Yang Wei, Jiang Xiao-Li
School of Geographical Science, Taiyuan Normal University, Jinzhong 030619, China.
Institute of Urban and District Development, Taiyuan Normal University, Jinzhong 030619, China.
Huan Jing Ke Xue. 2020 Jul 8;41(7):2995-3003. doi: 10.13227/j.hjkx.201911079.
Fine particulate matter (PM) is an important component of air pollution, and thus it is meaningful to analyze its influencing factors. According to existing literature, most studies to date have focused on the relationship between PM and meteorological or economic factors, whereas fewer have analyzed the relationship between PM and land use and land cover change (LUCC). This study employed spatial distribution data of PM and land use and land cover data to analyze the relationship between dynamic characteristics of PM and LUCC. A geographically weighted regression (GWR) model and spatial analysis tools based on ArcGIS were used to analyze the relationship between PM dynamic characteristics and LUCC. North China was selected as the study area, and the results showed that ① The spatial pattern of PM in North China was high in the southeast and low in the northwest for 18 years. From a time perspective, the PM reached its maximum value in 2006 and has maintained a high value since then. The PM exceeded the permissible standard in most of the cities, with serious environmental pollution generally. ② The main land use and land cover types in North China from 2000 to 2015 were cropland, woodland, and grassland, and the land use and land cover change showed a trend of great decline in cropland and a great increase in construction land. ③ The results of the GWR model showed that local is low in non-LUCC areas and high in LUCC areas, and the PM dynamic characteristics have a significant response to LUCC. ④ For different land use and land cover types, the distribution of PM showed a trend of construction land > cropland > water area > grassland > woodland > unused land, for different types of LUCC. PM concentration increased when natural land changed to artificial land and decreased when artificial land changed to natural land.
细颗粒物（PM）是空气污染的重要组成部分，因此分析其影响因素具有重要意义。根据现有文献，迄今为止大多数研究都集中在PM与气象或经济因素之间的关系上，而分析PM与土地利用和土地覆盖变化（LUCC）之间关系的研究较少。本研究利用PM的空间分布数据以及土地利用和土地覆盖数据，分析了PM动态特征与LUCC之间的关系。采用地理加权回归（GWR）模型和基于ArcGIS的空间分析工具，分析了PM动态特征与LUCC之间的关系。选取中国北方作为研究区域，结果表明：① 18年来中国北方PM的空间格局为东南高西北低。从时间角度来看，PM在2006年达到最大值，此后一直保持在较高水平。大多数城市的PM超过了许可标准，环境污染总体较为严重。② 2000年至2015年中国北方主要的土地利用和土地覆盖类型为耕地、林地和草地，土地利用和土地覆盖变化呈现出耕地大幅减少、建设用地大幅增加的趋势。③ GWR模型结果表明，非LUCC区域的局部[此处原文缺失具体内容]较低，LUCC区域较高，且PM动态特征对LUCC有显著响应。④ 对于不同的土地利用和土地覆盖类型，不同类型的LUCC下，PM的分布呈现出建设用地>耕地>水域>草地>林地>未利用地的趋势。当自然土地转变为人工土地时，PM浓度增加；当人工土地转变为自然土地时，PM浓度降低。
