A COMPREHENSIVE SPATIAL-TEMPORAL ANALYSIS OF URBAN AIR QUALITY AND CLIMATE ADAPTATION DYNAMICS

Abstract

Urban agglomerations in developing nations are increasingly positioned at the intersection of acute ambient air pollution and macro-level climate change. This case study examines the spatial-temporal dynamics of global warming and air pollution in Lahore, Pakistan. Utilizing longitudinal observational data from 2023 to 2025 alongside multi-variate statistical modeling (Pearson correlation and OLS multiple linear regression), this research evaluates the environmental drivers governing Lahore's Air Quality Index (AQI), Fine Particulate Matter (PM2.5), Coarse Particulate Matter (PM10), and key gaseous pollutants (CO, NO2, SO2). The results demonstrate severe winter peaks in AQI (exceeding 330) driven by thermal inversions and regional crop burning (r = 0.811), while industrial activities and transportation index remain chronic baseline contributors. Econometric modeling indicates an R² of 0.98, highlighting that PM2.5 (β = 1.352), Industrial Index (β = 1.076), and Traffic Index (β = 0.939) exert positive structural pressures on AQI, whereas temperature exhibits a strong inverse relationship (β = -1.760). To mitigate these impacts, this paper proposes an integrated urban adaptation framework incorporating spatial densification control, green infrastructure, thermal performance standards, and real-time cross-boundary environmental governance.