Delhi experiences a wide range of variation in temperature (T), relative humidity (RH), wind speeds, and precipitation across the year and by time of day (Fig. ). The winters (December to mid-February) are cool (T∼10–20 ∘C, average diurnal range) and humid (RH ∼45 %–90 %) with low wind speeds (∼2–3 m s-1). Delhi frequently experiences shallow inversion layers (depth <100 m) during the winter, especially at night and in the morning hours. Summers (April to June) are very hot (T∼25–40 ∘C) and dry (RH ∼30 %–55 %). Delhi and most of the Indo-Gangetic Plain experiences episodic heavy rainfall during the monsoon (July to mid-September), accompanied by slightly lower temperatures (T∼25–35 ∘C) than the summers. While the winds throughout most of the year are predominately from the northwest, during the monsoon the wind is from the south during the nighttime. Spring (mid-February to March) and autumn (mid-September to November) are periods of transition between these meteorological extremes. For all seasons, the ventilation coefficient is highest during the daytime when the boundary layer height and the wind speeds reach their diurnal maxima. Changes in ventilation play an important role in the large seasonal and diurnal variation of PM . Unfavorable meteorological conditions often amplify primary emissions to produce spectacularly high PM2.5 concentrations .

To investigate the composition of ambient air in New Delhi at high time resolution, we installed a suite of online aerosol measurement instrumentation at the Indian Institute of Technology Delhi (IITD) campus in South Delhi. The instruments are situated in a temperature-controlled laboratory on the top floor of a four-story building. The nearest source of local emissions is an arterial road located 150 m away from the building. We measured chemical composition of nonrefractory PM1 (NR-PM1) was measured using an Aerodyne Aerosol Chemical Speciation Monitor (ACSM; Aerodyne Research, Billerica, MA). BC was measured using a multi-channel aethalometer (Magee Scientific Model AE33, Berkeley, CA) with a multi-spot sampling system designed to minimize the filter loading artifact present on earlier aethalometer systems . Particle size distributions (PSDs) were measured using a scanning mobility particle sizer (SMPS; TSI, Shoreview, MN), consisting of an electrostatic classifier (TSI model 3080), a differential mobility analyzer (DMA; TSI model 3081), an X-ray aerosol neutralizer (TSI model 3088), and a water-based condensation particle counter (CPC; TSI model 3785).

The instruments were placed on two separate sampling lines. The first sampling line (SL1) had the ACSM and the SMPS in parallel. The second sampling line (SL2) was for the aethalometer. Both sampling lines had a PM2.5 cyclone at the inlet, followed by a water trap and a Nafion membrane diffusion dryer (Magee Scientific sample stream dryer, Berkeley, CA). The flow rate in SL1 was 3 L min-1, divided as follows: 1 L min-1 pulled by the SMPS, 0.1 L min-1 by the ACSM, and the remaining 1.9 L min-1 by an in-line flow controller which was in parallel with the SMPS and downstream from the ACSM. SL2 had a flow rate of 2 L min-1 pulled by the aethalometer. For the SMPS, the CPC pulled at a 1 L min-1 flow rate, and the electrostatic classifier was operated at a sheath flow rate of 4 L min-1 to enable SMPS scanning over a broad range of particle sizes. We conducted experiments at multiple sheath flow rates from 4 to 10 L min-1 and found the results to be consistent.

The ACSM measures NR-PM1, i.e., those compounds that flash vaporize at the heater temperature of ∼600 ∘C. The flash-vaporized compounds are subsequently ionized in the ACSM via 70 eV electron impact ionization and detected with a quadrupole mass spectrometer . The scan speed was set at 200 ms amu-1 and pause setting at 125 for a sampling time (64 s). Detailed operational procedures for the ACSM are provided in Appendix . Some submicron aerosol constituents are refractory, including BC, metals, and crustal materials. For our core analyses of PM1 mass, we use the sum of NR-PM1 + BC as a composition-based proxy for total PM1, which we term “C-PM1”. This C-PM1 metric excludes the contribution to submicron mass of refractory metals and crustal materials, which we estimate results in a 5 %–10 % underestimate of total PM1 mass (see below).

The SMPS scanned from 12 to 560 nm, with each subsequent scan 135 s apart. We used a mode fitting algorithm in the mass domain to estimate the PSD between 560 and 1000 nm. We validated the performance of our model by comparing the modeled and observed volume and number concentrations for the observed particle size range. We found that the model predicted the same volume as was observed (slope=1.00, R2=1.00) but slightly overestimated particle number concentrations (slope=1.06, R2=0.96), mostly for smaller particles. In order to develop a supplemental PSD-based estimate of submicron mass, we first estimated a complete (hybrid) PSD up to 1000 nm by combining the observed PSD from 12 to 560 nm and the modeled PSD from 560 to 1000 nm. Estimates of aerosol densities from Asia range between 1.3 and 1.6 g cm-3 . Using a particle density of 1.6 g cm-3 and the hybrid PSD, we developed a SMPS-based PM1 estimate (“SMPS-PM1”). On an hourly basis, the linear fit between our core C-PM1 and supplemental SMPS-PM1 estimates had a slope of 0.96 and an R2 of 0.85 (Fig. S1 in the Supplement). This linear fit suggested that our speciated PM1 data (NR-PM1 species and BC) agreed reasonably well with the SMPS-PM1 estimates. We used the PSD to estimate the transmission efficiency (TE) of the ACSM. The details of this correction along with other ACSM data processing steps are provided in Appendix . We estimate an overall uncertainty of up to 20 %–25 % in the ACSM data, which is within expectations for measurements from this instrument .

While we acquired data for each instrument at high time resolution (∼1 min for the aethalometer and the ACSM; ∼2 min for the SMPS), for analytical simplicity we generally present the hourly averaged data for each instrument in this study. We categorize the seasons as winters (December to mid-February), summers (April to June), the monsoon (July to mid-September), and spring (mid-February to March) . Autumn (mid-September to November) is not included in our core analyses due to the unavailability of ACSM data for that period. In our analysis, we define day as 07:00–19:00 and night as 19:00–07:00.

We retrieved the hourly temperature and relative humidity (RH) data from the Indira Gandhi International Airport (IGIA; 8 km from our site). To obtain mesoscale (regional) meteorological data for wind speed, direction (10 m from ground), and planetary boundary layer height (PBLH) in Delhi, we used a NASA meteorological reanalysis dataset, MERRA2 . MERRA2 has a spatial resolution of 0.5∘×0.625∘ (55 km × 60 km) and an hourly temporal resolution. We retrieved daily precipitation data for Delhi from the European Centre for Medium-Range Weather Forecasts' reanalysis dataset, ERA-Interim .

The hourly data for all species across the campaign are neither strictly normally nor log-normally distributed (Fig. S2). However, since the data are relatively closer to being log-normally distributed, we have included geometric mean (GM) and geometric standard deviation (GSD) in addition to the arithmetic mean (AM) wherever possible to provide a more complete representation of the central tendency of the data. Furthermore, the annual averages reported in this study are the averages of all the available hourly data from 2017 for the NR-PM1 species and BC. It should be noted that we do not have ACSM data (NR-PM1 species) for autumn and only a few days of aethalometer data (BC) for the monsoon. On the basis of available SMPS-PM1 data (our site) and PM2.5 data (multiple regulatory monitors in Delhi), we estimate that the true annual average differs from the data we collected by within ±20 %. As a sensitivity analysis, we reconstruct annual and campaign averages by giving equal weight to each 2-month period. For example, to calculate the synthetic (reconstructed) annual average for 2017, we averaged the averages of the six 2-month periods (January–February through November–December). In Table S1 we have provided a comparison between the AM, GM, and the synthetic averages of the PM1 components for the 2017 data against the entire campaign data.

We observed marked seasonal and diurnal variation in the PM mass concentration owing to the interactions of sources, atmospheric mixing, and physicochemical processing. Figure  shows the time series of NR-PM1, individual submicron species, PM2.5 at a background site, and selected meteorological parameters. The daily average NR-PM1 concentrations at our site varied between 12.7 and 392 µg m-3, with an annual average of 87.3 µg m-3. Most C-PM1 mass was nonrefractory – the average NR-PM1 fraction of C-PM1 was highest in the winter (94 %) and lowest for warmer months (85 %) (Fig. ). The average wintertime NR-PM1 concentration was ∼2 times higher than spring and ∼4 times higher than the warmer months. Using speciated mass concentrations and the PSD, we observed that C-PM1 was highly correlated with SMPS-PM1 (R2=0.83), and we achieved almost complete mass closure (Fig. S1). That most of the PM1 was composed of nonrefractory material and BC was consistent with past literature from Delhi which observed that metals and other nonrefractory crustal materials, which we did not measure in this study, constituted less than 5 % of PM1 .

We estimated that the C-PM1 concentrations observed at our site were generally ∼85 % of the PM2.5 concentrations (R2=0.54 and slope=0.85 for linear fit of hourly C-PM1 and PM2.5 concentrations over entire campaign) measured at the nearest monitoring station that is operated by the Delhi Pollution Control Committee (DPCC), R.K. Puram (3 km away), where the annual average PM2.5 concentration for 2017 was 140 µg m-3. There were strong seasonal and diurnal variations in mass loadings, with winter being the most polluted with average concentration ∼4 times higher than the least polluted summer and monsoon months. The daily average PM2.5 concentration exceeded the daily average Indian National Ambient Air Quality Standards (NAAQS; 60 µg m-3) on more than 80 % of the days and the World Health Organization (WHO) 24 h average air quality guidelines (25 µg m-3) on all but two days. A distinct feature of Delhi's wintertime air pollution is the nearly complete absence of periods of clean air, in contrast to some other polluted megacities (e.g., Beijing), which are characterized by episodic alternation between clean and polluted conditions . For wintertime, the daily average PM2.5 concentrations exceeded 100 µg m-3 on 94 % of the days, the Indian NAAQS on 99 % of the days, and the WHO guidelines on all days. Daily-average PM2.5 concentrations at R.K. Puram exceeded 500 µg m-3 on four days in 2017.

The concentrations and fractional contribution to PM1 of each species varied by season and time of day. Over the campaign, organics comprised 54 % of the submicron mass, inorganics (chloride, ammonium, nitrate, and sulfate) 36 %, and BC 10 %. There was a strong seasonality in C-PM1 loadings, with the wintertime average loadings exceeding the relatively less polluted and warmer summer and monsoon months by 3–4 times. We report the average seasonal concentrations of organics, sulfate, ammonium, nitrate, chloride, and BC in Table  and their contribution to C-PM1 in Fig. . Within each season there were distinct diurnal (time-of-day) trends for the average concentrations by hour of day for NR-PM1 and PM1 components (Fig. ). These diurnal swings of the average hourly concentrations were the most prominent for the colder winter and spring months. In winter, average hourly NR-PM1 concentrations ranged between 97.4 and 254 µg m-3 (minimum and maximum concentrations for the average diurnal cycle). Spring conditions were moderately less polluted, with hourly average concentrations ranging diurnally from 37.0 to 167 µg m-3. The NR-PM1 concentrations varied much less during summer (range of concentrations for an average diurnal cycle: 38.7 to 72.4 µg m-3) and the monsoon (32.1 to 47.7 µg m-3). For most seasons, the hourly averaged NR-PM1 concentrations peaked around 07:00–08:00 and then again around 21:00–22:00, with the daily minimum typically occurring around 15:00–16:00. However, for the monsoon months the NR-PM1 average hourly concentrations were similar throughout the day. The diurnal variation in average hourly concentrations and fractional composition of NR-PM1 species for each season is presented in Fig. . The day and night averages by season for each PM1 species along with the summary averages of meteorological parameters are presented in Table . We did not observe any marked day of the week difference in the levels or composition of C-PM1 (Fig. S3).

Organics were the single largest C-PM1 mass component for all seasons and at all times of the average diurnal cycle. Organics consistently contributed to more than ∼50 % of seasonal C-PM1 mass, with some episodes when their contribution was as high as 80 %. The high organic fraction of PM is consistent with studies from across the world . The daily averages of organics at our site varied between 6.4 and 293 µg m-3, with an annual average of 51.5 µg m-3. The average wintertime organic concentration was ∼2 times higher than spring and ∼4–5 times higher than summer and the monsoon. While the wintertime organic concentrations ranged between 53.3 and 166 µg m-3, with the highest concentration during the night, the diurnal variations were less dynamic for the warmer months, with the hourly average organic concentrations ranging between 20.8 and 49.8 µg m-3 for summertime. Comparing daytime and nighttime f43 and f44 values for each season, the bulk organic aerosol was generally more oxidized during the warmer periods (Fig. S4), presumably owing to the higher photochemical activity during that time .

Ammonium was the prominent inorganic cation in C-PM1 and generally balanced all the anionic inorganic species (chloride, nitrate, and sulfate). Over the campaign, the molar ratio of the inorganic anions to cations (ammonium) was 0.82 (R2=0.96). Ammonium mass concentrations were consistently around ∼10 % of the observed C-PM1. The daily average of ammonium at our site varied between 1.5 and 37.9 µg m-3, with an annual average of 9.0 µg m-3. The average ammonium concentration for wintertime was ∼2 times higher than spring and ∼4 times higher than summer and the monsoon. Ammonium concentration hourly averages ranged between 10.9 and 30.8 µg m-3 during the winter and between 4.2 and 8.3 µg m-3 during the summer.

We observed some of the highest chloride concentrations reported anywhere in the world, with episodes when hourly averages exceeded 100 µg m-3 (more than 40 such hours across the campaign). The 90th and 95th percentile values of the hourly concentrations of chloride over the campaign were 26.7 and 43.8 µg m-3, respectively. The daily average of chloride concentration at our site varied between 0.1 and 66.6 µg m-3, with an annual average of 6.1 µg m-3. Chloride concentrations showed the strongest seasonal variability, with the average wintertime concentration ∼2 times higher than during spring and more than 20 times higher than during the warm (summer and monsoon) months. During the cooler winter and spring months, chloride concentrations had the largest diurnal variation among all PM species observed, with the average diurnal minimum and maximum hourly concentration ranging between 4.6 and 47.3 µg m-3 in wintertime. The winter chloride peak is notable for its timing in the early morning hours (∼ 07:00), which is considerably later than the diurnal peak in organics and BC, which tended to occur shortly before midnight. While chloride contributed more than 10 % of the submicron mass in the winters, it comprised less than 2 % of the C-PM1 mass concentration during the summer and monsoon. Furthermore, chloride constituted around 12 %–16 % of NR-PM1 for temperatures below 15 ∘C but dropped to less than 4 % of the NR-PM1 concentrations for temperatures above 25 ∘C (Fig. S5). Given that ammonium was nearly always present in sufficient quantities to neutralize the major inorganic anions measured by the ACSM, we infer that the dominant fraction of chloride was usually present as ammonium chloride, for which gas–particle partitioning is strongly temperature dependent. (However, we cannot exclude the possibility that organic chlorides contributed a subsidiary fraction of the chloride mass.) Even for high episodic chloride concentrations, ammonium was present in sufficient levels to neutralize most of the anionic species, with a deficiency of only ∼20 % when considering only hours with chloride concentrations higher than the 90th percentile campaign value (26.7 µg m-3).

To understand whether the sharp drop in chloride concentrations for warmer times of day could be explained by evaporation of ammonium chloride, we used an inorganic aerosol thermodynamics model . The detailed methodology and results of the model used are presented in Appendix . Results from inorganic thermodynamic modeling suggest that most of the ammonium chloride observed in the winter is expected to evaporate at summer temperatures and relative humidity, consistent with our observations. The volatile nature of ammonium chloride has also been observed in other parts of the world and was consistent with the sharp drop in the chloride fraction that we observed for the warmer periods. We believe that gas–particle partitioning and episodic sources (Sect. ) may drive much of the diurnal and seasonal variation in particulate chloride. We would therefore expect a large fraction of chloride to be in the gas phase, especially for warmer periods. We did not collect gas-phase HCl measurements here, but future studies could validate this hypothesis through measurements of gas-phase chloride.

Nitrate comprised 6 %–12 % of Delhi's C-PM1, with daily averages between 0.6 and 58.5 µg m-3, with an annual average of 8.8 µg m-3. The average wintertime nitrate concentration was more than 2 times higher than spring and more than 6 times higher than summer and the monsoon. The average diurnal cycle (lowest and highest hourly average concentration) for wintertime concentrations ranged between 15.9 and 33.6 µg m-3, and the summer concentrations ranged between 2.2 and 6.3 µg m-3. The nitrate fraction of NR-PM1 dropped from 12 % at temperatures below 25 ∘C to 5 %–9 % at temperatures above 25 ∘C, likely due to the thermodynamics of ammonium nitrate. As with chloride, nitrate concentrations were also generally highly correlated with ammonium concentrations (R2=0.69 for hourly data over entire campaign), suggesting that most of the nitrate observed was present as ammonium nitrate. Considering the ubiquitous NOx sources in this megacity, organic nitrates may also contribute to the total nitrate measured by the ACSM.

The daily averages of sulfate at our sites varied between 3.1 and 34.5 µg m-3, with an annual average of 11.8 µg m-3. Sulfate had the least seasonal variability among the NR-PM1 species, with wintertime average concentration ∼1.5 times higher than each of the other seasons (spring, summer, and monsoon). In addition to the low seasonal variability, sulfate was also the chemical constituent with the least diurnal variation and had relatively higher daytime concentrations for the warmer summer months. The diurnal variation in sulfate concentration for the cooler months was similar to that of other PM1 species, with the average early morning concentrations for winter and spring almost 2 times higher than the daytime concentrations. Sulfate was the only NR-PM1 species that had a higher mass fraction during the warmer months, contributing 13 %–30 % to the C-PM1 mass in the warmer months, 8 %–20 % in spring, and 5 %–13 % in winter, with the mass fraction being highest during the daytime for all seasons. The sulfate fraction of NR-PM1 increased from less than 10 % for periods cooler than 25 ∘C to more than 25 % for periods above 35 ∘C. The increase in sulfate mass fraction for warmer periods can be explained by the lower diurnal and seasonal variability in its absolute concentration, possibly due to a combination of increased daytime photochemical formation rates for warmer months and sulfate being well mixed in the atmosphere because of its transport from longer distances .

BC contributed to 6.4 % of the C-PM1 mass concentration in the winter compared to 10 % in the spring and 14 % in the summer. We had limited monsoon data for BC. The daily average of BC at our site varied between 2.2 and 35.2 µg m-3, with an annual average of 12.4 µg m-3. The average wintertime BC concentration was ∼1.5 times higher than spring and summer. The seasonal differences in the absolute BC concentrations were not as high as any of the other PM1 species. One possible explanation for this result relates to the presence of nearby BC sources within Delhi, including the major ring road with truck traffic near our sampling site. These trucks are often restricted to only passing through Delhi at night . It is plausible that these nearby primary emissions would be incompletely mixed into the boundary layer and are therefore relatively less affected by atmospheric mixing (Sect.  and ). Accordingly, BC had sharp diurnal variability, with peak nocturnal BC concentrations typically ∼3–4 times higher than during midday hours, with peak concentrations occurring at a similar time to the temporal peak for organics (typically just before midnight).

The planetary boundary layer height (PBLH) had a strong seasonal variation with summer heights 2–4 times larger than those during the cooler months. The seasonal variability in the PBLH along with that in wind speed resulted in the ventilation coefficient (VC = PBLH × wind speed, sometimes referred to as normalized dilution rate) being 4–6 times slower for the wintertime compared to the summer. The VC is often used as a parameter to characterize the role of atmospheric dilution in pollutant concentrations, both in the Indian context and globally . Seasonal variability in the VC appears to reasonably agree with the higher NR-PM1 concentrations in less ventilated cold months and lower concentrations in the warmer months when the VC was higher (Fig. ). The week with the lowest VC was ∼6 times less ventilated than the most ventilated week and had ∼6 times higher NR-PM1 mass concentrations. For the non-monsoon periods, the VC was generally a good indicator of NR-PM1 concentrations (R2=0.56 for weekly averaged data). For the cooler winter and spring months, the R2 for the linear fit of the weekly averaged VC and NR-PM1 concentrations was 0.79. The monsoon concentrations were lower than those that would be expected by the VC calculated for those periods. This result could be explained by a combination of change in the prominent nighttime wind direction from northwest to south during the monsoon and the washout of PM by the monsoon rain. For the monsoon period, we observed that the average NR-PM1 mass concentration was almost half on days when it rained compared to the dry (no rain) days with no change in the composition of NR-PM1. The strong modulating effect of meteorology on air pollution is well appreciated for Delhi and other Indian cities .

Even within each season, the VC showed large time-of-day variations, with highest hourly average values 5–10 times larger than the lowest. For each season, times of day with a lower VC had the highest NR-PM1 concentrations, and the concentrations decreased as the VC value increased (Fig. S7). The large diurnal range of the VC seemed to explain most of the variability in NR-PM1 concentrations by time of day for most seasons (Rwinter2=0.88; Rspring2=0.93; Rsummer2=0.81). For the monsoon, the diurnal variability of most PM1 species was generally low, even though the VC varied by time of day, possibly due to precipitation washout of PM and a change in characteristic wind direction during the monsoon (as discussed above).

In general, the sharp variation in the VC by season and time of day appear to explain much of the variability in NR-PM1 concentrations. Furthermore, volatile species (e.g., ammonium chloride and ammonium nitrate) evaporate to the gas phase during warmer periods, further lowering the mass concentrations compared to the cooler periods. While there are seasonal differences in emissions from sources such as crop burning and local biomass burning for heat , our analysis suggests that in addition to episodic sources, meteorology being unfavorable is an important factor for some of the high PM concentrations observed.

Positive matrix factorization (PMF) conducted on the ACSM mass spectra provided further information on the sources and atmospheric processes that affect NR-PM1 concentrations in Delhi . The organic aerosol (OA) was separated into two factors: primary OA (POA) and oxygenated OA (OOA), with periods when the POA factor further separated into hydrocarbon-like OA (HOA) and biomass-burning OA (BBOA). POA exhibited strong diurnal variability, reflecting the impact of primary combustion emissions modulated by diurnal cycles in the PBLH. The POA fraction of organics was generally highest during the nighttime (∼50 % for winter and ∼40 % for summer) and lowest during the daytime (∼20 % for both winter and summer). As observed in other megacities, OOA was the largest constituent of the organic aerosol throughout the year , demonstrating the profound influence of secondary formation on particle concentrations in Delhi. OOA contributed to 50 %–80 % of the organics almost year-round (Fig. S9). We estimated primary particulate matter (PPM=POA+Chl+BC) and secondary particulate matter (SPM=OOA+NH4+NO3+SO4) following . Since chloride was considered primary, and ammonium was generally highly correlated with chloride, we apportioned a chloride-equimolar amount of ammonium as primary and the remaining as secondary organic aerosol. In Fig.  we separate C-PM1 into PPM and SPM by season and time of day. We observed that almost 50 %–70 % of Delhi's C-PM1 was secondary in nature for the winter and spring months and up to 60 %–80 % for the warmer summer and monsoon months. Our results show that secondary aerosol accounts for the dominant fraction of Delhi's ambient NR-PM1 under most conditions. While our analyses do not provide direct evidence for the origin of the secondary fraction of PM1, consideration of typical advection timescales from the upwind boundaries of Delhi (∼2–3 h at typical wind speeds) suggests that a substantial fraction of Delhi's secondary aerosol may be transported from upwind regions, which also experience high PM mass loadings . These findings suggest that improving Delhi's air quality will require a concerted effort at both at the local and the regional level. Future work could usefully apportion the composition of PM1 at receptor sites upwind of Delhi.

BC was found to be well correlated (R2=0.65) with HOA (for periods when HOA was a separate factor) , suggesting that traffic, diesel generators, and other liquid fossil fuel combustion contribute substantially to the BC inventory for Delhi. Furthermore, unlike chloride, the highest BC concentrations were uncorrelated with any particular wind direction (Fig. ) and also showed less seasonal variation than other PM1 species (Fig. ), potentially indicating a nearby year-round source that was less affected by atmospheric mixing. We suspect that trucks (and other diesel vehicles) were a major source of the high BC concentrations that we observed, similar to what has been observed in other urban environments in India . While BC absolute concentrations did not vary as much as other PM1 species, the fractional contribution to BC was as high as 20 % during periods when the C-PM1 was lower (Fig. ). These findings indicate the large local nature of BC emissions and the potential to reduce BC concentrations by targeting high emitters such as heavy-duty trucks and diesel generation systems . Previous studies have shown that a small fraction (10 %–20 %) of high-emitting heavy-duty trucks contribute to almost half of the total BC emissions from heavy-duty trucks .