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Air Pollution Characteristics and Meteorological Correlates in Lin’an, Hangzhou, China

机译:杭州临安的空气污染特征与气象的关系

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The concentration and distribution of atmospheric particulate matter depend primarily on the meteorological conditions associated with a fixed pollution source. The effects of meteorological factors on particulate matter have been analyzed on the meteorological seasonal scale, but few researchers have considered the climatic season, which is divided based on the distribution feature of climatic factors. In addition, the hysteresis effect of meteorological factors is easily neglected. Here, we reviewed the characteristics and influential factors of particle pollution based on particle concentration and meteorological data from January 2013 through December 2013. Results from nonparametric tests and Spearman’s nonparametric correlation coefficient showed that particle pollution exhibited a statistically significant seasonal trend. The pollution on workdays was slightly less than that on holidays, but no significant difference was found. The air pressure 1–2 days earlier showed a higher positive correlation with the current particle concentrations (except in winter), and the temperature 2–3 days earlier in summer and fall showed a stronger negative correlation with the particle concentration. Lower moisture and frequent precipitation would significantly reduce the pollution on the current day and the next day (except in summer). The variation of particulate matter concentration in summer exhibited a high-low-high variation, caused mainly by temperature and precipitation; the air quality during the plum rain period was significantly better than that in the period before the plum rain. The fine particle pollution level during the high-temperature and heat wave days was the lowest, after which the concentration increased.
机译:大气颗粒物的浓度和分布主要取决于与固定污染源相关的气象条件。在气象季节尺度上已经分析了气象因素对颗粒物的影响,但很少有研究者考虑气候季节,根据气候因素的分布特征将其划分。另外,很容易忽略气象因素的滞后效应。在这里,我们根据2013年1月至2013年12月的颗粒物浓度和气象数据,回顾了颗粒物污染的特征和影响因素。非参数测试和Spearman的非参数相关系数的结果表明,颗粒物污染表现出具有统计意义的季节性趋势。工作日的污染比假日少,但差异无统计学意义。提前1-2天的气压与当前颗粒浓度呈正相关(冬季除外),夏季和秋季提前2-3天的气温与颗粒浓度呈负相关。较低的湿度和频繁的降雨将显着减少当日和次日(夏季除外)的污染。夏季颗粒物浓度的变化呈现高-低-高的变化,主要是由温度和降水引起的。梅雨期的空气质量明显好于梅雨前的时期。高温和热浪天的细颗粒污染水平最低,然后浓度增加。

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