Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, China
This study investigates the climatic background of winter PM2.5 (particulate matter with a diameter of 2.5 micrometers or smaller) concentrations in Hubei Province (DJF-HBPMC) and evaluates its predictability. The key findings are as follows: (1) Elevated DJF-HBPMC levels are associated with an uppe...
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2025-01-01
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| author | Yuanyue Huang Zijun Tang Zhengxuan Yuan Qianqian Zhang |
| author_facet | Yuanyue Huang Zijun Tang Zhengxuan Yuan Qianqian Zhang |
| author_sort | Yuanyue Huang |
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| description | This study investigates the climatic background of winter PM2.5 (particulate matter with a diameter of 2.5 micrometers or smaller) concentrations in Hubei Province (DJF-HBPMC) and evaluates its predictability. The key findings are as follows: (1) Elevated DJF-HBPMC levels are associated with an upper-tropospheric northerly anomaly, a deepened southern branch trough (SBT) that facilitates southwesterly flow into central and eastern China, and a weakened East Asian winter monsoon (EAWM), which reduces the frequency and intensity of cold air intrusions. Near-surface easterlies and an anomalous anticyclonic circulation over Hubei contribute to reduced precipitation, thereby decreasing the dispersion of pollutants and leading to higher PM2.5 concentrations. (2) Significant correlations are observed between DJF-HBPMC and sea surface temperature (SST) anomalies in specific oceanic regions, as well as sea-ice concentration (SIC) anomalies near the Antarctic. For the atmospheric pattern anomalies over Hubei Province, the North Atlantic SST mode (NA) promotes the southward intrusion of northerlies, while the Northwest Pacific (NWP) and South Pacific (SPC) SST modes enhance wet deposition through increased precipitation, showing a negative correlation with DJF-HBPMC. Conversely, the South Atlantic–Southwest Indian Ocean SST mode (SAIO) and the Ross Sea sea-ice mode (ROSIC) contribute to more stable local atmospheric conditions, which reduce pollutant dispersion and increase PM2.5 accumulation, thus exhibiting a positive correlation with DJF-HBPMC. (3) A multiple linear regression (MLR) model, using selected seasonal SST and SIC indices, effectively predicts DJF-HBPMC, showing high correlation coefficients (CORR) and anomaly sign consistency rates (AS) compared to real-time values. (4) In daily HBPMC forecasting, both the Reversed Unrestricted Mixed-Frequency Data Sampling (RU-MIDAS) and Reversed Restricted-MIDAS (RR-MIDAS) models exhibit superior skill using only monthly precipitation, and the RR-MIDAS offers the best balance in prediction accuracy and trend consistency when incorporating monthly precipitation along with monthly SST and SIC indices. |
| format | Article |
| id | doaj-art-65642a9633844f02a3791acaf58d20b1 |
| institution | Kabale University |
| issn | 2073-4433 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-65642a9633844f02a3791acaf58d20b12025-01-24T13:21:51ZengMDPI AGAtmosphere2073-44332025-01-011615210.3390/atmos16010052Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, ChinaYuanyue Huang0Zijun Tang1Zhengxuan Yuan2Qianqian Zhang3School of Economics and Management, China University of Geosciences, Wuhan 430078, ChinaWuhan Regional Climate Center, Hubei Meteorological Service, Wuhan 430074, ChinaWuhan Regional Climate Center, Hubei Meteorological Service, Wuhan 430074, ChinaDepartment of Finance and Asset Management, China University of Geosciences, Wuhan 430074, ChinaThis study investigates the climatic background of winter PM2.5 (particulate matter with a diameter of 2.5 micrometers or smaller) concentrations in Hubei Province (DJF-HBPMC) and evaluates its predictability. The key findings are as follows: (1) Elevated DJF-HBPMC levels are associated with an upper-tropospheric northerly anomaly, a deepened southern branch trough (SBT) that facilitates southwesterly flow into central and eastern China, and a weakened East Asian winter monsoon (EAWM), which reduces the frequency and intensity of cold air intrusions. Near-surface easterlies and an anomalous anticyclonic circulation over Hubei contribute to reduced precipitation, thereby decreasing the dispersion of pollutants and leading to higher PM2.5 concentrations. (2) Significant correlations are observed between DJF-HBPMC and sea surface temperature (SST) anomalies in specific oceanic regions, as well as sea-ice concentration (SIC) anomalies near the Antarctic. For the atmospheric pattern anomalies over Hubei Province, the North Atlantic SST mode (NA) promotes the southward intrusion of northerlies, while the Northwest Pacific (NWP) and South Pacific (SPC) SST modes enhance wet deposition through increased precipitation, showing a negative correlation with DJF-HBPMC. Conversely, the South Atlantic–Southwest Indian Ocean SST mode (SAIO) and the Ross Sea sea-ice mode (ROSIC) contribute to more stable local atmospheric conditions, which reduce pollutant dispersion and increase PM2.5 accumulation, thus exhibiting a positive correlation with DJF-HBPMC. (3) A multiple linear regression (MLR) model, using selected seasonal SST and SIC indices, effectively predicts DJF-HBPMC, showing high correlation coefficients (CORR) and anomaly sign consistency rates (AS) compared to real-time values. (4) In daily HBPMC forecasting, both the Reversed Unrestricted Mixed-Frequency Data Sampling (RU-MIDAS) and Reversed Restricted-MIDAS (RR-MIDAS) models exhibit superior skill using only monthly precipitation, and the RR-MIDAS offers the best balance in prediction accuracy and trend consistency when incorporating monthly precipitation along with monthly SST and SIC indices.https://www.mdpi.com/2073-4433/16/1/52PM2.5 concentrations in Hubei provinceclimatic backgroundseasonal SST and SIC indicesmultiple linear regressionmixed-frequency data sampling |
| spellingShingle | Yuanyue Huang Zijun Tang Zhengxuan Yuan Qianqian Zhang Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, China Atmosphere PM2.5 concentrations in Hubei province climatic background seasonal SST and SIC indices multiple linear regression mixed-frequency data sampling |
| title | Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, China |
| title_full | Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, China |
| title_fullStr | Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, China |
| title_full_unstemmed | Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, China |
| title_short | Climatic Background and Prediction of Boreal Winter PM2.5 Concentrations in Hubei Province, China |
| title_sort | climatic background and prediction of boreal winter pm2 5 concentrations in hubei province china |
| topic | PM2.5 concentrations in Hubei province climatic background seasonal SST and SIC indices multiple linear regression mixed-frequency data sampling |
| url | https://www.mdpi.com/2073-4433/16/1/52 |
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