Long-term Trends in PM2.5 Levels in Delhi: A Statistical Approach (2010-2024)

Abstract

Air pollution has now been recognized as a global health risk, with Delhi being one of the most severely affected cities worldwide. Fine particulate matter (PM2.5), largely emitted from vehicle exhausts, industrial emissions, and biomass burning, remains a critical concern across Indian cities. Delhi has consistently been ranked among the most polluted cities globally, with pollution episodes particularly severe during winter months mainly due to temperature inversions and seasonal crop residue burning. This study aims to assess the long-term trends in PM2.5 from 2010 to 2024 using statistical and time series analysis methods. Annual averages were analysed using descriptive statistics, the non-parametric Mann–Kendall test, Sen’s slope, simple linear regression analysis, and ARIMA forecasting. The annual mean concentrations of PM2.5 over the study period were 118.03 µg/m³, which is approximately 23 percent higher than the WHO standards of 5 µg/m³. The results of the Mann-Kendall test and Sen’s slope observed a declining trend of 3.38 µg/m³/year (τ = –0.702, p < 0.001). The AutoRegressive Integrated Moving Average (ARIMA) model predicts a continuous yet gradual decline in PM2.5 levels. The observed trend shows a modest decline in PM2.5 levels over the study period, yet concentrations remain well above safe limits that pose significant health risks. There is a need to improve the existing policies to bring noticeable changes in pollution levels. Also, in the future, empirical studies should focus on developing more detailed and refined models that incorporate meteorological factors, spatial heterogeneity, and more detailed information on the sources of emission.