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• W2017313072 abstract "The purpose of this study was to provide effective strategies for ambient air quality management to ameliorate ambient PM 10 concentrations. The study investigated the association of meteorological parameters with occurrence of PM 10 episodes due to emissions from local sources. Spearman's rank correlations of atmospheric NO 2 and SO 2 and meteorological parameters with daily PM 10 concentrations, monitored in urban centres in Changsha, were conducted. The conditional logistic regression and time-stratified case-crossover were used to analyse effects of different local sources with adjustment for different meteorological parameters. Their association with diurnal hourly ambient PM 10 concentration and occurrence of PM 10 episodes was determined. The results showed that the frequency and risks of occurrence of PM 10 episodes were highest in winter and lowest in summer. An increase in atmospheric NO 2 concentration was illustrated to be more likely to induce PM 10 episode than SO 2 . Temperature and rainfall are key meteorological parameters to be adjusted for pollution mitigation to effectively reduce occurrence risk of PM 10 episodes. The episodic risk could be mitigated by controlling emission sources of SO 2 and NO 2 . Significant reduction in PM 10 concentrations can be achieved when simultaneously adjusted for temperature or rainfall. The episodic risk could be further minimized by controlling the meteorological conditions (e.g. surface temperature, atmospheric pressure and urban ventilation) during early morning period (03:00–06:00) and by controlling fuel use and traffic during late afternoon period (17:00–18:00). Implementation of air quality management strategies proposed should be crucial to mitigate pollution risk of particulate matter episodes and to protect human health and the environment." @default.
• W2017313072 created "2016-06-24" @default.
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• W2017313072 date "2015-04-20" @default.
• W2017313072 modified "2023-09-26" @default.
• W2017313072 title "Strategies for reduction of episodic risk of PM₁₀ by controlling industrial and traffic emissions of SO₂ and NO₂ and meteorological parameters" @default.
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• W2017313072 doi "https://doi.org/10.1177/1420326x15581718" @default.
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