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In recent years, the Indian capital city of Delhi has been impacted by very high levels of air pollution, especially during winter. Comprehensive knowledge of the composition and sources of the organic aerosol (OA), which constitutes a substantial fraction of total particulate mass (PM) in Delhi, is central to formulating effective public health policies. Previous source apportionment studies in Delhi identified key sources of primary OA (POA) and showed that secondary OA (SOA) played a major role but were unable to resolve specific SOA sources. We address the latter through the first field deployment of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) in Delhi, together with a high-resolution aerosol mass spectrometer (AMS). Measurements were conducted during the winter of 2018/19, and positive matrix factorization (PMF) was used separately on AMS and EESI-TOF datasets to apportion the sources of OA. AMS PMF analysis yielded three primary and two secondary factors which were attributed to hydrocarbon-like OA (HOA), biomass burning OA (BBOA-1 and BBOA-2), more oxidized oxygenated OA (MO-OOA), and less oxidized oxygenated OA (LO-OOA). On average, 40 % of the total OA mass was apportioned to the secondary factors. The SOA contribution to total OA mass varied greatly between the daytime (76.8 %, 10:00–16:00 local time (LT)) and nighttime (31.0 %, 21:00–04:00 LT). The higher chemical resolution of EESI-TOF data allowed identification of individual SOA sources. The EESI-TOF PMF analysis in total yielded six factors, two of which were primary factors (primary biomass burning and cooking-related OA). The remaining four factors were predominantly of secondary origin: aromatic SOA, biogenic SOA, aged biomass burning SOA, and mixed urban SOA. Due to the uncertainties in the EESI-TOF ion sensitivities, mass concentrations of EESI-TOF SOA-dominated factors were related to the total AMS SOA (i.e. MO-OOA + LO-OOA) by multiple linear regression (MLR). Aromatic SOA was the major SOA component during the daytime, with a 55.2 % contribution to total SOA mass (42.4 % contribution to total OA). Its contribution to total SOA, however, decreased to 25.4 % (7.9 % of total OA) during the nighttime. This factor was attributed to the oxidation of light aromatic compounds emitted mostly from traffic. Biogenic SOA accounted for 18.4 % of total SOA mass (14.2 % of total OA) during the daytime and 36.1 % of total SOA mass (11.2 % of total OA) during the nighttime. Aged biomass burning and mixed urban SOA accounted for 15.2 % and 11.0 % of total SOA mass (11.7 % and 8.5 % of total OA mass), respectively, during the daytime and 15.4 % and 22.9 % of total SOA mass (4.8 % and 7.1 % of total OA mass), respectively, during the nighttime. A simple dilution–partitioning model was applied on all EESI-TOF factors to estimate the fraction of observed daytime concentrations resulting from local photochemical production (SOA) or emissions (POA). Aromatic SOA, aged biomass burning, and mixed urban SOA were all found to be dominated by local photochemical production, likely from the oxidation of locally emitted volatile organic compounds (VOCs). In contrast, biogenic SOA was related to the oxidation of diffuse regional emissions of isoprene and monoterpenes. The findings of this study show that in Delhi, the nighttime high concentrations are caused by POA emissions led by traffic and biomass burning and the daytime OA is dominated by SOA, with aromatic SOA accounting for the largest fraction. Because aromatic SOA is possibly more toxic than biogenic SOA and primary OA, its dominance during the daytime suggests an increased OA toxicity and health-related consequences for the general public., Atmospheric Chemistry and Physics, 22 (11), ISSN:1680-7375, ISSN:1680-7367

Characterizing the chemical composition of ambient particulate matter (PM) provides valuable information on the concentration of secondary species and toxic metals and assists in the validation of abatement techniques. The chemical components of PM can be measured by sampling on filters and analyzing them in the laboratory or using real-time measurements of the species. It is important for the accuracy of the PM monitoring networks that measurements from the offline and online methods are comparable and biases are known. The concentrations of water-soluble inorganic ions (NO3−, SO42−, NH4+, and Cl−) in PM2.5 measured from 24 h filter samples using ion chromatography (IC) were compared with the online measurements of inorganics from an aerosol mass spectrometer (AMS) with a frequency of 2 min. Also, the concentrations of heavy and trace elements determined from 24 h filter samples using inductively coupled plasma mass spectroscopy (ICP-MS) were compared with the online measurements of half-hourly heavy and trace metal concentrations from an Xact 625i ambient metal mass monitor. The comparison was performed over two seasons (summer and winter) and at two sites (Indian Institute of Technology Delhi (IITD) and Indian Institute of Tropical Meteorology, Delhi (IITMD)) which are located in the Delhi National Capital Region (NCR), India, one of the most heavily polluted urban areas in the world. Collocated deployments of the instruments helped to quantify the differences between online and offline measurements and evaluate the possible reasons for positive and negative biases. The slopes for SO42− and NH4+ were closer to the 1:1 line during winter and decreased during summer at both sites. The higher concentrations on the filters were due to the formation of particulate (NH4)2SO4. Filter-based NO3− measurements were lower than online NO3− during summer at IITD and winter at IITMD due to the volatile nature of NO3− from the filter substrate. Offline-measured Cl− was consistently higher than AMS-derived Cl− during summer and winter at both sites. Based on their comparability characteristics, elements were grouped into three categories. The online element data were highly correlated (R2>0.8) with the offline measurements for Al, K, Ca, Ti, Zn, Mn, Fe, Ba, and Pb during summer at IITD and winter at both the sites. The higher correlation coefficient demonstrated the precision of the measurements of these elements by both the Xact 625i and ICP-MS. Some of these elements showed higher Xact 625i elemental concentrations than ICP-MS measurements by an average of 10 %–40 % depending on the season and site. The reasons for the differences in the concentration of the elements could be the distance between two inlets for the two methods, line interference between two elements in Xact measurements, the sampling strategy, variable concentrations of elements in blank filters, and the digestion protocol for ICP-MS measurements.

Characterizing the chemical composition of ambient particulate matter (PM) provides valuable information on the concentration of secondary species, toxic metals and assists in the validation of abatement techniques. The chemical components of PM can be measured by sampling on filters and analysing them in the laboratory or using real-time measurements of the species. It is important for the accuracy of the PM monitoring networks that measurements from the offline and online methods are comparable and biases are known. The concentrations of water-soluble inorganic ions (NO3−, SO42−, NH4+ and Cl−) in PM2.5 measured from the 24 hrs filter samples using ion chromatography (IC) were compared with the online measurements of inorganics from aerosol mass spectrometer (AMS) with a frequency of 2 mins. Also, the concentrations of heavy and trace elements determined from the 24 hrs filter samples using inductively coupled plasma mass spectroscopy (ICP-MS) were compared with the online measurements of half-hourly heavy and trace metal’s concentrations from Xact 625i ambient metal mass monitor. The comparison was performed over two seasons (summer and winter) characterized by their different metrological conditions at IITD and during winter at IITMD, two sites located in Delhi, NCR, India, one of the heavily polluted urban areas in the world. Collocated deployments of the instruments helped to quantify the differences between online and offline measurements and evaluate the possible reasons for positive and negative biases. The slopes for SO42− and NH4+ were closer to 1:1 line during winter and decreased during summer at both sites. The higher concentrations on the filters were due to the formation of particulate (NH4)2SO4. Filter-based NO3− measurements were lower than online NO3− during summer at IITD and winter at IITMD due to the volatile nature of NO3− from the filter substrate. Offline measured Cl− was consistently higher than AMS derived Cl− during summer and winter at both sites. Based on their comparability characteristics, elements were grouped under 3 categories. The online element data were highly correlated (R2 > 0.8) with the offline measurements for Al, K, Ca, Ti, Zn, Mn, Fe, Ba, and Pb during summer at IITD and winter at both the sites. The higher correlation coefficient demonstrated the precision of the measurements of these elements by both Xact 625i and ICP-MS. Some of these elements showed higher Xact 625i elemental concentrations than ICP-MS measurements by an average of 10–40 % depending on the season and site. The reasons for the differences in the concentration of the elements could be the distance between two inlets for the two methods, line interference between two elements in Xact measurements, sampling strategy, variable concentrations of elements in blank filters and digestion protocol for ICP measurements.