Variations in local, transported, and exposure risks of PM_2.5 pollution: Insights from long-term monitoring data in mega coastal city

Abstract

Urban air quality is influenced by both local and external sources of pollution. The outbreak of Coronavirus COVID-19 had led to implementation of stringent lockdowns at different levels of governance. National Level Lockdown (NLL) was imposed in 2020 and State Level Lockdown (SLL), in 2021 to curb the spread of disease. A direct consequence of lockdown is the dramatic improvement of air quality in various urban agglomerations. The present study investigated the effects of national and regional lockdown on PM_2.5 levels at various urban morphological units in the Chennai Metropolitan Region, the fourth-largest urban conglomeration in India. Hourly measurements of PM_2.5 over a 6-year period (2016–2021) at three monitoring sites in Chennai were segregated into Pre-lockdown Phase (PLP) (2016–2019), NLL, and SLL to analyze reductions in PM_2.5 levels. Local PM_2.5 sources were investigated using Conditional Bivariate Probability Function (CBPF) whereas transported PM_2.5 was evaluated using Concentration Weighted Trajectory (CWT) and Cluster Analysis. The results showed that PM_2.5 in Chennai Metropolitan Region reduced by 33.45% during NLL and 48.95% during SLL when compared to PLP. Mann Kendall Test showed a statistically significant (p < .001) decreasing PM_2.5 trend at Manali Monitoring Site, Alandur Monitoring Site, and Velachery Monitoring Site. CBPF showed variations in local contributions for all sites during the selected time frames. CWT and Cluster analysis showed reductions in transported PM_2.5 during NLL and SLL when compared to PLP. Health Risk Assessment using Integrated Exposure Response (IER) model function showed a decreasing trend of excess mortality for various health endpoints over 6-year period. Steep reductions in excess mortality cases were observed during NLL and SLL. The results show that lockdown implemented at the state level proved to be more effective than the national level in reducing PM_2.5 levels over Chennai metropolitan Region.

Keywords:

• Fine particulate matter (PM_2.5)
• conditional bivariate probability functions (CBPF)
• HYSPLIT
• concentration weighted trajectory (CWT)
• cluster analysis

Acknowledgments

The authors gratefully acknowledge Central Pollution Control Board (CPCB) for providing pollution data for the study. The authors also gratefully acknowledge NOAA Air Resources Laboratory (ARL) for provision of the HYSPLIT transport model.

Conflict of interest

The authors declare no competing interests.

Data availability statement

The data that support the findings of this study are available in Central Pollution Control Board (CPCB), India and Global Burden of Disease (GBD) These data were derived from the following resources available in the public domain: https://app.cpcbccr.com/ccr/#/caaqm-dashboard-all/caaqm-landing https://vizhub.healthdata.org/gbd-compare/.

Additional information

Funding

The first author (Pavanaditya Badida) gratefully acknowledges award of SRF from Council of Scientific and Industrial Research (CSIR), New Delhi (File No. 09/468/0503/2017-EMR-I), India in pursuit of his Ph.D. study.