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To improve the forecasting accuracy, the use of nudging as the data assimilation method, combined with extremely randomized trees (ExRT) as the machine learning method, was developed and applied to adjust the anthropogenic emissions in the Community Multiscale Air Quality modeling system (CMAQ). This nudging\u2013ExRT method can iterate with the forecast and is suitable for linear and nonlinear emissions. For example, an episode between 15 and 30 January 2019 was simulated for China\u2019s Beijing\u2013Tianjin\u2013Hebei (BTH) region. For PM2.5, the correlation coefficient of the site averaged concentration (Ra) increased from 0.85 to 0.94, and the root mean square error (RMSEa) decreased from 24.41 to 9.97 \u00b5g\/m3. For O3, the Ra increased from 0.75 to 0.81, and the RMSEa decreased from 13.91 to 12.07 \u00b5g\/m3. These results showed that nudging\u2013ExRT can significantly improve forecasting skills and can be applied to routine air quality forecasting in the future.<\/jats:p>","DOI":"10.3390\/rs15061711","type":"journal-article","created":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T08:36:16Z","timestamp":1679474176000},"page":"1711","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A Data Assimilation Method Combined with Machine Learning and Its Application to Anthropogenic Emission Adjustment in CMAQ"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3003-5549","authenticated-orcid":false,"given":"Congwu","family":"Huang","sequence":"first","affiliation":[{"name":"Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China"},{"name":"School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China"}]},{"given":"Tao","family":"Niu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Severe Weather and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}]},{"given":"Hao","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Transportation Meteorology of China Meteorological Administration, Nanjing Joint Institute for Atmospheric Sciences, Nanjing 210041, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7153-7567","authenticated-orcid":false,"given":"Yawei","family":"Qu","sequence":"additional","affiliation":[{"name":"College of Intelligent Science and Control Engineering, Jinling Institute of Technology, Nanjing 211169, China"}]},{"given":"Tijian","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China"}]},{"given":"Mengmeng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China"}]},{"given":"Rong","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Resources and Environmental Science, Hubei University, Wuhan 430062, China"}]},{"given":"Hongli","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Severe Weather and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,22]]},"reference":[{"key":"ref_1","unstructured":"Ministry of Ecology and Environment, The People\u2019s Republic of China (2021, May 01). 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