Chetna1, Surendra K. Dhaka This email address is being protected from spambots. You need JavaScript enabled to view it.2, Gagandeep Longiany3, Vivek Panwar2, Vinay Kumar2, Shristy Malik4, A.S. Rao4, Narendra Singh5, A.P. Dimri6, Yutaka Matsumi7, Tomoki Nakayama8, Sachiko Hayashida9 1 Department of Physics and Astrophysics, University of Delhi, Delhi, India
2 Radio and Atmospheric Physics Lab, Rajdhani College, University of Delhi, New Delhi, India
3 Keshav Mahavidyalaya, University of Delhi, New Delhi, India
4 Department of Physics, Delhi Technical University, New Delhi, India
5 Aryabhatta Research Institute of Observational SciencES (ARIES), Manora Peak, Nainital 263001, India
6 School of Environmental Sciences, JNU, New Delhi, India
7 Institute for Space-Earth Environmental Research, Nagoya University, Nagoya 4648601, Japan
8 Faculty of Environmental Science, Nagasaki University, Nagasaki 8528521, Japan
9 Research Institute for Humanity and Nature, Kyoto 6038047, Japan
Received:
April 30, 2022
Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.
Revised:
July 15, 2022
Accepted:
August 6, 2022
Download Citation:
||https://doi.org/10.4209/aaqr.220191
Chetna, Dhaka, S.K., Longiany, G., Panwar, V., Kumar, V., Malik, S., Rao, A.S., Singh, N., Dimri, A.P., Matsumi, Y., Nakayama, T., Hayashida, S. (2022). Trends and Variability of PM2.5 at Different Time Scales over Delhi: Long-term Analysis 2007–2021. Aerosol Air Qual. Res. https://doi.org/10.4209/aaqr.220191
Cite this article:
The present study investigated the long-term inter-annual, seasonal, and monthly trend analysis and variability of PM2.5 at different time scales over the national capital, Delhi, India using high-resolution surface observations from six stations during 2007–2021. The non-parametric Mann-Kendall and Theil-Sen slope estimator were used to study the temporal variations. The long-term PM2.5 concentration showed an overall small but statistically significant decreasing trend with an average decrease of –1.35 (95% CI: –2.3, –0.47) µg m–3 year–1. Seasonal trends revealed a significant decreasing value of –3.05 µg m–3 year–1 (p < 0.1) for summer, insignificant declining trend of –1.95 µg m–3 year–1 for monsoon and no significant trend was found for the post-monsoon and winter season. Except for December and January, all months displayed a decreasing trend for PM2.5 concentration. These findings indicate that particle pollution over the city is declining at a very slow rate. A rising trend was found for relative humidity and surface pressure, whereas a declining trend for wind speed and PBLH noted. No trend was observed for temperature and rainfall. The Pearson linear correlation between PM2.5 and meteorological variables was studied using monthly mean data. Rainfall, air temperature, PBLH, and wind speed showed a negative correlation with PM2.5, whereas surface pressure had a positive correlation and relative humidity displayed an inverted U-shape relationship. The average concentration of PM2.5 in the study period of 15 years remained 125 ± 86 µg m–3 (ranging between 20 to 985 µg m–3) and during winter, summer, monsoon, and post-monsoon seasons it was 174 ± 75, 101 ± 48, 66 ± 50, and 192 ± 93 µg m–3 respectively. The monthly average PM2.5 concentration observed minimum in August and maximum in November. Satellite data of fire events showed that the crop residue burning over the Punjab region had a significant contribution to the peak PM2.5 levels in Delhi during the crop burning period. Government agencies need more strict action plans, especially during winter, to comply with air quality standards.HIGHLIGHTS
ABSTRACT
Keywords:
Long-term trend analysis, Seasonal variation, Theil-Sen approach, Particulate matter, Stubble crop burning
