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Response of organic aerosol to Delhi's pollution control measures over the period 2011–2018

Cash, James M. ORCID: https://orcid.org/0000-0002-8567-1377; Di Marco, Chiara ORCID: https://orcid.org/0000-0002-9635-8191; Langford, Ben ORCID: https://orcid.org/0000-0002-6968-5197; Heal, Mathew R.; Mandal, Tuhin K.; Sharma, Sudhir K.; Gurjar, Bhola Ram; Nemitz, Eiko ORCID: https://orcid.org/0000-0002-1765-6298. 2023 Response of organic aerosol to Delhi's pollution control measures over the period 2011–2018. Atmospheric Environment, 315, 120123. 15, pp. 10.1016/j.atmosenv.2023.120123

Abstract
Some of the world's highest air pollution episodes occur in Delhi, India and studies have shown particulate matter (PM) is the leading air pollutant to cause adverse health effects on Delhi's population. It is therefore vital to chart sources of PM over long time periods to effectively identify trends, particularly as multiple air quality mitigation measures have been implemented in Delhi over the past 10 years but remain unevaluated. An automated offline aerosol mass spectrometry (AMS) method has been developed which has enabled high-throughput analysis of PM filters. This novel offline-AMS method uses an organic solvent mix of acetone and water to deliver high extraction recoveries of organic aerosol (OA) (95.4 ± 8.3%). Positive matrix factorisation (PMF) source apportionment was performed on the OA fraction extracted from PM10 filter samples collected in Delhi in 2011, 2015 and 2018 to provide snapshots of the responses of OA to changes in sources in Delhi. The nine factors of OA resolved by PMF group into four primary source categories: traffic, cooking, coal-combustion and burning-related (solid fuel or open burning). Burning-related OA made the largest contribution during the winter and post-monsoon, when total OA concentrations were at their highest. Annual mean burning-related OA concentrations declined by 47% between 2015 and 2018, likely associated with the 2015 ban on open waste burning and controls and incentives to reduce crop-residue burning. Compositional analysis of OA factors shows municipal waste burning tracers still present in 2018, indicating further scope to reduce burning-related OA. The closure of the two coal power stations, along with initiatives to decrease coal use in industry, businesses, and residential homes, resulted in a significant decrease (87%) in coal-combustion OA. This corresponds to a 17% reduction in total OA, which shows the effectiveness of these measures in reducing PM10. Increases in traffic OA appear to have been offset by the introduction of the Bharat stage emissions standards for vehicles as the increases do not reflect the rapid increase in registered vehicles. However, daytime restrictions on heavy goods vehicles (HGVs) entering the city is linked to large increases in PM10 during the winter and post-monsoon, likely because the large influx of diesel-engine HGVs during the early mornings and evenings is timed with a particularly low planetary boundary layer height that enhances surface concentrations.
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