The Reducing Effect of Green Spaces with Different Vegetation Structure on Atmospheric Particulate Matter Concentration in BaoJi City, China

With the acceleration of urbanisation and industrialisation, atmospheric particulate pollution has become one of the most serious environmental problems in China. In this study, green spaces in Baoji city were classified into different patterns on the basis of vegetation structural parameters, i.e.,...

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Bibliographic Details
Main Authors: Ling Qiu, Fang Liu, Xiang Zhang, Tian Gao
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Atmosphere
Subjects:
Online Access:http://www.mdpi.com/2073-4433/9/9/332
Description
Summary:With the acceleration of urbanisation and industrialisation, atmospheric particulate pollution has become one of the most serious environmental problems in China. In this study, green spaces in Baoji city were classified into different patterns on the basis of vegetation structural parameters, i.e., horizontal structure, vertical structure and vegetation type. Eleven types of green space with different structures were selected for investigating the relationships between atmospheric particulate matter (PM) concentration and green spaces with different vegetation structure, based on the “matrix effect” of environmental factors, i.e., location, time, wind velocity, temperature, humidity and area to the concentration of PM2.5 and PM10 in the green spaces. The results showed that: (1) Location, time, wind velocity, temperature and humidity had highly significant effects on the concentration of PM2.5 and PM10. In sunny and breeze weather conditions, PM2.5 and PM10 concentration increased with the wind velocity and humidity, and decreased with the temperature. The range of PM10 concentration was greater than the range of PM2.5 concentration. (2) Less than 2 hectares of the green space had no significant influence on the concentration of PM2.5 and PM10. (3) The concentration of PM2.5 and PM10 showed no significant difference between all the green spaces and the control group. There was no significant difference in the reduction of PM2.5 concentration between different structural green spaces, but there was a significant difference in the reduction of PM10 concentration. The above results will provide a theoretical basis and practical methods for the optimisation of urban green space structures for improving urban air quality effectively in the future.
ISSN:2073-4433