Advanced statistical analysis of air quality and its health impacts in India: Quantifying significance by detangling weather-driven effects

Abstract

Air quality has emerged as a significant concern due to its direct impact on human health. Over recent decades, India has witnessed a marked deterioration in air quality due to rising anthropogenic emissions and climate change. The COVID-19 lockdown offered a unique opportunity to examine air pollutant reductions under restricted human activities. This study conducted a long-term analysis of air quality in five major Indian cities—Delhi, Kolkata, Bengaluru, Hyderabad, and Visakhapatnam—by analysing variations in PM2.5, PM10, NOx, NH3, SO2, CO, and O3, incorporating a de-weathering strategy to isolate meteorological influences. In Delhi, we observed significant reductions in PM10 (92.50–136.70 μg/m³), NOx (62.13–151.91 ppb), and CO (0.53–0.88 mg/m³), which shifted health risks from the 'extreme' to 'low' category. Visakhapatnam also experienced notable declines in NOx levels (7.50–17.13 ppb). Conversely, Hyderabad exhibited no significant reductions, and AQHI increased (+0.97) due to rising NOx concentrations. Ozone concentrations showed a significant increase across cities, attributed to VOC-limited effects. The analysis revealed that meteorological variability and long-range transport of airmass played critical roles in shaping pollutant concentrations. These findings highlight the complexity of urban air quality dynamics and underscore the benefits of emission reductions for public health.

Keywords

• Urban air quality
• De-weathering analysis
• GAM model
• Statistical analysis
• Air quality health index
• COVID-19 lockdown