Vertical distribution of ozone in spring based on two high tower observations over the Pearl River Delta, China

被引:0
|
作者
Chen, Hongying [1 ,2 ]
Lu, Xiao [1 ,2 ]
Wang, Haichao [1 ,2 ]
Pei, Chenglei [3 ]
Qiu, Xiaonuan [3 ]
Gao, Ruiquan [4 ]
Wang, Chunlin [2 ,5 ]
Ab, Shaojia Fan
机构
[1] Sun Yat Sen Univ, Sch Atmospher Sci, Zhuhai 519082, Peoples R China
[2] Minist Educ, Key Lab Trop Atmosphere Ocean Syst, Southern Marine Sci & Engn Guangdong Lab, Guangdong Prov Observat & Res Stn Climate Environm, Zhuhai 519082, Peoples R China
[3] Environm Monitoring Ctr, Guangzhou Sub Branch Guangdong Ecol, Guangzhou 510060, Peoples R China
[4] Meteorol Bur Shenzhen Municipal, Shenzhen Natl Climate Observ, Shenzhen 518040, Peoples R China
[5] Guangzhou Climate & Agrometeorol Ctr, Guangzhou 511430, Peoples R China
关键词
Ozone; Vertical distribution; Two tall towers; Spring; Pearl River Delta; ATMOSPHERIC PARTICULATE MATTER; BOUNDARY-LAYER; ANTHROPOGENIC EMISSIONS; GROUND-LEVEL; POLLUTION; PM2.5; IMPACTS; TIANJIN; SUMMER; EVENTS;
D O I
10.1016/j.atmosenv.2024.120772
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study investigates the vertical distribution characteristics of ozone (O3) in the Pearl River Delta (PRD) region during spring, utilising observational data from two tall towers in urban and suburban areas of the PRD, i.e., the 600 m high Canton Tower and the 356 m high Shenzhen Meteorology Gradient Tower (SZMGT), between 2018 and 2020. The observations indicate that the peak times of O3 concentrations differ under polluted and clean conditions, with polluted conditions showing 1-3 h later peaks compared with clean conditions. The diurnal variation in the O3 concentration is more pronounced at the SZMGT than at the Canton Tower. The O3 vertical gradients differ between the two towers, with the Canton Tower showing larger daytime gradients and the SZMGT showing larger nighttime gradients under polluted conditions. The vertical O3 distribution patterns are categorised into three types: Polluted, Moderate, and Good levels. The O3 concentration initially rises with altitude and then decreases under polluted conditions. Elevated O3 is observed in the lower planetary boundary layer (PBL), approximately between 110 and 210 m in height, where the concentration is 1.1-1.4 times higher than the surface level. Both the Moderate and Good levels occur under clean conditions, in which the O3 of the Canton Tower increases with altitude, whereas the O3 of the SZMGT first increases and then decreases with altitude. The correlation between O3 and the meteorological conditions (temperature, relative humidity, wind direction, and wind speed) decreases with increasing altitude. The cluster analysis of backward trajectories identifies three main transport paths affecting the O3 levels: northeasterly continental, southerly oceanic, and easterly coastal paths. Combining the observations from O3 lidar in Guangzhou and Shenzhen and two additional cities within the PRD region, Foshan and Zhongshan, the analysis of a typical pollution case indicates that different cities have different local chemical generation and regional transport contributions to O3 pollution. A conceptual model reflecting the horizontal transport paths and vertical structures of O3 pollution in the spring over the PRD is proposed, which enhances our understanding of the O3 vertical distribution in different cities and contributes to the analysis of the O3 pollution mechanism in the PRD agglomeration.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] Characteristics of Aerosol Vertical Distribution over the Yangtze River Delta Region of China in 2018
    Shen J.
    Cao N.-W.
    Huanjing Kexue/Environmental Science, 2019, 40 (11): : 4743 - 4754
  • [32] Evaluation and intercomparison of ozone simulations by Models-3/CMAQ and CAMx over the Pearl River Delta
    SHEN Jin
    College of Environmental Sciences and Engineering
    Science China(Chemistry), 2011, (11) : 1789 - 1800
  • [33] Evaluation and intercomparison of ozone simulations by Models-3/CMAQ and CAMx over the Pearl River Delta
    Jin Shen
    XueSong Wang
    JinFeng Li
    YunPeng Li
    YuanHang Zhang
    Science China Chemistry, 2011, 54 : 1789 - 1800
  • [34] Vertical distribution of aerosol mass concentration over Pearl River Delta observed by Lidar during autumn and winter
    Wu Y.
    Deng R.
    Qin Y.
    Wang C.
    Liang Y.
    Xiong L.
    Yaogan Xuebao/Journal of Remote Sensing, 2020, 24 (03): : 302 - 318
  • [35] Spatial Distribution and Source Apportionment of Soil Heavy Metals in Pearl River Delta, China
    Yin, Guangcai
    Zhu, Hanghai
    Chen, Zhiliang
    Su, Chuanghong
    He, Zechen
    Chen, Xinglin
    Qiu, Jinrong
    Wang, Tieyu
    SUSTAINABILITY, 2021, 13 (17)
  • [36] Numerical simulations for the sources apportionment and control strategies of PM2.5 over Pearl River Delta, China, part II: Vertical distribution and emission reduction strategies
    Deng, Tao
    Huang, Yeqi
    Li, Zhenning
    Wang, Nan
    Wang, Shiqiang
    Zou, Yu
    Yin, Chanqin
    Fan, Shaojia
    SCIENCE OF THE TOTAL ENVIRONMENT, 2018, 634 : 1645 - 1656
  • [37] Aerosol optical thickness over Pearl River Delta region, China
    Xiao, Z. Y.
    Jiang, H.
    Song, X. D.
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 38 (01) : 258 - 272
  • [38] Effect of atmospheric aerosol on surface ozone variation over the Pearl River Delta region
    Deng XueJiao
    Zhou XiuJi
    Wu Dui
    Tie XueXi
    Tan HaoBo
    Li Fei
    Bi XueYan
    Deng Tao
    Jiang DeHai
    SCIENCE CHINA-EARTH SCIENCES, 2011, 54 (05) : 744 - 752
  • [39] Role of photoexcited nitrogen dioxide chemistry on ozone formation and emission control strategy over the Pearl River Delta, China
    Zhang, Rui
    Sarwar, Golam
    Fung, Jimmy C. H.
    Lau, Alexis K. H.
    ATMOSPHERIC RESEARCH, 2013, 132 : 332 - 344
  • [40] Use of high-resolution precipitation observations in quantifying the effect of urban extent on precipitation characteristics for different climate conditions over the Pearl River Delta, China
    Wang, Dashan
    Wang, Dagang
    Qi, Xiangyan
    Liu, Lin
    Wang, Xianwei
    ATMOSPHERIC SCIENCE LETTERS, 2018, 19 (06):