我国主要粮产区PM2.5、PM10时空分布特征及影响因素——以河南省为例

利用2018年河南省PM_2.5、PM₁₀监测数据,结合统计学方法及克里格插值技术,分析河南省PM_2.5、PM₁₀的时空分布特征及影响因素,结果表明:（1）PM_2.5、PM₁₀日均、月均浓度均呈现出“U”型变化特征,PM_2.5/PM₁₀月均值呈现出“W”型变化特征,PM_2.5、PM₁₀季均浓度及其比值均呈现出冬季>秋季>春季>夏季的规律;（2）PM_2.5、PM₁₀月均浓度的空间分布差异较大,而年均浓度则呈现出相似的分布规律,PM_2.5/PM₁₀季均值呈现出不同的空间分布规律,总体上东部及东南部较高,中西部区域较低;（3）PM_2.5、PM₁₀与NDVI、年降水量呈显著负相关,与人口密度、第二产业占比呈显著正相关。研究结论可为粮产区大气污染防治及粮食安全生产提供重要的科学依据。

Spatio-temporal distribution and affecting factors of PM2.5 and PM10 in major grain producing areas in China: A case study of Henan province

This research analyzed the spatio-temporal distribution characteristics and the affecting factors of PM_2.5 and PM₁₀ based on the daily monitoring data in Henan province in 2018, and using statistical methods and Kriging interpolation. The results showed that: (1) The daily and monthly average concentrations of PM_2.5 and PM₁₀ showed a U-shaped pattern, and the monthly average of PM_2.5/PM₁₀ showed a W-shaped pattern. The seasonal average concentrations and ratio of PM_2.5 and PM₁₀ showed the same pattern of winter>autumn> spring> summer. (2) The monthly average concentrations of PM_2.5 and PM₁₀ showed different spatial distribution characteristics, and the spatial distribution varied greatly. However, the spatial distribution of annual average concentration of PM₁₀ was similar to that of PM_2.5. The seasonal average of PM_2.5/PM₁₀ showed different spatial distribution characteristics, which was generally higher in the east and southeast, and lower in the central and western regions. (3) The correlation analysis showed that PM_2.5 and PM₁₀ were significantly negatively correlated with NDVI and annual precipitation, and significantly positively correlated with population density and the proportion of secondary industry. The conclusions can provide an important scientific basis for air pollution control and food safety production in grain producing areas.