重庆市北碚区空气质量改善效果评估分析

基于2014—2020年重庆市中心城区北碚区环境监测数据及地面观测气象要素，分析了北碚区大气污染特征，利用KNN算法建立大气污染的评估模型，对空气质量改善效果进行评估。结果表明，重庆市中心城区北碚区的PM_2.5浓度逐年呈明显下降趋势，O₃浓度除夏季有一个弱的下降趋势外，其余3个季节和年平均值整体均呈上升趋势。全年以优良天气为主且呈增加趋势。O₃与气温、日照时间呈正相关，与相对湿度呈负相关性，PM_2.5与气温、降水及风速呈负相关。基于KNN算法对空气质量改善状况评估表明，减排对O₃污染平均贡献率在-4.7%左右，对PM_2.5污染平均贡献率为-52%,气象条件对O₃污染的平均贡献率在17%左右，对PM_2.5污染的平均贡献率在-7%左右。该大气污染评估模型能够有效地评估空气改善效果。

Evaluation and Analysis on the Effect of Air Quality Improvement in Beibei District of Chongqing City

Based on the environmental monitoring data and surface meteorological observation elements of Beibei District,the central urban area of Chongqing from 2014 to 2020,the air pollution characteristics of the district are analyzed and the effectiveness of air quality improvements is evaluated by using the KNN algorithm to establish the assessment model of air pollution.It is found that the PM_2.5 concentration in Beibei District,the central urban area of Chongqing,is obviously decreasing year by year,and the O₃ concentration is increasing overall in the other three seasons and annual averages,except for a slight downward trend in summer.Throughout the year,fine weather dominates and shows an increasing trend.O₃ is positively correlated with temperature and sunshine conditions,negatively correlated with relative humidity,and PM_2.5 is negatively correlated with temperature,precipitation,and wind speed.The assessment of air quality improvement status based on the KNN algorithm shows that the average contribution of emission reduction to ozone pollution is about -4.7% and to PM_2.5 pollution is -52%,while the average contribution of meteorological conditions to O₃ pollution is about 17% and to PM_2.5 pollution is about -7%.This air pollution assessment model can effectively evaluate the effectiveness of air quality improvements.