Articles | Volume 22, issue 20
https://doi.org/10.5194/acp-22-13631-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-13631-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Oct 2022
Research article |
| 21 Oct 2022
| 21 Oct 2022
Contributions of primary sources to submicron organic aerosols in Delhi, India
Sahil Bhandari
McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas, USA
Department of Mechanical Engineering, University of British Columbia, Vancouver, Canada
Zainab Arub
Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi, India
Gazala Habib
Department of Civil Engineering, Indian Institute of Technology Delhi, New Delhi, India
Joshua S. Apte
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, UC Berkeley, Berkeley, California, USA
School of Public Health, UC Berkeley, Berkeley, California, USA
McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, Texas, USA
Related authors
Sahil Bhandari, Zainab Arub, Gazala Habib, Joshua S. Apte, and Lea Hildebrandt Ruiz
Atmos. Meas. Tech., 15, 6051–6074, https://doi.org/10.5194/amt-15-6051-2022, https://doi.org/10.5194/amt-15-6051-2022, 2022
Short summary
Short summary
We present a new method to conduct source apportionment resolved by time of day using the underlying approach of positive matrix factorization. We report results for four example time periods in two seasons (winter and monsoon 2017) in Delhi, India. Compared to the traditional approach, we extract a larger number of factors that represent the expected sources of primary organic aerosol. This method can capture diurnal time series patterns of sources at low computational cost.
Erin F. Katz, Caleb M. Arata, Eva Y. Pfannerstill, Robert J. Weber, Darian Ng, Michael J. Milazzo, Haley Byrne, Hui Wang, Alex B. Guenther, Camilo Rey-Sanchez, Joshua Apte, Dennis D. Baldocchi, and Allen H. Goldstein
EGUsphere, https://doi.org/10.5194/egusphere-2025-2682, https://doi.org/10.5194/egusphere-2025-2682, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Terpenoids are organic gases that can originate from natural and human-caused sources, and their fast reactions in the atmosphere can cause air pollution. Emissions of organic gases in an urban environment were measured. For some terpenoids, human-caused sources were responsible for about a quarter of the emissions, while others were likely to be entirely from vegetation. The terpenoids contributed substantially to the potential to form secondary pollutants.
Anil Kumar Mandariya, Ajit Ahlawat, Mohammed Haneef, Nisar Ali Baig, Kanan Patel, Joshua Apte, Lea Hildebrandt Ruiz, Alfred Wiedensohler, and Gazala Habib
Atmos. Chem. Phys., 24, 3627–3647, https://doi.org/10.5194/acp-24-3627-2024, https://doi.org/10.5194/acp-24-3627-2024, 2024
Short summary
Short summary
The current study explores the temporal variation of size-selected particle hygroscopicity in Delhi for the first time. Here, we report that the high volume fraction contribution of ammonium chloride to aerosol governs the high aerosol hygroscopicity and associated liquid water content based on the experimental data. The episodically high ammonium chloride present in Delhi's atmosphere could lead to haze and fog formation under high relative humidity in the region.
Mark Joseph Campmier, Jonathan Gingrich, Saumya Singh, Nisar Baig, Shahzad Gani, Adithi Upadhya, Pratyush Agrawal, Meenakshi Kushwaha, Harsh Raj Mishra, Ajay Pillarisetti, Sreekanth Vakacherla, Ravi Kant Pathak, and Joshua S. Apte
Atmos. Meas. Tech., 16, 4357–4374, https://doi.org/10.5194/amt-16-4357-2023, https://doi.org/10.5194/amt-16-4357-2023, 2023
Short summary
Short summary
We studied a low-cost air pollution sensor called PurpleAir PA-II in three different locations in India (Delhi, Hamirpur, and Bangalore) to characterize its performance. We compared its signal to more expensive reference sensors and found that the PurpleAir sensor was precise but inaccurate without calibration. We created a custom calibration equation for each location, which improved the accuracy of the PurpleAir sensor, and found that calibrations should be adjusted for different seasons.
Sahil Bhandari, Zainab Arub, Gazala Habib, Joshua S. Apte, and Lea Hildebrandt Ruiz
Atmos. Meas. Tech., 15, 6051–6074, https://doi.org/10.5194/amt-15-6051-2022, https://doi.org/10.5194/amt-15-6051-2022, 2022
Short summary
Short summary
We present a new method to conduct source apportionment resolved by time of day using the underlying approach of positive matrix factorization. We report results for four example time periods in two seasons (winter and monsoon 2017) in Delhi, India. Compared to the traditional approach, we extract a larger number of factors that represent the expected sources of primary organic aerosol. This method can capture diurnal time series patterns of sources at low computational cost.
Cited articles
Abdullahi, K. L., Delgado-Saborit, J. M., and Harrison, R. M.: Emissions and
indoor concentrations of particulate matter and its specific chemical
components from cooking: a review, Atmos. Environ., 71, 260–294,
https://doi.org/10.1016/j.atmosenv.2013.01.061, 2013.
Agarwal, R., Shukla, K., Kumar, S., Aggarwal, S. G., and Kawamura, K.:
Chemical composition of waste burning organic aerosols at landfill and urban
sites in Delhi, Atmos. Pollut. Res., 11, 554–565,
https://doi.org/10.1016/j.apr.2019.12.004, 2020.
Ahern, A. T., Robinson, E. S., Tkacik, D. S., Saleh, R., Hatch, L. E.,
Barsanti, K. C., Stockwell, C. E., Yokelson, R. J., Presto, A. A., Robinson,
A. L., Sullivan, R. C., and Donahue, N. M.: Production of secondary organic
aerosol during aging of biomass burning smoke from fresh fuels and its
relationship to VOC precursors, J. Geophys. Res.-Atmos., 124, 3583–3606,
https://onlinelibrary.wiley.com/doi/abs/10.1029/2018JD029068, 2019.
Allan, J. D., Williams, P. I., Morgan, W. T., Martin, C. L., Flynn, M. J., Lee, J., Nemitz, E., Phillips, G. J., Gallagher, M. W., and Coe, H.: Contributions from transport, solid fuel burning and cooking to primary organic aerosols in two UK cities, Atmos. Chem. Phys., 10, 647–668, https://doi.org/10.5194/acp-10-647-2010, 2010.
Apte, J. S. and Pant, P.: Toward cleaner air for a billion Indians,
P. Natl. Acad. Sci. USA, 166, 10614–10616,
https://doi.org/10.1073/pnas.1905458116, 2019.
Apte, J. S., Marshall, J. D., Cohen, A. J., and Brauer, M.: Addressing
global mortality from ambient PM2.5, Environ. Sci.
Technol., 49, 8057–8066, https://doi.org/10.1021/acs.est.5b01236,
2015.
ARAI and TERI: Source apportionment of PM2.5 and PM10 of Delhi NCR
for identification of major sources,
https://www.teriin.org/project/source-apportionment-pm25-pm10-delhi-ncr-identification-major-sources
(last access: 20 March 2022), 2018
Arub, Z., Bhandari, S., Gani, S., Apte, J. S., Hildebrandt Ruiz, L., and Habib, G.: Air mass physiochemical characteristics over New Delhi: impacts on aerosol hygroscopicity and cloud condensation nuclei (CCN) formation, Atmos. Chem. Phys., 20, 6953–6971, https://doi.org/10.5194/acp-20-6953-2020, 2020.
Bahreini, R., Keywood, M. D., Ng, N. L., Varutbangkul, V., Gao, S., Flagan,
R. C., Seinfeld, J. H., Worsnop, D. R., and Jimenez, J. L.: Measurements of
secondary organic aerosol from oxidation of cycloalkenes, terpenes, and
m-xylene using an aerodyne aerosol mass spectrometer, Environ. Sci. Technol., 39, 5674–5688,
https://doi.org/10.1021/es048061a, 2005.
Bhandari, S., Gani, S., Patel, K., Wang, D. S., Soni, P., Arub, Z., Habib, G., Apte, J. S., and Hildebrandt Ruiz, L.: Sources and atmospheric dynamics of organic aerosol in New Delhi, India: insights from receptor modeling, Atmos. Chem. Phys., 20, 735–752, https://doi.org/10.5194/acp-20-735-2020, 2020.
Bhandari, S., Arub, Z., Habib, G., Apte, J. S., and Hildebrandt Ruiz, L.: Source apportionment resolved by time of day for improved deconvolution of primary source contributions to air pollution, Atmos. Meas. Tech., 15, 6051–6074, https://doi.org/10.5194/amt-15-6051-2022, 2022.
Brown, S. G., Lee, T., Norris, G. A., Roberts, P. T., Collett Jr., J. L., Paatero, P., and Worsnop, D. R.: Receptor modeling of near-roadway aerosol mass spectrometer data in Las Vegas, Nevada, with EPA PMF, Atmos. Chem. Phys., 12, 309–325, https://doi.org/10.5194/acp-12-309-2012, 2012.
Canonaco, F., Slowik, J. G., Baltensperger, U., and Prévôt, A. S. H.: Seasonal differences in oxygenated organic aerosol composition: implications for emissions sources and factor analysis, Atmos. Chem. Phys., 15, 6993–7002, https://doi.org/10.5194/acp-15-6993-2015, 2015.
Cappa, C. D. and Jimenez, J. L.: Quantitative estimates of the volatility of ambient organic aerosol, Atmos. Chem. Phys., 10, 5409–5424, https://doi.org/10.5194/acp-10-5409-2010, 2010.
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., Shivani, Gadi, R., Gurjar, B. R., and 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., 21, 10133–10158, https://doi.org/10.5194/acp-21-10133-2021, 2021.
Collaborative Clean Air Policy Centre: Can an airshed governance framework
in India spur clean air for all?, Lessons from Mexico City and Los Angeles,
https://ccapc.org.in/policy-briefs/2020/lessonsonairshedgovernance (last access: 20 March 2022), 2020.
Chowdhury, Z., Zheng, M., Schauer, J. J., Sheesley, R. J., Salmon, L. G.,
Cass, G. R., and Russell, A. G.: Speciation of ambient fine organic carbon
particles and source apportionment of PM2.5 in Indian cities, J. Geophys. Res.-Atmos., 112, D15303,
https://doi.org/10.1029/2007JD008386, 2007.
Conibear, L., Butt, E. W., Knote, C., Arnold, S. R., and Spracklen, D. V.:
Residential energy use emissions dominate health impacts from exposure to
ambient particulate matter in India, Nat. Commun., 9, 1–9, https://doi.org/10.1038/s41467-018-02986-7, 2018.
Central Pollution Control Board: Air quality monitoring, emission inventory
and source apportionment study for Indian cities, National summary
report, https://cpcb.nic.in/source-apportionment-studies/ (last access: 20 March 2022), 2010.
Crippa, M., Solazzo, E., Huang, G., Guizzardi, D., Koffi, E., Muntean, M.,
Schieberle, C., Friedrich, R., and Janssens-Maenhout, G.: High resolution
temporal profiles in the Emissions Database for Global Atmospheric Research,
Sci. Data, 7, 1–17, 2020.
Dai, Q., Liu, B., Bi, X., Wu, J., Liang, D., Zhang, Y., Feng, Y., and Hopke,
P. K.: Dispersion normalized PMF provides insights into the significant
changes in source contributions to PM2.5 after the CoviD-19 outbreak,
Environ. Sci. Technol., 54, 9917–9927,
https://doi.org/10.1021/acs.est.0c02776, 2020.
Dallmann, T. R., Onasch, T. B., Kirchstetter, T. W., Worton, D. R., Fortner, E. C., Herndon, S. C., Wood, E. C., Franklin, J. P., Worsnop, D. R., Goldstein, A. H., and Harley, R. A.: Characterization of particulate matter emissions from on-road gasoline and diesel vehicles using a soot particle aerosol mass spectrometer, Atmos. Chem. Phys., 14, 7585–7599, https://doi.org/10.5194/acp-14-7585-2014, 2014.
Dall'Osto, M., Ovadnevaite, J., Ceburnis, D., Martin, D., Healy, R. M., O'Connor, I. P., Kourtchev, I., Sodeau, J. R., Wenger, J. C., and O'Dowd, C.: Characterization of urban aerosol in Cork city (Ireland) using aerosol mass spectrometry, Atmos. Chem. Phys., 13, 4997–5015, https://doi.org/10.5194/acp-13-4997-2013, 2013.
Dall'Osto, M., Paglione, M., Decesari, S., Facchini, M. C., O'Dowd, C.,
Plass-Duellmer, C., and Harrison, R. M.: On the origin of AMS “cooking
organic aerosol” at a rural site, Environ. Sci. Technol., 49,
13964–13972,
2015.
DeCarlo, P. F.: Beyond PM2.5 mass: Use of particle composition measurements
to identify and quantify air pollution sources, AGU Fall Meeting,
https://agu.confex.com/agu/fm21/meetingapp.cgi/Paper/933637, last access: 19 December 2021.
DEFRA, UK: Estimation of changes in air pollution emissions, concentrations,
and exposure during the COVID-19 outbreak in the UK,
https://uk-air.defra.gov.uk/library/reports?report_id=1005 (last access: 20 March 2022), 2020.
Donahue, N. M., Robinson, A. L., Stanier, C. O., and Pandis, S. N.: Coupled
partitioning, dilution, and chemical aging of semivolatile organics,
Environ. Sci. Technol., 40, 2635–2643,
https://doi.org/10.1021/es052297c, 2006.
Drinovec, L., Močnik, G., Zotter, P., Prévôt, A. S. H., Ruckstuhl, C., Coz, E., Rupakheti, M., Sciare, J., Müller, T., Wiedensohler, A., and Hansen, A. D. A.: The “dual-spot” Aethalometer: an improved measurement of aerosol black carbon with real-time loading compensation, Atmos. Meas. Tech., 8, 1965–1979, https://doi.org/10.5194/amt-8-1965-2015, 2015.
Drosatou, A. D., Skyllakou, K., Theodoritsi, G. N., and Pandis, S. N.: Positive matrix factorization of organic aerosol: insights from a chemical transport model, Atmos. Chem. Phys., 19, 973–986, https://doi.org/10.5194/acp-19-973-2019, 2019.
Fu, P. Q., Kawamura, K., Pavuluri, C. M., Swaminathan, T., and Chen, J.: Molecular characterization of urban organic aerosol in tropical India: contributions of primary emissions and secondary photooxidation, Atmos. Chem. Phys., 10, 2663–2689, https://doi.org/10.5194/acp-10-2663-2010, 2010.
Gadi, R., Shivani, Sharma, S. K., and 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, 221, 583–596,
https://doi.org/10.1016/j.chemosphere.2019.01.067, 2019.
Ganguly, T., Selvaraj, K. L., and Guttikunda, S. K.: National Clean Air
Programme (NCAP) for Indian cities: review and outlook of clean air action
plans, Atmos. Environ., 8, 100096,
https://doi.org/10.1016/j.aeaoa.2020.100096, 2020.
Gani, S., Bhandari, S., Seraj, S., Wang, D. S., Patel, K., Soni, P., Arub, Z., Habib, G., Hildebrandt Ruiz, L., and Apte, J. S.: Submicron aerosol composition in the world's most polluted megacity: the Delhi Aerosol Supersite study, Atmos. Chem. Phys., 19, 6843–6859, https://doi.org/10.5194/acp-19-6843-2019, 2019.
Gani, S., Bhandari, S., Patel, K., Seraj, S., Soni, P., Arub, Z., Habib, G., Hildebrandt Ruiz, L., and Apte, J. S.: Particle number concentrations and size distribution in a polluted megacity: the Delhi Aerosol Supersite study, Atmos. Chem. Phys., 20, 8533–8549, https://doi.org/10.5194/acp-20-8533-2020, 2020.
GBD MAPS Working Group: Burden of Disease Attributable to Major Air
Pollution Sources in India: Special Report 21,
https://www.healtheffects.org/publication/gbd-air-pollution-india (last
access: 5 November 2019), 2018.
Grieshop, A. P., Donahue, N. M., and Robinson, A. L.: Laboratory investigation of photochemical oxidation of organic aerosol from wood fires 2: analysis of aerosol mass spectrometer data, Atmos. Chem. Phys., 9, 2227–2240, https://doi.org/10.5194/acp-9-2227-2009, 2009.
Gulia, S., Mittal, A., and Khare, M.: Quantitative evaluation of source
interventions for urban air quality improvement – a case study of Delhi
city, Atmos. Pollut. Res., 9, 577–583,
https://doi.org/10.1016/j.apr.2017.12.003, 2018.
Guo, H., Kota, S. H., Sahu, S. K., Hu, J., Ying, Q., Gao, A., and Zhang, H.:
Source apportionment of PM2.5 in North India using source-oriented air
quality models, Environ. Pollut., 231, 426–436,
https://doi.org/10.1016/j.envpol.2017.08.016, 2017.
Guo, H., Kota, S. H., Chen, K., Sahu, S. K., Hu, J., Ying, Q., Wang, Y., and Zhang, H.: Source contributions and potential reductions to health effects of particulate matter in India, Atmos. Chem. Phys., 18, 15219–15229, https://doi.org/10.5194/acp-18-15219-2018, 2018.
Guo, H., Kota, S. H., Sahu, S. K., and Zhang, H.: Contributions of local and
regional sources to PM2.5 and its health effects in north India,
Atmos. Environ., 214, 116867,
https://doi.org/10.1016/j.atmosenv.2019.116867, 2019.
Guttikunda, S. K. and Calori, G.: A GIS based emissions inventory at 1 km × 1 km spatial resolution for air pollution analysis in Delhi,
India, Atmos. Environ., 67, 101–111,
https://doi.org/10.1016/j.atmosenv.2012.10.040, 2013.
He, L.-Y., Lin, Y., Huang, X.-F., Guo, S., Xue, L., Su, Q., Hu, M., Luan, S.-J., and Zhang, Y.-H.: Characterization of high-resolution aerosol mass spectra of primary organic aerosol emissions from Chinese cooking and biomass burning, Atmos. Chem. Phys., 10, 11535–11543, https://doi.org/10.5194/acp-10-11535-2010, 2010.
Hildebrandt Ruiz, L. and Bhandari, S.: Data published in “Contributions of primary sources to submicron organic aerosols in Delhi, India”, Texas Data Repository [data set], https://doi.org/10.18738/T8/8FAEDU, 2022.
Hu, W. W., Hu, M., Yuan, B., Jimenez, J. L., Tang, Q., Peng, J. F., Hu, W., Shao, M., Wang, M., Zeng, L. M., Wu, Y. S., Gong, Z. H., Huang, X. F., and He, L. Y.: Insights on organic aerosol aging and the influence of coal combustion at a regional receptor site of central eastern China, Atmos. Chem. Phys., 13, 10095–10112, https://doi.org/10.5194/acp-13-10095-2013, 2013.
Hu, W. W., Hu, M., Hu, W., Jimenez, J. L., Yuan, B., Chen, W., Wang, M., Wu,
Y., Chen, C., Wang, Z., Peng, J., Zeng, L., and Shao, M.: Chemical
composition, sources, and aging process of submicron aerosols in Beijing:
contrast between summer and winter, J. Geophys. Res., 121,
1955–1977, https://doi.org/10.1002/2015JD024020, 2016.
Indian National Science Academy: Seasons of Delhi,
https://www.insaindia.res.in/climate.php (last access: 20 March 2022), 2018.
Jain, S., Sharma, S. K., Vijayan, N., and Mandal, T. K.: Investigating the
seasonal variability in source contribution to PM2.5 and PM10
using different receptor models during 2013–2016 in Delhi, India,
Environ. Sci. Pollut. Res., 28, 4660–4675,
https://doi.org/10.1007/s11356-020-10645-y, 2021.
Jaiprakash, S. A., Habib, G., Raman, R. S., and Gupta, T.: Chemical
characterization of PM1 aerosol in Delhi and source apportionment using
positive matrix factorization, Environ. Sci. Pollut. Res.,
24, 445–462, https://doi.org/10.1007/s11356-016-7708-8, 2017.
Kaltsonoudis, C., Kostenidou, E., Louvaris, E., Psichoudaki, M., Tsiligiannis, E., Florou, K., Liangou, A., and Pandis, S. N.: Characterization of fresh and aged organic aerosol emissions from meat charbroiling, Atmos. Chem. Phys., 17, 7143–7155, https://doi.org/10.5194/acp-17-7143-2017, 2017.
IIT Kanpur: Comprehensive study on air pollution and greenhouse gases (GHGs)
in Delhi, https://cerca.iitd.ac.in/uploads/Reports/1576211826iitk.pdf, (last access: 20 March 2022) 2016.
Kar, A., Pachauri, S., Bailis, R., and Zerriffi, H.: Capital cost subsidies
through India's Ujjwala cooking gas programme promote rapid adoption of
liquefied petroleum gas but not regular use, Nat. Energ., 5, 125–126,
https://doi.org/10.1038/s41560-019-0429-8, 2020.
Karnezi, E., Louvaris, E., Kostenidou, E., Florou, K., Cain, K., and Pandis,
S.: Discrepancies between the volatility distributions of OA in the ambient
atmosphere and the laboratory, International Aerosol Conference,
http://aaarabstracts.com/2018IAC/viewabstract.php?pid=870, last access: 7 September 2018.
Khare, P., Machesky, J., Soto, R., He, M., Presto, A. A., and Gentner, D.
R.: Asphalt-related emissions are a major missing nontraditional source of
secondary organic aerosol precursors, Sci. Adv., 58, 562–586,
https://doi.org/10.1126/sciadv.abb9785, 2021.
Kodros, J. K., Papanastasiou, D. K., Paglione, M., Masiol, M., Squizzato,
S., Florou, K., Skyllakou, K., Kaltsonoudis, C., Nenes, A., and Pandis, S.
N.: Rapid dark aging of biomass burning as an overlooked source of oxidized
organic aerosol, P. Natl. Acad. Sci. USA, 117,
33028–33033, https://doi.org/10.1073/pnas.2010365117,
2020.
Kostenidou, E., Karnezi, E., Hite Jr., J. R., Bougiatioti, A., Cerully, K., Xu, L., Ng, N. L., Nenes, A., and Pandis, S. N.: Organic aerosol in the summertime southeastern United States: components and their link to volatility distribution, oxidation state and hygroscopicity, Atmos. Chem. Phys., 18, 5799–5819, https://doi.org/10.5194/acp-18-5799-2018, 2018.
Kroll, J. H., Smith, J. D., Worsnop, D. R., and Wilson, K. R.:
Characterisation of lightly oxidized organic aerosol formed from the
photochemical aging of diesel exhaust particles, Environ. Chem., 9,
211–220, https://doi.org/10.1071/EN11162, 2012.
Kumar, S., Aggarwal, S. G., Gupta, P. K., and Kawamura, K.: Investigation of
the tracers for plastic-enriched waste burning aerosols, Atmos. Environ., 108, 49–58,
https://doi.org/10.1016/j.atmosenv.2015.02.066, 2015.
Kumari, P. and Mandal, P.: Indoor air pollution at restaurant kitchen in
Delhi NCR, Sustainability in Environmental Engineering and Science,
159–165, https://doi.org/10.1007/978-981-15-6887-9_18,
2021.
Lalchandani, V., Kumar, V., Tobler, A., Thamban, N.M., Mishra, S., Slowik,
J.G., Bhattu, D., Rai, P., Satish, R., Ganguly, D. and Tiwari, S.: Real-time
characterization and source apportionment of fine particulate matter in the
Delhi megacity area during late winter, Sci. Total
Environ., 770, 145324, https://doi.org/10.1016/j.scitotenv.2021.145324, 2021.
Lelieveld, J. and Crutzen, P. J.: The role of clouds in tropospheric
photochemistry, J. Atmos. Chem., 12, 229–267, 1991.
Lin, C., Ceburnis, D., Hellebust, S., Buckley, P., Wenger, J., Canonaco, F.,
Prévôt, A. S. H., Huang, R. J., O'Dowd, C., and Ovadnevaite, J.:
Characterization of primary organic aerosol from domestic wood, peat, and
coal burning in Ireland, Environ. Sci. Technol., 51,
10624–10632, https://doi.org/10.1021/acs.est.7b01926, 2017.
Liu, H., Qi, L., Liang, C., Deng, F., Man, H., and He, K.: How aging process
changes characteristics of vehicle emissions? a review, Crit. Rev. Env. Sci. Tec., 50, 1796–1828, 2020.
Liu, T., Liu, Q., Li, Z., Huo, L., Chan, M. N., Li, X., Zhou, Z., and Chan,
C. K.: Emission of volatile organic compounds and production of secondary
organic aerosol from stir-frying spices, Sci. Total Environ.,
599, 1614–1621, https://doi.org/10.1016/j.scitotenv.2017.05.147,
2017.
Liu, T., Wang, Z., Wang, X., and Chan, C. K.: Primary and secondary organic aerosol from heated cooking oil emissions, Atmos. Chem. Phys., 18, 11363–11374, https://doi.org/10.5194/acp-18-11363-2018, 2018.
Louvaris, E. E., Florou, K., Karnezi, E., Papanastasiou, D. K., Gkatzelis,
G. I., and Pandis, S. N.: Volatility of source apportioned wintertime
organic aerosol in the city of Athens, Atmos. Environ., 158,
138–147, https://doi.org/10.1016/j.atmosenv.2017.03.042, 2017.
Milsom, A., Squires, A. M., Woden, B., Terrill, N. J., Ward, A. D., and Pfrang,
C.: The persistence of a proxy for cooking emissions in megacities: a
kinetic study of the ozonolysis of self-assembled films by simultaneous
small and wide angle X-ray scattering (SAXS/WAXS) and Raman microscopy,
Faraday Discuss., 226, 364–381, https://doi.org/10.1039/D0FD00088D,
2020.
Ministry of Law and Justice, Government of India: The Commission for Air
Quality Management in National Capital Region and Adjoining Areas Ordinance,
http://www.indiaenvironmentportal.org.in/content/469022/the-commission-for-air-quality-management-in-national-capital-region-and-adjoining-areas-ordinance-2020/
(last access: 20 March 2022), 2020.
Mishra, R. K., Pandey, A., Pandey, G., and Kumar, A.: The effect of odd-even
driving scheme on PM2.5 and PM1.0 emission, Transp. Res. D. Transp., 67, 541–552,
https://doi.org/10.1016/j.trd.2019.01.005, 2019.
Misra, P., Imasu, R., Hayashida, S., Arbain, A. A., Avtar, R., and Takeuchi,
W.: Mapping brick kilns to support environmental impact studies around Delhi
using Sentinel-2, ISPRS Int. J. Geo-Info., 9, 544,
https://www.mdpi.com/2220-9964/9/9/544 (last access: 20 March 2022), 2020.
Mitra, A. and Sharma, C.: Indian aerosols: Present status, Chemosphere, 49,
1175–1190, https://doi.org/10.1016/S0045-6535(02)00247-3, 2002.
Mohr, C., Huffman, J. A., Cubison, M. J., Aiken, A. C., Docherty, K. S.,
Kimmel, J. R., Ulbrich, I. M., Hannigan, M., and Jimenez, J. L.:
Characterization of primary organic aerosol emissions from meat cooking,
trash burning, and motor vehicles with high-resolution aerosol mass
spectrometry and comparison with ambient and chamber observations,
Environ. Sci. Technol., 43, 2443–2449,
https://doi.org/10.1021/es8011518, 2009.
Mönkkönen, P., Uma, R., Srinivasan, D., Koponen, I., Lehtinen, K.,
Hämeri, K., Suresh, R., Sharma, V., and Kulmala, M.: Relationship and
variations of aerosol number and PM10 mass concentrations in a highly
polluted urban environment – New Delhi, India, Atmos. Environ., 38,
425–433, https://doi.org/10.1016/j.atmosenv.2003.09071, 2004.
Mönkkönen, P., Koponen, I. K., Lehtinen, K. E. J., Hämeri, K., Uma, R., and Kulmala, M.: Measurements in a highly polluted Asian mega city: observations of aerosol number size distribution, modal parameters and nucleation events, Atmos. Chem. Phys., 5, 57–66, https://doi.org/10.5194/acp-5-57-2005, 2005a.
Mönkkönen, P., Pai, P., Maynard, A., E J Lehtinen, K., Hämeri,
K., Rechkemmer, P., Ramachandran, G., Prasad, B., and Kulmala, M.: Fine
particle number and mass concentration measurements in urban Indian
households, Sci. Total Environ., 347, 131–147,
https://doi.org/10.1016/j.scitotenv.2004.12.023, 2005b.
Nagar, P. K., Singh, D., Sharma, M., Kumar, A., Aneja, V. P., George, M. P.,
Agarwal, N., and Shukla, S. P.: Characterization of PM2.5 in Delhi:
role and impact of secondary aerosol, burning of biomass, and municipal
solid waste and crustal matter, Environ. Sci. Pollut. Res., 24, 25179–25189, https://doi.org/10.1007/s11356-017-0171-3,
2017.
Nagpure, A. S., Ramaswami, A., and Russell, A.: Characterizing the spatial
and temporal patterns of open burning of municipal solid waste (MSW) in
Indian cities, Environ. Sci. Technol., 49, 12911–12912,
https://doi.org/10.1021/acs.est.5b03243, 2015.
Nair, D. J., Gilles, F., Chand, S., Saxena, N., and Dixit, V.:
Characterizing multicity urban traffic conditions using crowdsourced data,
PLOS ONE, 14, e0212845,
https://dx.plos.org/10.1371/journal.pone.0212845, 2019.
NASA Jet Propulsion Laboratory: Getting to the heart of the (particulate)
matter – climate change: vital signs of the planet,
https://climate.nasa.gov/news/3027/getting-to-the-heart-of-the-particulate-matter/ (last access: 20 March 2022), 2020.
NERC-MRC-MoES-DBT: Atmospheric Pollution and Human Health in an Indian
megacity, https://www.urbanair-india.org/ (last access: 20 March 2022), 2021.
Ng, N. L., Canagaratna, M. R., Zhang, Q., Jimenez, J. L., Tian, J., Ulbrich, I. M., Kroll, J. H., Docherty, K. S., Chhabra, P. S., Bahreini, R., Murphy, S. M., Seinfeld, J. H., Hildebrandt, L., Donahue, N. M., DeCarlo, P. F., Lanz, V. A., Prévôt, A. S. H., Dinar, E., Rudich, Y., and Worsnop, D. R.: Organic aerosol components observed in Northern Hemispheric datasets from Aerosol Mass Spectrometry, Atmos. Chem. Phys., 10, 4625–4641, https://doi.org/10.5194/acp-10-4625-2010, 2010.
Ng, N. L., Canagaratna, M. R., Jimenez, J. L., Zhang, Q., Ulbrich, I. M.,
and Worsnop, D. R.: Realtime methods for estimating organic component mass
concentrations from aerosol mass spectrometer data, Environ. Sci. Technol., 45, 910–916,
https://pubs.acs.org/doi/abs/10.1021/es102951k, 2011a.
Ng, N. L., Herndon, S. C., Trimborn, A., Canagaratna, M. R., Croteau, P. L.,
Onasch, T. B., Sueper, D., Worsnop, D. R., Zhang, Q., Sun, Y. L., and Jayne,
J. T.: An Aerosol Chemical Speciation Monitor (ACSM) for routine monitoring
of the composition and mass concentrations of ambient aerosol, Aerosol
Sci. Technol., 45, 780–794, 2011b.
Norris, G., Duvall, R., Brown, S., and Bai, S.: EPA Positive Matrix
Factorization 5.0 fundamentals and user guide,
https://www.epa.gov/air-research/epa-positive-matrix-factorization-50-fundamentals-and-user-guide,
(last access: 20 March 2022), 2014.
Paatero, P.: The Multilinear Engine – a table-driven, least squares program
for solving multilinear problems, including the n-way parallel factor
analysis model, J. Comput. Graph. Stat., 8,
854–888, 1999.
Paatero, P. and Tapper, U.: Positive matrix factorization: a non-negative
factor model with optimal utilization of error estimates of data values,
Environmetrics, 5, 111–126, https://doi.org/10.1002/env.3170050203,
1994.
Paatero, P., Hopke, P. K., Song, X. H., and Ramadan, Z.: Understanding and
controlling rotations in factor analytic models, Chemomet. Int. Labor. Syst., 60, 253–264,
https://doi.org/10.1016/S0169-7439(01)00200-3, 2002.
Paciga, A., Karnezi, E., Kostenidou, E., Hildebrandt, L., Psichoudaki, M., Engelhart, G. J., Lee, B.-H., Crippa, M., Prévôt, A. S. H., Baltensperger, U., and Pandis, S. N.: Volatility of organic aerosol and its components in the megacity of Paris, Atmos. Chem. Phys., 16, 2013–2023, https://doi.org/10.5194/acp-16-2013-2016, 2016.
Pant, P. and Harrison, R. M.: Critical review of receptor modelling for
particulate matter: A case study of India, Atmos. Environ., 49,
1–12, https://doi.org/10.1016/j.atmosenv.2011.11.060, 2012.
Pant, P., Shukla, A., Kohl, S. D., Chow, J. C., Watson, J. G., and Harrison,
R. M.: Characterization of ambient PM2.5 at a pollution hotspot in New
Delhi, India and inference of sources, Atmos. Environ., 109,
178–189, https://doi.org/10.1016/j.atmosenv.2015.02.074, 2015.
Pant, P., Guttikunda, S. K., and Peltier, R. E.: Exposure to particulate
matter in India: A synthesis of findings and future directions,
Environ. Res., 147, 480–496,
https://doi.org/10.1016/j.envres.2016.03.011, 2016.
Pant, P., Habib, G., Marshall, J. D., and Peltier, R. E.: PM2.5
exposure in highly polluted cities: a case study from New Delhi, India,
Environ. Res., 156, 167–174,
https://doi.org/10.1016/j.envres.2017.03.024, 2017.
Park, M. B., Lee, T. J., Lee, E. S., and Kim, D. S.: Enhancing source
identification of hourly PM2.5 data in Seoul based on a dataset
segmentation scheme by positive matrix factorization (PMF), Atmos. Pollut. Res., 10, 1042–1059,
https://doi.org/10.1016/j.apr.2019.01.013, 2019.
Patel, K., Bhandari, S., Gani, S., Campmier, M. J., Kumar, P., Habib, G.,
Apte, J., and Ruiz, L. H.: Sources and dynamics of submicron aerosol during
the Autumn onset of the air pollution season in Delhi, India, ACS Earth Space Chem., 5, 118–128, 2021a.
Patel, K., Campmier, M.J., Bhandari, S., Baig, N., Gani, S., Habib, G.,
Apte, J.S. and Hildebrandt Ruiz, L., 2021. Persistence of Primary and
Secondary Pollutants in Delhi: Concentrations and Composition from 2017
through the COVID Pandemic, Environ. Sci. Technol. Lett.,
8, 492–497, https://doi.org/10.1021/acs.estlett.1c00211, 2021b.
Pauraite, J., Pivoras, A., Plauškaite, K., Bycenkiene, S., Mordas, G.,
Augustaitis, A., Marozas, V., Mozgeris, G., Baumgarten, M., Matyssek, R.,
and Ulevicius, V.: Characterization of aerosol mass spectra responses to
temperature over a forest site in Lithuania, J. Aerosol Sci.,
133, 56–65, https://doi.org/10.1016/j.jaerosci.2019.03.010, 2019.
Platt, S. M.: Primary emissions and secondary organic aerosol formation from
road vehicles, Doctoral thesis, ETH Zurich,
https://doi.org/10.3929/ethz-a-010476708, 2014.
Platt, S. M., El Haddad, I., Zardini, A. A., Clairotte, M., Astorga, C., Wolf, R., Slowik, J. G., Temime-Roussel, B., Marchand, N., Ježek, I., Drinovec, L., Močnik, G., Möhler, O., Richter, R., Barmet, P., Bianchi, F., Baltensperger, U., and Prévôt, A. S. H.: Secondary organic aerosol formation from gasoline vehicle emissions in a new mobile environmental reaction chamber, Atmos. Chem. Phys., 13, 9141–9158, https://doi.org/10.5194/acp-13-9141-2013, 2013.
Pope, C. A. and Dockery, D. W.: Health effects of fine particulate air
pollution: Lines that connect, J. Air Waste Manage.
Assoc., 56, 709–742,
https://doi.org/10.1080/10473289.2006.10464485, 2006.
R Core Team: R: A language and environment for statistical computing, R
Foundation for Statistical Computing, Vienna, Austria,
https://www.R-project.org/ (last access: 20 March 2022), 2019.
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., and Allan, J. D.: PM1 composition and source apportionment at two sites in Delhi, India, across multiple seasons, Atmos. Chem. Phys., 21, 11655–11667, https://doi.org/10.5194/acp-21-11655-2021, 2021.
Robinson, E. S., Gu, P., Ye, Q., Li, H. Z., Shah, R. U., Apte, J. S.,
Robinson, A. L., and Presto, A. A.: Restaurant impacts on outdoor air
quality: elevated organic aerosol mass from restaurant cooking with
neighborhood-scale plume extents, Environ. Sci. Technol., 52,
9285–9294, https://pubs.acs.org/doi/abs/10.1021/acs.est.8b02654, 2018.
Rooney, B., Zhao, R., Wang, Y., Bates, K. H., Pillarisetti, A., Sharma, S., Kundu, S., Bond, T. C., Lam, N. L., Ozaltun, B., Xu, L., Goel, V., Fleming, L. T., Weltman, R., Meinardi, S., Blake, D. R., Nizkorodov, S. A., Edwards, R. D., Yadav, A., Arora, N. K., Smith, K. R., and Seinfeld, J. H.: Impacts of household sources on air pollution at village and regional scales in India, Atmos. Chem. Phys., 19, 7719–7742, https://doi.org/10.5194/acp-19-7719-2019, 2019.
Sage, A. M., Weitkamp, E. A., Robinson, A. L., and Donahue, N. M.: Evolving mass spectra of the oxidized component of organic aerosol: results from aerosol mass spectrometer analyses of aged diesel emissions, Atmos. Chem. Phys., 8, 1139–1152, https://doi.org/10.5194/acp-8-1139-2008, 2008.
Sawlani, R., Agnihotri, R., and Sharma, C.: Chemical and isotopic
characteristics of PM2.5 over New Delhi from September 2014 to May
2015: evidences for synergy between air-pollution and meteorological
changes, Sci. Total Environ., 763, 142966, https://doi.org/10.1016/j.scitotenv.2020.142966, 2020.
Schneider, J., Weimer, S., Drewnick, F., Borrmann, S., Helas, G., Gwaze, P.,
Schmid, O., Andreae, M. O., and Kirchner, U.: Mass spectrometric analysis
and aerodynamic properties of various types of combustion-related aerosol
particles, Int. J. Mass Spectrom., 258, 37–49,
https://doi.org/10.1016/j.ijms.2006.07.008, 2006.
Sharma, D. N., Sawant, A. A., Uma, R., and Cocker, D. R.: Preliminary
chemical characterization of particle-phase organic compounds in New Delhi,
India, Atmos. Environ., 37, 4317–4323,
https://doi.org/10.1016/S1352-2310(03)00563-6, 2003.
Sharma, S. and Mandal, T.: Chemical composition of fine mode particulate
matter (PM2.5) in an urban area of Delhi, India and its source
apportionment, Urban Clim., 21, 106–122,
https://doi.org/10.1016/j.uclim.2017.05.009, 2017.
Shivani, Gadi, R., Sharma, S. K., and Mandal, T. K.: Seasonal variation,
source apportionment and source attributed health risk of fine carbonaceous
aerosols over National Capital Region, India, Chemosphere, 237, 124500,
https://doi.org/10.1016/j.chemosphere.2019.124500, 2019.
Shukla, A. K., Lalchandani, V., Bhattu, D., Dave, J. S., Rai, P., Thamban,
N. M., Mishra, S., Gaddamidi, S., Tripathi, N., Vats, P., and Rastogi, N.:
Real-time quantification and source apportionment of fine particulate matter
including organics and elements in Delhi during summertime, Atmos. Environ., 261, 118598, https://doi.org/10.1016/j.atmosenv.2021.118598, 2021.
Srivastava, A., Gupta, S., and K. Jain, V.: Source apportionment of total
suspended particulate matter in coarse and fine size ranges over Delhi,
Aerosol Air Qual. Res., 8, 188–200,
https://doi.org/10.4209/aaqr.2007.09.0040, 2008.
Srivastava, D., Favez, O., Petit, J., Zhang, Y., Sofowotee, U., Hopke, P.,
Bonnaire, N., Perraudin, E., Gros, V., and Villenave, Albinet, A.:
Speciation of organic fractions does matter for aerosol source
apportionment. Part 3: Combining off-line and on-line measurements, Sci. Total Environ., 690, 944–955,
https://doi.org/10.1016/j.scitotenv.2019.06.378, 2019.
Sun, Y., Du, W., Fu, P., Wang, Q., Li, J., Ge, X., Zhang, Q., Zhu, C., Ren, L., Xu, W., Zhao, J., Han, T., Worsnop, D. R., and Wang, Z.: Primary and secondary aerosols in Beijing in winter: sources, variations and processes, Atmos. Chem. Phys., 16, 8309–8329, https://doi.org/10.5194/acp-16-8309-2016, 2016.
The Indian Express: Delhi: trucks can enter city after 11 pm,
https://indianexpress.com/article/cities/delhi/delhi-trucks-can-enter-city-after-11-pm-4559487/ (last access: 20 March 2022), 2017.
Tiwari, S., Srivastava, A. K., Bisht, D. S., Bano, T., Singh, S., Behura,
S., Srivastava, M. K., Chate, D. M., and Padmanabhamurty, B.: Black carbon
and chemical characteristics of PM10 and PM2.5 at an urban site of
North India, J. Atmos. Chem., 62, 193–209,
https://doi.org/10.1007/s10874-010-9148-z, 2009.
Tobler, A., Bhattu, D., Canonaco, F., Lalchandani, V., Shukla, A., Thamban,
N. M., Mishra, S., Srivastava, A. K., Bisht, D. S., Tiwari, S., Singh, S.,
Mocnik, G., Baltensperger, U., Tripathi, S. N., Slowik, J. G., and
Prévôt, A. S.: Chemical characterization of PM2.5 and source
apportionment of organic aerosol in New Delhi, India, Sci. Total
Environ., 745, 140924,
https://doi.org/10.1016/j.scitotenv.2020.140924, 2020.
Ulbrich, I. M., Canagaratna, M. R., Zhang, Q., Worsnop, D. R., and Jimenez, J. L.: Interpretation of organic components from Positive Matrix Factorization of aerosol mass spectrometric data, Atmos. Chem. Phys., 9, 2891–2918, https://doi.org/10.5194/acp-9-2891-2009, 2009.
United Nations: World urbanization prospects,
https://population.un.org/wup/ (last access: 20 March 2022), 2018.
Upadhyay, A., Dey, S., Chowdhury, S., Kumar, R., and Goyal, P.: Tradeoffs
between air pollution mitigation and meteorological response in India,
Sci. Rep., 10, 1–10,
https://doi.org/10.1038/s41598-020-71607-5, 2020.
Venkataraman, C., Bhushan, M., Dey, S., Ganguly, D., Gupta, T., Habib, G.,
Kesarkar, A., Phuleria, H., and Raman, R. S.: Indian network project on
carbonaceous aerosol emissions, source apportionment and climate impacts
(COALESCE), B. Am. Meteorol. Soc., 101,
1052–1068, https://doi.org/10.1175/BAMS-D-19-0030.1, 2020.
Venturini, E., Vassura, I., Raffo, S., Ferroni, L., Bernardi, E., and
Passarini, F.: Source apportionment and location by selective wind sampling
and Positive Matrix Factorization, Environ. Sci. Pollut. Res., 21, 11634–11648, 2014.
Wang, X., Cotter, E., Iyer, K. N., Fang, J., Williams, B. J., and Biswas,
P.: Relationship between pyrolysis products and organic aerosols formed
during coal combustion, P. Combust. Inst., 35,
2347–2354, https://doi.org/10.1016/j.proci.2014.07.073, 2015.
Weimer, S., Alfarra, M. R., Schreiber, D., Mohr, M., Prévôt, A. S.,
and Baltensperger, U.: Organic aerosol mass spectral signatures from
wood-burning emissions: Influence of burning conditions and type, J. Geophys. Res.-Atmos., 113, D10304,
https://doi.org/10.1029/2007JD009309, 2008.
Werden, B., Giordano, M., Mahata, K., Goetz, J. D., Katz, E., Bhave, P.,
Praveen, P. S., Yokelson, R. J., Stone, E. A., Panday, A. K., and DeCarlo,
P.: Source apportionment of regional aerosols and spatial variability from
the 2nd Nepal Ambient Measurement and Source Testing Experiment [NAMaSTE]-2
in the Kathmandu valley, Nepal, AGU Fall Meeting,
https://agu.confex.com/agu/fm20/meetingapp.cgi/Paper/747517, last access: 15 December 2020.
World Health Organization: AAP air quality database,
http://www.who.int/phe/health_topics/outdoorair/databases/cities/en/ (last access: 20 December 2020), 2018.
Xu, W., He, Y., Qiu, Y., Chen, C., Xie, C., Lei, L., Li, Z., Sun, J., Li, J., Fu, P., Wang, Z., Worsnop, D. R., and Sun, Y.: Mass spectral characterization of primary emissions and implications in source apportionment of organic aerosol, Atmos. Meas. Tech., 13, 3205–3219, https://doi.org/10.5194/amt-13-3205-2020, 2020.
Yadav, S., Tandon, A., and Attri, A. K.: Characterization of aerosol
associated non-polar organic compounds using TD-GC-MS: a four year study
from Delhi, India, J. Hazard. Mat., 252, 29–44,
https://doi.org/10.1016/j.jhazmat.2013.02.024, 2013.
Zhang, K. and Batterman, S.: Air pollution and health risks due to vehicle
traffic, Sci. Tot. Environ., 450, 307–316,
https://doi.org/10.1016/j.scitotenv.2013.01.074, 2013.
Zhang, Q., Alfarra, M. R., Worsnop, D. R., Allan, J. D., Coe, H.,
Canagaratna, M. R., and Jimenez, J. L.: Deconvolution and quantification of
hydrocarbon-like and oxygenated organic aerosols based on aerosol mass
spectrometry, Environ. Sci. Technol., 39, 4938–4952,
https://doi.org/10.1021/es048568l, 2005.
Zhang, Q., Jimenez, J. L., Canagaratna, M. R., Ulbrich, I. M., Ng, N. L.,
Worsnop, D. R., and Sun, Y.: Understanding atmospheric organic aerosols via
factor analysis of aerosol mass spectrometry: a review, Anal.
Bioanal. Chem., 401, 3045–3067, 2011.
Zhang, Y., Williams, B. J., Goldstein, A. H., Docherty, K. S., and Jimenez, J. L.: A technique for rapid source apportionment applied to ambient organic aerosol measurements from a thermal desorption aerosol gas chromatograph (TAG), Atmos. Meas. Tech., 9, 5637–5653, https://doi.org/10.5194/amt-9-5637-2016, 2016.
Zhang, Y., Peräkylä, O., Yan, C., Heikkinen, L., Äijälä, M., Daellenbach, K. R., Zha, Q., Riva, M., Garmash, O., Junninen, H., Paatero, P., Worsnop, D., and Ehn, M.: A novel approach for simple statistical analysis of high-resolution mass spectra, Atmos. Meas. Tech., 12, 3761–3776, https://doi.org/10.5194/amt-12-3761-2019, 2019.
Zhang, Z., Zhu, W., Hu, M., Wang, H., Chen, Z., Shen, R., Yu, Y., Tan, R.,
and Guo, S.: Secondary organic aerosol from typical Chinese domestic cooking
emissions, Environ. Sci. Technol. Lett., 8, 24–31, 2021.
Zheng, Y., Cheng, X., Liao, K., Li, Y., Li, Y. J., Huang, R.-J., Hu, W., Liu, Y., Zhu, T., Chen, S., Zeng, L., Worsnop, D. R., and Chen, Q.: Characterization of anthropogenic organic aerosols by TOF-ACSM with the new capture vaporizer, Atmos. Meas. Tech., 13, 2457–2472, https://doi.org/10.5194/amt-13-2457-2020, 2020.
Zhu, Q., Huang, X.-F., Cao, L.-M., Wei, L.-T., Zhang, B., He, L.-Y., Elser, M., Canonaco, F., Slowik, J. G., Bozzetti, C., El-Haddad, I., and Prévôt, A. S. H.: Improved source apportionment of organic aerosols in complex urban air pollution using the multilinear engine (ME-2), Atmos. Meas. Tech., 11, 1049–1060, https://doi.org/10.5194/amt-11-1049-2018, 2018.
Short summary
Here we determine the sources of primary organic aerosol in Delhi, India, in two different seasons. In winter, the main sources are traffic and biomass burning; in the summer, the main sources are traffic and cooking. We obtain this result by conducting source apportionment resolved by time of day, using data from an aerosol chemical speciation monitor. Results from this work can be used to better design policies that target sources of organic aerosol.
Here we determine the sources of primary organic aerosol in Delhi, India, in two different...
Altmetrics
Final-revised paper
Preprint