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基于城市绿地滞尘模型的上海市绿色空间滞留PM2.5功能评估
引用本文:佘欣璐,高吉喜,张彪.基于城市绿地滞尘模型的上海市绿色空间滞留PM2.5功能评估[J].生态学报,2020,40(8):2599-2608.
作者姓名:佘欣璐  高吉喜  张彪
作者单位:中国人民大学, 北京 100872;生态环境部卫星环境应用中心, 北京 100094;中国科学院地理科学与资源研究所, 北京 100101
基金项目:上海城市生态功能特征指标监测与效益评估技术研究(上海市环保科研项目)
摘    要:绿色空间对大气颗粒物有一定吸收滞留作用,是改善空气环境质量与维护城市生态安全的重要区域。该文基于高分2号卫星影像识别2017年上海市绿色空间,并利用城市绿地滞尘模型,结合上海市降水、风速等气象数据与空气质量监测数据,评估了绿色空间滞留PM_(2.5)功能及其差异。结果表明:2017年上海市绿色空间面积3354 km~2,可滞留PM_(2.5) 3533 t,约合单位面积滞留PM_(2.5) 10.5 kg hm~(-2) a~(-1)。从绿色空间类型来看,林地滞留PM_(2.5)能力最强,可达20.2 kg hm~(-2) a~(-1),远高于草地9.1 kg hm~(-2) a~(-1)和农田8.7 kg hm~(-2) a~(-1)的滞留能力。从季节差异来看,绿色空间夏季滞留PM_(2.5)能力最高,然后依次为秋季、春季和冬季。从植被分布格局来看,林草地和农田吸滞PM_(2.5)的能力随植被盖度的增加而提高。在区域差异上,崇明区绿色空间滞留PM_(2.5)能力最高,其余地区呈现出中心城区低、周边高的趋势。为此建议上海市重点优化中心城区的绿色空间格局,增植立体绿化与高滞尘能力树种。

关 键 词:绿色空间  PM2.5  滞尘功能  模拟  上海
收稿时间:2019/2/26 0:00:00
修稿时间:2019/12/6 0:00:00

PM2.5 removal service of green spaces in Shanghai based on the dust retention simulation on urban vegetation
SHE Xinlu,GAO Jixi,ZHANG Biao.PM2.5 removal service of green spaces in Shanghai based on the dust retention simulation on urban vegetation[J].Acta Ecologica Sinica,2020,40(8):2599-2608.
Authors:SHE Xinlu  GAO Jixi  ZHANG Biao
Institution:Renmin University of China, Beijing 100872, China;Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment, Beijing 100094, China; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Abstract:Urban green spaces can intercept particulate matters in the air, and are often served as ecological and economical measures for the urban environment promotion and the ecological security maintenance. However, many studies at present pay more attention to the air purification at the plant scale, and few studies analyze the regional differences on the dust retention function of urban green spaces. Based on the regional dust retention model and combined with the meteorological and particulate characteristics of Shanghai, this paper assessed the PM2.5 retention service of green spaces in 2017. The results show that there are 3354 km2 green spaces in Shanghai. They could remove 3533 tons of PM2.5, with the average retention capacity of 10.5 kg hm-2 a-1. In Shanghai, the forestland can provide the strongest retention capacity of 20.2 kg hm-2 a-1. The retention capacity of the grassland and the farmland are both lower with 9.1 kg hm-2 a-1 and 8.7 kg hm-2 a-1, respectively. The urban green space in summer shows the strongest dust retention capacity, and descends successively in autumn, spring and winter. The retention ability of the woodland, the grassland, and the farmland increases with the increase of the vegetation coverage. In addition, the green spaces in Chongming district present the highest retention capacity of dust PM2.5 in 2017, and those in other regions emerge the low value in the central urban and the high value in surrounding areas. Therefore, Shanghai should implement the pattern optimization of the green space structure and the green corridor in the urban area. Besides, Shanghai should increase more vertical greening and plant more trees with higher retention capacity in order to promote the PM2.5 removal service.
Keywords:green space  PM2  5  dust detention  simulation  Shanghai
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