Akademik Veri Yönetim Sistemi
INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY, cilt.23, sa.6, 2026 (SCI-Expanded, Scopus)
Increasing urbanization, changing population dynamics, and the growing consumption of natural resources have led to significant environmental challenges, including declining urban air quality. To address these challenges, green infrastructure (GI) applications have emerged as sustainable strategies for improving air quality and fostering healthier, climate-resilient cities. However, identifying the most effective GI applications remains complex, often hindering their appropriate implementation. This study investigates the roles of different GI applications in improving urban air quality at a micro-scale and examines the relationships between these applications with a particular focus on solutions adaptable to hot climates under global warming conditions-Seasonal variations were analysed, and micro-scale air quality index (m-AQI) maps were developed based on field measurements. The study was conducted in Jumeirah Lakes Towers (JLT) Park, Dubai, using a grid-based monitoring framework comprising 39 measurement networks (50 & times; 50 m). A total of 5,616 air quality measurements were collected over one year. Air quality monitoring included CO, CO2, PM10 and PM2.5, and the micro-Air Quality Index (m-AQI) maps were produced based on USEPA AQI breakpoints.The results identify GI features that contribute to improved air quality across different seasons, providing insights into sustainable, year-round implementation strategies. Statistical analyses reveal strong relationships between specific GI applications, with particularly high correlations between pollinator gardens and seed-specialized plants (r = 0.984), and between permeable pavement and turf applications (r = 0.901). Xeriscaping, the use of natural materials, and rain gardens demonstrate the most significant impact on m-AQI.Model validation confirms that the relationship between GI applications and air quality is statistically significant (p < 0.05), with regression analysis indicating a strong association between GI variables and m-AQI (R = 0.928). The findings propose climate-sensitive, purpose-driven design scenarios that can support urban planning strategies aimed at mitigating air quality challenges under climate change conditions.