Seasonal analysis of submicron aerosol in Old Delhi using high resolution aerosol mass spectrometry: Chemical characterisation, source apportionment and new marker identification

Abstract

Abstract. We present the first real-time composition of submicron particulate matter (PM1) in Old Delhi using high resolution aerosol mass spectrometry (HR-AMS). Old Delhi is one of the most polluted locations in the world, and PM1 concentrations reached ~ 600 µg m−3 during the most polluted period, the post-monsoon, where PM1 increased by 178 % over the pre-monsoon period. Using positive matrix factorisation (PMF) to perform source apportionment analysis, two burning-related factors contribute the most (35 %) to the post-monsoon increase. The first PMF factor, semi-volatility biomass burning organic aerosol (SVBBOA), shows a high correlation with earth observation fire counts in surrounding states which links its origin to crop residue burning. The second is a solid-fuel OA (SFOA) factor with links to local open burning due to its high composition of polyaromatic hydrocarbons (PAH) and novel AMS measured marker species for polychlorinated dibenzodioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). Two traffic factors were resolved, one hydrocarbon-like OA (HOA) factor and another nitrogen-rich HOA (NHOA) factor. The N compounds within NHOA were mainly nitrile species which have not previously been identified within AMS measurements. Their PAH composition suggests that NHOA is linked to diesel, and HOA to compressed natural gas and gasoline. These factors combined make the largest relative contribution to primary PM1 mass during the pre-monsoon and monsoon periods, while contributing the second highest in the post-monsoon. A cooking OA (COA) factor shows strong links to the secondary factor, semi-volatility oxygenated OA (SVOOA). Correlations with co-located volatile organic compound (VOC) measurements and AMS measured organic nitrogen oxides (OrgNO) suggest SVOOA is formed from aged COA. It is also found that a significant increase in chloride concentrations (488 %) from pre-monsoon to post-monsoon correlates well with SVBBOA and SFOA suggesting that crop residue burning and open waste burning are responsible. A reduction in traffic emissions would effectively reduce concentrations across most of the year. In order to reduce the post-monsoon peak, sources such as funeral pyres, solid waste burning and crop residue burning should be considered when developing new air quality policy.

PM<sub>1</sub> composition and source apportionment at two sites in Delhi, India, across multiple seasons

“…This shows both the importance of primary sources and the fact that daily average temperatures remain above 20 • C throughout the year; 20 • C in winter and 43 • C pre-monsoon, compared, for example, with European urban environments where average temperatures can drop to 5 • C or lower in winter and summer temperatures are around 25-30 • C. This temperature might increase the regional pollutant transport allowing an even POA-SOA distribution over the Delhi region. When comparing these results with Cash et al (2021), it shows the importance POA has in OD during the post-monsoon season, where a POA relative contribution of 63 % is observed. Meteorology played an important role in aerosol concentrations.…”

“…These POA relative contributions close to 50 % over different times of the year have been previously observed in a study performed in 2017 at IIT Delhi, New Delhi (Bhandari et al, 2020), with similar average concentrations for POAs and OOAs (52 and 56 µg m −3 , respectively, for winter as well as 30 and 31 mug m −3 , respectively, for pre-monsoon). Cash et al (2021) identified POA relative contributions of 45 % and 52 % for pre-monsoon and monsoon and 64 % for post-monsoon, showing the importance of POA concentrations in OD during this latter season. OOA concentrations are produced by both POAs and precursor gas.…”

“…It is interesting to see that BBOAs have low concentrations (2.0-8.0 µg m −3 ) in the ND and pre-monsoon seasons with a low contribution to OA sources (0.10-0.15). However, Cash et al (2021), in the PostM_OD_T_H2 analysis, identified a BBOA average concentration of 48.22 µg m −3 , representing a relative contribution of 25 %. COAs are an important primary source in OD, with average concentrations of 2.0-12.0 µg m −3 .…”

“…Section S3 in the Supplement provides detailed information about the criteria to select the OA factors. The PMF analysis of the OD_H2 measurements presented in this work was performed by Cash et al (2021) for the complete dataset (26 May-20 November) using highresolution organic mass spectra. The PMF analysis of the PreM_ND_H1 dataset was performed with unit mass resolution data.…”

“…Mass spectra and diurnal plots of OA factors from PMF analysis in the different periods.Here the period all_OD_H2 is displayed to compare with the other periods. The period all_OD_H2, which shows the high-resolution PMF analysis performed with the complete dataset of the AMS instruments (H2) 26 May-23 November 2018, is analysed in detail byCash et al (2021). Detailed analysis of the all_OD_H2 dataset is presented in TableS4, where the PMF analysis identified seven factors, adding HOA = HOA + nHOA and BBOA = SFOA + SVBBOA to compare with our five-factor solutions.…”