城市空间结构对PM<sub>2.5</sub>浓度分布的影响

张智璇; 单宝艳; 林琪凯; 陈艳秋; 于新伟; 朱敏

doi:10.13205/j.hjgc.202109013

城市空间结构对PM_2.5浓度分布的影响

doi: 10.13205/j.hjgc.202109013

1. 山东建筑大学测绘地理信息学院, 济南 250101;
2. 山东省济南生态环境监测中心, 济南 250100

基金项目:

国家自然科学基金（51608309）；教育部人文社会科学研究规划基金项目（12YJA790019）。

详细信息

作者简介:
张智璇(1997-),女,硕士,主要研究方向为3S技术在城市建设及其管理中的应用。ycssch8023@163.com

通讯作者:
单宝艳(1970-),男,教授,主要研究方向为GIS空间分析与区域规划。shan7066@sdjzu.edu.cn

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- 文章访问数: 96
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出版历程
- 收稿日期: 2020-11-05
- 网络出版日期: 2022-01-21

INFLUENCE OF URBAN SPATIAL STRUCTURE ON PM_2.5 CONCENTRATION DISTRIBUTION

1. School of Surveying and Geo-informatics, Shandong Jianzhu University, Jinan 250101, China;
2. Jinan Ecological Environment Monitoring Center of Shandong Province, Jinan 250100, China

摘要

摘要: 城市空间结构影响空气流通等微环境，必然对PM_2.5分布和扩散产生影响，研究两者关系对城市规划和建设具有积极意义。基于建筑构建城市空间结构指标体系，采用克里金插值等方法研究济南市中心城区PM_2.5浓度的空间格局，运用相关分析方法基于全域和不同高程视角探究城市空间结构对PM_2.5分布的影响。结果表明：1）DEM平均值、建筑绝对高度平均值、户外活动面积与PM_2.5浓度呈负相关，建筑绝对高度最大值、建筑基底面积总和、建筑密度、占空比、建筑体积总和与PM_2.5浓度呈正相关。这些指标是影响PM_2.5分布的重要因素，城市规划布局时应重点考虑。2）不同高程和时间范围，PM_2.5分布存在时空差异。PM_2.5浓度越高，城市空间结构指标对其浓度分布的影响越明显。PM_2.5浓度空间分布的变异系数越大，PM_2.5浓度与各城市结构指标相关性越弱。3）地形高程是影响PM_2.5分布的重要因素，随着平均高程增加，城市空间结构指标与PM_2.5浓度呈显著相关的月份数量增加，且规律性更强。
- 城市空间结构 /
- PM_2.5浓度 /
- 相关分析 /
- 克里金插值 /
- 时空差异
Abstract: The urban spatial structure affects the microenvironment such as air circulation, which inevitably has an impact on PM_2.5 distribution and dispersion. Studying the relationship between the two has positive significance for urban planning and construction. Based on the construction of the urban spatial structure indicators system, the spatial pattern of PM_2.5 concentrations in the central city of Jinan was studied using methods of kriging interpolation, and the influence of urban spatial structure on PM_2.5 distribution was investigated based on the whole area and different elevation perspectives using correlation analysis methods. The results showed that:1) PM_2.5 concentration was negatively correlated with the average and standard deviation of DEM, the average and standard deviation of absolute building height, and outdoor activity area, and positively correlated with the maximum absolute building height, the sum of building floor area, building density, occupancy ratio, and the sum of building volume. These indicators were important factors affecting the distribution of PM_2.5 and should be considered in urban planning and layout. 2) there were spatial and temporal differences in PM_2.5 distribution at different elevations and time ranges. the higher the PM_2.5 concentration, the more obvious the influence of urban spatial structure indicators on its concentration distribution, the coefficient of variation of PM_2.5 concentration spatial distribution increased, and the correlation between PM_2.5 concentration and each urban structure indicator became weaker. 3) topographic elevation was an important factor influencing the distribution of PM_2.5. As the average elevation increased, the number of months with significant correlation between urban spatial structure indicators and PM_2.5 concentrations increased, and the regularity got stronger.
- urban spatial structure /
- PM_2.5 concentration /
- correlation analysis /
- kriging interpolation /
- spatial-temporal differences

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