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Investigation of the effects of tree species on air quality using i-Tree software: A case study in California.

Authors :
Ayturan, Zeynep Cansu
Kongoli, Cezar
Kunt, Fatma
Source :
Annals of Forest Research (1844-8135); 2024, Vol. 67 Issue 2, p201-213, 13p
Publication Year :
2024

Abstract

The USDA Forest Service has developed a unique software and tree modelling suite called i-Tree. Several of its instruments are capable of exploring the benefits of trees and forests for pollution mitigation, reduction of storm water runoff, carbon sequestration and storage. However, the system remains underutilized for investigating the effects of trees on air quality. In this study, counties in California (CA), United States, were selected using the i-Tree Landscape tool. Next, several characteristics including land cover details, forest details, population, air quality, carbon sequestration capacity, and air pollution removal capacity, were investigated. When considering the air quality situation in these counties, O<subscript>3</subscript> and PM<subscript>2.5</subscript> are the primary pollutants. The planting prioritization map of California was created based on population density, tree cover, plantable space, average PM<subscript>2.5</subscript> and O<subscript>3</subscript> concentration values, and the counties with the highest planting priority were selected using i-Tree Planting tool. Using this instrument, a case study on the modelling of the removal performances of these air pollutants by multiple new species (Turkey oak, Siberian elm, European hackberry, European white elm, common ash, European silver birch, velvet ash, black alder, bigleaf linden) in priority areas was conducted. The most effective modelled tree species in the area was found to be Turkey oak for its effects in improving air quality in general and O<subscript>3</subscript> in particular. When compared to the effects of modelled trees, the effects of the existing public trees in California were determined to have a comparatively minor impact. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18448135
Volume :
67
Issue :
2
Database :
Complementary Index
Journal :
Annals of Forest Research (1844-8135)
Publication Type :
Academic Journal
Accession number :
182559305
Full Text :
https://doi.org/10.15287/afr.2024.3605