Literature DB >> 31425992

Trend analysis of surface ozone at suburban Guangzhou, China.

Changqin Yin1, Xuejiao Deng2, Yu Zou3, Fabien Solmon4, Fei Li3, Tao Deng3.   

Abstract

The long-term variations of ozone are the combined results of climate change and air quality management. As Guangzhou is under the influence of both subtropical monsoon climate and rapid economic development, the ozone trend in recent years is uncertain. This paper presents the trend analysis of maximum daily average 8 h (MDA8) ozone and daily meteorological observations in Guangzhou from 2008 to 2018, using the Kolmogorov-Zurbenko (KZ) filter method. The observations were conducted at two sites in suburban Guangzhou, thus the datasets were processed in two periods. The first period (P1) is from 2008 to 2013, and the second period (P2) is from 2014 to 2018. Results show that the KZ filter method separates the short-term, seasonal, and long-term components efficiently, leaving a covariance term of 7.3% (5.4%) for P1 (P2). Through linear regression of long-term components, the trends were inferred as -0.06 ± 0.04 ppb year-1 (R2 = 0.00, p < 0.05) for P1, and 0.51 ± 0.08 ppb year-1 (R2 = 0.11, p < 0.05) for P2. It is found that the solar radiation has the strongest impact on ozone. With inclusion of temperature, relative humidity, and wind speed, these four meteorological factors held 71% (76%) variability in baseline ozone (sum of seasonal and long-term ozone) for P1 (P2). After applying the KZ filter method, the results reveal that the variance contribution of emission to long-term ozone variation is larger than that of meteorology in P1, while smaller in P2. Furthermore, 59% of the emission-induced ozone change in P2 could be explained by nitrogen dioxide variation, and their inverse correlation suggests that Guangzhou is mainly under volatile organic compounds-limited regime, despite continuous nitrogen oxides reduction.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Emission; KZ filter; Meteorology; Ozone trend

Year:  2019        PMID: 31425992     DOI: 10.1016/j.scitotenv.2019.133880

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

1.  Investigation of PM2.5 pollution during COVID-19 pandemic in Guangzhou, China.

Authors:  Luyao Wen; Chun Yang; Xiaoliang Liao; Yanhao Zhang; Xuyang Chai; Wenjun Gao; Shulin Guo; Yinglei Bi; Suk-Ying Tsang; Zhi-Feng Chen; Zenghua Qi; Zongwei Cai
Journal:  J Environ Sci (China)       Date:  2021-07-15       Impact factor: 5.565

2.  Integrated process analysis retrieval of changes in ground-level ozone and fine particulate matter during the COVID-19 outbreak in the coastal city of Kannur, India.

Authors:  Fei Ye; Dipesh Rupakheti; Lin Huang; Nishanth T; Satheesh Kumar Mk; Lin Li; Valsaraj Kt; Jianlin Hu
Journal:  Environ Pollut       Date:  2022-05-16       Impact factor: 9.988

3.  Analysis of the meteorological factors affecting the short-term increase in O3 concentrations in nine global cities during COVID-19.

Authors:  Zhongsong Bi; Zhixiang Ye; Chao He; Yunzhang Li
Journal:  Atmos Pollut Res       Date:  2022-08-17       Impact factor: 4.831

4.  Surface ozone changes during the COVID-19 outbreak in China: An insight into the pollution characteristics and formation regimes of ozone in the cold season.

Authors:  Lei Tong; Yu Liu; Yang Meng; Xiaorong Dai; Leijun Huang; Wenxian Luo; Mengrong Yang; Yong Pan; Jie Zheng; Hang Xiao
Journal:  J Atmos Chem       Date:  2022-10-07       Impact factor: 3.360

  4 in total

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