Abstract. Delhi, India, routinely experiences some of the world's highest urban particulate matter concentrations. We established the Delhi Aerosol Supersite study to provide long-term characterization of the ambient submicron aerosol composition in Delhi. Here we report on 1.25 years of highly time-resolved speciated submicron particulate matter (PM1) data, including black carbon (BC) and nonrefractory PM1 (NR-PM1), which we combine to develop a composition-based estimate of PM1 (“C-PM1” = BC + NR-PM1) concentrations. We observed marked seasonal and diurnal variability in the concentration and composition of PM1 owing to the interactions of sources and atmospheric processes. Winter was the most polluted period of the year, with average C-PM1 mass concentrations of ∼210 µg m−3. The monsoon was hot and rainy, consequently making it the least polluted (C-PM1 ∼50 µg m−3) period. Organics constituted more than half of the C-PM1 for all seasons and times of day. While ammonium, chloride, and nitrate each were ∼10 % of the C-PM1 for the cooler months, BC and sulfate contributed ∼5 % each. For the warmer periods, the fractional contribution of BC and sulfate to C-PM1 increased, and the chloride contribution decreased to less than 2 %. The seasonal and diurnal variation in absolute mass loadings were generally consistent with changes in ventilation coefficients, with higher concentrations for periods with unfavorable meteorology – low planetary boundary layer height and low wind speeds. However, the variation in C-PM1 composition was influenced by temporally varying sources, photochemistry, and gas–particle partitioning. During cool periods when wind was from the northwest, episodic hourly averaged chloride concentrations reached 50–100 µg m−3, ranking among the highest chloride concentrations reported anywhere in the world. We estimated the contribution of primary emissions and secondary processes to Delhi's submicron aerosol. Secondary species contributed almost 50 %–70 % of Delhi's C-PM1 mass for the winter and spring months and up to 60 %–80 % for the warmer summer and monsoon months. For the cooler months that had the highest C-PM1 concentrations, the nighttime sources were skewed towards primary sources, while the daytime C-PM1 was dominated by secondary species. Overall, these findings point to the important effects of both primary emissions and more regional atmospheric chemistry on influencing the extreme particle concentrations that impact the Delhi megacity region. Future air quality strategies considering Delhi's situation in both a regional and local context will be more effective than policies targeting only local, primary air pollutants.

<p><strong>Abstract.</strong> Delhi, India, is the second most populated city in the world and routinely experiences some of the highest particulate matter concentrations of any megacity on the planet, posing acute challenges to public health (World Health Organization, 2018). However, the current understanding of the sources and dynamics of PM pollution in Delhi is limited. Measurements at the Delhi Aerosol Supersite (DAS) provide a long-term chemical characterization of ambient submicron aerosol in Delhi, with near-continuous online measurements of aerosol composition. Here we report on source apportionment based on positive matrix factorization (PMF), conducted on 15 months of highly time-resolved speciated submicron non-refractory PM1 (NRPM1) between January 2017 and March 2018. We report on seasonal variability across four seasons of 2017 and interannual variability using data from the two winters and springs of 2017 and 2018. We show that a modified tracer-based organic component analysis provides an opportunity for a real-time source apportionment approach for organics in Delhi. Thermodynamic modeling allows estimation of the importance of ventilation coefficient (VC) and temperature in controlling primary and secondary organic aerosol. We also find that primary aerosol dominates severe air pollution episodes.</p>

Abstract. The Indian national capital, Delhi, routinely experiences some of the world's highest urban particulate matter concentrations. While fine particulate matter (PM2.5) mass concentrations in Delhi are at least an order of magnitude higher than in many western cities, the particle number (PN) concentrations are not similarly elevated. Here we report on 1.25 years of highly time-resolved particle size distribution (PSD) data in the size range of 12–560 nm. We observed that the large number of accumulation mode particles – that constitute most of the PM2.5 mass – also contributed substantially to the PN concentrations. The ultrafine particle (UFP; Dp<100 nm) fraction of PNs was higher during the traffic rush hours and for daytimes of warmer seasons, which is consistent with traffic and nucleation events being major sources of urban UFPs. UFP concentrations were found to be relatively lower during periods with some of the highest mass concentrations. Calculations based on measured PSDs and coagulation theory suggest UFP concentrations are suppressed by a rapid coagulation sink during polluted periods when large concentrations of particles in the accumulation mode result in high surface area concentrations. A smaller accumulation mode for warmer months results in an increased UFP fraction, likely owing to a comparatively smaller coagulation sink. We also see evidence suggestive of nucleation which may also contribute to the increased UFP proportions during the warmer seasons. Even though coagulation does not affect mass concentrations, it can significantly govern PN levels with important health and policy implications. Implications of a strong accumulation mode coagulation sink for future air quality control efforts in Delhi are that a reduction in mass concentration, especially in winter, may not produce a proportional reduction in PN concentrations. Strategies that only target accumulation mode particles (which constitute much of the fine PM2.5 mass) may even lead to an increase in the UFP concentrations as the coagulation sink decreases.

Abstract. Delhi, India, is the second most populated city in the world and routinely experiences some of the highest particulate matter concentrations of any megacity on the planet, posing acute challenges to public health (World Health Organization, 2018). However, the current understanding of the sources and dynamics of PM pollution in Delhi is limited. Measurements at the Delhi Aerosol Supersite (DAS) provide long-term chemical characterization of ambient submicron aerosol in Delhi, with near-continuous online measurements of aerosol composition. Here we report on source apportionment based on positive matrix factorization (PMF), conducted on 15 months of highly time-resolved speciated submicron non-refractory PM1 (NR-PM1) between January 2017 and March 2018. We report on seasonal variability across four seasons of 2017 and interannual variability using data from the two winters and springs of 2017 and 2018. We show that a modified tracer-based organic component analysis provides an opportunity for a real-time source apportionment approach for organics in Delhi. Phase equilibrium modeling of aerosols using the extended aerosol inorganics model (E-AIM) predicts equilibrium gas-phase concentrations and allows evaluation of the importance of the ventilation coefficient (VC) and temperature in controlling primary and secondary organic aerosol. We also find that primary aerosol dominates severe air pollution episodes, and secondary aerosol dominates seasonal averages.

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Low-cost sensors (LCS) offer the opportunity to measure urban air quality at a spatiotemporal scale that is finer than what is currently practical with expensive research-or regulatory-grade instruments. Recently, the LCS research community has focused largely on sensor calibration, pollution monitoring, and exposure assessment; here, we investigate the applicability of LCS for characterizing particulate pollution sources in an urban environment. Using an integrated multipollutant LCS system (which measures both gases and particles), we collected air quality data for 6 weeks during the winter at a site in Delhi, India. The results were compared to measurements taken by colocated research-grade particle instruments. Non-negative matrix factorization was used to deconvolve LCS data into unique factors that were then identified by examining the factor composition and comparing them to the research-grade measurements. The data were described well by three factors: a combustion factor characterized by high CO levels and two factors characterized by measured particles. These factors align well with measurements by research-grade instruments, including particle types determined from factor analysis of online particle composition measurements. This work demonstrates that multipollutant LCS measurements, despite their inherent limitations (e.g., calibration challenges and inability to measure smallest particles), can provide insight into sources of fine particulate matter in a complex urban environment.

Abstract. Delhi is a megacity subject to high local anthropogenic emissions and long-range transport of pollutants. This work presents for the first time time-resolved estimates of hygroscopicity parameter (κ) and cloud condensation nuclei (CCN), spanning for more than a year, derived from chemical composition and size distribution data. As a part of the Delhi Aerosol Supersite (DAS) campaign, the characterization of aerosol composition and size distribution was conducted from January 2017 to March 2018. Air masses originating from the Arabian Sea (AS), Bay of Bengal (BB), and southern Asia (SA) exhibited distinct characteristics of time-resolved sub-micron non-refractory PM1 (NRPM1) species, size distributions, and CCN number concentrations. The SA air mass had the highest NRPM1 loading with high chloride and organics, followed by the BB air mass, which was more contaminated than AS, with a higher organic fraction and nitrate. The primary sources were identified as biomass-burning, thermal power plant emissions, industrial emissions, and vehicular emissions. The average hygroscopicity parameter (κ), calculated by the mixing rule, was approximately 0.3 (varying between 0.13 and 0.77) for all the air masses (0.32±0.06 for AS, 0.31±0.06 for BB, and 0.32±0.10 for SA). The diurnal variations in κ were impacted by the chemical properties and thus source activities. The total, Aitken, and accumulation mode number concentrations were higher for SA, followed by BB and AS. The mean values of estimated CCN number concentration (NCCN; 3669–28926 cm−3) and the activated fraction (af; 0.19–0.87), for supersaturations varying from 0.1 % to 0.8 %, also showed the same trend, implying that these were highest in SA, followed by those in BB and then those in AS. The size turned out to be more important than chemical composition directly, and the NCCN was governed by either the Aitken or accumulation modes, depending upon the supersaturation (SS) and critical diameter (Dc). af was governed mainly by the geometric mean diameter (GMD), and such a high af (0.71±0.14 for the most dominant sub-branch of the SA air mass – R1 – at 0.4 % SS) has not been seen anywhere in the world for a continental site. The high af was a consequence of very low Dc (25–130 nm, for SS ranging from 0.1 % to 0.8 %) observed for Delhi. Indirectly, the chemical properties also impacted CCN and af by impacting the diurnal patterns of Aitken and accumulation modes, κ and Dc. The high-hygroscopic nature of aerosols, high NCCN, and high af can severely impact the precipitation patterns of the Indian monsoon in Delhi, impact the radiation budget, and have indirect effects and need to be investigated to quantify this impact.

polluted seasons in Delhi when PM 1 concentrations steadily increase throughout the season and can exceed 1000 µgm -3 during episodic events. Positive matrix factorization on the organic aerosol (OA) spectrum suggests comparable seasonal average contributions from HOA (Hydrocarbon-like OA), BBOA (Biomass-Burning OA) and OOA (Oxidized-OA), with BBOA dominating during episodic events. We demonstrate the influence of regional sources such as agricultural burning during this season through temporal trends of pollutants, PMF factors, meteorology, and non-parametric wind regression analysis. We use inorganic fragment ratios to show the influence of metals during the festival of Diwali. Furthermore, we demonstrate the influence of transitioning meteorology in governing PM 1 composition through the season. Overall, our analysis provides novel insights into the factors controlling PM 1 during one of the most polluted seasons in Delhi.