川渝地区空气质量时空分布格局及影响因素
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国家重点研发计划项目(2016YFC0500205);昆仑英才高端创新人才项目;国家自然科学青年基金项目(41701475)


Spatio-temporal distribution pattern and influencing factors of air quality in Sichuan-Chongqing region
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National Key Research and Development Program of China, No. 2016YFC0500205; Kunlun Yingcai High-end Innovative Talents Project;National Natural Science Foundation of China, No. 41701475

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    摘要:

    川渝地区尤其是四川盆地已成为我国空气污染最严重的地区之一,基于2018-2019年川渝地区128个城市站和71个县级站空气质量监测及自然与社会经济数据,采用全局和局部莫兰指数分析了川渝地区空气质量指数(AQI)和不同空气质量分指数(IAQI)的时空格局,并采用偏最小二乘回归(PLSR)从较为宏观的尺度综合分析了川渝地区空气污染的主要驱动因素。研究结果表明:(1)川渝地区空气质量整体为良,主要污染物为O3,其次为PM10和PM2.5。盆地区与高原区的主要污染物分别为PM2.5和O3;(2) AQI及PM2.5、PM10、NO2呈"U"型变化,春冬季最高,夏秋季最低;O3则在内部两区域都大致呈倒" U"型变化,但峰值分布时间与持续时长明显不同;SO2和CO年内无明显变化;(3)各污染物具有明显的空间聚集性特征,AQI及PM10、PM2.5、NO2、O3的高-高聚集区分布在盆地西部、中部和南部;(4)川渝地区不同污染物所受主要影响因素存在差异,PM2.5受风速、太阳辐射、气温、相对湿度与城镇化率等影响突出,PM10主要受风速和相对湿度影响,O3与城镇化率、人口密度、人均GDP以及植被状况(NDVI)关系密切。研究结果可为川渝地区的空气质量时空分布规律及形成机制的认识以及有关部门的环境保护政策制定提供参考。

    Abstract:

    Sichuan-Chongqing region, especially Sichuan Basin, has become one of the most serious air pollution areas in China. It is of great significance to understand the spatio-temporal pattern of air quality and its formation mechanism accurately in this area for the formulation of environmental protection policies. Based on the air monitoring data at 128 city stations and 71 county stations in Sichuan-Chongqing region from 2018 to 2019, this paper analyzed the spatio-temporal patterns of Air Quality Index (AQI) and Individual Air Quality Index (IAQI) in Sichuan-Chongqing region using global and local Moran's index, and explored the main driving factors of air pollution through Partial Least Squares Regression (PLSR) method. The influencing factors included annual average wind speed, annual average temperature, annual average relative humidity, annual total precipitation, Normalized Difference Vegetation Index (NDVI), annual average solar radiation, population density, urbanization rate, secondary industry proportion and per capita GDP. The results showed that (1) the air quality in Sichuan-Chongqing region was generally moderate, and O3 was the primary pollutant, followed by PM10 and PM2.5. The primary pollutant in the basin and plateau were PM2.5 and O3, respectively. (2) The AQI, PM2.5, PM10 and NO2 showed "U" shape with the highest value in spring and winter but the lowest value in summer and autumn; O3 showed "inverted U" shape, and the peak and duration time of the inner two regions were obviously different. SO2 and CO indicated no obvious variation within a year. (3) Each pollutant had obviously spatial autocorrelation characteristics. For AQI, PM10, PM2.5, NO2 and O3, high-high clusters were found in the western, central and southern parts of the basin region. Some low-low clusters were mostly distributed in the plateau area. (4) The driving factors of different pollutants in Sichuan-Chongqing region were different. PM2.5 was significantly affected by wind speed, solar radiation, air temperature, relative humidity and urbanization rate; PM10 was significantly affected by wind speed and relative humidity; O3 was closely related to urbanization rate, population density, per capita GDP and vegetation cover condition represented by NDVI. PM2.5 pollution in the basin area may be related to climatic conditions such as high-intensity economic activities together with low wind speed, high temperature and humidity. PM10 pollution may be mainly related to the accumulation and secondary transformation of particulate matter under low wind speed and high humidity conditions, so the PM10 concentration in the basin area is significantly higher than that in plateau area. The high O3 concentration may be mainly related to the poor vegetation condition in the plateau area, and the high-intensity human activities in the basin area. The results can improve the understanding the spatio-temporal patterns and formation mechanism of air pollution in Sichuan-Chongqing region, and be helpful for policies-making of environmental protection by local governments.

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金自恒,高锡章,李宝林,翟德超,许杰,李飞.川渝地区空气质量时空分布格局及影响因素.生态学报,2022,42(11):4379~4388

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