【摘要】 基于2014—2018年高密市大气监测数据,分析了SO₂、NO₂、PM₁₀、PM_2.5浓度的变化特征及成因,对四项污染物及降雨量进行了相关性分析,利用GM（1,1）模型对高密市未来空气质量进行了预测。结果表明,2014—2018年高密市环境空气中SO₂、NO₂、PM₁₀、PM_2.5年际变化呈现出逐年下降趋势;污染物月均值变化均为冬春季浓度高,夏秋季浓度低;通过相关性分析发现,环保政策对高密市空气质量总体改善起到了决定性作用,自然地理因素对高密市大气污染物月均值的变化影响明显。更多还原

【Abstract】 Based on the air automatic monitoring date of Gaomi from 2014 to 2018, the variation characteristics of SO2, NO2, PM10 and PM2.5 concentrations were analyzed, the correlation analysis of the four pollutants and rainfall were analyzed, and the air quality in Gaomi city was predicted by GM( 1,1) model. Results showed that the concentration of SO2, NO2, PM10, PM2.5 in Gaomi city showed a downward trend from 2014 to 2018. SO2, NO2, PM10 and PM2.5 exhibited obvious monthly differences in concentrations, with higher concentrations in winter but lower concentrations in summer. Through correlation analysis, it is found that environmental policies has played a decisive role in the improvement of air quality in the past five years. Natural geographical factors had obvious influence on the monthly changes of air pollutants.更多还原