, which implies that NO x emissions are underestimated in the current emissions inventory. Sensitivity tests show that a 30% decrease in anthropogenic NO x emissions in Korea increases the O 3 production efficiency throughout the country, making rural regions ~2 times more efficient in producing O 3 per NO x consumed. Simulated O 3 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 NO x and VOCs emissions by 30%, O 3 decreases in most of the country, including the SMA. This implies the importance of concurrent emission reductions for both NO x and VOCs in order to effectively reduce O 3 levels in Korea.

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“…This CREATE-2015 anthropogenic emission dataset was also used for the KORUS-AQ campaign period to predict aircraft DC-8 pathways. Detailed explanations were found in previous studies [3,[45][46][47]. It is worthwhile to note that the WRF-Chem model can calculate the biogenic emissions at each time step during the model integration ("on-line").…”

Section: Emissionmentioning

confidence: 95%

Sensitivity of Simulated PM2.5 Concentrations over Northeast Asia to Different Secondary Organic Aerosol Modules during the KORUS-AQ Campaign

Lee

Song

et al. 2020

Atmosphere

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A numerical sensitivity study on secondary organic aerosol formation has been carried out by employing the WRF-Chem (Weather Research and Forecasting model coupled with Chemistry). Two secondary organic aerosol formation modules, the Modal Aerosol Dynamics model for Europe/Volatility Basis Set (MADE/VBS) and the Modal Aerosol Dynamics model for Europe/Secondary Organic Aerosol Model (MADE/SORGAM) were employed in the WRF-Chem model, and surface PM2.5 (particulate matter less than 2.5 μm in size) mass concentration and the composition of its relevant chemical sources, i.e., SO42−, NO3−, NH4+, and organic carbon (OC) were simulated during the Korea-United States Air Quality (KORUS-AQ) campaign period (1 May to 12 June 2016). We classified the KORUS-AQ period into two cases, the stagnant period (16–21 May) which was dominated by local emission and the long-range transport period (25–31 May) which was affected by transport from the leeward direction, and focused on the differences in OC secondary aerosol formation between two modules over Northeast Asia. The simulated surface PM2.5 chemical components via the two modules showed the largest systematic biases in surface OC, with a mean bias of 4.5 μg m−3, and the second largest in SO42− abundance of 2.2 μg m−3 over Seoul. Compared with surface observations at two ground sites located near the western coastal Korean Peninsula, MADE/VBS exhibited the overpredictions in OC by 170–180%, whereas MADE/SORGAM showed underpredictions by 49–65%. OC and sulfate via MADE/VBS were simulated to be much higher than that simulated by MADE/SORGAM by a factor of 2.8–3.5 and 1.5–1.9, respectively. Model verification against KORUS-AQ aircraft measurements also showed large discrepancies in simulated non-surface OC between the two modules by a factor of five, with higher OC by MADE/VBS and lower IC by MADE/SORGAM, whereas much closer MADE/VBS simulations to the KORUS-AQ aircraft measurements were found. On the basis of the aircraft measurements, the aggregated bias (sum of four components) for PM2.5 mass concentrations from the MADE/VBS module indicated that the simulation was much closer to the measurements, nevertheless more elaborate analysis on the surface OC simulation performance would be needed to improve the ground results. Our findings show that significant inconsistencies are present in the secondary organic aerosol formation simulations, suggesting that PM2.5 forecasts should be considered with great caution, as well as in the context of policymaking in the Northeast Asia region.

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Improvement China Point Source for Improving Bottom-Up Emission Inventory

Cited by 33 publications

References 13 publications

Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory

Fine-Scale Columnar and Surface NOx Concentrations over South Korea: Comparison of Surface Monitors, TROPOMI, CMAQ and CAPSS Inventory

Evaluation of simulated O3 production efficiency during the KORUS-AQ campaign: Implications for anthropogenic NOx emissions in Korea

Sensitivity of Simulated PM2.5 Concentrations over Northeast Asia to Different Secondary Organic Aerosol Modules during the KORUS-AQ Campaign

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