Assessing the PM<sub>2.5</sub>–O<sub>3</sub> Correlation and Unraveling Their Drivers in Urban Environment: Insights from the Bohai Bay Region, China
Understanding the correlation between PM<sub>2.5</sub> and O<sub>3</sub> is critical for complex air pollution control. This study comprehensively analyzed PM<sub>2.5</sub> and O<sub>3</sub> pollution characteristics, uncovered spatiotemporal variation...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Atmosphere |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4433/16/5/512 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850257703646003200 |
|---|---|
| author | Yan Nie Yongxin Yan Yuanyuan Ji Rui Gao Yanqin Ren Fang Bi Fanyi Shang Jidong Li Wanghui Chu Hong Li |
| author_facet | Yan Nie Yongxin Yan Yuanyuan Ji Rui Gao Yanqin Ren Fang Bi Fanyi Shang Jidong Li Wanghui Chu Hong Li |
| author_sort | Yan Nie |
| collection | DOAJ |
| description | Understanding the correlation between PM<sub>2.5</sub> and O<sub>3</sub> is critical for complex air pollution control. This study comprehensively analyzed PM<sub>2.5</sub> and O<sub>3</sub> pollution characteristics, uncovered spatiotemporal variations in their correlation, and investigated the driving mechanisms of their association in Dongying, a typical petrochemical city in China’s Bohai Bay region. Results showed that PM<sub>2.5</sub>–O<sub>3</sub> correlation in Dongying exhibited significant seasonal variations, spatial patterns, and concentration threshold effects from 2017 to 2023. PM<sub>2.5</sub> and O<sub>3</sub> showed strong positive correlations in summer, negative in winter, and weak positive in spring/autumn, with strongest links in western areas. The strongest positive PM<sub>2.5</sub>–O<sub>3</sub> correlation occurred in summer when PM<sub>2.5</sub> ≤ 35 μg·m<sup>−3</sup> and O<sub>3</sub> >160 μg·m<sup>−3</sup>, while the strongest negative correlation was exhibited in winter with PM<sub>2.5</sub> > 75 μg·m<sup>−3</sup> and O<sub>3</sub> ≤ 100 μg·m<sup>−3</sup>. Meteorological conditions (T > 20 °C, RH < 30%, wind speed < 1.73 m/s, O<sub>x</sub> > 125 μg·m<sup>−3</sup>) and non-sea-breeze periods enhanced the PM<sub>2.5</sub>–O<sub>3</sub> positive correlation. During the four typical pollution episodes, the positive PM<sub>2.5</sub>–O<sub>3</sub> correlation in summer was propelled by synchronous increases in O<sub>3</sub> and secondary components via shared precursors. In autumn, strong positivity resulted from secondary component–O<sub>3</sub> correlations (r > 0.7) and dominance of secondary formation in PM<sub>2.5</sub>. In winter, the negative correlation stemmed from primary emissions inhibiting photochemistry. Random forest analysis showed that O<sub>x</sub>, RH, and T drove positive PM<sub>2.5</sub>–O<sub>3</sub> correlation via photochemistry in summer, whereas winter primary emissions and NO titration caused negative correlation. This study offers guidance for the collaborative PM<sub>2.5</sub> and O<sub>3</sub> control in the petrochemical cities of the Bay region. |
| format | Article |
| id | doaj-art-dd813861b6ef4bab9e5d3f5aba57bbf7 |
| institution | OA Journals |
| issn | 2073-4433 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-dd813861b6ef4bab9e5d3f5aba57bbf72025-08-20T01:56:20ZengMDPI AGAtmosphere2073-44332025-04-0116551210.3390/atmos16050512Assessing the PM<sub>2.5</sub>–O<sub>3</sub> Correlation and Unraveling Their Drivers in Urban Environment: Insights from the Bohai Bay Region, ChinaYan Nie0Yongxin Yan1Yuanyuan Ji2Rui Gao3Yanqin Ren4Fang Bi5Fanyi Shang6Jidong Li7Wanghui Chu8Hong Li9State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaDongying Municipal Ecology and Environment Bureau, Dongying 257000, ChinaDongying Municipal Ecology and Environment Bureau, Dongying 257000, ChinaState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaState Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, ChinaUnderstanding the correlation between PM<sub>2.5</sub> and O<sub>3</sub> is critical for complex air pollution control. This study comprehensively analyzed PM<sub>2.5</sub> and O<sub>3</sub> pollution characteristics, uncovered spatiotemporal variations in their correlation, and investigated the driving mechanisms of their association in Dongying, a typical petrochemical city in China’s Bohai Bay region. Results showed that PM<sub>2.5</sub>–O<sub>3</sub> correlation in Dongying exhibited significant seasonal variations, spatial patterns, and concentration threshold effects from 2017 to 2023. PM<sub>2.5</sub> and O<sub>3</sub> showed strong positive correlations in summer, negative in winter, and weak positive in spring/autumn, with strongest links in western areas. The strongest positive PM<sub>2.5</sub>–O<sub>3</sub> correlation occurred in summer when PM<sub>2.5</sub> ≤ 35 μg·m<sup>−3</sup> and O<sub>3</sub> >160 μg·m<sup>−3</sup>, while the strongest negative correlation was exhibited in winter with PM<sub>2.5</sub> > 75 μg·m<sup>−3</sup> and O<sub>3</sub> ≤ 100 μg·m<sup>−3</sup>. Meteorological conditions (T > 20 °C, RH < 30%, wind speed < 1.73 m/s, O<sub>x</sub> > 125 μg·m<sup>−3</sup>) and non-sea-breeze periods enhanced the PM<sub>2.5</sub>–O<sub>3</sub> positive correlation. During the four typical pollution episodes, the positive PM<sub>2.5</sub>–O<sub>3</sub> correlation in summer was propelled by synchronous increases in O<sub>3</sub> and secondary components via shared precursors. In autumn, strong positivity resulted from secondary component–O<sub>3</sub> correlations (r > 0.7) and dominance of secondary formation in PM<sub>2.5</sub>. In winter, the negative correlation stemmed from primary emissions inhibiting photochemistry. Random forest analysis showed that O<sub>x</sub>, RH, and T drove positive PM<sub>2.5</sub>–O<sub>3</sub> correlation via photochemistry in summer, whereas winter primary emissions and NO titration caused negative correlation. This study offers guidance for the collaborative PM<sub>2.5</sub> and O<sub>3</sub> control in the petrochemical cities of the Bay region.https://www.mdpi.com/2073-4433/16/5/512correlation between PM<sub>2.5</sub> and O<sub>3</sub>causal investigationmeteorological conditionsatmospheric oxidation capacityprecursorsbay area |
| spellingShingle | Yan Nie Yongxin Yan Yuanyuan Ji Rui Gao Yanqin Ren Fang Bi Fanyi Shang Jidong Li Wanghui Chu Hong Li Assessing the PM<sub>2.5</sub>–O<sub>3</sub> Correlation and Unraveling Their Drivers in Urban Environment: Insights from the Bohai Bay Region, China Atmosphere correlation between PM<sub>2.5</sub> and O<sub>3</sub> causal investigation meteorological conditions atmospheric oxidation capacity precursors bay area |
| title | Assessing the PM<sub>2.5</sub>–O<sub>3</sub> Correlation and Unraveling Their Drivers in Urban Environment: Insights from the Bohai Bay Region, China |
| title_full | Assessing the PM<sub>2.5</sub>–O<sub>3</sub> Correlation and Unraveling Their Drivers in Urban Environment: Insights from the Bohai Bay Region, China |
| title_fullStr | Assessing the PM<sub>2.5</sub>–O<sub>3</sub> Correlation and Unraveling Their Drivers in Urban Environment: Insights from the Bohai Bay Region, China |
| title_full_unstemmed | Assessing the PM<sub>2.5</sub>–O<sub>3</sub> Correlation and Unraveling Their Drivers in Urban Environment: Insights from the Bohai Bay Region, China |
| title_short | Assessing the PM<sub>2.5</sub>–O<sub>3</sub> Correlation and Unraveling Their Drivers in Urban Environment: Insights from the Bohai Bay Region, China |
| title_sort | assessing the pm sub 2 5 sub o sub 3 sub correlation and unraveling their drivers in urban environment insights from the bohai bay region china |
| topic | correlation between PM<sub>2.5</sub> and O<sub>3</sub> causal investigation meteorological conditions atmospheric oxidation capacity precursors bay area |
| url | https://www.mdpi.com/2073-4433/16/5/512 |
| work_keys_str_mv | AT yannie assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT yongxinyan assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT yuanyuanji assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT ruigao assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT yanqinren assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT fangbi assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT fanyishang assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT jidongli assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT wanghuichu assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina AT hongli assessingthepmsub25subosub3subcorrelationandunravelingtheirdriversinurbanenvironmentinsightsfromthebohaibayregionchina |