中文摘要：

基于江苏省2013年12月-2014年11月期间71个监测点PM_（2.5）日数据以及2014年土地利用数据,以年、季为时间尺度,利用泰森多边形划分研究区域,在系统分析PM_（2.5）时空分异规律基础上,揭示PM_（2.5）浓度变化及其与土地利用的关系。结果表明：（1）PM_（2.5）浓度分布存在明显的时空变化趋势。时间上,冬季浓度最高,达109.72μg/m~3,春季次之,为70.13μg/m~3,秋季最低,仅53.20μg/m~3;空间上,从各监测点一年PM_（2.5）浓度看,南京、泰州和宿迁数个监测点是PM_（2.5）高浓度区域,浓度范围81~85μg/m~3。盐城开发区管委会浓度最低,仅49.75μg/m~3,全省呈现＂内陆高,沿海低;内陆南高北低＂的趋势。（2）土地利用类型及景观格局对PM_（2.5）浓度分布有一定影响。耕地、草地、水域和未利用地与PM_（2.5）呈负相关,林地和建设用地则呈正相关。景观面积、密度、破碎度和聚散性是影响PM_（2.5）的主要因素,冬夏季较为敏感。

英文摘要：

Based on PM_（2.5）concentration data of 71 monitoring stations over Jiangsu Province during the period Dec.2013 to Nov.2014 as well as the land-use information of 2014,the relation of PM_（2.5）concentration to the variation of land-use pattern was studied with the time-scale of year and season,and the zoning of the study area by use of Thiessen polygon method;and the spatial and temporal differentiation of PM_（2.5）was systematically analyzed.The results of the study showed that distribution of PM_（2.5）concentration obviously tended changing in terms of time and space,i.e.,in time scale,the concentration of PM_（2.5）was the highest with 109.72 μg/m~3 in winter,followed by spring,70.13 μg/m~3,and the lowest in autumn,only 53.20 μg/m~3;while in space scale,according to the data of annual average PM_（2.5）concentrations in each monitoring point,several sites such as the cities of Nanjing,Taizhou and Suqian had high PM_（2.5）concentrations,ranging between 81 to 85 μg/m~3,while PM_（2.5）concentrations in the Yancheng Development Zone was the lowest：only 49.75 μg/m~3;generally showing PM_（2.5）concentration pattern in the province was ＂higher towards inland,but lower towards coast＂and＂higher in the south,but lower in the north＂.On the other hand,land-use and landscape patterns somewhat affected PM_（2.5）concentration,i.e.,arable land,grassland,water and barren land were negatively correlated with PM_（2.5）,while woodland and construction land were positively correlated with PM_（2.5）;in general,the landscape in terms of area,density,fragmentation and accumulation degree was the main factors affecting the PM_（2.5）.