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An analysis of the effects of weather and air pollution on tropospheric ozone using a generalized additive model in Western China: Lanzhou, Gansu

机译:西部广义添加剂模型对对流层臭氧的天气和空气污染影响分析:兰州,甘肃

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摘要

In recent years, near-surface ozone (O-3) concentrations have been increasing, which aggravates O-3 pollution. Due to the environmental threat it poses to human health, O-3 pollution has become a hot topic among researchers. In this paper, we used a generalized additive model (GAM) to evaluate the complex nonlinear relationships between O-3 concentration and the factors influencing O-3 concentration from 2013 to 2017 in Lanzhou in Western China. We considered factors such as long-term trend, seasonality at a quarterly interval, and the weekend effect. The results showed that O-3 concentration in Lanzhou was affected by many factors, and these influencing factors were correlated with each other. In the single-factor model, the adjusted coefficient of determination (R-2) was 0.594, and the total deviance explained of O-3 concentration was 62.3%. We detected significantly nonlinear relationships between O-3 concentration and the influencing factors like air temperature, sunshine hours, wind speed, relative humidity, and the concentrations of NO2 and PM2.5. In particular, air temperature was the main driving factor for O-3 concentration, which explained 24.2% of the variance (F = 350.84). In addition, we built a double-factor model to investigate the interactive influences of these influencing factors on O-3 concentration variation. In the fitted double-factor model, R-2 was 0.636 and the total deviance explained was 68.1%, both of which were higher (i.e., better performance) than that in the single-factor model. Among these studied influencing factors, the interaction between air temperature and air pollutants showed the greatest influence on O-3 concentration variation. The results of this study can be used to assist local environmental authorities to take proactive measures for O-3 pollution control in Lanzhou, Gansu.
机译:近年来,近地表臭氧(O-3)浓度增加,其加剧了O-3污染。由于环境威胁它对人类健康构成,O-3污染已成为研究人员之间的热门话题。在本文中,我们使用了广义添加剂模型(GAM)来评估O-3浓度与影响2013年至2017年兰州兰州兰州浓度的复杂非线性关系。我们考虑了长期趋势,季节性的因素,季节性间隔,周末效应。结果表明,兰州的O-3浓度受许多因素的影响,这些影响因素彼此相关。在单因素模型中,调整后的测定系数(R-2)为0.594,o-3浓度的总偏差为62.3%。我们检测到O-3浓度与气温,阳光小时,风速,相对湿度等影响因素之间的显着非线性关系,以及NO2和PM2.5的浓度。特别地,空气温度是O-3浓度的主要驱动因子,其差异的24.2%(f = 350.84)。此外,我们建立了一种双因素模型,以研究这些影响因素对O-3浓度变异的互动影响。在拟合的双因子模型中,R-2为0.636,所解释的总偏差为68.1%,两者均较高(即,性能更好),比单因素模型更高(即,性能更好)。在这些研究的影响因素中,空气温度和空气污染物之间的相互作用对O-3浓度变异的影响最大。本研究的结果可用于协助当地环境机构在甘肃兰州兰州劳州污染控制采取积极措施。

著录项

  • 来源
    《Atmospheric environment》 |2020年第3期|117342.1-117342.9|共9页
  • 作者单位

    Lanzhou Univ Coll Atmospher Sci Key Lab Semiarid Climate Change Minist Educ Lanzhou 730000 Peoples R China;

    Lanzhou Univ Coll Atmospher Sci Key Lab Semiarid Climate Change Minist Educ Lanzhou 730000 Peoples R China;

    Lanzhou Univ Coll Atmospher Sci Key Lab Semiarid Climate Change Minist Educ Lanzhou 730000 Peoples R China;

    Lanzhou Univ Coll Atmospher Sci Key Lab Semiarid Climate Change Minist Educ Lanzhou 730000 Peoples R China;

    Chinese Acad Sci Inst Atmospher Sci Beijing 10081 Peoples R China;

    Lanzhou Univ Coll Atmospher Sci Key Lab Semiarid Climate Change Minist Educ Lanzhou 730000 Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    O-3 concentration; Influencing factor; Generalized additive model (GAM); Interaction; Meteorological factor;

    机译:O-3浓度;影响因子;广义添加剂模型(GAM);互动;气象因素;

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