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Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000
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High Resolution Image Download MS PowerPoint Slide PM 2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China’s PM 2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM 2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting–Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM 2.5 data. PM 2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM 2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of −9.0, −7.2, −8.1, −8.4, and −9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM 2.5 components. As part of Tracking Air Pollution in China ( http://tapdata.org.cn ), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.
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Citations
Cites
Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., et al. (2018) · Atmospheric Chemistry and Physics · doi:10.5194/acp-18-14095-2018 · Cited by 2,916
Self-citationDrivers of improved PM 2.5 air quality in China from 2013 to 2017
Zhang, Q., Zheng, Y., Tong, D., Shao, M., Wang, S., Zhang, Y., Xu, X., Wang, J., He, H., Liu, W., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1907956116 · Cited by 2,204
Self-citationSources and distributions of dust aerosols simulated with the GOCART model
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O., & Lin, S. (2001) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2000jd000053 · Cited by 2,167
Turpin, B. J., & Lim, H.-J. (2001) · Aerosol Science and Technology · doi:10.1080/02786820119445 · Cited by 2,036
Asian emissions in 2006 for the NASA INTEX-B mission
Zhang, Q., Streets, D. G., Carmichael, G. R., He, K. B., Huo, H., Kannari, A., Klimont, Z., Park, I. S., Reddy, S., Fu, J. S., et al. (2009) · Atmospheric Chemistry and Physics · doi:10.5194/acp-9-5131-2009 · Cited by 1,950
Self-citationThe CAMS reanalysis of atmospheric composition
Inness, A., Ades, M., Agustí-Panareda, A., Barré, J., Benedictow, A., Blechschmidt, A.-M., Dominguez, J. J., Engelen, R., Eskes, H., Flemming, J., et al. (2019) · Atmospheric Chemistry and Physics · doi:10.5194/acp-19-3515-2019 · Cited by 1,480
Randles, C. A., da Silva, A. M., Buchard, V., Colarco, P. R., Darmenov, A., Govindaraju, R., Smirnov, A., Holben, B., Ferrare, R., Hair, J., et al. (2017) · Journal of Climate · doi:10.1175/jcli-d-16-0609.1 · Cited by 1,469
Formation of Urban Fine Particulate Matter
Zhang, R., Wang, G., Guo, S., Zamora, M. L., Ying, Q., Lin, Y., Wang, W., Hu, M., & Wang, Y. (2015) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00067 · Cited by 1,426
Modeling the atmospheric dust cycle: 1. Design of a soil‐derived dust emission scheme
Marticorena, B., & Bergametti, G. (1995) · Journal of Geophysical Research: Atmospheres · doi:10.1029/95jd00690 · Cited by 1,409
Anthropogenic emission inventories in China: a review
Li, M., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B., Cui, H., Man, H., et al. (2017) · National Science Review · doi:10.1093/nsr/nwx150 · Cited by 1,304
Self-citationKelly, F. J., & Fussell, J. C. (2012) · Atmospheric Environment · doi:10.1016/j.atmosenv.2012.06.039 · Cited by 1,276
Severe haze in northern China: A synergy of anthropogenic emissions and atmospheric processes
An, Z., Huang, R.-J., Zhang, R., Tie, X., Li, G., Cao, J., Zhou, W., Shi, Z., Han, Y., Gu, Z., et al. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1900125116 · Cited by 1,015
Zheng, G. J., Duan, F. K., Su, H., Ma, Y. L., Cheng, Y., Zheng, B., Zhang, Q., Huang, T., Kimoto, T., Chang, D., et al. (2015) · Atmospheric Chemistry and Physics · doi:10.5194/acp-15-2969-2015 · Cited by 951
Self-citationZhang, X. Y., Wang, Y. Q., Niu, T., Zhang, X. C., Gong, S. L., Zhang, Y. M., & Sun, J. Y. (2012) · Atmospheric Chemistry and Physics · doi:10.5194/acp-12-779-2012 · Cited by 867
van Donkelaar, A., Martin, R. V., Li, C., & Burnett, R. T. (2019) · Environmental Science & Technology · doi:10.1021/acs.est.8b06392 · Cited by 715
Zheng, B., Zhang, Q., Zhang, Y., He, K. B., Wang, K., Zheng, G. J., Duan, F. K., Ma, Y. L., & Kimoto, T. (2015) · Atmospheric Chemistry and Physics · doi:10.5194/acp-15-2031-2015 · Cited by 670
Self-citationTracking Air Pollution in China: Near Real-Time PM 2.5 Retrievals from Multisource Data Fusion
Geng, G., Xiao, Q., Liu, S., Liu, X., Cheng, J., Zheng, Y., Xue, T., Tong, D., Zheng, B., Peng, Y., et al. (2021) · Environmental Science & Technology · doi:10.1021/acs.est.1c01863 · Cited by 629
Self-citationLiu, F., Zhang, Q., Tong, D., Zheng, B., Li, M., Huo, H., & He, K. B. (2015) · Atmospheric Chemistry and Physics · doi:10.5194/acp-15-13299-2015 · Cited by 465
Self-citationWinter and Summer PM 2.5 Chemical Compositions in Fourteen Chinese Cities
Cao, J.-J., Shen, Z.-X., Chow, J. C., Watson, J. G., Lee, S.-C., Tie, X.-X., Ho, K.-F., Wang, G.-H., & Han, Y.-M. (2012) · Journal of the Air & Waste Management Association · doi:10.1080/10962247.2012.701193 · Cited by 412
Elser, M., Huang, R.-J., Wolf, R., Slowik, J. G., Wang, Q., Canonaco, F., Li, G., Bozzetti, C., Daellenbach, K. R., Huang, Y., et al. (2016) · Atmospheric Chemistry and Physics · doi:10.5194/acp-16-3207-2016 · Cited by 389
Control of particulate nitrate air pollution in China
Zhai, S., Jacob, D. J., Wang, X., Liu, Z., Wen, T., Shah, V., Li, K., Moch, J. M., Bates, K. H., Song, S., et al. (2021) · Nature Geoscience · doi:10.1038/s41561-021-00726-z · Cited by 363
Self-citationChanges in China's anthropogenic emissions and air quality during the COVID-19 pandemic in 2020
Zheng, B., Zhang, Q., Geng, G., Chen, C., Shi, Q., Cui, M., Lei, Y., & He, K. (2021) · Earth System Science Data · doi:10.5194/essd-13-2895-2021 · Cited by 363
Self-citationWang, Z., Li, J., Wang, Z., Yang, W., Tang, X., Ge, B., Yan, P., Zhu, L., Chen, X., Chen, H., et al. (2014) · Science China Earth Sciences · doi:10.1007/s11430-013-4793-0 · Cited by 325
The absorption Ångström exponent of black carbon: from numerical aspects
Liu, C., Chung, C. E., Yin, Y., & Schnaiter, M. (2018) · Atmospheric Chemistry and Physics · doi:10.5194/acp-18-6259-2018 · Cited by 298
Geng, G., Zhang, Q., Tong, D., Li, M., Zheng, Y., Wang, S., & He, K. (2017) · Atmospheric Chemistry and Physics · doi:10.5194/acp-17-9187-2017 · Cited by 285
Self-citationParameterization of size-resolved dust emission and validation with measurements
Shao, Y., Ishizuka, M., Mikami, M., & Leys, J. F. (2011) · Journal of Geophysical Research · doi:10.1029/2010jd014527 · Cited by 277
Ding, A., Huang, X., Nie, W., Chi, X., Xu, Z., Zheng, L., Xu, Z., Xie, Y., Qi, X., Shen, Y., et al. (2019) · Atmospheric Chemistry and Physics · doi:10.5194/acp-19-11791-2019 · Cited by 249
Satellite Aerosol Remote Sensing over Land
(2009) · Springer eBooks · doi:10.1007/978-3-540-69397-0 · Cited by 245
Xiao, Q., Zheng, Y., Geng, G., Chen, C., Huang, X., Che, H., Zhang, X., He, K., & Zhang, Q. (2021) · Atmospheric Chemistry and Physics · doi:10.5194/acp-21-9475-2021 · Cited by 245
Self-citationGlobal Chemical Composition of Ambient Fine Particulate Matter for Exposure Assessment
Philip, S., Martin, R. V., van Donkelaar, A., Lo, J. W.-H., Wang, Y., Chen, D., Zhang, L., Kasibhatla, P. S., Wang, S., Zhang, Q., et al. (2014) · Environmental Science & Technology · doi:10.1021/es502965b · Cited by 213
Self-citationTrends in particulate matter and its chemical compositions in China from 2013–2017
Wang, Y., Li, W., Gao, W., Liu, Z., Tian, S., Shen, R., Ji, D., Wang, S., Wang, L., Tang, G., et al. (2019) · Science China Earth Sciences · doi:10.1007/s11430-018-9373-1 · Cited by 191
Variation in global chemical composition of PM 2.5 : emerging results from SPARTAN
Snider, G., Weagle, C. L., Murdymootoo, K. K., Ring, A., Ritchie, Y., Stone, E., Walsh, A., Akoshile, C., Anh, N. X., Balasubramanian, R., et al. (2016) · Atmospheric Chemistry and Physics · doi:10.5194/acp-16-9629-2016 · Cited by 189
Self-citationEvaluation of gap-filling approaches in satellite-based daily PM2.5 prediction models
Xiao, Q., Geng, G., Cheng, J., Liang, F., Li, R., Meng, X., Xue, T., Huang, X., Kan, H., Zhang, Q., et al. (2021) · Atmospheric Environment · doi:10.1016/j.atmosenv.2020.117921 · Cited by 187
Self-citationMa, Q., Wu, Y., Zhang, D., Wang, X., Xia, Y., Liu, X., Tian, P., Han, Z., Xia, X., Wang, Y., et al. (2017) · Science of The Total Environment · doi:10.1016/j.scitotenv.2017.04.193 · Cited by 185
Self-citationMurphy, B. N., Woody, M. C., Jimenez, J. L., Carlton, A. M. G., Hayes, P. L., Liu, S., Ng, N. L., Russell, L. M., Setyan, A., Xu, L., et al. (2017) · Atmospheric Chemistry and Physics · doi:10.5194/acp-17-11107-2017 · Cited by 174
Self-citationGeng, G., Xiao, Q., Zheng, Y., Tong, D., Zhang, Y., Zhang, X., Zhang, Q., He, K., & Liu, Y. (2019) · Science China Earth Sciences · doi:10.1007/s11430-018-9353-x · Cited by 170
Self-citationChang, X., Zhao, B., Zheng, H., Wang, S., Cai, S., Guo, F., Gui, P., Huang, G., Wu, D., Han, L., et al. (2022) · One Earth · doi:10.1016/j.oneear.2022.03.015 · Cited by 164
Trends of PM2.5 and Chemical Composition in Beijing, 2000–2015
Lang, J., Zhang, Y.-Y., Zhou, Y., et al. (2017) · Aerosol and Air Quality Research · doi:10.4209/aaqr.2016.07.0307 · Cited by 158
Krall, J. R., Mulholland, J. A., Russell, A. G., Balachandran, S., Winquist, A. G., Tolbert, P. E., Waller, L. A., & Sarnat, S. E. (2016) · Environmental Health Perspectives · doi:10.1289/ehp271 · Cited by 152
Huang, L., Zhu, Y., Zhai, H., Xue, S., Zhu, T., Shao, Y. F., Liu, Z., Emery, C. A., Yarwood, G., Wang, Y., et al. (2021) · Atmospheric chemistry and physics · doi:10.5194/acp-21-2725-2021 · Cited by 150
Ding, K., Huang, X., Ding, A., Wang, M., Su, H., Kerminen, V., Petäjä, T., Tan, Z., Wang, Z., Zhou, D., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26728-4 · Cited by 142
Snider, G., Weagle, C. L., Martin, R. V., van Donkelaar, A., Conrad, K., Cunningham, D., Gordon, C., Zwicker, M., Akoshile, C. O., Artaxo, P. E., et al. (2015) · Atmospheric measurement techniques · doi:10.5194/amt-8-505-2015 · Cited by 133
Self-citationLiu, Y., Koutrakis, P., Kahn, R. A., Turquéty, S., & Yantosca, R. M. (2007) · Journal of the Air & Waste Management Association · doi:10.3155/1047-3289.57.11.1360 · Cited by 110
Meng, X., Hand, J. L., Schichtel, B. A., & Liu, Y. (2018) · Environment International · doi:10.1016/j.envint.2018.10.029 · Cited by 104
He, L., Lin, A., Chen, X., Zhou, H., Zhou, Z., & He, P. (2019) · Remote Sensing · doi:10.3390/rs11040460 · Cited by 104
Foroutan, H., Young, J., Napelenok, S. L., Ran, L., Appel, K. W., Gilliam, R. C., & Pleim, J. (2017) · Journal of Advances in Modeling Earth Systems · doi:10.1002/2016ms000823 · Cited by 99
Liu, J., Zheng, Y., Geng, G., Hong, C., Li, M., Li, X., Liu, F., Tong, D., Wu, R., Zheng, B., et al. (2020) · Atmospheric chemistry and physics · doi:10.5194/acp-20-7783-2020 · Cited by 95
Self-citationAccuracy assessment of CAMS and MERRA-2 reanalysis PM2.5 and PM10 concentrations over China
Ali, M. A., Bilal, M., Wang, Y., Nichol, J. E., Mhawish, A., Qiu, Z., de Leeuw, G., Zhang, Y., Zhan, Y., Liao, K., et al. (2022) · Atmospheric Environment · doi:10.1016/j.atmosenv.2022.119297 · Cited by 89
Qiu, X., Ying, Q., Wang, S., Duan, L., Zhao, J., Xing, J., Ding, D., Sun, Y., Liu, B., Shi, A., et al. (2019) · Atmospheric chemistry and physics · doi:10.5194/acp-19-6737-2019 · Cited by 73
Shi, W., Liu, C., Annesi‐Maesano, I., Norbäck, D., Deng, Q., Huang, C., Qian, H., Zhang, X., Sun, Y., Wang, T., et al. (2020) · Environment International · doi:10.1016/j.envint.2020.106176 · Cited by 70
Jiang, Y., Yang, X., Liu, X., Yang, D., Sun, X., Wang, M., Ding, A., Wang, T., & Fu, C. (2017) · Journal of Geophysical Research Atmospheres · doi:10.1002/2016jd026237 · Cited by 66
Self-citationDao, X., Lin, Y., Cao, F., Di, S.-Y., Hong, Y., Xing, G., Li, J., Fu, P., & Zhang, Y. (2019) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-18-0325.1 · Cited by 63
Zeng, Y., Wang, M., Zhao, C., Chen, S., Liu, Z., Huang, X., & Gao, Y. (2020) · Geoscientific model development · doi:10.5194/gmd-13-2125-2020 · Cited by 62
Meng, X., Garay, M. J., Diner, D. J., Калашникова, О. В., Xu, J., & Liu, Y. (2018) · Atmospheric Environment · doi:10.1016/j.atmosenv.2018.03.019 · Cited by 60
Jin, C., Wang, Y., Li, T., & Yuan, Q. (2022) · Atmospheric Environment · doi:10.1016/j.atmosenv.2022.118972 · Cited by 60
Gao, M. C., Yang, Y., Liao, H., Zhu, B., Zhang, Y., Liu, Z., Lu, X. H., Wang, C., Zhou, Q., Wang, Y., et al. (2021) · Atmospheric chemistry and physics · doi:10.5194/acp-21-11405-2021 · Cited by 27
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Cited by
Feng, C., Shao, Y., Ye, T., Cai, C., Yin, C., Li, X., Liu, H., Ma, H., Yu, B., Qin, M., et al. (2023) · Science of The Total Environment · doi:10.1016/j.scitotenv.2023.166755 · Cited by 33
Metadata
- Authors
- Liu, S., Geng, G., Xiao, Q., Zheng, Y., Liu, X., Cheng, J., & Zhang, Q.
- Venue
- Environmental Science & Technology
- Publisher
- American Chemical Society (ACS)
- Published
- 2022-11-01
- Volume
- 56
- Issue
- 22
- Pages
- 16517-16527
- ISSN
- 0013-936X (ISSN-L)
- 1520-5851
- OpenAlex
- W4307804709
- Cited by
- 359
- References
- 56
- FWCI
- 24.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
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