Zhou Meng-Ge, Yang Yi, Sun Yuan, Zhang Feng-Ying, Li Yong-Hua
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
University of Chinese Academy of Sciences, Beijing 100049, China.
Huan Jing Ke Xue. 2022 Jun 8;43(6):2937-2946. doi: 10.13227/j.hjkx.202109020.
Based on the daily monitoring data of urban air quality in Shandong province from 2016 to 2020, combined with socio-economic data such as population density and urbanization rate, as well as meteorological data such as wind speed, temperature, and relative humidity, the methods of geographic weighted regression (GWR), multiscale geographically weighted regression (MGWR), and wavelet analysis were comprehensively applied to explore the temporal and spatial distribution characteristics of air pollutants and their relationship with socio-economic and meteorological elements. The results showed that:① In the past five years, the air quality in Shandong province has shown an overall improvement trend. Except for ozone, the concentrations of SO, NO, PM, and PM decreased annually. Additionally, their distribution had obvious spatial differences, which was reflected in the lower concentration of air pollutants in coastal areas. ② PM in Shandong province had an extremely significant positive correlation with population density and the proportion of secondary industry (<0.01) but had a very negative correlation with urbanization rate (<0.01). Moreover, there were scale differences in the spatial relationship. The spatial relationship between population density, civil vehicle volume, industrial power consumption, and PM was relatively stable, whereas the spatial heterogeneity of the impact of urbanization rate and the proportion of secondary industry on PM concentration was high. ③ Meteorological factors had different effects on PM in Heze and Weihai. PM in Heze had a stronger correlation with air temperature, relative humidity, and sunshine hours, whereas sea land breeze prevailed in Weihai, resulting in a higher correlation between PM and wind speed. ④ Wavelet analysis showed that the frequency of air pollution in Heze was higher than that in Weihai, approximately one-two weeks/time in winter. In the annual cycle, the PM in Heze lagged behind the wind speed, whereas the PM and wind speed in Weihai were in the same phase. To summarize, there were obvious temporal and spatial differences in air quality in Shandong province, which was comprehensively affected by socio-economic and meteorological factors.
基于2016年至2020年山东省城市空气质量的逐日监测数据，结合人口密度、城市化率等社会经济数据以及风速、温度、相对湿度等气象数据，综合运用地理加权回归（GWR）、多尺度地理加权回归（MGWR）和小波分析方法，探讨空气污染物的时空分布特征及其与社会经济和气象要素的关系。结果表明：①过去五年，山东省空气质量总体呈改善趋势。除臭氧外，SO、NO、PM和PM的浓度逐年下降。此外，其分布存在明显的空间差异，表现为沿海地区空气污染物浓度较低。②山东省PM与人口密度和第二产业比重呈极显著正相关（<0.01），与城市化率呈极显著负相关（<0.01）。而且，空间关系存在尺度差异。人口密度、民用汽车保有量、工业用电量与PM的空间关系相对稳定，而城市化率和第二产业比重对PM浓度影响的空间异质性较高。③气象因素对菏泽和威海的PM影响不同。菏泽的PM与气温、相对湿度和日照时数的相关性较强，而威海海陆风盛行，导致PM与风速的相关性较高。④小波分析表明，菏泽的空气污染频率高于威海，冬季约为1-2周/次。在年周期中，菏泽的PM滞后于风速，而威海的PM与风速同相位。综上所述，山东省空气质量存在明显的时空差异，受社会经济和气象因素综合影响。
