Investigating the causes and reduction approaches of nocturnal ozone increase events over Tai ' an in the North China Plain

被引:0
|
作者
Li, Jiayi [1 ]
Wang, Shanshan [1 ,2 ]
Yang, Tongsuo [3 ]
Zhang, Sanbao [1 ]
Zhu, Jian [1 ]
Xue, Ruibin [1 ]
Liu, Jiaqi [1 ]
Li, Xiaomeng [4 ]
Ge, Yanzhen [4 ]
Zhou, Bin [1 ,2 ,5 ]
机构
[1] Fudan Univ, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Preve, Shanghai 200438, Peoples R China
[2] Inst Ecochongming IEC, 20 Cuiniao Rd, Shanghai 202162, Peoples R China
[3] Shandong Acad Environm Sci Co Ltd, Jinan 250000, Peoples R China
[4] Taian Ecol Environm Bur, Taian Ecol Environm Protect & Control Ctr, Tai An 271000, Peoples R China
[5] Fudan Univ, Inst Atmospher Sci, Shanghai 200433, Peoples R China
基金
上海市自然科学基金; 中国国家自然科学基金;
关键词
Nocturnal O 3 increase; Machine learning; DOAS; Meteorological transport; Chemical reactions; PEARL RIVER DELTA; LONG-TERM TREND; SURFACE OZONE; QUANTITATIVE IMPACTS; TROPOSPHERIC OZONE; SENSITIVITY; TRANSPORT; POLLUTION; CHEMISTRY; MODEL;
D O I
10.1016/j.atmosres.2024.107499
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
China 's O 3 pollution events continue to be frequent, and accurately understanding the sources and sinks of O 3 pollution is crucial. Previous research predominantly focused on controlling O 3 pollution through daytime photochemical production, overlooking the significant impact of nocturnal high O 3 values on the subsequent days ' O 3 concentrations. Understanding the causes of nocturnal O 3 pollution and implementing effective control measures are essential for O 3 pollution alleviation. In light of this, we utilized clustering analysis, combined with meteorological and chemical factors to comprehend the nocturnal variation characteristics and mechanisms of nocturnal O 3 increase (NOI) events in Tai 'an from July 2021 to June 2022. The results qualitatively identified that three clusters have distinct influencing factors: horizontal transport predominantly drives NOI flucts , meanwhile, NOI decline events, mainly occurring in summer, experienced more intense photochemical reactions. For NOI stable events, primarily observed in spring, there was greater downward transport of high -altitude O 3 and more intense titration reactions. Further, using interpretable machine learning models, we quantitatively assessed the contributions of several factors to nocturnal O 3 . The results reveal that nocturnal titration is the predominant factor, followed by the accumulation of daytime photochemical generation. Additionally, we explored approaches for reducing daytime nitrogen dioxide (NO 2 ) and formaldehyde (HCHO), quantifying their impact on nocturnal O 3 concentrations. The results indicate that reducing emissions of HCHO and NO 2 can effectively lower O 3 levels in NOI decline and focusing on reducing HCHO emissions proves to be more beneficial in NOI stable events, with NOI flucts events falling in between these two clusters. Targeted implementation of diverse reduction approaches and proportions in different NOI clusters can more effectively mitigate the occurrence of nocturnal O 3 pollution, thereby influencing the O 3 levels of the following day.
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页数:11
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