Articles | Volume 25, issue 7
https://doi.org/10.5194/acp-25-4291-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-4291-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Local and transboundary contributions to NOy loadings across East Asia using CMAQ-ISAM and a GEMS-informed emission inventory during the winter–spring transition
Jincheol Park
Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
Sagun Kayastha
Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
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Cited articles
AirKorea: Quality-assured (final) air quality station measurement dataset, Korea Ministry of Environment [data set], https://www.airkorea.or.kr/web/last_amb_hour_data?pMENU_NO=123, last access: 16 October 2024 (in Korean).
Bae, C., Kim, B.-U., Kim, H. C., Yoo, C., and Kim, S.: Long-range transport influence on key chemical components of PM2.5 in the Seoul Metropolitan Area, South Korea, during the years 2012–2016, Atmosphere-Basel, 11, 1, https://doi.org/10.3390/atmos11010048, 2020.
Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G., and Wagner, T.: Megacity emissions and lifetimes of nitrogen oxides probed from space, Science, 333, 1737–1739, 2011.
Byun, D. and Schere, K. L.: Review of the governing equations, computational algorithms, and other components of the Models-3 Community Multiscale Air Quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51–77, https://doi.org/10.1115/1.2128636, 2006.
Carmichael, G. R., Calori, G., Hayami, H., Uno, I., Cho, S. Y., Engardt, M., Kim, S.-B., Ichikawa, Y., Ikeda, Y., Woo, J.-H., Ueda, H., and Amann, M.: The MICS-Asia study: Model intercomparison of long-range transport and sulfur deposition in East Asia, Atmos. Environ., 36, 175–199, https://doi.org/10.1016/S1352-2310(01)00448-4, 2002.
Chen, D., Xia, L., Guo, X., Lang, J., Zhou, Y., Wei, L., and Fu, X.: Impact of inter-annual meteorological variation from 2001 to 2015 on the contribution of regional transport to PM2.5 in Beijing, China, Atmos. Environ., 260, 118545, https://doi.org/10.1016/j.atmosenv.2021.118545, 2021.
Choi, W. J., Moon, K.-J., Yoon, J., Cho, A., Kim, S., Lee, S., Ko, D. ho, Kim, J., Ahn, M. H., Kim, D.-R., Kim, S.-M., Kim, J.-Y., Nicks, D., and Kim, J.-S.: Introducing the geostationary environment monitoring spectrometer, J. Appl. Remote. Sens., 12, 044005, https://doi.org/10.1117/1.JRS.12.044005, 2018.
Clough, S. A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative transfer modeling: A summary of the AER codes, J. Quant. Spectrosc. Ra., 91, 233–244, https://doi.org/10.1016/j.jqsrt.2004.05.058, 2005.
Collet, S., Kidokoro, T., Karamchandani, P., Jung, J., and Shah, T.: Future year ozone source attribution modeling study using CMAQ-ISAM, J. Air. Waste. Manage., 68, 1239–1247, https://doi.org/10.1080/10962247.2018.1496954, 2018.
Crippa, M., Solazzo, E., Huang, G., Guizzardi, D., Koffi, E., Muntean, M., Schieberle, C., Friedrich, R., and Janssens-Maenhout, G.: High resolution temporal profiles in the Emissions Database for Global Atmospheric Research, Sci. Data, 7, 1, https://doi.org/10.1038/s41597-020-0462-2, 2020.
Dong, Z., Wang, S., Xing, J., Chang, X., Ding, D., and Zheng, H.: Regional transport in Beijing-Tianjin-Hebei region and its changes during 2014–2017: The impacts of meteorology and emission reduction, Sci. Total Environ., 737, 139792, https://doi.org/10.1016/j.scitotenv.2020.139792, 2020.
Eck, T. F., Holben, B. N., Kim, J., Beyersdorf, A. J., Choi, M., Lee, S., Koo, J.-H., Giles, D. M., Schafer, J. S., Sinyuk, A., Peterson, D. A., Reid, J. S., Arola, A., Slutsker, I., Smirnov, A., Sorokin, M., Kraft, J., Crawford, J. H., Anderson, B. E., Thornhill, K. L., Diskin, G., Kim, S., and Park, S.: Influence of cloud, fog, and high relative humidity during pollution transport events in South Korea: Aerosol properties and PM2.5 variability, Atmos. Environ., 232, 117530, https://doi.org/10.1016/j.atmosenv.2020.117530, 2020.
Environmental Satellite Center: GEMS Level 2 Tropospheric NO2 product, Korea National Institute of Environmental Research [data set], https://nesc.nier.go.kr/ko/html/svc/openapi/explain.do, last access: 16 October 2024 (in Korean).
Feng, X., Zhang, X., and Wang, J.: Update of SO2 emission inventory in the Megacity of Chongqing, China by inverse modeling, Atmos. Environ., 294, 119519, https://doi.org/10.1016/j.atmosenv.2022.119519, 2023.
Goldberg, D. L., Saide, P. E., Lamsal, L. N., de Foy, B., Lu, Z., Woo, J.-H., Kim, Y., Kim, J., Gao, M., Carmichael, G., and Streets, D. G.: A top-down assessment using OMI NO2 suggests an underestimate in the NOx emissions inventory in Seoul, South Korea, during KORUS-AQ, Atmos. Chem. Phys., 19, 1801–1818, https://doi.org/10.5194/acp-19-1801-2019, 2019.
Goldberg, D. L., Tao, M., Kerr, G. H., Ma, S., Tong, D. Q., Fiore, A. M., Dickens, A. F., Adelman, Z. E., and Anenberg, S. C.: Evaluating the spatial patterns of U.S. urban NOx emissions using TROPOMI NO2, Remote. Sens. Environ., 300, 113917. https://doi.org/10.1016/j.rse.2023.113917, 2024.
Guenther, A., Jiang, X., Shah, T., Huang, L., Kemball-Cook, S., and Yarwood, G.: Model of Emissions of Gases and Aerosol from Nature Version 3 (MEGAN3) for Estimating Biogenic Emissions, In C. Mensink, W. Gong, and A. Hakami (Eds.), Air Pollution Modeling and its Application XXVI, 187–192, Springer International Publishing, https://doi.org/10.1007/978-3-030-22055-6_29, 2020.
Han, X., Cai, J., Zhang, M., and Wang, X.: Numerical simulation of interannual variation in transboundary contributions from Chinese emissions to PM2.5 mass burden in South Korea, Atmos. Environ., 256, 118440, https://doi.org/10.1016/j.atmosenv.2021.118440, 2021.
Hertel, O., Skjøth, C. A., Reis, S., Bleeker, A., Harrison, R. M., Cape, J. N., Fowler, D., Skiba, U., Simpson, D., Jickells, T., Kulmala, M., Gyldenkærne, S., Sørensen, L. L., Erisman, J. W., and Sutton, M. A.: Governing processes for reactive nitrogen compounds in the European atmosphere, Biogeosciences, 9, 4921–4954, https://doi.org/10.5194/bg-9-4921-2012, 2012.
Hoek, G., Krishnan, R. M., Beelen, R., Peters, A., Ostro, B., Brunekreef, B., and Kaufman, J. D.: Long-term air pollution exposure and cardio- respiratory mortality: A review, Environ. Health, 12, 43, https://doi.org/10.1186/1476-069X-12-43, 2013.
Houyoux, M. R., Vukovich, J. M., Coats Jr., C. J., Wheeler, N. J. M., and Kasibhatla, P. S.: Emission inventory development and processing for the Seasonal Model for Regional Air Quality (SMRAQ) project, J. Geophys. Res-Atmos., 105, 9079–9090, https://doi.org/10.1029/1999JD900975, 2000.
Hui, G.: Comparison of East Asian winter monsoon indices, Adv. Geosci., 10, 31–37, https://doi.org/10.5194/adgeo-10-31-2007, 2007.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res.-Atmos., 113, D13103, https://doi.org/10.1029/2008JD009944, 2008.
Ikeda, K., Yamaji, K., Kanaya, Y., Taketani, F., Pan, X., Komazaki, Y., Kurokawa, J., and Ohara, T.: Source region attribution of PM2.5 mass concentrations over Japan, Geochem. J., 49, 185–194, https://doi.org/10.2343/geochemj.2.0344, 2015.
Itahashi, S., Uno, I., and Kim, S.: Source contributions of sulfate aerosol over East Asia estimated by CMAQ-DDM, Environ. Sci. Technol., 46, 6733–6741, https://doi.org/10.1021/es300887w, 2012.
Jeon, W., Choi, Y., Lee, H. W., Lee, S.-H., Yoo, J.-W., Park, J., and Lee, H.-J.: A quantitative analysis of grid nudging effect on each process of PM2.5 production in the Korean Peninsula, Atmos. Environ., 122, 763–774, https://doi.org/10.1016/j.atmosenv.2015.10.050, 2015.
Jiang, Z., Vargas, M., and Csiszar, I.: New operational real-time daily rolling weekly Green Vegetation fraction product derived from suomi NPP VIIRS reflectance data. 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China, 10–15 July 2016, 3524–3527, https://doi.org/10.1109/IGARSS.2016.7729911, 2016.
Jordan, C. E., Crawford, J. H., Beyersdorf, A. J., Eck, T. F., Halliday, H. S., Nault, B. A., Chang, L.-S., Park, J., Park, R., Lee, G., Kim, H., Ahn, J., Cho, S., Shin, H. J., Lee, J. H., Jung, J., Kim, D.-S., Lee, M., Lee, T., Whitehill, A., Szykman, J., Schueneman, M. K., Campuzano-Jost, P., Jimenez, J. L., DiGangi, J. P., Diskin, G. S., Anderson, B. E., Moore, R. H., Ziemba, L. D., Fenn, M. A., Hair, J. W., Kuehn, R. E., Holz, R. E., Chen, G., Travis, K., Shook, M., Peterson, D. A., Lamb, K. D., and Schwarz, J. P.: Investigation of factors controlling PM2.5 variability across the South Korean Peninsula during KORUS-AQ, Elementa-Sci. Anthrop., 8, 28, https://doi.org/10.1525/elementa.424, 2020.
Jung, J., Choi, Y., Wong, D. C., Nelson, D., and Lee, S.: Role of Sea Fog Over the Yellow Sea on Air Quality With the Direct Effect of Aerosols, J. Geophys. Res.-Atmos., 126, e2020JD033498. https://doi.org/10.1029/2020JD033498, 2021.
Jung, J., Choi, Y., Souri, A. H., Mousavinezhad, S., Sayeed, A., and Lee, K.: The impact of springtime-transported air pollutants on local air quality with satellite-constrained NOx emission adjustments over East Asia, J. Geophy. Res-Atmos., 127, e2021JD035251, https://doi.org/10.1029/2021JD035251, 2022a.
Jung, J., Choi, Y., Mousavinezhad, S., Kang, D., Park, J., Pouyaei, A., Ghahremanloo, M., Momeni, M., and Kim, H.: Changes in the ozone chemical regime over the contiguous United States inferred by the inversion of NOx and VOC emissions using satellite observation, Atmos. Res., 270, 106076, https://doi.org/10.1016/j.atmosres.2022.106076, 2022b.
Kain, J. S.: The Kain–Fritsch convective parameterization: An update, J. Appl. Meteorol. Clim., 43, 170–181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
Kajino, M., Sato, K., Inomata, Y., and Ueda, H.: Source–receptor relationships of nitrate in Northeast Asia and influence of sea salt on the long-range transport of nitrate, Atmos. Environ., 79, 67–78, https://doi.org/10.1016/j.atmosenv.2013.06.024, 2013.
Kang, M.-S., Park, D.-S., Chae, C.-B., Sunwoo, Y., and Hong, K.-H.: Monthly characteristics and source–receptor relationships of anthropogenic total nitrate in Northeast Asia, Atmosphere-Basel, 15, 9, https://doi.org/10.3390/atmos15091121, 2024.
Kashfi Yeganeh, A., Momeni, M., Choi, Y., Park, J., and Jung, J.: A case study of surface ozone source contributions in the Seoul metropolitan area using the adjoint of CMAQ, Japca. J. Air. Waste. Ma, 74, 511–530, https://doi.org/10.1080/10962247.2024.2361021, 2024.
Kim, Y., Kim, K.-Y., and Jhun, J.-G.: Seasonal evolution mechanism of the East Asian winter monsoon and its interannual variability, Clim. Dynam., 41, 1213–1228, https://doi.org/10.1007/s00382-012-1491-0, 2013.
Kwok, R. H. F., Baker, K. R., Napelenok, S. L., and Tonnesen, G. S.: Photochemical grid model implementation and application of VOC, NOx, and O3 source apportionment, Geoscie. Model Dev., 8, 99–114, https://doi.org/10.5194/gmd-8-99-2015, 2015.
Lange, K., Richter, A., and Burrows, J. P.: Variability of nitrogen oxide emission fluxes and lifetimes estimated from Sentinel-5P TROPOMI observations, Atmos. Chem. Phys., 22, 2745–2767, https://doi.org/10.5194/acp-22-2745-2022, 2022.
Lee, H.-J., Jo, H.-Y., Song, C.-K., Jo, Y.-J., Park, S.-Y., and Kim, C.-H.: Sensitivity of simulated PM2.5 concentrations over northeast Asia to different secondary organic aerosol modules during the KORUS-AQ campaign, Atmosphere-Basel, 11, 9, https://doi.org/10.3390/atmos11091004, 2020.
Li, M., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B., Cui, H., Man, H., Zhang, Q., and He, K: Anthropogenic emission inventories in China: A review, Natl. Sci. Rev., 4, 834–866, https://doi.org/10.1093/nsr/nwx150, 2017a.
Li, Z., Guo, J., Ding, A., Liao, H., Liu, J., Sun, Y., Wang, T., Xue, H., Zhang, H., and Zhu, B.: Aerosol and boundary-layer interactions and impact on air quality, Natl. Sci. Rev., 4, 810–833, https://doi.org/10.1093/nsr/nwx117, 2017b.
Li, R., Mei, X., Wei, L., Han, X., Zhang, M., and Jing, Y.: Study on the contribution of transport to PM2.5 in typical regions of China using the regional air quality model RAMS-CMAQ, Atmos. Environ., 214, 116856, https://doi.org/10.1016/j.atmosenv.2019.116856, 2019.
Li, M., McDonald, B. C., McKeen, S. A., Eskes, H., Levelt, P., Francoeur, C., Harkins, C., He, J., Barth, M., Henze, D. K., Bela, M. M., Trainer, M., de Gouw, J. A., and Frost, G. J.: Assessment of Updated Fuel-Based Emissions Inventories Over the Contiguous United States Using TROPOMI NO2 Retrievals, J. Geophys. Res.-Atmos., 126, e2021JD035484, https://doi.org/10.1029/2021JD035484, 2021a.
Li, N., Tang, K., Wang, Y., Wang, J., Feng, W., Zhang, H., Liao, H., Hu, J., Long, X., Shi, C., and Su, X.: Is the efficacy of satellite-based inversion of SO2 emission model dependent?, Environ. Res. Lett., 16, 035018, https://doi.org/10.1088/1748-9326/abe829, 2021b.
Lin, J.-T., Liu, Z., Zhang, Q., Liu, H., Mao, J., and Zhuang, G.: Modeling uncertainties for tropospheric nitrogen dioxide columns affecting satellite-based inverse modeling of nitrogen oxides emissions, Atmos. Chem. Phys., 12, 12255–12275, https://doi.org/10.5194/acp-12-12255-2012, 2012.
Liu, F., Beirle, S., Zhang, Q., Dörner, S., He, K., and Wagner, T.: NOx lifetimes and emissions of cities and power plants in polluted background estimated by satellite observations, Atmos. Chem. Phys., 16, 5283–5298, https://doi.org/10.5194/acp-16-5283-2016, 2016.
Liu, B., Jin, Y., and Li, C.: Analysis and prediction of air quality in Nanjing from autumn 2018 to summer 2019 using PCR–SVR–ARMA combined model, Sci. Rep.-UK, 11, 348, https://doi.org/10.1038/s41598-020-79462-0, 2021.
Martin, R. V., Jacob, D. J., Chance, K., Kurosu, T. P., Palmer, P. I., and Evans, M. J.: Global inventory of nitrogen oxide emissions constrained by space-based observations of NO2 columns, J. Geophys. Res.-Atmos., 108, 4537, https://doi.org/10.1029/2003JD003453, 2003.
Momeni, M., Choi, Y., Kashfi Yeganeh, A., Pouyaei, A., Jung, J., Park, J., Shephard, M. W., Dammers, E., and Cady-Pereira, K. E.: Constraining East Asia ammonia emissions through satellite observations and iterative Finite Difference Mass Balance (iFDMB) and investigating its impact on inorganic fine particulate matter, Environ. Int., 184, 108473, https://doi.org/10.1016/j.envint.2024.108473, 2024.
Mun, J., Choi, Y., Jeon, W., Lee, H. W., Kim, C.-H., Park, S.-Y., Bak, J., Jung, J., Oh, I., Park, J., and Kim, D.: Assessing mass balance-based inverse modeling methods via a pseudo-observation test to constrain NOx emissions over South Korea, Atmos. Environ., 292, 119429, https://doi.org/10.1016/j.atmosenv.2022.119429, 2023.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes, Mon. Weather. Rev., 137, 991–1007, https://doi.org/10.1175/2008MWR2556.1, 2009.
Napelenok, S. L., Cohan, D. S., Hu, Y., and Russell, A. G.: Decoupled direct 3D sensitivity analysis for particulate matter (DDM-3D/PM), Atmos. Environ., 40, 6112–6121, https://doi.org/10.1016/j.atmosenv.2006.05.039, 2006.
National Institute of Environmental Research (NIER): Geostationary Environment Monitoring Spectrometer (GEMS) algorithm theoretical basis document: NO2 retrieval algorithm,, https://nesc.nier.go.kr/en/html/satellite/doc/doc.do (last access: 30 November 2024), 2020.
Nault, B. A., Campuzano-Jost, P., Day, D. A., Schroder, J. C., Anderson, B., Beyersdorf, A. J., Blake, D. R., Brune, W. H., Choi, Y., Corr, C. A., de Gouw, J. A., Dibb, J., DiGangi, J. P., Diskin, G. S., Fried, A., Huey, L. G., Kim, M. J., Knote, C. J., Lamb, K. D., Lee, T., Park, T., Pusede, S. E., Scheuer, E., Thornhill, K. L., Woo, J.-H., and Jimenez, J. L.: Secondary organic aerosol production from local emissions dominates the organic aerosol budget over Seoul, South Korea, during KORUS-AQ, Atmos. Chem. Phys., 18, 17769–17800, https://doi.org/10.5194/acp-18-17769-2018, 2018.
Newell, K., Kartsonaki, C., Lam, K. B. H., and Kurmi, O.: Cardiorespiratory health effects of gaseous ambient air pollution exposure in low and middle income countries: A systematic review and meta-analysis, Environ. Health., 17, 41, https://doi.org/10.1186/s12940-018-0380-3, 2018.
Pan, L., Tong, D., Lee, P., Kim, H.-C., and Chai, T.: Assessment of NOx and O3 forecasting performances in the U.S. National Air Quality Forecasting Capability before and after the 2012 major emissions updates, Atmos. Environ., 95, 610–619, https://doi.org/10.1016/j.atmosenv.2014.06.020, 2014.
Park, J., Jung, J., Choi, Y., Mousavinezhad, S., and Pouyaei, A.: The sensitivities of ozone and PM2.5 concentrations to the satellite-derived leaf area index over East Asia and its neighboring seas in the WRF-CMAQ modeling system, Environ. Pollut., 306, 119419, https://doi.org/10.1016/j.envpol.2022.119419, 2022.
Park, J., Jung, J., Choi, Y., Lim, H., Kim, M., Lee, K., Lee, Y. G., and Kim, J.: Satellite-based, top-down approach for the adjustment of aerosol precursor emissions over East Asia: the TROPOspheric Monitoring Instrument (TROPOMI) NO2 product and the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol optical depth (AOD) data fusion product and its proxy, Atmos. Meas. Tech., 16, 3039–3057, https://doi.org/10.5194/amt-16-3039-2023, 2023.
Park, J., Choi, Y., Jung, J., Lee, K., and Yeganeh, A. K.: First top-down diurnal adjustment to NOx emissions inventory in Asia informed by the Geostationary Environment Monitoring Spectrometer (GEMS) tropospheric NO2 columns, Sci. Rep-UK, 14, 24338, https://doi.org/10.1038/s41598-024-76223-1, 2024.
Peterson, D. A., Hyer, E. J., Han, S.-O., Crawford, J. H., Park, R. J., Holz, R., Kuehn, R. E., Eloranta, E., Knote, C., Jordan, C. E., and Lefer, B. L.: Meteorology influencing springtime air quality, pollution transport, and visibility in Korea, Elementa, 7, 57, https://doi.org/10.1525/elementa.395, 2019.
Placet, M., Mann, C. O., Gilbert, R. O., and Niefer, M. J., Emissions of ozone precursors from stationary sources: A critical review, Atmos. Environ., 34, 2183–2204, https://doi.org/10.1016/S1352-2310(99)00464-1, 2000.
Pleim, J. E.: A simple, efficient solution of flux–profile relationships in the atmospheric surface layer, J. Appl. Meteorol. Clim., 45, 341–347, https://doi.org/10.1175/JAM2339.1, 2006.
Pleim, J. E.: A combined local and nonlocal closure model for the atmospheric boundary layer Part I: Model description and testing, J. Appl. Meteorol. Clim., 46, 1383–1395, https://doi.org/10.1175/JAM2539.1, 2007a.
Pleim, J. E.: A combined local and nonlocal closure model for the atmospheric boundary layer Part II: Application and evaluation in a mesoscale meteorological model, J. Appl. Meteorol. Clim., 46, 1396–1409, https://doi.org/10.1175/JAM2534.1, 2007b.
Quosoft: National air quality monitoring network dataset, China Ministry of Ecology and Environment [data set], https://quotsoft.net/air, last access: 11 April 2024 (in Chinese).
Rodgers, C. D.: Inverse methods for atmospheric sounding: Theory and practice, Series on Atmospheric, Oceanic and Planetary Physics, World Scientific, World Scientific Publishing, https://doi.org/10.1142/3171, 2000.
Rohde, R. A. and Muller, R. A.: Air pollution in China: Mapping of concentrations and sources, PLOS ONE, 10, e0135749, https://doi.org/10.1371/journal.pone.0135749, 2015.
Russo, M. A., Gama, C., and Monteiro, A.: How does upgrading an emissions inventory affect air quality simulations?, Air. Qual. Atmos. Hlth., 12, 731–741, https://doi.org/10.1007/s11869-019-00692-x, 2019.
Rypdal, K. and Winiwarter, W.: Uncertainties in greenhouse gas emission inventories – Evaluation, comparability and implications, Environ. Sci. Policy., 4, 107–116, https://doi.org/10.1016/S1462-9011(00)00113-1, 2001.
Ryu, Y.-H. and Min, S.-K.: Anthropogenic warming degrades spring air quality in Northeast Asia by enhancing atmospheric stability and transboundary transport, Npj. Clim. Atmos. Sci., 7, 1–10, https://doi.org/10.1038/s41612-024-00603-7, 2024.
Sargent, M. R., Floerchinger, C., McKain, K., Budney, J., Gottlieb, E. W., Hutyra, L. R., Rudek, J., and Wofsy, S. C.: Majority of US urban natural gas emissions unaccounted for in inventories, P. Natl. Acad. Sci. USA, 118, e2105804118, https://doi.org/10.1073/pnas.2105804118, 2021.
Shen, A., Liu, Y., Lu, X., Wang, X., Chang, M., Zhang, J., Tian, C., and Fan, Q.: Sulfur deposition in the Beijing-Tianjin-Hebei region, China: Spatiotemporal characterization and regional source attributions, Atmos. Environ., 286, 119225, https://doi.org/10.1016/j.atmosenv.2022.119225, 2022.
Shimadera, H., Hayami, H., Chatani, S., Morino, Y., Mori, Y., Morikawa, T., Yamaji, K., and Ohara, T.: Sensitivity analyses of factors influencing CMAQ performance for fine particulate nitrate, J. Air. Waste. Manage., 64, 374–387, https://doi.org/10.1080/10962247.2013.778919, 2014.
Silver, B., Reddington, C. L., Arnold, S. R., and Spracklen, D. V.: Substantial changes in air pollution across China during 2015–2017, Environ. Res. Lett., 13, 114012, https://doi.org/10.1088/1748-9326/aae718, 2018.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D., Duda, M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A description of the advanced research WRF version 3, NCAR technical note, No. NCAR/TN-475CSTR, University Corporation for Atmospheric Research, https://doi.org/10.5065/D68S4MVH, 2008.
Smith, S. J., McDuffie, E. E., and Charles, M.: Opinion: Coordinated development of emission inventories for climate forcers and air pollutants, Atmos. Chem. Phys., 22, 13201–13218, https://doi.org/10.5194/acp-22-13201-2022, 2022.
Son, K., Kim, B.-U., Kim, H. C., and Kim, S.: Source apportionment of ambient concentration and population exposure to elemental carbon in South Korea using a three-dimensional air quality model, Air. Qual. Atmos. Hlth., 15, 1729–1744, https://doi.org/10.1007/s11869-022-01213-z, 2022.
Souri, A. H., Choi, Y., Jeon, W., Li, X., Pan, S., Diao, L., and Westenbarger, D. A.: Constraining NOx emissions using satellite NO2 measurements during 2013 DISCOVER-AQ Texas campaign, Atmos. Environ., 131, 371–381, https://doi.org/10.1016/j.atmosenv.2016.02.020, 2016.
Souri, A. H., Choi, Y., Jeon, W., Woo, J.-H., Zhang, Q., and Kurokawa, J.: Remote sensing evidence of decadal changes in major tropospheric ozone precursors over East Asia, J. Geophys. Res.-Atmos., 122, 2474–2492, https://doi.org/10.1002/2016JD025663, 2017.
Souri, A. H., Choi, Y., Pan, S., Curci, G., Nowlan, C. R., Janz, S. J., Kowalewski, M. G., Liu, J., Herman, J. R., and Weinheimer, A. J.: First Top-Down Estimates of Anthropogenic NOx Emissions Using High-Resolution Airborne Remote Sensing Observations, J. Geophys. Res-Atmos., 123, 3269–3284, https://doi.org/10.1002/2017JD028009, 2018.
Souri, A. H., Nowlan, C. R., González Abad, G., Zhu, L., Blake, D. R., Fried, A., Weinheimer, A. J., Wisthaler, A., Woo, J.-H., Zhang, Q., Chan Miller, C. E., Liu, X., and Chance, K.: An inversion of NOx and non-methane volatile organic compound (NMVOC) emissions using satellite observations during the KORUS-AQ campaign and implications for surface ozone over East Asia, Atmos. Chem. Phys., 20, 9837–9854, https://doi.org/10.5194/acp-20-9837-2020, 2020.
Sun, M., Cui, J., Zhao, X., and Zhang, J.: Impacts of precursors on peroxyacetyl nitrate (PAN) and relative formation of PAN to ozone in a southwestern megacity of China, Atmos. Environ., 231, 117542, https://doi.org/10.1016/j.atmosenv.2020.117542, 2020.
Tang, B., Saide, P. E., Gao, M., Carmichael, G. R., and Stanier, C. O.: WRF-Chem quantification of transport events and emissions sensitivity in Korea during KORUS-AQ, Elementa-Sci. Anthrop., 11, 00096, https://doi.org/10.1525/elementa.2022.00096, 2023.
Wang, S., Zhang, Q., Martin, R. V., Philip, S., Liu, F., Li, M., Jiang, X., and He, K.: Satellite measurements oversee China's sulfur dioxide emission reductions from coal-fired power plants, Environ. Res. Lett., 10, 114015, https://doi.org/10.1088/1748-9326/10/11/114015, 2015.
Wang, C.-Y., Chen, J.-P., and Wang, W.-C.: Meteorology-driven PM2.5 interannual variability over East Asia, Sci. Total. Environ., 904, 166911, https://doi.org/10.1016/j.scitotenv.2023.166911, 2023.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Woo, J.-H., Kim, Y., Kim, H.-K., Choi, K.-C., Eum, J.-H., Lee, J.-B., Lim, J.-H., Kim, J., and Seong, M.: Development of the CREATE inventory in support of integrated climate and air quality modeling for Asia, Sustainability-Basel, 12, 7930, https://doi.org/10.3390/su12197930, 2020.
Wu, C.-H.: Seasonal adjustment of particulate matter pollution in coastal East Asia during the 2020 COVID lockdown, Environ. Res. Lett., 16, 124023, https://doi.org/10.1088/1748-9326/ac343c, 2021.
Wyrwoll, K.-H., Wei, J., Lin, Z., Shao, Y., and He, F.: Cold surges and dust events: Establishing the link between the East Asian Winter Monsoon and the Chinese loess record, Quaternary Sci. Rev., 149, 102–108. https://doi.org/10.1016/j.quascirev.2016.04.015, 2016.
Xian, Y., Zhang, Y., Liu, Z., Wang, H., and Xiong, T.: Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002–2020, Sci. Total. Environ., 947, 174557, https://doi.org/10.1016/j.scitotenv.2024.174557, 2024.
Xiu, A. and Pleim, J. E.: Development of a land surface model Part I: Application in a mesoscale meteorological model, J. Appl. Meteorol. Clim., 40, 192–209, https://doi.org/10.1175/1520-0450(2001)040<0192:DOALSM>2.0.CO;2, 2001.
Yuan, H., Dai, Y., Xiao, Z., Ji, D., and Shangguan, W.: Reprocessing the MODIS Leaf Area Index products for land surface and climate modelling, Remote Sens. Environ., 115, 1171–1187, https://doi.org/10.1016/j.rse.2011.01.001, 2011.
Yuan, J., Ling, Z., Wang, Z., Lu, X., Fan, S., He, Z., Guo, H., Wang, X., and Wang, N.: PAN–precursor relationship and process analysis of PAN variations in the Pearl River Delta region, Atmosphere-Basel, 9, 10, https://doi.org/10.3390/atmos9100372, 2018.
Yumimoto, K., Uno, I., and Itahashi, S.: Long-term inverse modeling of Chinese CO emission from satellite observations, Environ. Pollut., 195, 308–318, https://doi.org/10.1016/j.envpol.2014.07.026, 2014.
Zhai, S., Jacob, D. J., Wang, X., Shen, L., Li, K., Zhang, Y., Gui, K., Zhao, T., and Liao, H.: Fine particulate matter (PM2.5) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology, Atmos. Chem. Phys., 19, 11031–11041, https://doi.org/10.5194/acp-19-11031-2019, 2019.
Zhao, S., Feng, T., Tie, X., Li, G., and Cao, J.: Air Pollution Zone Migrates South Driven by East Asian Winter Monsoon and Climate Change, Geophys. Res. Lett., 48, e2021GL092672, https://doi.org/10.1029/2021GL092672, 2021.
Short summary
We investigated NOx emission contributions to NOy loadings across five regions of East Asia during the 2022 winter–spring transition through chemical transport modeling informed by satellite data. As seasons progress, local contributions within each region to its NOy budget decreased from 32 %–43 % to 23 %–30 %, while transboundary contributions increased from 16 %–33 % to 27 %–37 %, driven by a shift in synoptic settings that allowed pollutants to spread more broadly across the regions.
We investigated NOx emission contributions to NOy loadings across five regions of East Asia...
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