Literature DB >> 30849611

An experimental study to quantify road greenbelts and their association with PM2.5 concentration along city main roads in Nanjing, China.

Qianqian Sheng1, Yanli Zhang2, Zunling Zhu3, Weizheng Li1, Jingyuan Xu1, Rui Tang4.   

Abstract

Air pollution is an important environmental and health concern all over the world and PM2.5 is one of the most important constituents of air pollution. In urban area with high population density, vehicles contribute a big portion of PM2.5. The effect of vegetations along road, i.e., road greenbelts, on PM2.5 concentration is still a hot research topic. This study used three-dimensional green volume (3DGV, the three-dimensional volume of the crown and stems of all vegetations including trees, shrubs and grass) to evaluate the vegetation quantity of road greenbelts along four main roads in Nanjing, China. High spatial resolution images were collected with unmanned aerial vehicle (UAV) for othomosaic and feature extraction analysis. A Geographic Information System (GIS) database was developed to cover the location, crown diameter, crown height, and 3DGV information of vegetations in the road greenbelts. The environmental benefits of the road greenbelts were evaluated based on 3DGV information. The relationship between 3DGV of road greenbelts and PM2.5 concentration was analyzed and it was found that large 3DGV does not mean lower PM2.5 concentration. A road greenbelt with even vertical distribution of biomass and diversified vegetation species works better to reduce PM2.5 concentration. The implication of this research is that road greenbelt development should systematically consider surface water control, noise reduction, recreation, aesthetic, and air pollution control, thus to maximize its ecoservices to human being.
Copyright © 2019 Elsevier B.V. All rights reserved.

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Keywords:  Air pollution; GIS; PM(2.5); Road greenbelt; Three-dimensional green volume (3DGV); UAV

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Year:  2019        PMID: 30849611     DOI: 10.1016/j.scitotenv.2019.02.306

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Direct Measuring Particulate Matters in Smoke Plumes from Chimneys in a Textile Dyeing Industrial Park by a Self-Developed PM Detector on an UAV in Yangtze River Delta of China.

Authors:  Zhentao Wu; Xiaobing Pang; Zhangliang Han; Kaibin Yuan; Shang Dai; Jingjing Li; Jianmeng Chen; Bo Xing
Journal:  Sensors (Basel)       Date:  2022-06-08       Impact factor: 3.847

  1 in total

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