京津冀地区PM_(2.5)空间分布特征及其影响因素分析

Spatial distribution characteristics of PM_(2.5)and its influencing factors in Beijing-Tianjin-Hebei region

文章选取2016—2020年京津冀地区的PM_(2.5)监测站点数据为研究对象,分析京津冀地区PM_(2.5)浓度的时空分布特征,并构建地理加权回归模型(GWR)分析PM_(2.5)浓度受各因素影响的空间变化特征。结果表明:(1)2016—2020年京津冀地区的PM_(2.5)浓度基本呈下降趋势,2018与2020年的PM_(2.5)浓度最低且污染区域最少;PM_(2.5)浓度表现出明显的季节变化特征,春夏季节较低,冬季最高。(2)京津冀北部的张家口、承德和秦皇岛为PM_(2.5)浓度低值区,南部的石家庄、邢台、邯郸、保定和衡水为PM_(2.5)浓度高值区。(3)京津冀地区PM_(2.5)浓度空间分布存在明显的聚集特征,北部保持“低-低”聚集,南部保持“高-高”聚集,非显著区域在中间位置,呈现倒“U”型分布。(4)不同的影响因素对于PM_(2.5)浓度的影响程度有着较为明显的空间差异性。

Fine particulate matter(PM_(2.5)) has become a major air pollutant affecting Air Quality in China.In this paper,the spatio-temporal effects of PM_(2.5) concentrations in Beijing-Tianjin-Hebei region were analyzed from 2016 to 2020,and the spatial variation characteristics of PM_(2.5) concentrations affected by various factors were analyzed by a geographically weighted regression model(GWR).The results showed that from 2016 to 2020,the PM_(2.5) concentration in the Beijing-Tianjin-Hebei region basically showed a downward trend.In 2018 and 2020,the PM_(2.5) concentration was the lowest and the polluted area was the least with a seasonal characteristis of low in spring&summer and highest in winter.Zhangjiakou,Chengde and Qinhuangdao in the north of Beijing-Tianjin-Hebei were low-value areas for PM_(2.5) concentrations,and Shijiazhuang,Xingtai,Handan,Baoding and Hengshui in the south were high-value areas for PM_(2.5) concentrations.There were obvious aggregation characteristics in the spatial distribution of PM_(2.5) concentration in the Beijing-Tianjin-Hebei region,with the northern part maintaining"low-low"aggregation,the southern part maintaining"high-high"aggregation,and the non-significant area in the middle position showing an inverted "U-shaped"distribution.Different influencing factors had obvious spatial differences in the degree of influence of PM_(2.5) concentration.