中文关键词大气细颗粒物(PM_2.5)土地利用/覆被变化(LUCC)热点分析地理加权回归(GWR)空间响应 英文关键词fine particulate matter (PM_2.5)land use and land cover change (LUCC)hot spot analysisgeographically weighted regression model (GWR)spatial response 中文摘要 大气细颗粒物（PM_2.5）是大气污染的重要组成成分，对其影响因素进度探讨具有重要的意义.但目前来看，多数的研究都聚焦于PM_2.5与气象要素以及经济因素之间的关系，分析土地利用/覆被变化对PM_2.5影响的研究相对较少，需要进一步的深入探讨.基于PM_2.5空间分布数据及土地利用/覆被数据，对华北地区PM_2.5变化特征及土地利用/覆被变化特征进行了系统分析，并利用地理加权回归、GIS空间分析等手段探讨了PM_2.5变化与土地利用/覆被变化的响应关系，结果表明：①华北地区PM_2.5浓度整体呈现东南高、西北低的空间格局，且18a均保持这一态势没有变化.时间上来看，在2006年达到污染最大值，之后虽有波动但一直居高不下.多数城市PM_2.5浓度超标，整体环境污染形势严峻；②2000~2015年研究区土地利用类型/覆被以耕地、林地和草地为主，土地利用/覆被变化趋势主要表现为耕地的大量减少以及建设用地的持续增加，水域和未利用地面积略有减少，林地和草地转入转出面积接近，因而总量变化不大；③地理加权回归模型计算结果表明，Local R²（衡量局部拟合度）较低的区域为土地利用/覆被未发生变化的区域，而在土地利用/覆被变化明显的区域，Local R²较高，说明PM_2.5变化对土地利用/覆被变化有着显著的响应作用；④对于不同土地利用/覆被状况而言，PM_2.5分布特征表现出建设用地 > 耕地 > 水域 > 草地 > 林地 > 未利用地的趋势.对于不同土地利用/覆被转换方式而言，当自然用地向人工用地转换时PM_2.5浓度上升，而人工用地向自然用地转变时PM_2.5浓度降低. 英文摘要 Fine particulate matter (PM_2.5) 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_2.5 and meteorological or economic factors, whereas fewer have analyzed the relationship between PM_2.5 and land use and land cover change (LUCC). This study employed spatial distribution data of PM_2.5 and land use and land cover data to analyze the relationship between dynamic characteristics of PM_2.5 and LUCC. A geographically weighted regression (GWR) model and spatial analysis tools based on ArcGIS were used to analyze the relationship between PM_2.5 dynamic characteristics and LUCC. North China was selected as the study area, and the results showed that ① The spatial pattern of PM_2.5 in North China was high in the southeast and low in the northwest for 18 years. From a time perspective, the PM_2.5 reached its maximum value in 2006 and has maintained a high value since then. The PM_2.5 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 R² is low in non-LUCC areas and high in LUCC areas, and the PM_2.5 dynamic characteristics have a significant response to LUCC. ④ For different land use and land cover types, the distribution of PM_2.5 showed a trend of construction land > cropland > water area > grassland > woodland > unused land, for different types of LUCC. PM_2.5 concentration increased when natural land changed to artificial land and decreased when artificial land changed to natural land.

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