A Weighted Index Framework for Optimal Selection of Urban Trees to Mitigate Particulate Matter Pollution in South Korea

Abstract

Industrialization in East Asia has significantly impacted air quality, with South Korea facing severe particulate matter (PM) pollution. Urban forests offer a promising solution, but selecting the most effective tree species requires a nuanced approach. This study introduces the Particulate Matter Index (PMI), a structured weighting system that prioritizes tree species based on PM reduction capacity, regional suitability, and environmental compatibility within urban settings. Additional indices—the Regional Index (RI) and Place Index (PI)—evaluate optimal growth conditions and local environmental factors, such as allergen levels and air pollution tolerance. By applying this framework, tree species are categorized according to PM reduction potential and tailored to meet the unique environmental needs of residential, traffic, and industrial areas. This research aims to support urban forest initiatives, empowering local governments to create healthier, sustainable urban environments through informed tree selection.