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Isoprene and monoterpene emissions to the atmosphere are generally dominated by biogenic sources. The oxidation of these compounds can lead to the production of secondary organic aerosol; however the impact of this chemistry in polluted urban settings has been poorly studied. Isoprene and monoterpenes can form secondary organic aerosol (SOA) heterogeneously via anthropogenic–biogenic interactions, resulting in the formation of organosulfate (OS) and nitrooxy-organosulfate (NOS) species. Delhi, India, is one of the most polluted cities in the world, but little is known about the emissions of biogenic volatile organic compounds (VOCs) or the sources of SOA. As part of the DELHI-FLUX project, gas-phase mixing ratios of isoprene and speciated monoterpenes were measured during pre- and post-monsoon measurement campaigns in central Delhi. Nocturnal mixing ratios of the VOCs were substantially higher during the post-monsoon (isoprene: (0.65±0.43) ppbv; limonene: (0.59±0.11) ppbv; α-pinene: (0.13±0.12) ppbv) than the pre-monsoon (isoprene: (0.13±0.18) ppbv; limonene: 0.011±0.025 (ppbv); α-pinene: 0.033±0.009) period. At night, isoprene and monoterpene concentrations correlated strongly with CO during the post-monsoon period. Filter samples of particulate matter less than 2.5 µm in diameter (PM2.5) were collected and the OS and NOS content analysed using ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS2). Inorganic sulfate was shown to facilitate the formation of isoprene OS species across both campaigns. Sulfate contained within OS and NOS species was shown to contribute significantly to the sulfate signal measured via AMS. Strong nocturnal enhancements of NOS species were observed across both campaigns. The total concentration of OS and NOS species contributed an average of (2.0±0.9) % and (1.8±1.4) % to the total oxidized organic aerosol and up to a maximum of 4.2 % and 6.6 % across the pre- and post-monsoon periods, respectively. Overall, this study provides the first molecular-level measurements of SOA derived from isoprene and monoterpene in Delhi and demonstrates that both biogenic and anthropogenic sources of these compounds can be important in urban areas.

The Indian megacity of Delhi suffers from some of the poorest air quality in the world. While ambient NO2 and particulate matter (PM) concentrations have received considerable attention in the city, high ground-level ozone (O3) concentrations are an often overlooked component of pollution. O3 can lead to significant ecosystem damage and agricultural crop losses, and adversely affect human health. During October 2018, concentrations of speciated non-methane hydrocarbon volatile organic compounds (C2–C13), oxygenated volatile organic compounds (o-VOCs), NO, NO2, HONO, CO, SO2, O3, and photolysis rates, were continuously measured at an urban site in Old Delhi. These observations were used to constrain a detailed chemical box model utilising the Master Chemical Mechanism v3.3.1. VOCs and NOx (NO + NO2) were varied in the model to test their impact on local O3 production rates, P(O3), which revealed a VOC-limited chemical regime. When only NOx concentrations were reduced, a significant increase in P(O3) was observed; thus, VOC co-reduction approaches must also be considered in pollution abatement strategies. Of the VOCs examined in this work, mean morning P(O3) rates were most sensitive to monoaromatic compounds, followed by monoterpenes and alkenes, where halving their concentrations in the model led to a 15.6 %, 13.1 %, and 12.9 % reduction in P(O3), respectively. P(O3) was not sensitive to direct changes in aerosol surface area but was very sensitive to changes in photolysis rates, which may be influenced by future changes in PM concentrations. VOC and NOx concentrations were divided into emission source sectors, as described by the Emissions Database for Global Atmospheric Research (EDGAR) v5.0 Global Air Pollutant Emissions and EDGAR v4.3.2_VOC_spec inventories, allowing for the impact of individual emission sources on P(O3) to be investigated. Reducing road transport emissions only, a common strategy in air pollution abatement strategies worldwide, was found to increase P(O3), even when the source was removed in its entirety. Effective reduction in P(O3) was achieved by reducing road transport along with emissions from combustion for manufacturing and process emissions. Modelled P(O3) reduced by ∼ 20 ppb h−1 when these combined sources were halved. This study highlights the importance of reducing VOCs in parallel with NOx and PM in future pollution abatement strategies in Delhi.

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.

We present the first real-time composition of submicron particulate matter (PM1) in Old Delhi using high-resolution aerosol mass spectrometry (HR-AMS). Old Delhi is one of the most polluted locations in the world, and PM1 concentrations reached ∼ 750 µg m−3 during the most polluted period, the post-monsoon period, where PM1 increased by 188 % over the pre-monsoon period. Sulfate contributes the largest inorganic PM1 mass fraction during the pre-monsoon (24 %) and monsoon (24 %) periods, with nitrate contributing most during the post-monsoon period (8 %). The organics dominate the mass fraction (54 %–68 %) throughout the three periods, and, using positive matrix factorisation (PMF) to perform source apportionment analysis of organic mass, two burning-related factors were found to contribute the most (35 %) to the post-monsoon increase. The first PMF factor, semi-volatility biomass burning organic aerosol (SVBBOA), shows a high correlation with Earth observation fire counts in surrounding states, which links its origin to crop residue burning. The second is a solid fuel OA (SFOA) factor with links to local open burning due to its high composition of polyaromatic hydrocarbons (PAHs) and novel AMS-measured marker species for polychlorinated dibenzodioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs). Two traffic factors were resolved: one hydrocarbon-like OA (HOA) factor and another nitrogen-rich HOA (NHOA) factor. The N compounds within NHOA were mainly nitrile species which have not previously been identified within AMS measurements. Their PAH composition suggests that NHOA is linked to diesel and HOA to compressed natural gas and petrol. These factors combined make the largest relative contribution to primary PM1 mass during the pre-monsoon and monsoon periods while contributing the second highest in the post-monsoon period. A cooking OA (COA) factor shows strong links to the secondary factor, semi-volatility oxygenated OA (SVOOA). Correlations with co-located volatile organic compound (VOC) measurements and AMS-measured organic nitrogen oxides (OrgNO) suggest SVOOA is formed from aged COA. It is also found that a significant increase in chloride concentrations (522 %) from pre-monsoon to post-monsoon correlates well with SVBBOA and SFOA, suggesting that crop residue burning and open waste burning are responsible. A reduction in traffic emissions would effectively reduce concentrations across most of the year. In order to reduce the post-monsoon peak, sources such as funeral pyres, solid waste burning and crop residue burning should be considered when developing new air quality policy.

Megacities and other major population centers represent large, concentrated sources of anthropogenic pollutants to the atmosphere, with consequences for both local air quality and for regional and global atmospheric chemistry. The tradeoffs between the regional buildup of pollutants near their sources versus long-range export depend on meteorological characteristics which vary as a function of geographical location and season. Both horizontal and vertical transport contribute to pollutant export, and the overall degree of export is strongly governed by the lifetimes of pollutants. We provide a first quantification of these tradeoffs and the main factors influencing them in terms of "regional pollution potentials", metrics based on simulations of representative tracers using the 3-D global model MATCH (Model of Atmospheric Transport and Chemistry). The tracers have three different lifetimes (1, 10, and 100 days) and are emitted from 36 continental large point sources. Several key features of the export characteristics emerge. For instance, long-range near-surface pollutant export is generally strongest in the middle and high latitudes, especially for source locations in Eurasia, for which 17–34% of a tracer with a 10-day lifetime is exported beyond 1000 km and still remains below 1 km altitude. On the other hand, pollutant export to the upper troposphere is greatest in the tropics, due to transport by deep convection, and for six source locations, more than 50% of the total mass of the 10-day lifetime tracer is found above 5 km altitude. Furthermore, not only are there order of magnitude interregional differences, such as between low and high latitudes, but also often substantial intraregional differences, which we discuss in light of the regional meteorological characteristics. We also contrast the roles of horizontal dilution and vertical mixing in reducing the pollution buildup in the regions including and surrounding the sources. For some regions such as Eurasia, dilution due to long-range horizontal transport governs the local and regional pollution buildup; however, on a global basis, differences in vertical mixing are dominant in determining the pollution buildup both around and further downwind of the source locations.