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Delhi is one of the world's most polluted cities, with very high concentrations of airborne particulate matter. However, little is known about the factors controlling the characteristics of wide-range particle number size distributions. Here, new measurements are reported from three field campaigns conducted in winter and pre-monsoon and post-monsoon seasons at the Indian Institute of Technology campus in the south of the city. Particle number size distributions were measured simultaneously, using a scanning mobility particle sizer and a GRIMM optical particle monitor, covering 15 nm to >10 ?m diameter. The merged, wide-range size distributions were categorized into the following five size ranges: nucleation (15-20 nm), Aitken (20-100 nm), accumulation (100 nm-1 ?m), large fine (1-2.5 ?m), and coarse (2.5-10 ?m) particles. The ultrafine fraction (15-100 nm) accounts for about 52 % of all particles by number (PN10 is the total particle number from 15 nm to 10 ?m) but just 1 % by PM10 volume (PV10 is the total particle volume from 15 nm to 10 ?m). The measured size distributions are markedly coarser than most from other parts of the world but are consistent with earlier cascade impactor data from Delhi. Our results suggest substantial aerosol processing by coagulation, condensation, and water uptake in the heavily polluted atmosphere, which takes place mostly at nighttime and in the morning hours. Total number concentrations are highest in winter, but the mode of the distribution is largest in the post-monsoon (autumn) season. The accumulation mode particles dominate the particle volume in autumn and winter, while the coarse mode dominates in summer. Polar plots show a huge variation between both size fractions in the same season and between seasons for the same size fraction. The diurnal pattern of particle numbers is strongly reflective of a road traffic influence upon concentrations, especially in autumn and winter, although other sources, such as cooking and domestic heating, may influence the evening peak. There is a clear influence of diesel traffic at nighttime, when it is permitted to enter the city, and also indications in the size distribution data of a mode < 15 nm, which is probably attributable to CNG/LPG vehicles. New particle formation appears to be infrequent and is, in this dataset, limited to 1 d in the summer campaign. Our results reveal that the very high emissions of airborne particles in Delhi, particularly from traffic, determine the variation in particle number size distributions.

Air pollution in urban environments has been shown to have a negative impact on air quality and human health, particularly in megacities. Over recent decades, Delhi, India, has suffered high atmospheric pollution, with significant particulate matter (PM) concentrations as a result of anthropogenic activities. Organic aerosols (OAs) are composed of thousands of different chemical species and are one of the main constituents of submicron particles. However, quantitative knowledge of OA composition, their sources and their processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, where we would expect the apportionment and concentrations to vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need for multisite measurements. This study presents the first multisite analysis carried out in India over different seasons, with a focus on identifying OA sources. The measurements were taken during 2018 at two sites in Delhi, India. One site was located at the India Meteorological Department, New Delhi (ND). The other site was located at the Indira Gandhi Delhi Technical University for Women, Old Delhi (OD). Non-refractory submicron aerosol (NR-PM1) concentrations (ammonium, nitrate, sulfate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of volatile organic compounds, black carbon, NOx and CO were performed. Positive matrix factorisation (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OAs (HOAs) related to traffic emissions, biomass burning OAs (BBOAs), cooking OAs (COAs) and secondary OAs (SOAs). A composition-based estimate of PM1 is defined by combining black carbon (BC) and NR-PM1 (C-PM1= BC + NR-PM1). No significant difference was observed in C-PM1 concentrations between sites, OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m3), from post-monsoon measurements. A wider variability was observed between seasons, where pre-monsoon and monsoon showed C-PM1 concentrations lower than 60 µg m−3. A seasonal variation in C-PM1 composition was observed; SO42- showed a high contribution over pre-monsoon and monsoon seasons, while NO3- and Cl− had a higher contribution in winter and post-monsoon. The main primary aerosol source was from traffic, which is consistent with the PMF analysis and Aethalometer model analysis. Thus, in order to reduce PM1 concentrations in Delhi through local emission controls, traffic emission control offers the greatest opportunity. PMF–aerosol mass spectrometer (AMS) mass spectra will help to improve future aerosol source apportionment studies. The information generated in this study increases our understanding of PM1 composition and OA sources in Delhi, India. Furthermore, the scientific findings provide significant information to strengthen legislation that aims to improve air quality in India.

Measurements of OH, HO2, complex RO2 (alkene- and aromatic-related RO2) and total RO2 radicals taken during the integrated Study of AIR Pollution PROcesses in Beijing (AIRPRO) campaign in central Beijing in the summer of 2017, alongside observations of OH reactivity, are presented. The concentrations of radicals were elevated, with OH reaching up to 2.8×107moleculecm−3, HO2 peaking at 1×109moleculecm−3 and the total RO2 concentration reaching 5.5×109moleculecm−3. OH reactivity (k(OH)) peaked at 89 s−1 during the night, with a minimum during the afternoon of ≈22s−1 on average. An experimental budget analysis, in which the rates of production and destruction of the radicals are compared, highlighted that although the sources and sinks of OH were balanced under high NO concentrations, the OH sinks exceeded the known sources (by 15 ppbv h−1) under the very low NO conditions (

Nitrogen oxides (NOx=NO+NO2) are critical intermediates in atmospheric chemistry and air pollution. NOx levels control the cycling and hence abundance of the primary atmospheric oxidants OH and NO3 and regulate the ozone production which results from the degradation of volatile organic compounds (VOCs) in the presence of sunlight. They are also atmospheric pollutants, and NO2 is commonly included in air quality objectives and regulations. NOx levels also affect the production of the nitrate component of secondary aerosol particles and other pollutants, such as the lachrymator peroxyacetyl nitrate (PAN). The accurate measurement of NO and NO2 is therefore crucial for air quality monitoring and understanding atmospheric composition. The most commonly used approach for the measurement of NO is the chemiluminescent detection of electronically excited NO2 (NO2∗) formed from the NO + O3 reaction within the NOx analyser. Alkenes, ubiquitous in the atmosphere from biogenic and anthropogenic sources, also react with ozone to produce chemiluminescence and thus may contribute to the measured NOx signal. Their ozonolysis reaction may also be sufficiently rapid that their abundance in conventional instrument background cycles, which also utilises the reaction with ozone, differs from that in the measurement cycle such that the background subtraction is incomplete, and an interference effect results. This interference has been noted previously, and indeed, the effect has been used to measure both alkenes and ozone in the atmosphere. Here we report the results of a systematic investigation of the response of a selection of commercial NOx monitors to a series of alkenes. These NOx monitors range from systems used for routine air quality monitoring to atmospheric research instrumentation. The species-investigated range was from short-chain alkenes, such as ethene, to the biogenic monoterpenes. Experiments were performed in the European PHOtoREactor (EUPHORE) to ensure common calibration and samples for the monitors and to unequivocally confirm the alkene levels present (via Fourier transform infrared spectroscopy – FTIR). The instrument interference responses ranged from negligible levels up to 11 %, depending upon the alkene present and conditions used (e.g. the presence of co-reactants and differing humidity). Such interferences may be of substantial importance for the interpretation of ambient NOx data, particularly for high VOC, low NOx environments such as forests or indoor environments where alkene abundance from personal care and cleaning products may be significant.

Measurements of OH, HO2, RO2-complex (alkene and aromatic-related RO2) and total RO2 radicals taken during the AIRPRO campaign in central Beijing in the summer of 2017, alongside observations of OH reactivity are presented. The concentrations of radicals were elevated with OH reaching up to 2.8 × 107 molecule cm−3, HO2 peaked at 1 × 109 molecule cm−3 and the total RO2 concentration reached 5.5 × 109 molecule cm−3. OH reactivity (k(OH)) peaked at 89 s−1 during the night, with a minimum during the afternoons of ~ 22 s−1 on average. An experimental budget analysis, in which the rates of production and destruction of the radicals are compared, highlighted that although the sources and sinks of OH were balanced under high NO concentrations, the OH sinks exceeded the known sources (by 15 ppbv hr−1) under the very low NO conditions (2 production rate exceeded the rate of destruction by ~ 50 ppbv hr−1, whilst the rate of destruction of total-RO2 exceeded the production by the same rate indicating that the net propagation rate of RO2 to HO2 may be substantially slower than assumed. If just 10 % of the RO2 radicals propagate to HO2 upon reaction with NO, the HO2 and RO2 budgets could be closed at high NO, but at low NO this lower RO2 to HO2 propagation rate revealed a missing RO2 sink that was similar in magnitude to the missing OH source. A detailed box model that incorporated the latest MCM chemical mechanism (MCM3.3.1) reproduced the observed OH concentrations well, but over-predicted the observed HO2 under low concentrations of NO (2 (both the complex-RO2 fraction and other RO2 types which we classify as simple-RO2) most significantly at the highest NO concentrations. The model also under-predicted the observed k(OH) consistently by ~ 10 s−1 across all NOx levels highlighting that the good agreement for OH was fortuitous due to a cancellation of missing OH source and sink terms in its budget. Including heterogeneous loss of HO2 to aerosol surfaces did reduce the modelled HO2 concentrations in-line with the observations, but only at NO mixing ratios 2 concentration on several mornings when the Cl atom concentration was calculated to exceed 1 × 104 atoms cm−3 and could reconcile the modelled and measured RO2 concentrations at these times. However, on other mornings, when the Cl atom concentration was lower, large under-predictions in total RO2 remained. Furthermore, the inclusion of Cl atom chemistry did not enhance the modelled RO2 beyond the first few hours after sunrise and so was unable to resolve the modelled under-prediction in RO2 observed at other times of the day. Model scenarios, in which missing VOC reactivity was included as an additional reaction that converted OH to RO2, highlighted that the modelled OH, HO2 and RO2 concentrations were sensitive to the choice of RO2 product. The level of modelled to measured agreement for HO2 and RO2 (both complex and simple) could be improved if the missing OH reactivity formed a larger RO2 species that was able to undergo reaction with NO, followed by isomerisation reactions reforming other RO2 species, before eventually generating HO2. In this work an α-pinene-derived RO2 species was used as an example. In this simulation, consistent with the experimental budget analysis, the model underestimated the observed OH indicating a missing OH source. The model uncertainty, with regards to the types of RO2 species present and the radicals they form upon reaction with NO (HO2 directly or another RO2 species), leads to over an order of magnitude less O3 production calculated from the predicted peroxy radicals than calculated from the observed peroxy radicals at the highest NO concentrations. This demonstrates the rate at which the larger RO2 species propagate to HO2 or to another RO2 or indeed to OH needs to be understood to accurately simulate the rate of ozone production in environments such as Beijing where large multifunctional VOCs are likely present.

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants in air, soil, and water and are known to have harmful effects on human health and the environment. The diurnal and nocturnal variations of 17 PAHs in ambient particle-bound PAHs were measured in urban Beijing (China) and Delhi (India) during the summer season using gas-chromatography–quadrupole time-of-flight mass spectrometry (GC-Q-TOF-MS). The mean concentration of particles less than 2.5 µm (PM2.5) observed in Delhi was 3.6 times higher than in Beijing during the measurement period in both the daytime and night-time. In Beijing, the mean concentration of the sum of the 17 PAHs (∑17 PAHs) was 8.2 ± 5.1 ng m−3 in daytime, with the highest contribution from indeno[1,2,3-cd]pyrene (12 %), while at night-time the total PAHs was 7.2 ± 2.0 ng m−3, with the largest contribution from benzo[b]fluoranthene (14 %). In Delhi, the mean ∑17 PAHs was 13.6 ± 5.9 ng m−3 in daytime and 22.7 ± 9.4 ng m−3 at night-time, with the largest contribution from indeno[1,2,3-cd]pyrene in both the day (17 %) and night (20 %). Elevated mean concentrations of total PAHs in Delhi observed at night were attributed to emissions from vehicles and biomass burning and to meteorological conditions leading to their accumulation from a stable and low atmospheric boundary layer. Local emission sources were typically identified as the major contributors to total measured PAHs in both cities. Major emission sources were characterized based on the contribution from each class of PAHs, with the four-, five- and six-ring PAHs accounting ∼ 95 % of the total PM2.5-bound PAHs mass in both locations. The high contribution of five-ring PAHs to total PAH concentration in summer Beijing and Delhi suggests a high contribution from petroleum combustion. In Delhi, a high contribution from six-ring PAHs was observed at night, suggesting a potential emission source from the combustion of fuel and oil in power generators, widely used in Delhi. The lifetime excess lung cancer risk (LECR) was calculated for Beijing and Delhi, with the highest estimated risk attributed to Delhi (LECR = 155 per million people), which is 2.2 times higher than the Beijing risk assessment value (LECR = 70 per million people). Finally, we have assessed the emission control policies in each city and identified those major sectors that could be subject to mitigation measures.