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我国城市大气环境与周边区域二维和三维景观格局关系
引用本文:李迪康,刘淼,李春林,胡远满,王聪,刘冲. 我国城市大气环境与周边区域二维和三维景观格局关系[J]. 应用生态学报, 2021, 32(5): 1593-1602. DOI: 10.13287/j.1001-9332.202105.015
作者姓名:李迪康  刘淼  李春林  胡远满  王聪  刘冲
作者单位:1.中国科学院沈阳应用生态研究所, 中国科学院森林生态与管理重点实验室, 沈阳 110016;2.中国科学院大学, 北京 100049
基金项目:国家自然科学基金项目(32071580,41871192)和国家自然科学基金重点基金项目(41730647)资助
摘    要:城市内部的大气环境受到周边区域景观格局的剧烈影响,小尺度上大气污染状况与周边区域景观格局的关系研究对从城市建设角度减缓城市大气污染有着重要现实意义.本研究以2017年中国30个省会城市的266个大气污染监测站点的NO2、SO2、PM2.5和PM 10年均浓度为因变量,选择监测站点周边3 km区域内的10个二维和三维景观...

关 键 词:二维城市景观格局  三维城市景观格局  大气污染物  增强回归树  影响因素
收稿时间:2020-12-16

Relationship between urban atmospheric environment and surrounding two-dimensional and three-dimensional landscape pattern in China.
LI Di-kang,LIU Miao,LI Chun-lin,HU Yuan-man,WANG Cong,LIU Chong. Relationship between urban atmospheric environment and surrounding two-dimensional and three-dimensional landscape pattern in China.[J]. The journal of applied ecology, 2021, 32(5): 1593-1602. DOI: 10.13287/j.1001-9332.202105.015
Authors:LI Di-kang  LIU Miao  LI Chun-lin  HU Yuan-man  WANG Cong  LIU Chong
Affiliation:1.Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;2.University of Chinese Academy of Sciences, Beijing 100049, China
Abstract:Atmospheric environment in urban built-up area is severely influenced by the surrounding landscape pattern. Understanding the relationship between air pollution and surrounding landscape pattern at small scale has great significance for mitigating air pollution from the perspective of urban construction. The annual average concentrations of NO2, SO2, PM2.5 and PM10 from 266 air pollution monitoring stations in 30 provincial capitals of China in 2017 were chosen as dependent variables. Ten two-dimensional and three-dimensional landscape pattern indices (number of buildings, building aggregation, building density, impervious water ratio, quantitative density of catering, building footprint area, high building ratio, floor area ratio, total building area and building type Shannon diversity index) within the 3 km area around the monitoring stations were used as independent variables. The effects of landscape pattern on the concentration of four air pollutants were analyzed using the boosted regression trees model. The results showed that the concentration of four air pollutants in the central and northern cities were significantly higher than that in the southeast coastal cities and southwest cities. The most important factor affecting the concentrations of NO2, SO2, PM2.5 and PM10 was the impervious ratio, with relative contribution rates of 40.7%, 36.3%, 51.0% and 51.8% respectively. The results of sub-region analysis showed that the most important influencing factor differed in different regions, including the impervious ratio in the East and Central China; the number and density of buildings in South China; the impervious ratio and diversity of building types in North China; the impervious ratio and the number of buildings in Northeast China, the density of buildings in Northwest China. Such differences were mainly caused by climate, topography, urban planning, and other factors.
Keywords:two-dimensional urban landscape pattern  three-dimensional urban landscape pattern  atmospheric pollutant  boosted regression tree  influencing factor  
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