2015~2018年中国代表性城市PM2.5浓度的城乡差异

选取中国6大城市群中的11座代表性城市为研究区域，将监测站点划分为城区、郊区和乡村站，进而分析各城市间PM_2.5浓度的城乡差异规律.结果表明，同一城市群各城市之间，或同一城市的城区、郊区、乡村站间PM_2.5日变化皆较为相似.京津冀和长三角地区的城市城区PM_2.5浓度最高，高于郊区7.8%~9.7%，高于乡村11.3%~16.9%，而粤港澳大湾区和内陆城市群（成渝、长江中游、关中平原城市群）的城市郊区PM_2.5浓度最高，高于城区2.6%~11.2%，高于乡村16.7%~26.5%.各城市间城乡PM_2.5浓度差值的日变化规律不尽相同，可呈单峰（如上海）或双峰（如杭州）变化，极值可出现在白天（如广州），亦可在夜间（如深圳）.PM_2.5的排放与传输扩散共同对11城市城乡PM_2.5浓度分布产生影响.

Urban-rural differences in PM2.5 concentrations in the representative cities of China during 2015~2018

Observation sites in the 11 representative cities from 6 main city clusters in China were selected in this study. These observation sites were categorized into urban, suburban and rural to investigate urban-rural differences in PM_2.5 concentrations. Results showed that the diurnal variation patterns of PM_2.5 were relatively similar in the cities from the same city cluster, and they were also similar among the urban, suburban and rural areas in a specific city. In Jingjinji Megalopolis and Yangtze River Delta Megalopolis, the PM_2.5 concentrations from the urban sites were the highest, 7.8%~9.7% higher than those from the suburban sites and 11.3%~16.9% higher than those from the rural sites. However, in Guangdong-Hong Kong-Macao Greater Bay Area and the inland city clusters (i.e., Chengyu Megalopolis, Middle Yangtze River Valley Megalopolis and Guanzhong Plain Megalopolis), the PM_2.5 concentrations from the suburban sites were the highest, 2.6%~11.2% higher than those from the urban sites and 16.7%~26.5% higher than those from the rural sites. Moreover, different diurnal variation patterns of urban-rural PM_2.5 concentration differences were observed in different cities. For example, the diurnal variation of urban-rural PM_2.5 concentration difference was unimodal in Shanghai but bimodal in Hangzhou. The maximum of urban-rural PM_2.5 concentration difference occurred during the daytime in Guangzhou but during the nighttime in Shenzhen. Further, the PM_2.5 concentration distribution in the urban, suburban and rural areas of the 11representative cities were under the combined effects of PM_2.5 emission, transportation and diffusion.