Suitability Assessment of Six Tree Species through Combined Analysis of PM 2.5 Capture Ability and Air Pollution Tolerance Index for Urban Green Belt

Muni Li, Peng Tan, Prabhat Kumar Rai, Yu Li, Huan Meng, Tong Zhang, Zhi Zhang () and Weikang Zhang ()
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Muni Li: Department of Landscape Architecture, Landscape Planning Laboratory, Shenyang Agricultural University, Shenyang 110866, China
Peng Tan: Department of Landscape Architecture, Landscape Planning Laboratory, Shenyang Agricultural University, Shenyang 110866, China
Prabhat Kumar Rai: Department of Environmental Science, School of Earth Sciences and Natural Resources Management, Mizoram University, Aizawl 796004, India
Yu Li: Department of Landscape Architecture, Landscape Planning Laboratory, Shenyang Agricultural University, Shenyang 110866, China
Huan Meng: Department of Landscape Architecture, Landscape Planning Laboratory, Shenyang Agricultural University, Shenyang 110866, China
Tong Zhang: Department of Landscape Architecture, Landscape Planning Laboratory, Shenyang Agricultural University, Shenyang 110866, China
Zhi Zhang: Department of Landscape Architecture, Landscape Planning Laboratory, Shenyang Agricultural University, Shenyang 110866, China
Weikang Zhang: Department of Landscape Architecture, Landscape Planning Laboratory, Shenyang Agricultural University, Shenyang 110866, China

Sustainability, 2023, vol. 15, issue 20, 1-15

Abstract: Increasing concentrations of atmospheric particulate matter (PM) can cause a serious threat to urban air quality and human health. To reduce PM pollution in urban environments, pragmatic screening and planting of tolerant tree species can be effective and sustainable ways. However, our understanding of the effects of the capture ability of PM 2.5 on plant tolerance, and efforts to devise explicit assessment tools for suitability analysis for urban green belt plantations, are still inadequate. In this study, six common green tree species ( Pinus tabuliformis , Abies holophylla , Juniperus chinensis , Salix babylonica , Robinia pseudoacacia , and Populus alba ) from three pollution sites in Shenyang City, China, were collected in order to assess their PM 2.5 capture ability, biochemical characteristics, leaf microstructures, and air pollution tolerance index (APTI). The results revealed that different sites and tested plant species can significantly affect the amount of PM 2.5 retained by leaf surfaces. The PM 2.5 retention amount of Abies holophylla was the highest at the SFH site and 1.41–8.89 times that of other tested species ( p < 0.05). Morphological plant attributes, such as leaf surface roughness ( r = 0.52 **) and contact angle ( r = −0.57 **), were strongly related to the PM 2.5 retention amount. The PM 2.5 retention amount per unit leaf area had the strongest and most significant negative influence on total chlorophyll content ( r = −0.743 **), indicating that the accumulation of leaf PM 2.5 reduced the photosynthetic efficiency of the plants. Among the tested plants, Robinia pseudoacacia had the highest APTI value and was identified as the most resilient plant at all three sites, whereas Juniperus chinensis had the lowest APTI at all study sites. However, the integration of PM 2.5 capture ability with APTI showed Pinus tabuliformis to be the best species for the construction of urban green belts in Shenyang City.

Keywords: PM 2.5; leaf microstructures; air pollution tolerance index; ascorbic acid; green belt plant (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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