Cleaning activities are essential for maintaining hygiene in indoor environments but can significantly influence indoor air quality (IAQ). We investigated emissions of volatile organic compounds (VOCs) and particulate matter (PM) during cleaning events across various indoor settings including two laboratories, an office, and a residential bathroom, with room volumes ranging from 22 to 206 m3 and air changes rates (ACR) of 0.85-9.14 h-1. Four cleaning solutions with different active ingredients were evaluated: quaternary ammonium compounds (quats), hydrogen peroxide (H2O2), sodium hypochlorite (bleach), and thymol. Cleaning increased PM2.5 by 0.7-14.5 μg m-3, depending on location and cleaning solution, with quats generally yielding the greatest increases. Measured total volatile organic compound (TVOC) mixing ratios also increased following cleaning by 10-104 ppbv, with the exception of experiments performed using thymol. We note that sensors such as the photoionization detector (PID) used in this work do not provide quantitative TVOC measurements. In general, greater emissions of PM2.5 and TVOCs were observed in locations with lower ACR. We also measured PM2.5 in a lobby, elevator, and public bathroom in a hotel with a number of COVID-positive occupants during routine surface disinfection using a quats-based disinfectant: increases of 5.5-14.2 μg m-3 were observed. This study demonstrates that emissions other than active ingredients can affect IAQ during surface cleaning, and provides information that may help mitigate harmful effects. It also provides insight into the use and limitations of low-cost sensors (LCS) in determining IAQ impacts from cleaning.

In this study, we evaluate the relative redox activity of various water-soluble organic aerosol (WSOA) sources in Delhi's winter PM2.5, focusing on their capacity to generate reactive oxygen species (ROS). Using offline-aerosol mass spectrometry (AMS) and positive matrix factorization (PMF), we identified two oxidized factors—more oxidized oxygenated organic aerosol (MO-OOA) and less oxidized oxygenated organic aerosol (LO-OOA)—and three primary factors, namely nitrogen-enriched hydrocarbon-like organic aerosol (NHOA), biomass-burning organic aerosol (BBOA), and solid-fuel combustion organic aerosol (SFC-OA). The ROS-generating capability of PM2.5 was assessed using a real-time oxidative potential (OP) measurement system based on the dithiothreitol (DTT) assay. We employed multivariate linear regression technique (MLR) to explore the association between the DTT activity of water-soluble PM2.5 and these identified factors. We found BBOA, SFCOA, and MO-OOA significantly contributed to volume-normalized OP, with intrinsic water-soluble activities of 39 ± 11, 106 ± 31 and 160 ± 43 pmol/min/μg, respectively. MO-OOA, primarily from non-fossil precursors, serves as a proxy for aged biomass burning, which intensifies during winter and significantly influences the DTT activity. Additionally, OP is significantly influenced by WSOA derived from local incomplete solid fuel combustion sources, including coal and wood burning for household cooking and heating, burning of leaves, biodegradable waste, and garbage along the roadside. Interestingly, water-soluble metals (Mn, Cu, and Fe) showed no discernible contribution to the OP. These findings highlight the need for targeted mitigation strategies addressing local combustion processes and unregulated biomass burning to effectively reduce PM health exposure in Delhi.

Exposure to elevated particulate matter (PM) concentrations in ambient air has become a major health concern over urban areas worldwide. Reactive oxygen species (ROS) generation due to ambient PM (termed as their oxidative potential, OP) is shown to play a major role in PM-induced health effects. In the present study, the OP of the ambient PM2.5 samples, collected during summer 2019 from New Delhi, were measured using the dithiothreitol (DTT) assay. Average volume-normalized OP (OPV) was 2.9 ± 1.1 nmol DTT min−1 m−3, and mass-normalized OP (OPm) was 61 ± 29 pmol DTT min−1 μg−1. The regression statistics of OPv vs chemical species show the maximum slope of OPV with the elemental carbon (EC, r2 = 0.72) followed by water-soluble organic carbon (WSOC, r2 = 0.72), and organic carbon (OC, r2 = 0.64). A strong positive correlation between OPm and secondary inorganic aerosols (SIA, such as NH4+ and NO3− mass fractions) was also observed, indicating that the sources emitting NO2 and NH3, precursors of NO3− and NH4+, also emit DTT-active species. Interestingly, the slope value of OPv vs OC for aged aerosols (OM/OC > 1.7, f44 > 0.12 and f43 < 0.04) was 1.7 times higher than relatively fresh organic aerosols (OA, OM/OC < 1.7, f44 < 0.12, f43 > 0.04). An increase in OPv and OPoc with f44 indicates the formation of more DTT active species with the ageing of OA. A linear increase in OPoc with increasing Nitrogen/Carbon (N/C) ratio suggests that nitrogenous OA have higher OP.

Delhi's post-monsoon and winter haze reduces visibility, causes health hazards, and interrupts usual routines. Multiple source apportionment (SA) studies recently apportioned sources and discussed organic and elemental PM source characteristics independently. To design effective pollution control strategies, it's important to obtain a comprehensive picture of particulate matter (PM2.5) sources by doing SA on consolidated data that combines organics, inorganics, black carbon (BC), and metals. In this study, we tried to improve the understanding of PM2.5 sources by performing double-PMF (D-PMF) analysis on a consolidated dataset encompassing non-refractory PM2.5 factors, elements, and BC. Real-time instrumentation (HR-ToF-AMS, Xact, and Aethalometer) were used at two urban sites (IITD and IITMD) in Delhi during post-monsoon and winter seasons. The hourly average C-PM2.5 (Composition based PM2.5 is sum of NR-PM2.5, BC and metals) at IITD for the overall study period (1(st) Oct 2019 to 8(th) Jan 2020) was 91.9 +/- 56.5 mu gm(-3), while at IITMD for the overall sampling period (31(st) Oct 2019 to 31(st) Dec 2019) was 105.2 +/- 61.2 mu gm(-3). The sources identified by the double-PMF at both sites were road dust, traffic, secondary nitrate, secondary sulfate, oxidized organic aerosol (OOA), biomass burning (BB), and industrial. In contrast, fireworks were only resolved at IITD, and secondary chloride at IITMD. At IITD, the temporal variation of sources was noted between the post-monsoon, Diwali, and winter seasons. The secondary nitrate (17%, 15.8 +/- 9.4 mu gm(-3)) and BB (39.4%, 36.6 +/- 43.6 mu gm(-3)) were dominant during winter suggest the rapid-nighttime oxidation with favourable low temperature condition and increased heating activities, while OOA (33.4%, 17.2 +/- 8.0 mu gm(-3)) and secondary sulfate (12.7%, 6.5 +/- 4.4 mu gm(-3)) were dominating during the post-monsoon at IITD due to the high photochemical oxidation and long-range transport. The fireworks (22.2%, 26.6 +/- 43.8 mu gm(-3)) contributed a major fraction of sources during Diwali at IITD. For the concurrent measurement period (14(th) Nov 2019 to 31(st) Dec 2019) at both the sites, the mean hourly average concentration (C-PM2.5) was 102.2 +/- 53.2 mu g m(-3) at IITD and 99.7 +/- 59.6 mu gm(-3) at the IITMD site. Secondary nitrate and secondary sulfate were prevalent at IITMD, while OOA and traffic dominated at IITD. D-PMF improved interpretation of sources such as the SO4_OA and NO3_OA contributions to industrial sources (Pb-rich and Zn-rich) indicate the possibility of sulfate and nitrate accumulation on metal-rich particles (for example, the formation of ZnSO4 and PbSO4). The signals of NO3_OA in the fireworks factor are due to the gunpowder (KNO3), while HOA and BBOA suggest the role of burn-related organics. The elemental ratios K/Pb (17 at IITD) and K/As (137 at IITMD) in the secondary sulfate source from D-PMF further highlighted the role of coal combustion. The D-PMF results were in excellent agreement with single PMF on combined data (SC-PMF) done as a part of an extended study.

Abstract. 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.

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.

Delhi metropolitan area suffers from extreme haze during the post‐monsoon and winter season, impacting climate, public health, and economy. We used a high‐resolution time‐of‐flight aerosol mass spectrometer (HR‐ToF‐AMS) and aethalometer at two urban locations in Delhi to capture non‐refractory PM2.5 (NR‐PM2.5) and black carbon (BC) during the post‐monsoon and winter season of 2019–2020. Four haze periods with high composition based‐PM2.5 (C‐PM2.5 = NR‐PM2.5 + BC) concentration and distinct chemical composition were identified, during all of which organics dominated but with varying contribution (∼[50%–70%] of C‐PM2.5). Biomass burning organic aerosol (BBOA) was dominant in all periods (∼[31%–45%] of OA), but the majority of it was highly aged ∼(45%–50%) with high O/C (0.71 and 0.46 at the two sites), formed most likely through rapid dark oxidation of freshly emitted and partially oxidized BBOA. High polycyclic aromatic hydrocarbons (PAH) signals in the fresh BBOA mass spectra suggest incomplete combustion activities such as open biomass burning emissions as major source. During an agricultural burning event in north‐western India, we estimated that ∼(44%–53%) of total C‐PM2.5 (combined contribution of aged BBOA and oxygenated OA) measured in Delhi was influenced by long‐range transported biomass burning emissions. During winter, secondary inorganics constituted a significant fraction apart from organics ∼(48%–55%), mainly in the form of ammonium nitrate (NH4NO3; up to ∼[19%–25%] of C‐PM2.5) and ammonium sulfate (NH4SO4; up to ∼[27%–38%]). Enhanced formation of NH4NO3 and related‐secondary organic aerosol (SOA) were linked to nighttime oxidation of BBOA, while NH4SO4 and related‐SOA were linked to heterogeneous aqueous phase oxidation under high RH conditions (>90%).

This study investigates the dithiothreitol (DTT)-based oxidative potential (OP) and corresponding hydroxyl radical (& BULL;OH) generations capacity of PM2.5 (particulate matter with aerodynamic diameter & LE; 2.5 mu m) over a high-altitude site, Shillong (25.7 N, 91.9 E; 1064 m above mean sea level), located in the northeastern Himalaya. Measured OP and & BULL;OH are reported in two units: per m3 of filtered air (OPV and OHV) or per unit mass of PM2.5 in mu g (OPM and OHM). Based on the characteristic ratios of chemical species in different sources, PM2.5 were classified into three source categories: Biomass Burning (BB) (N = 10), Secondary Organic Aerosols (SOA) (N = 12), and Mixed (N = 12). Consistently higher OP and & BULL;OH generation per m3 of air (OPV: 6.2 & PLUSMN; 1.0 (average & PLUSMN; SD, 1 & USigma;) nmol DTT min- 1 m- 3, and OHV: 1.2 & PLUSMN; 0.31 nmol & BULL;OH m- 3) in all BB-dominated PM2.5 samples indicate relatively hazardous exposure dose from BB emissions among all sources. Characteristic OC/EC, WSOC/ OC, and nss-K+/EC ratios evoked that SOA from biogenic precursors was a significant source for the observed OP and & BULL;OH in SOA-categorized samples. Distinctly different chemical composition of PM2.5 over Shillong (about 55% composed of organic matter) makes it relatively more (2-4 times) intrinsically redox-active compare to a reported study over another high-altitude site in a semi-arid region of India. Despite-1.7 times lower PM2.5 mass over Shillong (characterized by more aged PM2.5) compare to Patiala (30.3N, 76.4E; 250m amsl, a semi-urban city, characterized by fresher PM2.5 from mixed sources), the observed OPV over Shillong was about 1.2 times higher, and the OPM was about 2 times higher. It is attributed to the effect of atmospheric processing on particle's redox-activity. While examining the relationship of OPV and OHV with chemical species, it was observed that & BULL;OH generation capacity was more influenced by WSOC species' origin (primary or secondary) compare to DTT consumption. Such an observation restricts the practicality of particle-induced OP to be considered as the only metric for aerosol particle toxicity, and suggests also to consider simultaneous measurements of & BULL;OH generations. For the BB-dominated category, OC-normalized OP (OPOC) was correlated strongly with the fractions of N -containing water-soluble organic aerosols (i.e., a fraction of WSON and a fraction of familyCHO1N). Corre-sponding OC/EC, nss-K+/EC and nss-SO2-4/EC ratios hint that coal combustion, in addition to BB, could be a significant source of redox-active WSON species in these samples. Such studies are important for identifying redox-active aerosol species and developing appropriate mitigation policies for healthy air.

Diwali is among the most important Indian festivals, and elaborate firework displays mark the evening's festivities. This study assesses the impact of Diwali on the concentration, composition, and sources of ambient PM2.5. We observed the total PM2.5 concentrations to rise to 16 times the pre-firework levels, while each of the elemental, organic, and black carbon fractions of ambient PM2.5 increased by a factor of 46.1, 3.7, and 5.6, respectively. The concentration of species like K, Al, Sr, Ba, S, and Bi displayed distinct peaks during the firework event and were identified as tracers. The average concentrations of potential carcinogens, like As, exceeded US EPA screening levels for industrial air by a factor of ~9.6, while peak levels reached up to 16.1 times the screening levels. The source apportionment study, undertaken using positive matrix factorization, revealed the fireworks to account for 95% of the total elemental PM2.5 during Diwali. The resolved primary organic emissions, too, were enhanced by a factor of 8 during Diwali. Delhi has encountered serious haze events following Diwali in recent years; this study highlights that biomass burning emissions rather than the fireworks drive the poor air quality in the days following Diwali.

We investigated the influence of biomass burning (BURN), Diwali fireworks, and fog events on the ambient fine particulate matter (PM2.5) oxidative potential (OP) during the postmonsoon (PMON) and winter season in Delhi, India. The real-time hourly averaged OP (based on a dithiothreitol assay) and PM2.5 chemical composition were measured intermittently from October 2019 to January 2020. The peak extrinsic OP (OPv: normalized by the volume of air) was observed during the winter fog (WFOG) (5.23 ± 4.6 nmol·min-1·m-3), whereas the intrinsic OP (OPm; normalized by the PM2.5 mass) was the highest during the Diwali firework-influenced period (29.4 ± 18.48 pmol·min-1·μg-1). Source apportionment analysis using positive matrix factorization revealed that traffic + resuspended dust-related emissions (39%) and secondary sulfate + oxidized organic aerosols (38%) were driving the OPv during the PMON period, whereas BURN aerosols dominated (37%) the OPv during the WFOG period. Firework-related emissions became a significant contributor (∼32%) to the OPv during the Diwali period (4 day period from October 26 to 29), and its contribution peaked (72%) on the night of Diwali. Discerning the influence of seasonal and episodic sources on health-relevant properties of PM2.5, such as OP, could help better understand the causal relationships between PM2.5 and health effects in India.

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.

This study investigates the impact of reduced anthropogenic emissions during the lockdown period on the concentration, composition, and characteristics of non-refractory particular matter <= 2.5 mu m aerodynamic diameter (NR-PM2.5) and black carbon (BC) at Ahmedabad, a big city in western India. Online measurements were performed from February 29 to March 23 (before lockdown, P1), April 10 to May 01 (during the lockdown, P2), and June 1 to June 16 (post lockdown, P3) using a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and an Aethalometer. On average, organic aerosols (OA), NO3?, SO4 2?, NH4+, Cl? , BC at 370 nm (BC370), and BC at 880 nm (BC880) were reduced by 52, 64, 43, 62, 86, 52, and 57%, respectively, during P2 compare to P1. However, the diurnal trends of species were similar during the lockdown and no-lockdown periods. Source apportionment of OA using positive matrix factorization analysis revealed three factors: hydrocarbon-like organic aerosol (HOA), low volatile oxygenated OA (LV-OOA), and semi-volatile oxygenated OA (SV-OOA), contributing 26%, 44% and, 30%, respectively, to the total OA during the study period. Such studies are very crucial in assessing the effects of reduced anthropogenic emissions on the air quality of big cities, and planning appropriate mitigation strategies.

Delhi is one of the most polluted cities globally, with frequent severe air pollution episodes and haze events occurring in recent years, thereby compelling us to understand the sources to develop effective mitigation plans. Complete chemical characterization of fine particulate matter (PM2.5) components (non-refractory, refractory and elements) with high time resolution has been done during the summer season (June-July 2019). The total PM equivalent (PM2.5(eq)) was 28.7 +/- 13.2 mu g m(-3) of which elements dominated the PM2.5(eq) with 34% contribution followed by organics (28%), black carbon (BC) (17%), SO42- (10%), Cl- (5%) NH4+ (3.5%) and NO3(2.5%). The contributions from organic aerosols (OA) and SO42- were observed to be more than Cl- and NO3- . The total elemental mass concentration (PMEl) was mostly contributed (similar to 96%) by Si, S, Cl, Ca, K, Fe and Al with Si and S alone contributing around 50% of PMEl. Crustal elements (Al, Fe, Ca and Si) were highly enhanced in summer than elements emitted from anthropogenic emissions (Cl, S, K, Pb and Zn). Source apportionment (SA) of PM was performed using positive matrix factorization (PMF) together with ME-2 (multilinear engine) for OA and elements, separately. PMF on both datasets helped resolve sources such as combustion, industrial, dust-related, incineration and traffic. OA PMF identified three factors related to primary emissions: hydrocarbon-like OA (HOA, 12.3%), solid fuel combustion (SFC, 16.2%) and cooking OA (COA, 7.3%) and two oxygenated OA (OOA): semi-volatile OOA (SVOOA, 15.2%) and low-volatile OOA (LVOOA, 49.1%). The elemental PMF resolved 8 factors: dust (52.5%), S-rich (16.2%), Cl-rich (10.7%), 2 SFC factors (10.5%), non-exhaust (7.2%), Cu-rich (1.5%) and industrial (1.4%). The contribution of BC to total PM mass is shown to increase in the summer compared to previous studies reported for the winter season. The secondary oxidized sources dominated both the OA and elements SA during the summer with 64.3% and 27% (dust not considered) contribution, respectively. The domination of secondary sources implies that it is crucial to control the secondary aerosols' precursors in Delhi for developing pollution control strategies. The ME-2 resolved factors, coupled with concentration weighted trajectory (CWT) showed the probable major elemental source regions of local origin (Delhi-National Capital Region (Delhi-NCR)) as well as regional (from Punjab, Haryana, Uttar Pradesh and Pakistan). The local sources included Cu-rich (Haryana) and SFC-II (Delhi and Uttar Pradesh), while the regional sources were dust (southwest (SW)), industrial, Cl-rich (north-west (NW)), SFC-I (east and south-east (SE)) and S-rich (SE).

Avg± Stdev Min Max Avg± Stdev Min Max Avg± Stdev Min Max Online NO3 - 4.61±2.401.19 12.61 8.53±5.431.28 26.33 10.04±6.960.72 30.03Offline NO3 - 1.15±0.880.04 5.31 13.53±9.652.41 45.18 9.21±6.5 1.17 25.79 Online SO4 2- 0.97±0.740.19 2.68 7.08±4.321.82 19.55 9.52±8.20.81 42.46 Offline SO4 2- 5.17±4.190.66 16.31 12.18±5.752.61 31.68 10.84±10.341.57 39.58 Online NH4 + 1.36±0.370.51 3.32 6.26±3.631.74 14.73 8.24±5.610.45 24.33 Offline NH4 + 2.47±1.320.96 6.43 7.55±3.592.23 21.43 8.89±6.621.23 27.32 Online Cl - 0.28±0.320.03 1.44 1.96±3.590.14 7.04 4.48±3.110.07 11.40 Offline Cl - 1.64±0.730.28 3.47 3.46±1.861.14 8.57 5.18±3.610.32 14.12

In recent times, a significant number of studies on the composition and sources of fine particulate matters and volatile organic compounds have been carried out over Delhi, either initiated by or in association with the researchers from the Indian Institute of Technology Kanpur (IIT Kanpur), in collaboration with researchers from within and outside India. All these studies utilized highly time-resolved, campaign-mode observations made with state-of-the-art instrumentation during the late winter months (mid-January to March) of 2018. Individually, each of these studies were rigorous in nature, containing explicit detailing about different types of ambient air pollutants in Delhi such as organic aerosols, inorganic elements, metals, carbonaceous aerosols, and volatile organic compounds. This study consolidates the extremely useful knowledge on source attribution of these air pollutants in the Delhi National Capital Region currently contained in these fragmented studies, which is vital to further enhancing our understanding of composition, characteristics, and sources of air pollutants over Delhi, as well as to designing appropriate mitigation measures tailored to local specifics.

Diwali is among the most important Indian festivals, and elaborate firework displays mark the festivities in the evening. This study assesses the impact of Diwali on the concentration, composition, and sources of ambient PM2.5. The total PM2.5 concentrations were observed to rise by ~16 times their pre-firework levels, while each of the elements, organics, and black carbon were augmented by a factor of 12.3, 1.6, and 2.3, respectively. Concentration levels of species like K, Al, Sr, Ba, S, and Bi displayed distinct peaks during the firework event and were identified as tracers for the same. The average concentrations of potential carcinogens like As, exceeded US EPA screening levels for industrial air by a factor of ~9.6, while peak levels reached up to 16.1 times the screening levels. The source apportionment study, undertaken using positive matrix factorization, revealed the fireworks to account for 95% of the total elemental PM2.5 during Diwali. The resolved primary organic emissions, too, were enhanced by a factor of ~8 during Diwali. Delhi has encountered serious haze events following Diwali in recent years, this study highlights that it is the biomass burning emissions rather than the fireworks that dominate Delhi's air quality in the days following Diwali.

Diwali is among the most important Indian festivals, and elaborate firework displays mark the festivities in the evening. This study assesses the impact of Diwali on the concentration, composition, and sources of ambient PM2.5. The total PM2.5 concentrations were observed to rise by ~16 times their pre-firework levels, while each of the elements, organics, and black carbon were augmented by a factor of 12.3, 1.6, and 2.3, respectively. Concentration levels of species like K, Al, Sr, Ba, S, and Bi displayed distinct peaks during the firework event and were identified as tracers for the same. The average concentrations of potential carcinogens like As, exceeded US EPA screening levels for industrial air by a factor of ~9.6, while peak levels reached up to 16.1 times the screening levels. The source apportionment study, undertaken using positive matrix factorization, revealed the fireworks to account for 95% of the total elemental PM2.5 during Diwali. The resolved primary organic emissions, too, were enhanced by a factor of ~8 during Diwali. Delhi has encountered serious haze events following Diwali in recent years, this study highlights that it is the biomass burning emissions rather than the fireworks that dominate Delhi's air quality in the days following Diwali.