The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

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.

Characteristics and sources of volatile organic compounds (VOCs) were investigated with highly time-resolved simultaneous measurements by two proton-transfer-reaction time-of-flight mass spectrometers (PTR-ToF-MS) at an urban and a suburban site in New Delhi, India, from January to March 2018. During the measurement period, high mixing ratios of VOCs and trace gases were observed, with high nocturnal mixing ratios and strong day–night variations. The positive matrix factorization (PMF) receptor model was applied separately to the two sites, and six major factors of VOCs were identified at both sites, i.e., two factors related to traffic emissions, two to solid fuel combustion, and two secondary factors. At the urban site, traffic-related emissions comprising mostly mono-aromatic compounds were the dominant sources, contributing 56.6 % of the total mixing ratio, compared to 36.0 % at the suburban site. Emissions from various solid fuel combustion processes, particularly in the night, were identified as a significant source of aromatics, phenols and furans at both sites. The secondary factors accounted for 15.9 % of the total VOC concentration at the urban site and for 33.6 % at the suburban site. They were dominated by oxygenated VOCs and exhibited substantially higher contributions during daytime.

In recent years, intense haze events in megacities such as Beijing have received significant attention. Although secondary organic aerosol (SOA) has been identified as a major contributor to such events, knowledge of its sources and formation mechanisms remains uncertain. We investigate this question through the first field deployment of the extractive electrospray ionisation time-of-flight mass spectrometer (EESI-TOF) in Beijing, together with an Aerodyne long-time-of-flight aerosol mass spectrometer (L-TOF AMS). Measurements were performed during autumn and winter 2017, capturing the transition from non-heating to heating seasons. Source apportionment resolved four factors related to primary organic aerosols (traffic, cooking, biomass burning, and coal combustion), as well as four related to SOA. Of the SOA factors, two were related to solid fuel combustion (SFC), one to SOA generated from aqueous chemistry, and one to mixed/indeterminate sources. The SFC factors were identified from spectral signatures corresponding to aromatic oxidation products, while the aqueous SOA factor was characterised by signatures of small organic acids and diacids and unusually low ${\mathrm{CO}}^{+}/{\mathrm{CO}}_{\mathrm{2}}^{+}$ fragment ratios measured by the AMS. Solid fuel combustion was the dominant source of SOA during the heating season. However, a comparably intense haze event was also observed in the non-heating season and was dominated by the aqueous SOA factor. During this event, aqueous chemistry was promoted by the combination of high relative humidity and air masses passing over high-NO_x regions to the south and east of Beijing, leading to high particulate nitrate. The resulting high liquid water content was highly correlated with the concentration of the aqueous SOA factor. These results highlight the strong compositional variability between different haze events, indicating the need to consider multiple formation pathways and precursor sources to describe SOA during intense haze events in Beijing.

We present highly time-resolved (30 to 120 min) measurements of size-fractionated (PM₁₀ and PM_2.5) elements in two cities in Asia (Delhi and Beijing) and Europe (Krakow and London). For most elements, the mean concentrations in PM₁₀ and PM_2.5 are higher in the Asian cities (up to 24 and 28 times, respectively) than in Krakow and often higher in Delhi than in Beijing. Among European cities, Krakow shows higher elemental concentrations (up to 20 and 27 times, respectively) than London. Hourly maximum concentrations of Pb and Zn reach up to 1 µg m⁻³ in Delhi, substantially higher than at the other sites. The enrichment factor of an element together with the size distribution allows for a rough classification of elements by major source. We define five groups: (1) dust emissions, (2) non-exhaust traffic emissions, (3) solid fuel combustion, (4) mixed traffic/industrial emissions, and (5) industrial/coal/waste burning emissions, with the last group exhibiting the most site-to-site variability. We demonstrate that the high time resolution and size-segregated elemental dataset can be a powerful tool to assess aerosol composition and sources in urban environments. Our results highlight the need to consider the size distributions of toxic elements, diurnal patterns of targeted emissions, and local vs. regional effects in formulating effective environmental policies to protect public health.