广州市2022年臭氧污染特征与成因分析

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Abstract In this study, observational data of O₃ and its precursors, meteorological observations, and ERA5reanalysis data for 2022 were selected to analyze the characteristics of O₃ pollution in Guangzhou. Utilizing both Observation-Based Modeling (OBM) and backward trajectory models, we identified O₃ generation sensitivity control zones and key sensitive species, and conducted an analysis of O₃ pollution causes from three aspects: O₃ precursor emissions, meteorological conditions, and regional transport. The results indicate that: O₃ generation in Guangzhou is primarily controlled by volatile organic compounds (VOCs) and NO_x-VOCs synergy, with the current VOCs to NO_x emission reduction ratio not being less than 1:1. O₃ generation is most sensitive to oxygen-containing VOCs, followed by biogenic VOCs (BVOCs), alkenes, aromatics, and alkanes. Despite a 14.7% decrease in NO_x and a 30.4% decrease in VOC concentrations in 2022, the effectiveness of local emission reduction in Guangzhou was offset by adverse meteorological conditions such as the strong subtropical high, frequent influences of peripheral circulation from typhoons, and unfavorable meteorological conditions such as enhanced radiation, high temperature, and low humidity, along with regional transport, leading to an increase in O₃ concentrations. During typical O₃ pollution events (September 16~22, 2022), airflow trajectories shifted from northwest and southwest directions to east and southeast directions, making it susceptible to regional transport from surrounding urban areas. Recommendations for future actions include continued efforts to reduce NO_x emissions, promoting a shift in O₃ sensitivity from NO_x-sensitive to NO_x-insensitive, and actively building regional joint prevention and control mechanisms to reduce regional transport contributions.

Key words： Guangzhou ozone pollution Observation Based Model (OBM) precursor meteorological conditions regional transmission

Received: 07 October 2023

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X511

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	HUANG Ji-zhang
	GAO Jian
	YU Mei-fang
	GAO Rui
	PEI Cheng-lei
	YANG Su-xia
	ZHANG Jin-pu
	SONG Wei
	LI lei
	LI Yin-song
	GUO Hao
	YE Zi-ming

Cite this article:

HUANG Ji-zhang,GAO Jian,YU Mei-fang等. Analysis of characteristics and cause of ozone pollution in Guangzhou in 2022[J]. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(6): 3100-3110.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2024/V44/I6/3100

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