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. 2023 May 3;10(6):520–527. doi: 10.1021/acs.estlett.3c00171

Extreme Concentrations of Nitric Oxide Control Daytime Oxidation and Quench Nocturnal Oxidation Chemistry in Delhi during Highly Polluted Episodes

Beth S Nelson †,*, Daniel J Bryant †,*, Mohammed S Alam ‡, Roberto Sommariva §, William J Bloss §, Mike J Newland †, Will S Drysdale †,∥, Adam R Vaughan †, W Joe F Acton ⊥, C Nicholas Hewitt ⊥, Leigh R Crilley §, Stefan J Swift †, Pete M Edwards †, Alastair C Lewis †,∥, Ben Langford #, Eiko Nemitz #, Shivani @, Ranu Gadi @, Bhola R Gurjar ∇, Dwayne E Heard ■, Lisa K Whalley ■,□, Ülkü A Şahin ●, David C S Beddows §,○, James R Hopkins †,∥, James D Lee †,∥, Andrew R Rickard †,∥, Jacqueline F Hamilton †,∥
PMCID: PMC10275353  PMID: 37333938

Abstract

graphic file with name ez3c00171_0004.jpg

Delhi, India, suffers from periods of very poor air quality, but little is known about the chemical production of secondary pollutants in this highly polluted environment. During the postmonsoon period in 2018, extremely high nighttime concentrations of NOx (NO and NO2) and volatile organic compounds (VOCs) were observed, with median NOx mixing ratios of ∼200 ppbV (maximum of ∼700 ppbV). A detailed chemical box model constrained to a comprehensive suite of speciated VOC and NOx measurements revealed very low nighttime concentrations of oxidants, NO3, O3, and OH, driven by high nighttime NO concentrations. This results in an atypical NO3 diel profile, not previously reported in other highly polluted urban environments, significantly perturbing nighttime radical oxidation chemistry. Low concentrations of oxidants and high nocturnal primary emissions coupled with a shallow boundary layer led to enhanced early morning photo-oxidation chemistry. This results in a temporal shift in peak O3 concentrations when compared to the premonsoon period (12:00 and 15:00 local time, respectively). This shift will likely have important implications on local air quality, and effective urban air quality management should consider the impacts of nighttime emission sources during the postmonsoon period.

Keywords: air quality, atmospheric oxidation chemistry, nocturnal atmospheric chemistry, ozone, VOC

Introduction

Delhi, India, is one of the most polluted megacities in the world and has previously been shown to have levels of numerous air pollutants such as particulate matter (PM), NOx (NO and NO2), O3, SO2, and CO significantly above World Health Organization (WHO) guidelines.1−4 High concentrations have led to an increase in morbidity and premature mortality, leading to economic losses.5−7 Exposure to air pollution has been shown to reduce life expectancy on average by six years in Delhi.8 Previous studies have highlighted significant amounts of premature mortality within Delhi, with estimates of up to 12 000 deaths per year associated with poor air quality.3

Measured concentrations of volatile organic compounds (VOCs) and NOx in Delhi are among the highest recorded in a polluted urban environment, on a scale similar to those observed in Los Angeles in the 1970s.9 The concentrations of pollutants are especially high during the winter periods, largely due to emissions from the burning of crop residues, domestic heating, cooking, along with local meteorology.10−17 High NOx concentrations have been observed throughout the year,2 with the highest observed during winter, and nighttime concentrations on average of >100 ppbV.18,19 Within Delhi, the transport sector is the dominant source of NOx emissions, accounting for 66–74%.20 Of these transport emissions, heavy goods vehicles (HGVs) make the largest contribution (>50%).21 To combat transport pollution, the Government of National Capital Territory of Delhi introduced prohibitive regulations impacting the transport of goods into and out of the city. Prohibitions on the movement of goods vehicles vary across Delhi but generally restrict HGVs during peak times for passenger vehicles [07:00–11:00 and 17:00–23:00 Indian Standard Time (IST)].22 These daytime restrictions lead to increased HGV movement at night, and thus increased nighttime emissions. Delhi also suffers from unfavorable meteorological conditions, with shallow boundary layer heights and low wind speeds leading to stagnant conditions, especially during the winter. This, in turn, allows for the accumulation of pollutants at night, exacerbated by the high emission rates.23

The nature of radical chemistry at night, when pollution is high, may have significant consequences on the subsequent daytime oxidation chemistry and secondary pollution formation. A recent study by Bryant et al. presented evidence of the removal of nighttime NO3 radicals by NO in Delhi via a decrease in the concentration of isoprene-derived nitrooxy-organosulfate (NOSi) species produced via NO3 oxidation chemistry.24 In addition, a study by Nelson et al., corroborated by Chen et al., found central Delhi to be VOC-limited with respect to O3 production and significant titration of O3, owing to very high NO concentrations at night during the winter periods.18,19 The ratio of NOx to non-methane VOCs has also been shown to impact rates of secondary organic aerosol formation.25 These studies have highlighted the importance of reducing levels of VOCs alongside those of NOx, to mitigate both O3 and PM formation. Our findings build on the work by Nelson et al. and Bryant et al. by focusing on the role NO plays in regulating OH and NO3 radical concentrations within Delhi.19,24 The unique chemistry investigated in this study deviates from our typical understanding of nocturnal radical oxidation chemistry and has important policy implications, highlighting the need to reduce nighttime NOx emissions alongside VOC emissions, to not further exacerbate PM and O3 concentrations through secondary formation.

Methodology

Description of the Site

The APHH-India Delhi Flux campaigns took place during the premonsoon (May 28–June 5, 2018) and postmonsoon (October 4–November 5, 2018) periods. The primary site was located on the campus of the Indira Gandhi Delhi Technical University for Women in Delhi. The campus is situated close to major roads and highways, including National Highway 44 (0.3 km east). The campus has some green areas and is mostly pedestrianized with low-level traffic activity from delivery cars, taxis, and auto rickshaws. Observations were made from the roof of a one-story building (∼5 m) and included levels of VOCs, o-VOCs, NOx, CO, SO2, O3, and HONO, photolysis rates, PM, and meteorological measurements. Further details on the site can be found in ref (19).

VOC Measurements

VOCs were measured via a dual-channel gas chromatography flame ionization detector (DC-GC FID, C2–C8), a two-dimensional GC flame ionization detector (GC × GC-FID, C6–C13), and a proton transfer reaction time-of-flight mass spectrometer with a quadrupole ion guide (PTR-QiTOF, Ionicon Analytik, Innsbruck, Austria). The two GC instruments shared an inlet, located 5 m above ground level. The sample line from the inlet to the laboratory was made from 1/2 in. (outside diameter) perfluoroalkoxy (PFA) and was heated. VOCs were calibrated using standard cylinders containing a variety of VOCs. Further details can be found in refs (19) and (26).

Measurements of NOx, O3, and HONO

Measurements of nitrogen oxides (NO and NO2) were made using a dual-channel chemiluminescence instrument (Air Quality Designs Inc.) that was calibrated every 2–3 days throughout the campaign using standard gas cylinders from the National Physical Laboratories in the U.K. O3 was measured using an O3 analyzer (49i, Thermo Scientific). The instrument setup and calibration methodology are as described by Squires et al.27 HONO was measured using a long-path absorption photometer (LOPAP) with baseline measurements taken at regular intervals (8 h). Further details along with measurement descriptions for the aerosol surface area, photolysis rates, and meteorological data can be found in refs (19) and (22).

Description of the Model

Two campaign-tailored zero-dimensional chemical box models (premonsoon and postmonsoon) incorporating a subset of the Master Chemical Mechanism (MCM version 3.3.1)28,29 were used to investigate radical production chemistry, utilizing the AtChem2 modeling toolkit.30 The pre- and postmonsoon models were constrained to the measured concentrations of ambient VOCs (57 and 86, respectively), NOx, CO, O3, SO2, aerosol surface area (postmonsoon only), 34 photolysis rates derived from the measured photolysis frequencies of j(O1D), j(NO2), and j(HONO), temperature, pressure, and relative humidity. The premonsoon model was constrained to a reduced range of VOCs due to the concentration of some species being below the instrumental limits of detection. Measurement data were averaged or linearly interpolated to 15 min time resolution prior to inclusion in the models. The first 24 h of measurements were repeated for 3 days prior to the full campaign time series. These modeled data were then discarded before analysis to ensure radical spin-up was achieved. Measured species not described in the MCM were incorporated using a surrogate mechanism (Table S1), chosen on the basis of the structural similarity to the species of interest (more details in ref (19)). For these species, reaction rates with OH, HO2, and NO3 were set to values found in the IUPAC evaluated chemical kinetics database.31,32 For both campaigns, a fixed deposition rate of 1.2 × 10–5 s–1 was applied to all model-generated species, resulting in a lifetime with respect to dry deposition of ∼24 h. Where vertical velocity data were available (postmonsoon only), the concentration of HONO was adjusted to account for variations within the vertical profile due to its very short lifetime relative to that of VOCs, and the atmospheric mixing time.33 This adjustment is particularly important for the postmonsoon period, given the very high levels of HONO measured at ground level. The model also accounted for aerosol uptake of HO2. A more detailed description of the adjustments to HONO observations, calculation of photolysis rates, and HO2 uptake is presented in ref (19).

Results

The median diel profiles of NO mixing ratios observed during both campaigns are shown in Figure 1. The observed NO levels are at a minimum during the day, likely driven by differences in emissions but also corresponding to the period during which the planetary boundary layer height (PBLH) is greatest (Figure S1). The reaction of NO with O3 converts NO to NO2, resulting in NO mixing ratios in the afternoon of ∼1–2 ppbV. The NO2:NOx ratio in the afternoon is ∼0.92–0.96, indicating a high NO2 conversion rate under strong photochemically active conditions. In the evening, a shallow nocturnal boundary layer is formed (Figure S1), leading to a rapid increase in the mixing ratio of NO. The nighttime PBLH minimum is much lower during the postmonsoon period (median PBLH is 33 m, vs 210 m during the premonsoon), leading to a median nocturnal mixing ratio of 200 ppbV for NO, ∼400 times higher than during the premonsoon period (∼0.50 ppbV). On some nights, extremely high NO mixing ratios were observed, up to a maximum of ∼700 ppbV.19 Simultaneously, O3 mixing ratios decreased due to reaction with NO, with median nocturnal O3 mixing ratios in the postmonsoon period of <2 ppbV, compared to ∼30 ppbV during the premonsoon period (Figure 1). However, measured nighttime O3 concentrations should be treated with caution as chemical interference from, for example, aromatic compounds can cause small positive artifacts.34 The extremely high levels of NO at night during the postmonsoon period are likely to entirely remove all nighttime O3 through chemical titration, evidenced by model simulations of O3 (Figure S2). The lifetime of NO in a typical urban atmosphere is relatively short, such that NO2:NOx ratios can increase significantly within tens of seconds after emission.35 Overnight, the postmonsoon NO2:NOx ratio was ∼0.15 on average, indicative of direct combustion emissions of NO.36 The observed ratio is comparable to previous observations in road tunnels, indicating a lack of NO oxidation at night in Delhi once all of the O3 produced during the day has been consumed.37

Figure 1.

Figure 1

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Median diel profiles of (a) NO, (b) NO2, (c) NO2:NOx ratio, and (d) O3 measured during the premonsoon (yellow) and postmonsoon (purple) campaigns. Note that pre/postmonsoon NO values are plotted on separate y-axes owing to the large differences in observed mixing ratios. The shaded region represents the interquartile range.

NOx plays a key role in the production of all three major oxidants (OH, NO3, and O3) in polluted atmospheres and therefore impacts radical production and loss.32,38 VOC oxidation is predominantly driven by OH and O3 during the day and NO3 and O3 at night. We used an observationally constrained zero-dimensional chemical box model to predict short-lived radical oxidant concentrations during the pre- and postmonsoon periods. During the premonsoon period, the OH radical followed the expected diel profile, peaking at solar noon with a concentration of ∼9 × 106 molecules cm–3 (Figure 2a). During the postmonsoon period, the OH radical concentrations peak in the morning, reaching a maximum of 6 × 106 molecules cm–3 at 9:00 IST which begins to decrease only after 13:00 IST (Figure 2b). NO3 showed more significant seasonal differences. During the premonsoon period, the modeled NO3 concentrations peaked just after sunset (17:00–19:00 IST, 8 × 107 molecules cm–3, 3.2 pptV) and remained high overnight before rapidly decreasing after sunrise due to photolysis (Figure 2c). NO3 concentrations then increased throughout the day due to NO concentrations being suppressed through reactions with O3, reducing this important NO3 sink. During the postmonsoon period, modeled NO3 concentrations peaked between 12:00 and 14:00 IST, at a concentration comparable to that observed at the same time during the premonsoon period (∼3 × 107 molecules cm–3, 1.2 pptV) (Figure 2d). A comparison between NO3 photolysis rates and modeled NO3 suggests that daytime peaks in NO3 are not significantly influenced by haze events (see Figure S3). The differences seen in the NO3 diel profiles are striking, with the extreme levels of NO at night rapidly scavenging any NO3 that is formed during the postmonsoon period. It should be noted that the model does not account for N2O5 uptake, though we expect the impact of this to be minimal as our modeled N2O5 midday peak is small (<10 pptV), relative to the daytime concentration of NO (>1.8 ppbV). The impact of N2O5 uptake on modeled NO3 concentrations is investigated in more detail in ref (39).

Figure 2.

Figure 2

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Mean diel variations of modeled OH and NO3 concentrations across the (a and c) premonsoon and (b and d) postmonsoon periods. The shaded band represents one standard deviation from the mean. Note that the y-axis scales on all plots are distinct.

To further investigate the drivers of Delhi’s radical chemistry, the rates of radical production and loss were determined for each campaign. The average modeled diel rates of production (initiation, positive values) and loss (termination, negative values) of OH, HO2, and RO2 (ROx) radicals are shown as a stacked plot in Figure 3 for both campaigns. The pre- and postmonsoon percentage contribution to radical initiation/termination (by time of day) for each source is shown in Figures S4 and S5. During the premonsoon period, the radical production rate is symmetrical around noon (maximum of ∼10 ppbV h–1), with roughly similar contributions from ozonolysis, photolysis of carbonyls, photolysis of O3 (j(O1D)), and HONO photolysis. VOC + NO3 reactions start to make a significant contribution to radical initiation in the late afternoon (Figure 3). In contrast, there is a large burst of ROx radical formation after sunrise during the postmonsoon period (maximum of ∼24 ppbV h–1), more than double the radical production observed during the premonsoon period (Figures S6). This is largely driven by the photolysis of high levels of HONO (∼12 ppbV) remaining from the previous night (Figure S7). The morning radical production peak is sustained into the afternoon by ozonolysis and carbonyl photolysis, whereas the photolysis of O3 plays an only minor role (Figures S4 and S5). The postmonsoon morning burst in radical production results in a temporal shift in the peak O3 concentration, from 15:00 IST during the premonsoon period to 13:00 IST during the postmonsoon period, although overall the maximum O3 mixing ratios are similar between the two campaigns. The temporal O3 peak shift observed in the measurements was also seen by the model in a simulation in which O3 was unconstrained, with modeled O3 also peaking around midday.

Figure 3.

Figure 3

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Stacked area plots showing the average modeled diel production (initiation, positive) and loss (termination, negative) rates for OH + HO2 + RO2 (ROx) radicals during the (a) premonsoon and (b) postmonsoon campaigns, under zero oxidant nighttime conditions during the postmonsoon period. PAN (net) refers to the PAN ⇌ CH3CO3 + NO2 equilibrium, where CH3CO3 is being formed in the positive direction (PAN loss) and being lost in the negative direction (PAN formation). Note the magnitudinal difference between the y-axes scales on the two plots.

A similar pattern is seen for radical loss processes, with the premonsoon period showing a symmetrical diel profile, with OH + NO2, RO2 + HO2, ROx + NO, and HO2 + HO2 all acting as important termination reactions. The postmonsoon radical losses are driven by high NO levels present after sunrise with the ROx + NO reaction dominating the termination reactions initially. The ROx + NO term is a combination of OH + NO (=HONO) and RO2 + NO (=RONO2) terminating loss routes and is dominated by OH + NO loss during the pre- and postmonsoon periods (∼60% and ∼86%, respectively). During the premonsoon period, RO2 products derived from isoprene and monoterpenes make the next largest contributions (∼20%). During the postmonsoon period, dodecane-derived RO2 makes the next largest contribution (∼2%). All other pathways in both campaigns make minor contributions to the overall ROx + NO termination term, with OH + NO2 and net peroxyacetyl nitrate (PAN) formation becoming increasingly important by 9:00 IST. This balance between radical production and loss, driven by the high levels of NOx, likely stops O3 concentrations during the postmonsoon period reaching the increased levels observed in Los Angeles in the 1970s.

Discussion

We conclude that the very high NO levels observed in Delhi at night during the postmonsoon period quench nocturnal oxidation chemistry, evidenced by very low levels of measured O3 and modeled NO3 present and extremely low model radical initiation rates. This also suggests a concurrent lack of N2O5 formation at night. Therefore, even though very high levels of chloride (Cl–) in the particle phase have been reported in Delhi,40 limited nighttime ClNO2 formation, which is an important photochemical Cl radical reservoir, is likely to occur. The lack of nocturnal oxidation chemistry can also be confirmed using the VOC observations. Very high nighttime levels of monoterpenes were observed (mean of 2.5 ppbV), with eight nights having a peak over 5 ppbV (Figure S8).19 Species such as α-phellandrene, α-terpinene, and terpinolene are extremely reactive toward OH, O3, and NO3 (see Table S2) but did not accumulate overnight, reaching maximum mixing ratios of 120–350 pptV. During the premonsoon period, nighttime concentrations of these reactive monoterpenes were usually below the instrument detection limits and so were not included in the premonsoon model. The absence of nighttime oxidation chemistry is further corroborated by a study by Cash et al., which reported a reduction in oxidized aerosol levels in Delhi during the postmonsoon period at night, alongside increased levels of hydrocarbon-like organic aerosol (HOA).41 Together, these model and measurement observations provide strong evidence for a deviation from the typical nocturnal oxidation chemistry observed in other highly polluted urban atmospheres. More details about the observed VOC concentrations and diel profiles can be found in refs (19) and (42).

The observed postmonsoon overnight accumulation of a highly reactive mix of NOx and oxidized nitrogen species (NOy) and VOCs, in a very shallow boundary layer, has important consequences for the subsequent day’s photochemistry. These trapped emissions act as a reservoir of photochemical fuel leading to high radical formation rates, initially driven by nitrous acid photolysis in the morning, and efficient photochemical O3 formation, shifting the postmonsoon maximum O3 peak earlier (by 3 h compared to the premonsoon peak). The observed temporal shift in maximum O3 coinciding with solar noon supports the presence of highly active oxidation chemistry in the morning. As the sun rises and the nocturnal boundary layer collapses in the morning, some of the accumulated pollution will be ventilated away from the surface. However, we observed that the modeled radical initiation pathways during the morning were very efficient after these stagnation events.

Recent pollution abatement policies that restrict the movement of HGVs during the day may be exacerbating nighttime pollution leading to the modeled early morning burst in secondary pollutant formation initiated by photolysis at sunrise. We propose that pollution reduction policies in central Delhi should focus on diel emission reductions, as policies that move emissions from daytime to nighttime may not be effective at reducing O3 and may lead only to a temporal shift in its peak. Further work is needed to determine the impact of reducing nighttime emissions on changes to daytime exposure to secondary pollutants, and future policies should consider the emission profile and atmospheric chemistry across the entire 24 h period.

Acknowledgments

The authors acknowledge Tuhin Mandal at CSIR National Physical Laboratory for his support in facilitating the measurement sites used in this project and Gareth Stewart for VOC measurements. This work was supported by the Newton Bhabha fund administered by the UK Natural Environment Research Council through the DelhiFlux (NE/P016502/1) and ASAP projects of the Atmospheric Pollution and Human Health in an Indian Megacity (APHH-India) program. The authors gratefully acknowledge the financial support provided by the UK Natural Environment Research Council and the Earth System Science Organization, Ministry of Earth Sciences, Government of India, under the Indo-UK Joint Collaboration (DelhiFlux). B.S.N. and D.J.B. acknowledge the NERC SPHERES doctoral training program for studentships. This project was undertaken on the Viking Cluster, which is a high-performance computing facility provided by the University of York. The authors are grateful for computational support from the University of York High Performance Computing service, Viking, and the Research Computing team.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.estlett.3c00171.

  • List of measured VOCs used in the model (Table S1); diel profiles for boundary layer height, HONO, and total monoterpenes (Figures S1, S7, and S8, respectively); O3 postmonsoon modeled versus measured normalized diel profiles (Figure S2); photolysis rate variations (Figure S3); atmospheric lifetimes of selected species (Table S2); hourly modeled contributions to radical initiation and termination during the postmonsoon period (Figures S4 and S5); and full model radical flux analysis (Figure S6) (PDF)

Author Present Address

▲ W.J.F.A.: School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, U.K

Author Present Address

△ L.R.C.: WSP Australia, Brisbane 4006, Australia.

Author Present Address

▼ S.J.S.: Department of Chemistry of Ions in Gaseous Phase, J. Heyrovsky Institute of Physical Chemistry, 182 00 Prague, Czech Republic.

Author Contributions

B.S.N. and D.J.B. prepared the manuscript with contributions from all authors. M.S.A., W.S.D., A.R.V., W.J.F.A., L.R.C., S.J.S., P.M.E., B.L., L.K.W., Ü.A.Ş., D.C.S.B., C.N.H., and J.R.H. provided measurements and data processing of pollutants used in this study. M.J.N., A.R.R., J.F.H., D.E.H., R.S., M.S.A., and W.J.B. contributed to scientific discussion. S., R.G., B.R.G., and E.N. assisted with logistics. J.R.H., J.D.L., A.R.R., and J.F.H. provided overall guidance to the experimental setup and design.

The authors declare no competing financial interest.

Supplementary Material

ez3c00171_si_001.pdf (842.2KB, pdf)

References

  1. Rizwan S. A.; Nongkynrih B.; Gupta S. K. Air Pollution in Delhi: Its Magnitude and Effects on Health. Indian J. Community Med. 2013, 38 (1), 4. 10.4103/0970-0218.106617. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Sharma P.; Sharma P.; Jain S.; Kumar P. An Integrated Statistical Approach for Evaluating the Exceedence of Criteria Pollutants in the Ambient Air of Megacity Delhi. Atmos. Environ. 2013, 70, 7–17. 10.1016/j.atmosenv.2013.01.004. [DOI] [Google Scholar]
  3. Balakrishnan K.; Dey S.; Gupta T.; Dhaliwal R. S.; Brauer M.; Cohen A. J.; Stanaway J. D.; Beig G.; Joshi T. K.; Aggarwal A. N.; Sabde Y.; Sadhu H.; Frostad J.; Causey K.; Godwin W.; Shukla D. K.; Kumar G. A.; Varghese C. M.; Muraleedharan P.; Agrawal A.; Anjana R. M.; Bhansali A.; Bhardwaj D.; Burkart K.; Cercy K.; Chakma J. K.; Chowdhury S.; Christopher D. J.; Dutta E.; Furtado M.; Ghosh S.; Ghoshal A. G.; Glenn S. D.; Guleria R.; Gupta R.; Jeemon P.; Kant R.; Kant S.; Kaur T.; Koul P. A.; Krish V.; Krishna B.; Larson S. L.; Madhipatla K.; Mahesh P. A.; Mohan V.; Mukhopadhyay S.; Mutreja P.; Naik N.; Nair S.; Nguyen G.; Odell C. M.; Pandian J. D.; Prabhakaran D.; Prabhakaran P.; Roy A.; Salvi S.; Sambandam S.; Saraf D.; Sharma M.; Shrivastava A.; Singh V.; Tandon N.; Thomas N. J.; Torre A.; Xavier D.; Yadav G.; Singh S.; Shekhar C.; Vos T.; Dandona R.; Reddy K. S.; Lim S. S.; Murray C. J. L.; Venkatesh S.; Dandona L. The Impact of Air Pollution on Deaths, Disease Burden, and Life Expectancy across the States of India: The Global Burden of Disease Study 2017. Lancet Planet. Heal. 2019, 3 (1), e26–e39. 10.1016/S2542-5196(18)30261-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Hama S. M. L.; Kumar P.; Harrison R. M.; Bloss W. J.; Khare M.; Mishra S.; Namdeo A.; Sokhi R.; Goodman P.; Sharma C. Four-Year Assessment of Ambient Particulate Matter and Trace Gases in the Delhi-NCR Region of India. Sustain. Cities Soc. 2020, 54, 102003. 10.1016/j.scs.2019.102003. [DOI] [Google Scholar]
  5. Chakrabarti S.; Khan M. T.; Kishore A.; Roy D.; Scott S. P. Risk of Acute Respiratory Infection from Crop Burning in India: Estimating Disease Burden and Economic Welfare from Satellite and National Health Survey Data for 250 000 Persons. Int. J. Epidemiol. 2019, 48 (4), 1113–1124. 10.1093/ije/dyz022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chen Y.; Wild O.; Conibear L.; Ran L.; He J.; Wang L.; Wang Y. Local Characteristics of and Exposure to Fine Particulate Matter (PM2.5) in Four Indian Megacities. Atmos. Environ. X 2020, 5, 100052. 10.1016/j.aeaoa.2019.100052. [DOI] [Google Scholar]
  7. Joshi P.; Ghosh S.; Dey S.; Dixit K.; Choudhary R. K.; Salve H. R.; Balakrishnan K. Impact of Acute Exposure to Ambient PM2.5 on Non-Trauma All-Cause Mortality in the Megacity Delhi. Atmos. Environ. 2021, 259, 118548. 10.1016/j.atmosenv.2021.118548. [DOI] [Google Scholar]
  8. Ghude S. D.; Chate D. M.; Jena C.; Beig G.; Kumar R.; Barth M. C.; Pfister G. G.; Fadnavis S.; Pithani P. Premature Mortality in India Due to PM2.5 and Ozone Exposure. Geophys. Res. Lett. 2016, 43 (9), 4650–4658. 10.1002/2016GL068949. [DOI] [Google Scholar]
  9. Pollack I. B.; Ryerson T. B.; Trainer M.; Neuman J. A.; Roberts J. M.; Parrish D. D. Trends in Ozone, Its Precursors, and Related Secondary Oxidation Products in Los Angeles, California: A Synthesis of Measurements from 1960 to 2010. J. Geophys. Res. Atmos. 2013, 118 (11), 5893–5911. 10.1002/jgrd.50472. [DOI] [Google Scholar]
  10. Cusworth D. H.; Mickley L. J.; Sulprizio M. P.; Liu T.; Marlier M. E.; Defries R. S.; Guttikunda S. K.; Gupta P. Quantifying the Influence of Agricultural Fires in Northwest India on Urban Air Pollution in Delhi, India. Environ. Res. Lett. 2018, 13 (4), 044018. 10.1088/1748-9326/aab303. [DOI] [Google Scholar]
  11. Bhuvaneshwari S.; Hettiarachchi H.; Meegoda J. N. Crop Residue Burning in India: Policy Challenges and Potential Solutions. Int. J. Environ. Res. Public Heal. 2019, Vol. 16, Page 832 2019, 16 (5), 832. 10.3390/ijerph16050832. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Bray C. D.; Battye W. H.; Aneja V. P. The Role of Biomass Burning Agricultural Emissions in the Indo-Gangetic Plains on the Air Quality in New Delhi, India. Atmos. Environ. 2019, 218, 116983. 10.1016/j.atmosenv.2019.116983. [DOI] [Google Scholar]
  13. Ojha N.; Sharma A.; Kumar M.; Girach I.; Ansari T. U.; Sharma S. K.; Singh N.; Pozzer A.; Gunthe S. S. On the Widespread Enhancement in Fine Particulate Matter across the Indo-Gangetic Plain towards Winter. Sci. Reports 2020 101 2020, 10 (1), 1–9. 10.1038/s41598-020-62710-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Sembhi H.; Wooster M.; Zhang T.; Sharma S.; Singh N.; Agarwal S.; Boesch H.; Gupta S.; Misra A.; Tripathi S. N.; Mor S.; Khaiwal R. Post-Monsoon Air Quality Degradation across Northern India: Assessing the Impact of Policy-Related Shifts in Timing and Amount of Crop Residue Burnt. Environ. Res. Lett. 2020, 15 (10), 104067. 10.1088/1748-9326/aba714. [DOI] [Google Scholar]
  15. Shivani; Gadi R.; Sharma S. K.; Mandal T. K. Seasonal Variation, Source Apportionment and Source Attributed Health Risk of Fine Carbonaceous Aerosols over National Capital Region, India. Chemosphere 2019, 237, 124500. 10.1016/j.chemosphere.2019.124500. [DOI] [PubMed] [Google Scholar]
  16. Shivani; Gadi R.; Saxena M.; Sharma S. K.; Mandal T. K. Short-Term Degradation of Air Quality during Major Firework Events in Delhi, India. Meteorol. Atmos. Phys. 2019, 131 (4), 753–764. 10.1007/s00703-018-0602-9. [DOI] [Google Scholar]
  17. Gadi R.; Shivani; Sharma S. K.; Mandal T. K. Source Apportionment and Health Risk Assessment of Organic Constituents in Fine Ambient Aerosols (PM2.5): A Complete Year Study over National Capital Region of India. Chemosphere 2019, 221, 583–596. 10.1016/j.chemosphere.2019.01.067. [DOI] [PubMed] [Google Scholar]
  18. Chen Y.; Beig G.; Archer-Nicholls S.; Drysdale W.; Acton W. J. F.; Lowe D.; Nelson B.; Lee J.; Ran L.; Wang Y.; Wu Z.; Sahu S. K.; Sokhi R. S.; Singh V.; Gadi R.; Nicholas Hewitt C.; Nemitz E.; Archibald A.; McFiggans G.; Wild O. Avoiding High Ozone Pollution in Delhi, India. Faraday Discuss. 2021, 226 (0), 502–514. 10.1039/D0FD00079E. [DOI] [PubMed] [Google Scholar]
  19. Nelson B. S.; Stewart G. J.; Drysdale W. S.; Newland M. J.; Vaughan A. R.; Dunmore R. E.; Edwards P. M.; Lewis A. C.; Hamilton J. F.; Acton W. J.; Hewitt C. N.; Crilley L. R.; Alam M. S.; Şahin Ü. A.; Beddows D. C. S.; Bloss W. J.; Slater E.; Whalley L. K.; Heard D. E.; Cash J. M.; Langford B.; Nemitz E.; Sommariva R.; Cox S.; Shivani; Gadi R.; Gurjar B. R.; Hopkins J. R.; Rickard A. R.; Lee J. D. In Situ Ozone Production Is Highly Sensitive to Volatile Organic Compounds in Delhi, India. Atmos. Chem. Phys. 2021, 21 (17), 13609–13630. 10.5194/acp-21-13609-2021. [DOI] [Google Scholar]
  20. Gulia S.; Shiva Nagendra S. M.; Khare M.; Khanna I. Urban Air Quality Management-A Review. Atmos. Pollut. Res. 2015, 6 (2), 286–304. 10.5094/APR.2015.033. [DOI] [Google Scholar]
  21. Guttikunda S. K.; Goel R. Health Impacts of Particulate Pollution in a Megacity-Delhi, India. Environ. Dev. 2013, 6 (1), 8–20. 10.1016/j.envdev.2012.12.002. [DOI] [Google Scholar]
  22. Şahin Ü. A.; Harrison R. M.; Alam M. S.; Beddows D. C. S.; Bousiotis D.; Shi Z.; Crilley L. R.; Bloss W.; Brean J.; Khanna I.; Verma R. Measurement Report: Interpretation of Wide-Range Particulate Matter Size Distributions in Delhi. Atmos. Chem. Phys. 2022, 22 (8), 5415–5433. 10.5194/acp-22-5415-2022. [DOI] [Google Scholar]
  23. Guttikunda S. K.; Gurjar B. R. Role of Meteorology in Seasonality of Air Pollution in Megacity Delhi, India. Environ. Monit. Assess. 2012, 184 (5), 3199–3211. 10.1007/s10661-011-2182-8. [DOI] [PubMed] [Google Scholar]
  24. Bryant D. J.; Nelson B. S.; Swift S. J.; Budisulistiorini S. H.; Drysdale W. S.; Vaughan A. R.; Newland M. J.; Hopkins J. R.; Cash J. M.; Langford B.; Nemitz E.; Acton W. J. F.; Hewitt C. N.; Mandal T.; Gurjar B. R.; Gadi R.; Lee J. D.; Rickard A. R.; Hamilton J. F. Biogenic and Anthropogenic Sources of Isoprene and Monoterpenes and Their Secondary Organic Aerosol in Delhi, India. Atmos. Chem. Phys. 2023, 23 (1), 61–83. 10.5194/acp-23-61-2023. [DOI] [Google Scholar]
  25. Zhao Y.; Saleh R.; Saliba G.; Presto A. A.; Gordon T. D.; Drozd G. T.; Goldstein A. H.; Donahue N. M.; Robinson A. L. Reducing Secondary Organic Aerosol Formation from Gasoline Vehicle Exhaust. Proc. Natl. Acad. Sci. U. S. A. 2017, 114 (27), 6984–6989. 10.1073/pnas.1620911114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Stewart G. J.; Nelson B. S.; Drysdale W. S.; Acton W. J. F.; Vaughan A. R.; Hopkins J. R.; Dunmore R. E.; Hewitt C. N.; Nemitz E.; Mullinger N.; Langford B.; Shivani; Reyes-Villegas E.; Gadi R.; Rickard A. R.; Lee J. D.; Hamilton J. F. Sources of Non-Methane Hydrocarbons in Surface Air in Delhi, India. Faraday Discuss. 2021, 226 (0), 409–431. 10.1039/D0FD00087F. [DOI] [PubMed] [Google Scholar]
  27. Squires F. A.; Nemitz E.; Langford B.; Wild O.; Drysdale W. S.; Acton W. J. F.; Fu P.; Grimmond C. S. B.; Hamilton J. F.; Hewitt C. N.; Hollaway M.; Kotthaus S.; Lee J.; Metzger S.; Pingintha-Durden N.; Shaw M.; Vaughan A. R.; Wang X.; Wu R.; Zhang Q.; Zhang Y. Measurements of Traffic-Dominated Pollutant Emissions in a Chinese Megacity. Atmos. Chem. Phys. 2020, 20 (14), 8737–8761. 10.5194/acp-20-8737-2020. [DOI] [Google Scholar]
  28. Jenkin M. E.; Young J. C.; Rickard A. R. The MCM v3.3.1 Degradation Scheme for Isoprene. Atmos. Chem. Phys. 2015, 15 (20), 11433–11459. 10.5194/acp-15-11433-2015. [DOI] [Google Scholar]
  29. Saunders S. M.; Jenkin M. E.; Derwent R. G.; Pilling M. J. Protocol for the Development of the Master Chemical Mechanism, MCM v3 (Part A): Tropospheric Degradation of Non-Aromatic Volatile Organic Compounds. Atmos. Chem. Phys. 2003, 3 (1), 161–180. 10.5194/acp-3-161-2003. [DOI] [Google Scholar]
  30. Sommariva R.; Cox S.; Martin C.; Borońska K.; Young J.; Jimack P. K.; Pilling M. J.; Matthaios V. N.; Nelson B. S.; Newland M. J.; Panagi M.; Bloss W. J.; Monks P. S.; Rickard A. R. AtChem (Version 1), an Open-Source Box Model for the Master Chemical Mechanism. Geosci. Model Dev. 2020, 13 (1), 169–183. 10.5194/gmd-13-169-2020. [DOI] [Google Scholar]
  31. Atkinson R.; Baulch D. L.; Cox R. A.; Crowley J. N.; Hampson R. F.; Hynes R. G.; Jenkin M. E.; Rossi M. J.; Troe J. Evaluated Kinetic and Photochemical Data for Atmospheric Chemistry: Volume II - Gas Phase Reactions of Organic Species. Atmos. Chem. Phys. 2006, 6 (11), 3625–4055. 10.5194/acp-6-3625-2006. [DOI] [Google Scholar]
  32. Atkinson R.; Arey J. Gas-Phase Tropospheric Chemistry of Biogenic Volatile Organic Compounds: A Review. Atmos. Environ. 2003, 37 (Suppl. 2), 197–219. 10.1016/S1352-2310(03)00391-1. [DOI] [Google Scholar]
  33. Lee J. D.; Whalley L. K.; Heard D. E.; Stone D.; Dunmore R. E.; Hamilton J. F.; Young D. E.; Allan J. D.; Laufs S.; Kleffmann J. Detailed Budget Analysis of HONO in Central London Reveals a Missing Daytime Source. Atmos. Chem. Phys. 2016, 16 (5), 2747–2764. 10.5194/acp-16-2747-2016. [DOI] [Google Scholar]
  34. Fiedrich M.; Kurtenbach R.; Wiesen P.; Kleffmann J. Artificial O3 Formation during Fireworks. Atmos. Environ. 2017, 165, 57–61. 10.1016/j.atmosenv.2017.06.028. [DOI] [Google Scholar]
  35. Wild R. J.; Dubé W. P.; Aikin K. C.; Eilerman S. J.; Neuman J. A.; Peischl J.; Ryerson T. B.; Brown S. S. On-Road Measurements of Vehicle NO2/NOx Emission Ratios in Denver, Colorado, USA. Atmos. Environ. 2017, 148 (2), 182–189. 10.1016/j.atmosenv.2016.10.039. [DOI] [Google Scholar]
  36. NSW Government ACTAQ . In-Tunnel Air Quality (Nitrogen Dioxide) Policy. 2016, February.
  37. Richmond-Bryant J.; Owen R. C.; Graham S.; Snyder M.; McDow S.; Oakes M.; Kimbrough S. Estimation of On-Road NO2 Concentrations, NO2/NOx Ratios, and Related Roadway Gradients from near-Road Monitoring Data. Air Qual., Atmos. Health 2017, 10 (5), 611–625. 10.1007/s11869-016-0455-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Atkinson R. Gas-Phase Tropospheric Chemistry of Volatile Organic Compounds: 1. Alkanes and Alkenes. J. Phys. Chem. Ref. Data 1997, 26 (2), 215–290. 10.1063/1.556012. [DOI] [Google Scholar]
  39. Haslett S. L.; Bell D. M.; Kumar V.; Slowik J. G.; Wang D. S.; Mishra S.; Rastogi N.; Singh A.; Ganguly D.; Thornton J.; Zheng F.; Li Y.; Liu Y.; Ma W.; Yan C.; Kulmala M.; Daellenbach K. R.; Baltensperger U.; Prevot A. S. H.; Tripathi S. N.; Mohr C. Night-Time NO Emissions Strongly Suppress Chlorine and Nitrate Radical Formation during the Winter in Delhi. EGUsphere 2023, 10.5194/egusphere-2023-497. [DOI] [Google Scholar]
  40. Reyes-Villegas E.; Panda U.; Darbyshire E.; Cash J. M.; Joshi R.; Langford B.; Di Marco C. F.; Mullinger N. J.; Alam M. S.; Crilley L. R.; Rooney D. J.; Acton W. J. F.; Drysdale W.; Nemitz E.; Flynn M.; Voliotis A.; McFiggans G.; Coe H.; Lee J.; Hewitt C. N.; Heal M. R.; Gunthe S. S.; Mandal T. K.; Gurjar B. R.; Shivani; Gadi R.; Singh S.; Soni V.; Allan J. D. PM1 Composition and Source Apportionment at Two Sites in Delhi, India, across Multiple Seasons. Atmos. Chem. Phys. 2021, 21 (15), 11655–11667. 10.5194/acp-21-11655-2021. [DOI] [Google Scholar]
  41. Cash J. M.; Langford B.; Di Marco C.; Mullinger N. J.; Allan J.; Reyes-Villegas E.; Joshi R.; Heal M. R.; Acton W. J. F.; Hewitt C. N.; Misztal P. K.; Drysdale W.; Mandal T. K.; Gadi R.; Gurjar B. R.; Nemitz E. Seasonal Analysis of Submicron Aerosol in Old Delhi Using High-Resolution Aerosol Mass Spectrometry: Chemical Characterisation, Source Apportionment and New Marker Identification. Atmos. Chem. Phys. 2021, 21 (13), 10133–10158. 10.5194/acp-21-10133-2021. [DOI] [Google Scholar]
  42. Stewart G. J.; Nelson B. S.; Acton W. J. F.; Vaughan A. R.; Farren N. J.; Hopkins J. R.; Ward M. W.; Swift S. J.; Arya R.; Mondal A.; Jangirh R.; Ahlawat S.; Yadav L.; Sharma S. K.; Yunus S. S. M.; Hewitt C. N.; Nemitz E.; Mullinger N.; Gadi R.; Sahu L. K.; Tripathi N.; Rickard A. R.; Lee J. D.; Mandal T. K.; Hamilton J. F. Emissions of Intermediate-Volatility and Semi-Volatile Organic Compounds from Domestic Fuels Used in Delhi, India. Atmos. Chem. Phys. 2021, 21 (4), 2407–2426. 10.5194/acp-21-2407-2021. [DOI] [Google Scholar]

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