Title: | "Trend analysis of surface ozone at suburban Guangzhou, China" |
Author(s): | Yin C; Deng X; Zou Y; Solmon F; Li F; Deng T; |
Address: | "Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou, China. Electronic address: yincq@gd121.cn. Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China. Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou, China. Laboratoire d'Aerologie, Centre National de la Recherche Scientifique, Toulouse, France" |
DOI: | 10.1016/j.scitotenv.2019.133880 |
ISSN/ISBN: | 1879-1026 (Electronic) 0048-9697 (Linking) |
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?ª+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?ª++/-?ª+0.04?ª+ppb?ª+year(-1) (R(2)?ª+=?ª+0.00, p?ª+ª+0.05) for P1, and 0.51?ª++/-?ª+0.08?ª+ppb?ª+year(-1) (R(2)?ª+=?ª+0.11, p?ª+ª+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" |
Keywords: | Emission KZ filter Meteorology Ozone trend; |
Notes: | "PubMed-not-MEDLINEYin, Changqin Deng, Xuejiao Zou, Yu Solmon, Fabien Li, Fei Deng, Tao eng Netherlands 2019/08/20 Sci Total Environ. 2019 Dec 10; 695:133880. doi: 10.1016/j.scitotenv.2019.133880. Epub 2019 Aug 13" |