Greenspace pattern, meteorology and air pollutant in Taiwan: A multifaceted connection

• Published in: The Science of the total environment Vol. 914; p. 169883
• Main Authors: Nguyen, Quang-Viet, Liou, Yuei-An
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.03.2024
• Subjects: Air pollutant, meteorology; Air quality; Greenspace; Landscape metric; Partial least squares-structural equation modeling (PLS-SEM); Air quality; Greenspace; Partial least squares-structural equation modeling (PLS-SEM); Landscape metric; Air pollutant, meteorology
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2024.169883

Air pollution is a global environmental concern that poses a significant threat to human health. Given the impact of urbanization and climate change, green planning is being encouraged to improve air quality. The study aims to examine the intricate relationships between greenspace pattern and outdoor air around 73 in-situ stations over Taiwan during the dry (November to April) and wet (May to December) seasons from 2015 to 2020. To achieve this, Partial Least Squares – Structural Equation Modeling was utilized to analyze the interactions among seven dimensions: greenspace – GS, gaseous pollutant – GP, particle pollutant – PP, O3 – OZONE, air temperature – TEMP, relative humidity – RH, and wind speed – WS. The GS involves seven landscape metrics: edge density, total edge, effective mesh size, largest patch area, percentage of landscape, total core area, and patch cohesion index. The results indicate that the GS has a stronger effect on the GP, whereas its effect on the PP is weaker during the dry season compared to the wet season. While its effect on the TEMP is weaker, it shows a slightly stronger effect on the RH during the dry season. Moreover, the GS mediates the air pollutant dimensions during the two seasons, with the RH acting as a primary mediator. The meteorological dimensions primarily have a greater influence on the air pollutant dimensions during the dry season than the wet season. Consequently, the GS explains 11.3 % more and 18.4 % less of the variances in the RH and TEMP during the dry season, respectively. Moreover, the GS and meteorological dimensions yield a seasonal difference in explained variance, with the highest value observed for the OZONE (R2 = 24.2 %), followed by the PP (R2 = 9.7 %) and GP (R2 = 7.7 %). Notably, seven landscape metrics serve as potential indicators for green strategies in urban planning to enhance outdoor air quality. [Display omitted] •GS has a stronger impact on GP, but weaker on PP in dry season.•GS has a stronger impact on RH, but weaker on TEMP in dry season.•Meteorology mainly affects air pollutants in dry season.•RH mediates GS-air pollutants interactions.•Seven landscape metrics show potential as greenness indicators for urban planning.