4.7 Article

Analyzing temporal changes in urban forest structure and the effect on air quality improvement

Journal

SUSTAINABLE CITIES AND SOCIETY
Volume 48, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scs.2019.101548

Keywords

Air purification; i-Tree Eco; Green infrastructure; Urban ecosystem services; Quantification; Iran

Funding

  1. Iranian National Science Foundation [96000398]

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Tree planting practices are being increasingly advocated as measures to improve the air and living quality in urban landscapes around the world. Nevertheless, there is still a lack of quantitative understanding of the effects of the increases in tree cover on the future potential of urban forests when it comes to air quality improvement. Therefore, this research aims to assess and quantify the current and future biophysical and monetary value of the regulating ecosystem service provided by urban forest in Tabriz, Iran (as a case study). Both the current conditions and future prospect are assessed through tree planting scenarios based on the i-tree Eco model. The results indicate that the trees and shrubs removed 238.4 t of pollutants during a year (in 2015), which suggests only a modest potential in air purification when compared with other cities around the world. However, through appropriate - though feasible - urban forest management and development practices, they may improve up to 814.46 t cumulatively over the next 20 years. Tree planting schemes have different efficacies in terms of providing air purification services. Our data-rich temporal approach allowed identifying the optimum tree planting strategy, taking into account the growth and mortality dynamics. Thus, the paper illustrates a methodology to assess the current and future potentials of urban forests to reduce air pollution at the city-scale, which helps the development of future urban tree planting strategies in cities to improve air quality as well as the management of the green infrastructure. Our approach paves the way for the quantitative assessment and optimization of the future condition of (urban) ecosystem services.

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