Study of the meteorological influence on ozone in urban areas and their use in assessing ozone trends in all seasons from 2009 to 2015 in Tianjin, China
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Ozone pollution in urban areas has increasingly become a topic of intense research in China. Assessing the impact of emission control strategies on O3 levels is complicated by the disturbance of meteorological factors. This study employs a statistical methodology named generalized additive model (GAM) to characterize the relationship between meteorological factors and ozone levels as well as to meteorologically adjust the ozone trends in Tianjin from 2009 to 2015. The results indicate that the afternoon temperature and the morning solar radiation are the leading meteorological factors controlling O3 in Tianjin. GAM proves to be an effective tool in predicting ozone levels, because it could capture 40–77% of the variance in the daily ozone maxima for different seasons. Only 3–5 parameters are incorporated into the final model for each season. During summer months, the most important explanatory variables are those influencing the photochemical production. Whereas in winter, ozone destruction by titration with NO is the dominant mechanism affecting the O3 levels. After adjustment for meteorological effect, general upward trends are evident in ozone levels, which is − 0.34, 0.97, 0.70 and 0.12 ppb year−1 in spring, summer, autumn and winter, respectively, indicating that the emission reduction strategies in Tianjin from 2009 to 2015 appear to be more beneficial in reducing the effect of O3 loss using titration rather than mitigating the photochemical pollution. The clear rising tendency of yearly medians of the meteorologically adjusted ozone (0.24 ppb year−1) strongly suggests formulating a specialized mitigation strategy for regional O3 pollution.
This work was funded by National Key R&D Program of China (2016YFC0203302), National Science and Technology Program of China (41771242), the Public Welfare Projects for Environmental Protection (201409001), and the Scientific research project of Tianjin Meteorological Bureau (201761bsjj06).
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