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Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran
The increased population in megacities has recently exacerbated the need to combat air pollution. This study examined the concept that the sensitivity and tolerance of urban plant species to air pollution might be used to determine Tehran, Iran's air quality and obtain suitable urban greening....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9470701/ https://www.ncbi.nlm.nih.gov/pubmed/36100647 http://dx.doi.org/10.1038/s41598-022-19865-3 |
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author | Dadkhah-Aghdash, Hamed Rasouli, Milad Rasouli, Kabir Salimi, Azam |
author_facet | Dadkhah-Aghdash, Hamed Rasouli, Milad Rasouli, Kabir Salimi, Azam |
author_sort | Dadkhah-Aghdash, Hamed |
collection | PubMed |
description | The increased population in megacities has recently exacerbated the need to combat air pollution. This study examined the concept that the sensitivity and tolerance of urban plant species to air pollution might be used to determine Tehran, Iran's air quality and obtain suitable urban greening. The air pollution tolerance index (APTI) was derived using the total chlorophyll, relative water content, pH, and ascorbic acid content of leaf extract from Morus alba, Ailanthus altissima, and Salix babylonica trees as an indicator of the sensitivity and tolerance of urban plant species. A. altissima and S. babylonica, with APTI values of 11.15 and 11.08, respectively, were sensitive to air pollution and can be employed as bioindicators, whereas M. alba, with an APTI value of 14.08, exhibited moderate resistance to air pollution and is therefore recommended for urban planting. Furthermore, the content of enzymatic and non-enzymatic parameters (carotenoid, phenol, and flavonoids) and proline concentration in the polluted seasons and sites (3 and 4) have been increased in M. alba. Collectively, we expect our findings to contribute to the rapidly growing body of research aiming to find a suitable urban greening for a wide range of polluted megacities. |
format | Online Article Text |
id | pubmed-9470701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-94707012022-09-15 Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran Dadkhah-Aghdash, Hamed Rasouli, Milad Rasouli, Kabir Salimi, Azam Sci Rep Article The increased population in megacities has recently exacerbated the need to combat air pollution. This study examined the concept that the sensitivity and tolerance of urban plant species to air pollution might be used to determine Tehran, Iran's air quality and obtain suitable urban greening. The air pollution tolerance index (APTI) was derived using the total chlorophyll, relative water content, pH, and ascorbic acid content of leaf extract from Morus alba, Ailanthus altissima, and Salix babylonica trees as an indicator of the sensitivity and tolerance of urban plant species. A. altissima and S. babylonica, with APTI values of 11.15 and 11.08, respectively, were sensitive to air pollution and can be employed as bioindicators, whereas M. alba, with an APTI value of 14.08, exhibited moderate resistance to air pollution and is therefore recommended for urban planting. Furthermore, the content of enzymatic and non-enzymatic parameters (carotenoid, phenol, and flavonoids) and proline concentration in the polluted seasons and sites (3 and 4) have been increased in M. alba. Collectively, we expect our findings to contribute to the rapidly growing body of research aiming to find a suitable urban greening for a wide range of polluted megacities. Nature Publishing Group UK 2022-09-13 /pmc/articles/PMC9470701/ /pubmed/36100647 http://dx.doi.org/10.1038/s41598-022-19865-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Dadkhah-Aghdash, Hamed Rasouli, Milad Rasouli, Kabir Salimi, Azam Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran |
title | Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran |
title_full | Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran |
title_fullStr | Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran |
title_full_unstemmed | Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran |
title_short | Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran |
title_sort | detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in tehran, iran |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9470701/ https://www.ncbi.nlm.nih.gov/pubmed/36100647 http://dx.doi.org/10.1038/s41598-022-19865-3 |
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