Literature DB >> 33773209

Distinct spatiotemporal variation patterns of surface ozone in China due to diverse influential factors.

Mingliang Ma1, Guobiao Yao1, Jianping Guo2, Kaixu Bai3.   

Abstract

A better knowledge of surface ozone variations and the relevant influential factors is of great significance for controlling frequent ozone pollution events. In this study, we first examined the primary variation patterns of surface ozone in space and time across China via a clustering analysis on the basis of daily maximum 8h average surface ozone (MDA8) between 2015 and 2018. Statistical models were then established between MDA8 and a set of influential factors to pinpoint dominant factors contributing to regional MDA8 variations. The clustering results revealed four typical variation patterns of MDA8 in China given distinct pollution levels, seasonality, and long-term trends. Statistical modeling results indicated that the seasonal variability of MDA8 was closely associated with UV radiation and meteorological factors like boundary layer height, temperature and relative humidity. In contrast, the long-term trends of MDA8 were largely linked to ozone precursors and meteorological variables including temperature, relative humidity, and total cloud cover. Moreover, the phenomenal increasing trends of MDA8 in North China were found to be statistically associated with the depletion of nitrogen dioxide (NO2) and carbon monoxide (CO). Specifically, substantial increases in volatile organic compounds (VOCs) along with depletions in NO2 and CO significantly boosted the photochemical ozone formation chain process in a VOC-limited regime like the North China plain. Overall, the inferred linkage in this study provides evidence and clues to help control increasing ozone pollution events in North China.
Copyright © 2021 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Air quality management; Ozone pollution; Spatial clustering; Statistical modeling; Surface ozone

Year:  2021        PMID: 33773209     DOI: 10.1016/j.jenvman.2021.112368

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  3 in total

1.  New Deep Learning Model to Estimate Ozone Concentrations Found Worrying Exposure Level over Eastern China.

Authors:  Sichen Wang; Xi Mu; Peng Jiang; Yanfeng Huo; Li Zhu; Zhiqiang Zhu; Yanlan Wu
Journal:  Int J Environ Res Public Health       Date:  2022-06-11       Impact factor: 4.614

2.  Multi-Year Variation of Ozone and Particulate Matter in Northeast China Based on the Tracking Air Pollution in China (TAP) Data.

Authors:  Hujia Zhao; Ke Gui; Yanjun Ma; Yangfeng Wang; Yaqiang Wang; Hong Wang; Yu Zheng; Lei Li; Lei Zhang; Yuqi Zhang; Huizheng Che; Xiaoye Zhang
Journal:  Int J Environ Res Public Health       Date:  2022-03-23       Impact factor: 3.390

3.  Analysis of Vertical Distribution Changes and Influencing Factors of Tropospheric Ozone in China from 2005 to 2020 Based on Multi-Source Data.

Authors:  Yong Zhang; Yang Zhang; Zhihong Liu; Sijia Bi; Yuni Zheng
Journal:  Int J Environ Res Public Health       Date:  2022-10-03       Impact factor: 4.614

  3 in total

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