American Association for Aerosol Research - Abstract Submission

AAAR 38th Annual Conference
October 5 - October 9, 2020

Virtual Conference

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Effect of Biomass Burning, Firework Emissions, and Haze Events on the Oxidative Potential of Ambient Particulate Matter in Delhi, India

JOSEPH V PUTHUSSERY, Ashutosh Shukla, Jay Dave, Sreenivas Gaddamidi, Atinder Singh, Dilip Ganguly, Neeraj Rastogi, Sachchida N. Tripathi, Vishal Verma, University of Illinois Urbana-Champaign

     Abstract Number: 117
     Working Group: Health-Related Aerosols

Abstract
Delhi, the capital of India, has the worst air quality among all major megacities in the world. Delhi experiences annual daily peaks of fine particulate matter (PM2.5) concentrations in the months of October - January, because of the various episodic events [biomass burning (BB), Diwali fireworks and the frequent haze events] which occur during this period. This increase in the PM2.5 mass concertation is expected to have an extremely adverse impact on the local and regional public health. Recent studies have shown that the oxidative potential (OP) of PM2.5 is a promising health metric over mass concentrations to estimate the PM2.5 toxicity.

In this study, we investigated the effect of BB emissions, fireworks emissions, and haze events on the OP [based on a dithiothreitol (DTT) assay] of ambient PM2.5. We sampled ambient PM2.5 at Delhi intermittently from October 11, 2019, to January 8, 2020 (~50 days). We used an automated OP measuring instrument, which was recently developed in our lab, to measure the hourly averaged real-time OP of ambient PM2.5. The chemical composition of PM2.5 was also measured using various collocated online instruments such as high-resolution time-of-flight aerosol mass spectrometer, aethalometer, and Xact® (total metals). Preliminary results showed extremely elevated ambient PM2.5 OP on the night of Diwali and during haze events, reaching up to 13 nmol/min/m3, which is among the highest reported DTT activity at any site in the world. We are currently combining the OP data with the chemical composition to perform source apportionment modeling, which is aimed to quantify the relative contribution of each of these episodic events on the PM2.5 OP. The results from this study would assist epidemiologists in quantifying the health risks associated with short term exposure to PM2.5 derived from these episodic events.