Assessing the impact of urban green spaces on air quality improvement

Thesis Abstract

Urban air pollution remains a critical environmental and public health challenge in rapidly expanding metropolitan areas worldwide. Despite widespread recognition of green spaces as potential mitigating elements, empirical evidence quantifying their specific impact on air quality and identifying effective mechanisms remains limited and context-specific. This study aims to assess the influence of urban green spaces on ambient air quality, with particular emphasis on particulate matter (PM10 and PM2.5), nitrogen dioxide (NO2), and ozone (O3) concentrations. The objectives include quantifying variations in air pollutant levels across different green space types, examining the relationship between green space attributes and air quality improvements, and identifying the key vegetation and spatial factors that contribute to pollution reduction. Employing a mixed-methods research design, the study integrates quantitative field measurements with qualitative assessments. The primary data collection involved a stratified random sample of 15 urban green spaces within the metropolitan area of twenty square kilometers, selected based on size, vegetation density, and usage patterns. Gas and particulate monitoring was conducted over a twelve-month period, utilizing calibrated portable air quality sensors positioned at multiple sampling points within each green space to record hourly pollutant concentrations, resulting in a dataset of over 150,000 observations. Additionally, GIS-based spatial analysis was employed to characterize the green space attributes, complemented by structured interviews with 30 park managers and environmental officials to garner insights into green space management practices and perceived air quality trends. Data analysis involved descriptive statistical techniques to summarize pollutant levels, followed by multivariate regression analysis to determine the relationships between quantified green space attributes—such as tree canopy cover, plant diversity, and proximity to traffic corridors—and air quality indicators. The analysis further applied ANOVA tests to compare pollution levels across various categories of green spaces, and path analysis within Structural Equation Modeling (SEM) frameworks to explore the causal pathways through which green spaces influence air pollution dynamics, rooted in the Biogenic Volatile Organic Compounds and Ecosystem Services theories. Expected findings suggest that increased tree canopy cover and greater plant diversity are significantly associated with reductions in PM10, PM2.5, and NO2 levels, whereas ozone levels tend to increase slightly within certain green spaces, reflecting complex photochemical interactions. The study anticipates identifying specific vegetation species and spatial configurations that optimize air quality improvement, providing nuanced insights into ecosystem service valuation in urban settings. By offering comprehensive empirical evidence, this research contributes to the body of knowledge on urban ecological infrastructure and its role in mitigating air pollution. It advances theoretical understanding through the integration of ecosystem service models with urban environmental management frameworks. The findings are intended to inform urban planning policies and green space design strategies that maximize air quality benefits, emphasizing the importance of strategic vegetation placement and biodiversity conservation. In conclusion, the study underscores the vital role of well-planned urban green spaces in improving air quality and highlights practical recommendations for city planners, environmental policymakers, and landscape architects to enhance the pollution-buffering capacity of urban green infrastructure. It also suggests avenues for further research, including longitudinal studies on green space expansion and technological innovations in real-time air quality monitoring, to refine strategies for sustainable urban environmental management.