Suitability Assessment of Six Tree Species through Combined Analysis of PM2.5 Capture Ability and Air Pollution Tolerance Index for Urban Green Belt

Author:

Li Muni1,Tan Peng1,Rai Prabhat Kumar2,Li Yu1,Meng Huan13,Zhang Tong1,Zhang Zhi134,Zhang Weikang134ORCID

Affiliation:

1. Department of Landscape Architecture, Landscape Planning Laboratory, Shenyang Agricultural University, Shenyang 110866, China

2. Department of Environmental Science, School of Earth Sciences and Natural Resources Management, Mizoram University, Aizawl 796004, India

3. Yiwulvshan Forest Ecosystem National Observation and Research Station, Jinzhou 121109, China

4. Key Laboratory of Forest Tree Genetics, Breeding, and Cultivation of Liaoning Province, Shenyang 110866, China

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 PM2.5 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 PM2.5 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 PM2.5 retained by leaf surfaces. The PM2.5 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 PM2.5 retention amount. The PM2.5 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 PM2.5 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 PM2.5 capture ability with APTI showed Pinus tabuliformis to be the best species for the construction of urban green belts in Shenyang City.

Funder

Educational Department of Liaoning Province

the National Science Foundation of China

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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