Comparative Analysis of Urban Green Spaces' Impact on Local Air Quality

Thesis Abstract

Urban air pollution remains a critical environmental concern, particularly in rapidly expanding metropolitan areas where the influence of green spaces on air quality is increasingly recognized but inadequately quantified. This study aims to conduct a comparative analysis of the impact of different types and configurations of urban green spaces—namely parks, street trees, and community gardens—on local air quality parameters within the metropolitan zone of a major urban center. The specific objectives include quantifying concentrations of key air pollutants (PM2.5, NO2, SO2, and O3), analyzing spatial variations in air quality related to the proximity and type of green spaces, and evaluating the extent to which green space attributes contribute to pollutant mitigation. The research adopts a cross-sectional, observational design integrated with quantitative analytical methods. The population comprises air quality monitoring stations strategically located within and around various urban green spaces. A stratified sampling technique was employed to select 30 monitoring stations distributed across high-density green spaces, low-density green spaces, and control sites devoid of substantial vegetation. Data collection involved deploying portable air quality sensors for continuous measurement of pollutants over a period of six months, complemented by satellite imagery and Geographic Information System (GIS) mapping for spatial analysis of green space distribution and characteristics. To enhance measurement validity, supplementary data were gathered from existing governmental air quality monitoring stations for validation purposes. The instruments' reliability was established through calibration against standard reference instruments prior to deployment. Data analysis employed descriptive statistics for initial data characterization, followed by inferential statistical tests such as Analysis of Variance (ANOVA) to identify differences in pollutant levels among the different site categories. Multiple regression analysis tested the influence of green space attributes—area size, vegetation density, and connectivity—on pollutant concentrations, framed within the Environmental Preference Theory and the Biogenic Volatile Organic Compounds (BVOC) mitigation model as the theoretical backdrop. Anticipated findings include statistically significant reductions in PM2.5, NO2, and SO2 concentrations in areas proximate to high-density green spaces compared to control sites, alongside potential variations in ozone levels due to complex photochemical interactions. The regression models are expected to reveal that larger, denser, and well-connected green spaces have greater mitigating effects on specific pollutants, thereby elucidating the importance of green space configuration in urban air quality management. The study also aims to identify threshold sizes and vegetation types most effective in pollutant reduction, offering insights tailored to urban planning and environmental policy. This research contributes to the academic discourse by providing empirical evidence on the roles of various green space typologies in pollutant mitigation, addressing gaps related to spatial heterogeneity and vegetation attributes in existing literature. It advances understanding of the mechanistic links between urban greenery and air quality, particularly within the context of sustainable city planning. The study concludes that strategic development and management of green spaces can significantly improve urban air quality, recommending policies that prioritize green space expansion, connectivity, and native vegetation integration. Furthermore, it suggests avenues for future research, including longitudinal assessments to evaluate long-term effects and the integration of biological air quality indicators. Overall, this thesis underscores the environmental, health, and urban planning benefits of optimized green space deployment, advocating for evidence-based policies that foster healthier and more resilient urban environments.