Rapid urbanization has emerged as a major global environmental challenge and a key driver of air quality deterioration in metropolitan regions, particularly in rapidly developing cities. Among atmospheric pollutants, PM2.5 is of particular concern due to its severe health impacts and ability to penetrate deep into the respiratory system. This study investigates the influence of urban expansion intensity on PM2.5 concentrations in Delhi, India, by integrating urban growth indicators, demographic factors, land-use characteristics, and meteorological parameters. Multi-temporal Landsat imagery, PM2.5 observations, demographic datasets, and climatic variables were utilized to characterize urban expansion and its effects on air quality. Urban growth typologies, including infill, edge-expansion, and outlying development, were quantified using the Landscape Expansion Index (LEI), while Geographically Weighted Regression (GWR), correlation analysis, and mutual information metrics were employed to assess spatial and seasonal relationships. The urban expansion classification achieved an overall accuracy of 91.2% with a Kappa coefficient of 0.88. Correlation analysis confirmed the absence of significant multicollinearity among explanatory variables. Results revealed a moderate positive association between urban expansion intensity and PM2.5 concentrations, with infill development exhibiting the strongest influence compared to edge-expansion and outlying growth patterns. GWR analysis demonstrated substantial spatial heterogeneity, with 42.8% of monitoring locations showing statistically significant positive relationships between urban expansion and PM2.5 levels. Population density emerged as the most influential factor, whereas green spaces and water bodies exhibited mitigating effects. Seasonal analysis further indicated that urban morphology modifies meteorological influences and amplifies anthropogenic impacts on air quality. The study provides a spatially explicit framework for understanding urban-air quality interactions and supports sustainable urban planning, green infrastructure development, and climate-resilient environmental management in rapidly urbanizing cities. Graphical Abstract Based on the analytical framework, this study was conducted to examine the influence of urban expansion intensity on PM2.5 concentrations and to understand the interplay between urban growth dynamics, environmental factors, and air quality in Delhi. The work captures complex relationships among demographic, land-use, and meteorological variables within a rapidly transforming metropolitan landscape. Air quality and urban growth indicators were assessed considering both spatial and statistical controls to uncover underlying mechanisms driving pollution patterns. Techniques including correlation analysis and Geographically Weighted Regression were employed to ensure robust inference and spatial understanding. The results indicate a moderate positive association between urban expansion and PM2.5, with stronger effects in compact growth areas. Population density emerged as a dominant contributing factor, while green spaces and water bodies showed mitigating influences. Seasonal variability analysis further highlights the role of urban form in shaping pollution dynamics, offering valuable insights for sustainable urban planning and environmental management strategies.

Urban Growth Dynamics and Air Quality in an Indian Metropolitan City: Deciphering Through Intra-Urban Heterogeneity and Inter-Variable Interactions

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发表日期：

2026年7月21日

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Gajender Kumar Sharma,
Ayyoob Sharifi

摘要

Rapid urbanization has emerged as a major global environmental challenge and a key driver of air quality deterioration in metropolitan regions, particularly in rapidly developing cities. Among atmospheric pollutants, PM_2.5 is of particular concern due to its severe health impacts and ability to penetrate deep into the respiratory system. This study investigates the influence of urban expansion intensity on PM_2.5 concentrations in Delhi, India, by integrating urban growth indicators, demographic factors, land-use characteristics, and meteorological parameters. Multi-temporal Landsat imagery, PM_2.5 observations, demographic datasets, and climatic variables were utilized to characterize urban expansion and its effects on air quality. Urban growth typologies, including infill, edge-expansion, and outlying development, were quantified using the Landscape Expansion Index (LEI), while Geographically Weighted Regression (GWR), correlation analysis, and mutual information metrics were employed to assess spatial and seasonal relationships. The urban expansion classification achieved an overall accuracy of 91.2% with a Kappa coefficient of 0.88. Correlation analysis confirmed the absence of significant multicollinearity among explanatory variables. Results revealed a moderate positive association between urban expansion intensity and PM_2.5 concentrations, with infill development exhibiting the strongest influence compared to edge-expansion and outlying growth patterns. GWR analysis demonstrated substantial spatial heterogeneity, with 42.8% of monitoring locations showing statistically significant positive relationships between urban expansion and PM_2.5 levels. Population density emerged as the most influential factor, whereas green spaces and water bodies exhibited mitigating effects. Seasonal analysis further indicated that urban morphology modifies meteorological influences and amplifies anthropogenic impacts on air quality. The study provides a spatially explicit framework for understanding urban-air quality interactions and supports sustainable urban planning, green infrastructure development, and climate-resilient environmental management in rapidly urbanizing cities.

Graphical Abstract

Based on the analytical framework, this study was conducted to examine the influence of urban expansion intensity on PM_2.5 concentrations and to understand the interplay between urban growth dynamics, environmental factors, and air quality in Delhi. The work captures complex relationships among demographic, land-use, and meteorological variables within a rapidly transforming metropolitan landscape. Air quality and urban growth indicators were assessed considering both spatial and statistical controls to uncover underlying mechanisms driving pollution patterns. Techniques including correlation analysis and Geographically Weighted Regression were employed to ensure robust inference and spatial understanding. The results indicate a moderate positive association between urban expansion and PM_2.5, with stronger effects in compact growth areas. Population density emerged as a dominant contributing factor, while green spaces and water bodies showed mitigating influences. Seasonal variability analysis further highlights the role of urban form in shaping pollution dynamics, offering valuable insights for sustainable urban planning and environmental management strategies.