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Atmosphere 2018, 9(5), 199; https://doi.org/10.3390/atmos9050199

Effects of Urban Greenspace Patterns on Particulate Matter Pollution in Metropolitan Zhengzhou in Henan, China

1
Forestry College, Henan Agricultural University, 95 Wenhua Road, Zhengzhou 450002, China
2
School of Environment and Natural Resources, The Ohio State University, 2021 Coffey Road, Columbus, OH 43210, USA
3
OSU South Centers, The Ohio State University, 1864 Shyville Road, Piketon, OH 45661, USA
4
Institute of Geographic, Space Information Engineer University, Zhengzhou 450001, China
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Received: 2 April 2018 / Revised: 13 May 2018 / Accepted: 17 May 2018 / Published: 21 May 2018
(This article belongs to the Special Issue Air Quality in China: Past, Present and Future)
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Abstract

This case study was conducted to quantify the effects of urban greenspace patterns on particle matter (PM) concentration in Zhengzhou, China by using redundancy and variation partitioning analysis. Nine air-quality monitoring stations (AQMS) were selected as the central points. Six distances of 1 km, 2 km, 3 km, 4 km, 5 km, and 6 km were selected as the side lengths of the squares with each AQMS serving as the central point, respectively. We found: (1) the fine size of PM (PM2.5) and coarse size of PM (PM10) among four seasons showed significant differences; during winter, the concentration of PM2.5 and PM10 were both highest, and PM2.5 and PM10 concentration in summer were lowest. (2) To effectively reduce the PM2.5 pollution, the percentage of greenspace, the differences in areas among greenspace patches, and the edge complexity of greenspace patches should be increased at distances of 2 km and 3 km. To effectively reduce PM10, the percentage of greenspace at a distance of 4 km, the edge density at distances of 2 km and 4 km, and the average area of greenspace patches at a distance of 1 km should be increased. (3) Greenspace pattern significantly affected PM2.5 at a distance of 3 km, and PM10 at a distance of 4 km. From shorter distance to longer distance, the proportion of variance explained by greenspace showed a decline–increase–decline–increase trend for PM2.5, and a decline–increase–decline trend for PM10. At shorter distances, the composition of greenspace was more effective in reducing the PM pollution, and the configuration of greenspace played a more important role at longer distances. The results should lead to specific guidelines for more cost-effective and environmentally sound greenspace planning. View Full-Text
Keywords: particulate matter; spatial pattern; greenspace; redundancy analysis particulate matter; spatial pattern; greenspace; redundancy analysis
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Lei, Y.; Duan, Y.; He, D.; Zhang, X.; Chen, L.; Li, Y.; Gao, Y.G.; Tian, G.; Zheng, J. Effects of Urban Greenspace Patterns on Particulate Matter Pollution in Metropolitan Zhengzhou in Henan, China. Atmosphere 2018, 9, 199.

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