中国机动车总颗粒物排放时空演变特征及驱动因子

机动车尾气颗粒物排放已成为城市空气污染的主要来源，严重影响环境空气质量和人体健康。研究基于2011-2015年中国市级机动车总颗粒物（total particulate matter，TPM）排放量数据，运用空间分析方法从存量和增量角度探究中国机动车TPM排放的时空演变特征，进而利用地理探测器模型定量评价其主要驱动因素的影响强度。结果表明：中国机动车TPM排放量呈逐年降低趋势，省会和直辖市是中国机动车TPM排放量减少的主要贡献者。省会和直辖市的机动车TPM排放量和减排量最大，其各年均值均超全国市级年均值的2倍。中国机动车TPM排放量和减排量均呈东部沿海至西部内陆地区递减趋势，且呈"低排放，高增加；高排放、高减少"的空间分布特征。"低排放，高增加"区域主要集中在中西部地区，特别是西南各省市；"高排放、高减少"区域为以京津冀为核心的泛华北平原地区。机动车TPM排放量的空间集聚性下降，空间随机分布趋势加强，热点区破碎化的空间分布格局日趋显著。地理探测分析表明，机动车TPM排放量受机动车数量的驱动作用最强，其次是机动车的使用强度，受自然环境条件的驱动作用最弱。年平均气温和海拔等自然因素主要通过与人类活动的共同作用显著增强对机动车TPM排放量的解释力。探究机动车颗粒物排放的时空异质特征和驱动因素，对提高中国机动车尾气治理的精准性具有重大意义。

Spatio-temporal evolution and influencing factors of total particulate matter emissions of vehicles in China

The particulate matter emissions of vehicles exhaust has become the main source of urban air pollution, which seriously affects ambient air quality and human health. Based on the total particulate matter (TPM) emissions data of municipal vehicles in China from 2011 to 2015, this paper explores the spatio-temporal evolution characteristics of TPM emissions of vehicles in China from emissions and emission increments by using spatial analysis method, and then quantitatively evaluates the influence intensity of main driving factors by using geographical detector model. The results show that the TPM emissions of vehicles in China have been decreasing year by year, and provincial capitals and municipalities are the main contributors to the reduction of TPM emissions of vehicles in China. The TPM emissions and emission reductions of vehicles in provincial capitals and municipalities are the largest, and their annual averages are more than twice the national municipal average. Both the TPM emissions and emission reductions of vehicles in China showed a decreasing trend from the eastern coast to the western inland, and the spatial distribution characteristics of "low emission, and high increase; high emission, and high reduction". The "low emission and high increase" region is mainly concentrated in the central and western of China, especially in the southwest provinces. The "high emission and high reduction" area is the pan-North China Plain with Beijing-Tianjin-Hebei region as the core. The number and spatial distribution range of the High-High cluster and Low-Low cluster areas of TPM emissions of vehicles have been reduced year by year, and the spatial agglomeration has declined. On the contrary, the trend of spatial random distribution has strengthened. The Low-High outlier areas have separated the concentrated and contiguous distribution of High-High cluster areas, so the spatial distribution pattern of fragmentation in the High-High cluster areas has become increasingly prominent. The analysis of geographical detection shows that the TPM emissions of vehicles are the most affected by the number of vehicles, followed by the use intensity of vehicles, and the least affected by natural environmental factors such as average annual temperature and altitude. The natural environmental factors such as annual average temperature and altitude significantly enhance the driving explanatory power of TPM emissions of vehicles through the interaction with human activities. Exploring the spatio-temporal heterogeneity and driving factors of vehicle particulate emissions is of great significance to improve the accuracy of vehicle exhaust control in China.