| 汾渭平原PM2.5空间分布的地形效应 |
| 摘要点击 2904 全文点击 865 投稿时间：2021-02-03 修订日期：2021-03-26 |
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| 中文关键词 汾渭平原 PM2.5浓度 空间分布 地形起伏度 地形效应 |
| 英文关键词 Fen-Wei Plain concentration of PM2.5 spatial distribution relief amplitude orographic influence |
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| 中文摘要 |
| 地形不仅通过制约人口和产业布局作用于污染物排放的空间分布，而且对PM2.5的形成、传输、累积、扩散和沉降有深刻影响，是PM2.5空间分布的重要影响因素，盆地地区表现尤为显著.本文基于栅格数据，利用均值变点法、回归分析、地理探测器和双变量空间自相关分析等方法，从自然和人为因素两方面选取指标，探讨汾渭平原PM2.5浓度分布的地形效应及影响机制.结果表明：①汾渭平原地形起伏度总体呈中部低、四周高分布，与海拔分布基本一致.②PM2.5分布格局与地形起伏度相反，总体呈中部高、四周低，且随地形起伏度的升高呈对数关系递减.③地理探测器分析结果显示，汾渭平原PM2.5分布格局主要由人口、GDP和能源消费等人为因素决定，气象和植被等自然因素对PM2.5分布也有一定的调节作用.④地形对人为和自然因素均有显著影响，随着地形起伏度的增加，人口、GDP和能源消费而呈幂函数关系递减，气温呈线性递减，降水量、相对湿度和风速呈线性递增，植被指数呈对数关系递增. |
| 英文摘要 |
| Topography not only has an effect on the spatial distribution of pollutants by restricting populations and industrial activities, but also affects the formation, transmission, accumulation, diffusion, and sedimentation of PM2.5. Topography is, therefore, an essential variable for understanding the spatial distribution of PM2.5, especially in basin areas. Based on gridded data and both natural and human indexes, this paper examines orographic effects on the distribution of PM2.5 on the Fen-Wei Plain based on the change point method, regression, the geographical detector method, and bivariate spatial autocorrelation. The results indicate that:① The relief amplitude of the plain is generally lower in its central part than at its edge, which is similar to the attitudinal distribution in this region; ② The distribution of PM2.5 is negatively related to relief amplitude, with high concentrations in central area and lower concentrations at the edge; ③ Based on the geographical detector analysis, PM2.5 patterns in this region are shaped by human factors including population, gross domestic product(GDP), and energy consumption, as well as natural factors including meteorological conditions and vegetation; and ④ Topography has a significant effect on both human and natural factors; an increase of relief amplitude is associated with a decrease in population, GDP, and energy consumption based on power function. Accordingly, temperature goes down linearly; precipitation, relative moisture, and wind speed increase linearly; and the vegetation index increases based on a logarithmic function. |
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