Meteorological influences on air pollution dynamics in pollution epicentre of National Capital Region, India

Abstract

This study analyzes the temporal variations and source characteristics of air pollution in Delhi, examining the influence of meteorological conditions on pollutant concentrations. The goal is to provide insights for policymakers to develop effective emission reduction strategies and improve air quality. Innovative Trend Analysis (ITA) and Detrended Fluctuation Analysis (DFA) were used to identify long-term trends and fluctuations in pollutants such as PM₁₀, PM₂.₅, NO₂, SO₂, CO, O₃, and NH₃ from 2018 to 2023. Continuous Wavelet Transformation (CWT) and Cross-Wavelet Transformation (XWT) were utilized to explore seasonal patterns and pollutant-meteorology interactions. Receptor modeling techniques, including non-parametric wind regression and conditional probability function analysis, were applied to identify major pollution sources. The study found that key emission sources were located to the west, south, and southwest of the monitoring site for most pollutants, with ozone precursors predominantly originating from the north. ITA and DFA revealed persistent long-range correlations in pollutant levels, driven by stable emission sources and seasonal meteorological effects. CWT analysis showed distinct periodic patterns in air quality, with worsening conditions during winter and summer. The research highlights the role of temperature inversions, low wind speeds, and regional pollutant transport in exacerbating pollution levels but emphasizes that human-driven emission sources remain the primary contributors to air quality deterioration. While meteorological factors influence pollution dispersion, they do not diminish the urgency of emission control measures. The findings support the development of targeted pollution control policies, including emission reduction from industrial, vehicular, and biomass burning sources. Advancing real-time air quality monitoring and integrating socio-economic considerations into air pollution management will enhance the effectiveness of interventions, aligning with Sustainable Development Goals (SDG 11 - urban sustainability and SDG 3 - public health).