Ground-Level Ozone Concentration Variability Analysis in the Karadag Nature Reserve

被引:0
|
作者
Fedorova, E. I. [1 ]
Lapchenko, V. A. [2 ]
Elansky, N. F. [1 ]
Rakitin, V. S. [1 ]
Skorohod, A. I. [1 ]
Vasilyeva, A. V. [1 ]
机构
[1] Russian Acad Sci, Obukhov Inst Atmospher Phys, Moscow 119017, Russia
[2] Russian Acad Sci, Nat Reserve Russian Acad Sci, TI Vyazemsky Karadag Sci Stn, Branch Kovalevsky Inst Biol Southern Seas, Kurortnoye 298188, Russia
基金
俄罗斯科学基金会;
关键词
monitoring of atmospheric composition; tropospheric ozone; ozone precursors; maximum permissible ozone concentrations; long-range transport of impurities; trajectory analysis; remote sensing of the atmosphere; SURFACE OZONE; CHEMISTRY; MOSCOW; GASES;
D O I
10.1134/S0001433824700208
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
This paper presents the results of a study of ground-level ozone concentration variability in Crimea at the background environmental monitoring station (BEMS) of the Karadag State Nature Reserve for 2012-2021 with a more detailed analysis of the last 6 years from 2016 to 2021. A significantly high level of air pollution by ground-level ozone in the observation area was revealed, despite the absence of significant sources of anthropogenic pollution in the vicinity of the station. The relationship between the ground-level ozone concentration and meteorological parameters has been studied, and characteristic wind directions leading to increased levels of ground-level ozone pollution have been established. Intra-annual variations are analyzed, and factors causing a local summer minimum of ground-level ozone concentration in individual years are identified. Using the NOAA HYSPLIT model and ERA5 reanalysis meteorological fields, a spatial analysis of the atmospheric circulation pattern in the region has been carried out. The recurrence of episodes in which the permissible 8-h average ozone concentration level of 100 mu g/m(3), as recommended by World Health Organization (WHO), was exceeded has been assessed, and the possible causes of these episodes are identified. Mechanisms of long-range transport and their contribution to the ozone regime in the station area have been established. Annual trends in ground-level ozone concentration between 2012 and 2021 are assessed as statistically insignificant.
引用
收藏
页码:175 / 186
页数:12
相关论文
共 50 条
  • [1] Multi-objective analysis of ground-level ozone concentration control
    Guariso, G
    Pirovano, G
    Volta, M
    [J]. JOURNAL OF ENVIRONMENTAL MANAGEMENT, 2004, 71 (01) : 25 - 33
  • [2] Modelling ground-level ozone concentration using copulas
    Fernández-Durán, JJ
    [J]. BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2004, 707 : 406 - 413
  • [3] Ground-level ozone
    不详
    [J]. JOCCA-SURFACE COATINGS INTERNATIONAL, 1999, 82 (09): : 436 - 436
  • [4] Estimation of ground-level ozone concentration based on GBRT
    Li, Yi-Fei
    Qin, Kai
    Li, Ding
    Fan, Wen-Zhi
    He, Qin
    [J]. Zhongguo Huanjing Kexue/China Environmental Science, 2020, 40 (03): : 997 - 1007
  • [5] A Comparison of Representations for the Prediction of Ground-Level Ozone Concentration
    Daniels, Benjamin
    Corns, Steven
    Cudney, Elizabeth
    [J]. 2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2012,
  • [6] Variation of Ground-Level Ozone Concentration in Urbanized Area in Malaysia
    Noor, N. Mohamed
    Hasim, N. I. Mohamad
    Yusof, S. Y.
    [J]. EUROINVENT ICIR 2018, 2018, 374
  • [7] The ground-level ozone concentration in forest and urban environments in central Slovakia
    Janik, Rastislav
    Kubov, Martin
    Schieber, Branislav
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2023, 195 (01)
  • [8] A data-driven approach to forecasting ground-level ozone concentration
    Marvin, Dario
    Nespoli, Lorenzo
    Strepparava, Davide
    Medici, Vasco
    [J]. INTERNATIONAL JOURNAL OF FORECASTING, 2022, 38 (03) : 970 - 987
  • [9] The ground-level ozone concentration in forest and urban environments in central Slovakia
    Rastislav Janík
    Martin Kubov
    Branislav Schieber
    [J]. Environmental Monitoring and Assessment, 2023, 195
  • [10] Forecasting ground-level ozone concentration levels using machine learning
    Du, Jianbang
    Qiao, Fengxiang
    Lu, Pan
    Yu, Lei
    [J]. RESOURCES CONSERVATION AND RECYCLING, 2022, 184