基于泰森多边形的南京市PM 2.5时空特征及其与土地利用的相关性研究
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国家自然科学基金项目“面向城市扩张过程的动态空间格局指标与自组织空间结构分析模型”(41571385);中央高校自主科研项目(2042016kf0175)


Spatial and Temporal Variation of PM 2.5 Concentrations Basen on Thiesen Polygon and its Correlation with Land-use Patterns in Nanjing City
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    [目的]分析南京市PM 2.5时空分异规律,探讨PM 2.5浓度变化与土地利用的关系,为南京市生态保护和空气污染治理决策提供依据。[方法]基于南京市2013年12个月的日均PM 2.5浓度数据以及2013年土地利用数据,利用泰森多边形将南京市划分为9个研究区域,以月、季、年为时间尺度,对各个研究区内的PM 2.5浓度的时空特征以及与土地利用的关系进行分析。[结果]时间上,南京市PM 2.5浓度冬季呈现最高,达到129.93 μg/m3,夏季最低,达到44.65 μg/m3。空间上,迈皋桥和瑞金路监测区片年均浓度最高,达到78.90和78.56 μg/m3,仙林大学城和中华门监测区片年均PM 2.5浓度最低,为72.09和72.64 μg/m3。在与土地利用类型的相关性分析中,与水域用地的相关性较强,春夏秋呈现正相关,冬季呈现负相关;年均PM 2.5浓度与5种土地利用类型成不同程度的负相关。[结论]南京市PM 2.5浓度具有明显的时空分异规律,土地利用类型对PM 2.5浓度变化具有重要影响。

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    [Objective] To analyze the spatial and temporal pattern of PM 2.5 concentration and explore its correlation with land-use pattern in order to provide a basis for decision making in ecological protection and air pollution control.[Methods] Based on PM 2.5 concentration data as well as the land-use information in 2013, we divided the whole Nanjing City into 9 regions by means of Thiessen polygon method. We then systematically analyzed the temporal-spatial differentiation of PM 2.5 and its correlation with the variation of land-use pattern in a time-scale of year and season.[Results] In time scale, the concentration of PM 2.5 was the highest (129.93 μg/m3) in winter, and the lowest in summer (only 44.65 μg/m3). In spatial scale, according to the data of annual average PM 2.5 concentrations in each monitoring station, several sites such as Maigaoqiao and Ruijinlu had high PM 2.5 concentrations, reaching 78.90 and 78.56 μg/m3, while PM 2.5 concentrations in the Xianlin and Zhonghuamen Development Zone was the lowest with only 72.08 and 72.64 μg/m3. On the other hand, land-use patterns affected average PM 2.5 concentration, i. e., arable land, grassland, water and barren land, rural residential land were negatively correlated with PM 2.5, and water body has highest correlation 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 concentration.[Conclusion] PM 2.5 concentration showed an obvious spatial and temporal distribution pattern. The variation of land-use had important effects on PM 2.5 concentration.

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陈晓杰,张金亭,张长城,彭晓军.基于泰森多边形的南京市PM 2.5时空特征及其与土地利用的相关性研究[J].水土保持通报,2018,38(1):293-298

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  • 收稿日期:2017-06-29
  • 最后修改日期:2017-07-14
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  • 在线发布日期: 2018-03-08
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