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重庆市绿色空间景观格局与PM_2.5浓度时空相关性(PDF)

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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:: 第46卷
期数:: 2024年第01期

页码:: 25-37

栏目:: 环境与可持续发展

出版日期:: 2024-01-15

文章信息/Info

Title:: Spatiotemporal Correlation Between Green Space Landscape Pattern and PM_2.5 Concentration in Chongqing City, China

文章编号:: 1672-6561(2024)01-0025-13

作者:: 苟爱萍¹; 李皖新¹; 王江波^2*; (1. 上海应用技术大学生态技术与工程学院,上海 201418; 2. 南京工业大学建筑学院,江苏南京 211816)

Author(s):: GOU Ai-ping¹; LI Wan-xin¹; WANG Jiang-bo^2*; (1. School of Ecological Technology and Engineering, Shanghai Institute of Technology, Shanghai 201418, China; 2. College of Architecture, Nanjing Tech University, Nanjing 211816, Jiangsu, China)

关键词:: 绿色空间; 景观格局指数; 消减效应; PM_2.5浓度; 空间自相关分析; 时空地理加权回归模型; 时空异质性; 重庆

Keywords:: green space; landscape pattern index; reduction effect; PM_2.5 concentration; spatial autocorrelation analysis; GTWR model; spatiotemporal heterogeneity; Chongqing

分类号:: X513; TU985

DOI:: 10.19814/j.jese.2023.08011

文献标志码:: A

摘要:: 空气中的细颗粒物对人民群众身体健康产生严重威胁,探究绿色空间景观格局对PM_2.5浓度的影响,有助于通过调整绿色空间格局降低PM_2.5浓度。以重庆市1980～2020年土地利用遥感监测数据和PM_2.5浓度数据作为基础数据,通过景观格局指数法、空间自相关分析研究绿色空间景观格局及PM_2.5浓度变化特征,再通过时空地理加权回归(GTWR)模型研究绿色空间景观格局指数变化对PM_2.5浓度的影响及其时空异质性。结果表明:①重庆市PM_2.5浓度从1980年至2010年逐渐上升,2010年至今逐渐降低; 同时,其空间分布具有显著聚集特征,主要显示为东部低-低聚集、西部高-高聚集的特征。②林地、草地和耕地的面积指数(TA)、斑块密度指数(PD)和斑块连接度指数(COHESION)与PM_2.5浓度具有显著的相关性。其中,林地面积指数呈负影响,耕地、草地面积指数呈正影响; 林地、草地斑块密度指数呈正影响,耕地斑块密度指数呈负影响; 林地、草地和耕地斑块连接度指数均呈负影响。③主城都市区内,草地面积指数和耕地斑块密度指数对PM_2.5浓度的负影响较强。渝东北三峡库区城镇群和渝东南武陵山区城镇群内,林地聚合度指数(AI)、斑块密度指数和斑块连接度指数以及耕地面积指数对PM_2.5浓度的影响较强。

Abstract:: Airborne fine particulate matter poses a serious threat to human health, and investigating the impact of green space landscape patterns on PM_2.5 concentrations is conducive to reducing the risk of respiratory diseases by adjusting the green space pattern to decrease PM_2.5 concentrations. Utilizing land use remote sensing monitoring data and PM_2.5 concentration data in Chongqing city from 1980 to 2020 as the foundational dataset, the landscape pattern index method and spatial autocorrelation analysis were employed to study the characteristics of green space landscape patterns and PM_2.5 concentration changes. Furthermore, a geographical and temporal weighted regression(GTWR)model was applied to explore the influence of changes in green space landscape pattern indices on PM_2.5 concentrations and their spatiotemporal heterogeneity. The results show that ① PM_2.5 concentrations in Chongqing city gradually increase from 1980 to 2010, followed by a gradual decrease from 2010 to the present; simultaneously, the spatial distribution exhibits significant agglomeration characteristics, primarily manifesting as low-low agglomeration in the east and high-high agglomeration in the west. ② Area index(TA), patch density index(PD), and patch cohesion index(COHESION)of forest, grassland and agricultural land show significant correlations with PM_2.5 concentrations; specifically, area index of forest is negatively correlated, while area indexes of arable land and grassland are positively correlated; patch density indexes of forest and grassland are positively correlated, while patch density index of arable land is negatively correlated; patch cohesion indexes of forest, grassland and arable land are all negatively correlated. ③ In the metropolitan area, area index of grassland and patch density index of arable land exhibit a stronger negative impact on PM_2.5 concentrations; in the urban clusters of Three Gorges reservoir area in the northeast and Wuling mountain area in the southeast of Chongqing city, aggregation index(AI), patch density index, patch cohesion index of forest, and area index of arable land exert a stronger influence on PM_2.5 concentrations.

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相似文献/References:

备注/Memo

备注/Memo:: 收稿日期:2023-08-07; 修回日期:2023-12-13投稿网址:http:∥jese.chd.edu.cn/
基金项目:国家自然科学基金项目(51778364,51978329)
作者简介:苟爱萍(1971-),女,重庆市人,教授,工学博士,E-mail:aipinggou@hotmail.com。
*通信作者:王江波(1976-),男,河南鹤壁人,教授,工学博士,E-mail:wjb623@163.com。

更新日期/Last Update: 2024-01-25

《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

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