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Quantifying PM(2.5) capture capability of greening trees based on leaf factors analyzing

As PM(2.5) affect human health, it is important to target tree planting in the role of reducing air pollution concentrations. PM(2.5) capture capability of greening trees is associated with leaf morphology, while quantitative research is scanty. In this paper, the PM(2.5) capture capability of 25 sp...

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Autores principales: Liang, Dan, Ma, Chao, Wang, Yun-qi, Wang, Yu-jie, Chen-xi, Zhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5099360/
https://www.ncbi.nlm.nih.gov/pubmed/27646446
http://dx.doi.org/10.1007/s11356-016-7687-9
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author Liang, Dan
Ma, Chao
Wang, Yun-qi
Wang, Yu-jie
Chen-xi, Zhao
author_facet Liang, Dan
Ma, Chao
Wang, Yun-qi
Wang, Yu-jie
Chen-xi, Zhao
author_sort Liang, Dan
collection PubMed
description As PM(2.5) affect human health, it is important to target tree planting in the role of reducing air pollution concentrations. PM(2.5) capture capability of greening trees is associated with leaf morphology, while quantitative research is scanty. In this paper, the PM(2.5) capture capability of 25 species in Beijing and Chongqing were examined by a chamber device. Groove proportion, leaf hair, stomatal density, and stomata size were selected as indexes of leaf morphology. Results showed that groove proportion and stomata size significantly relate to PM(2.5) capture quantity, while no significantly positive correlations were found for leaf hairs and stomatal density. Broadleaf species are conducive to PM(2.5) capture for their rich leaf morphology and have an edge over coniferous in PM(2.5) capture per leaf area. However, coniferous had a larger PM(2.5) capture capability per tree due to the advantage of a large leaf area. Significant difference existed between the species in Beijing and Chongqing due to the different leaf morphology. Urban greening trees are diverse and the structures are complicated. Complex ecological environment may lead to different morphology characteristics. Climate and pollution conditions should be considered when greening.
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spelling pubmed-50993602016-11-21 Quantifying PM(2.5) capture capability of greening trees based on leaf factors analyzing Liang, Dan Ma, Chao Wang, Yun-qi Wang, Yu-jie Chen-xi, Zhao Environ Sci Pollut Res Int Research Article As PM(2.5) affect human health, it is important to target tree planting in the role of reducing air pollution concentrations. PM(2.5) capture capability of greening trees is associated with leaf morphology, while quantitative research is scanty. In this paper, the PM(2.5) capture capability of 25 species in Beijing and Chongqing were examined by a chamber device. Groove proportion, leaf hair, stomatal density, and stomata size were selected as indexes of leaf morphology. Results showed that groove proportion and stomata size significantly relate to PM(2.5) capture quantity, while no significantly positive correlations were found for leaf hairs and stomatal density. Broadleaf species are conducive to PM(2.5) capture for their rich leaf morphology and have an edge over coniferous in PM(2.5) capture per leaf area. However, coniferous had a larger PM(2.5) capture capability per tree due to the advantage of a large leaf area. Significant difference existed between the species in Beijing and Chongqing due to the different leaf morphology. Urban greening trees are diverse and the structures are complicated. Complex ecological environment may lead to different morphology characteristics. Climate and pollution conditions should be considered when greening. Springer Berlin Heidelberg 2016-09-19 2016 /pmc/articles/PMC5099360/ /pubmed/27646446 http://dx.doi.org/10.1007/s11356-016-7687-9 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research Article
Liang, Dan
Ma, Chao
Wang, Yun-qi
Wang, Yu-jie
Chen-xi, Zhao
Quantifying PM(2.5) capture capability of greening trees based on leaf factors analyzing
title Quantifying PM(2.5) capture capability of greening trees based on leaf factors analyzing
title_full Quantifying PM(2.5) capture capability of greening trees based on leaf factors analyzing
title_fullStr Quantifying PM(2.5) capture capability of greening trees based on leaf factors analyzing
title_full_unstemmed Quantifying PM(2.5) capture capability of greening trees based on leaf factors analyzing
title_short Quantifying PM(2.5) capture capability of greening trees based on leaf factors analyzing
title_sort quantifying pm(2.5) capture capability of greening trees based on leaf factors analyzing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5099360/
https://www.ncbi.nlm.nih.gov/pubmed/27646446
http://dx.doi.org/10.1007/s11356-016-7687-9
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