Sources and atmospheric dynamics of organic aerosol in New Delhi, India: Insights from receptor modeling

Bhandari, Sahil; Gani, Shahzad; Patel, Kanan; Wang, Dongyu; Soni, Prashant; Arub, Zainab; Habib, Gazala; Apte, Joshua S.; Ruiz, Lea Hildebrandt

doi:10.5194/acp-2019-403

Cited by 17 publications

(68 citation statements)

References 44 publications

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“…Ammonium and organic aerosol underwent a ~2-3 fold increase, whereas 225 sulphate is the only species whose absolute concentrations did not increase during the post-monsoon. This has also been noted in previous measurements taken in Delhi using an ACSM where sulphate was on average 10 μg m -3 across spring, summer and the monsoon period (Gani et al, 2019).…”

Section: Inorganic and Organic Pm Concentrationssupporting

confidence: 85%

“…This time a 9-factor solution was chosen (Section S3) and was developed partly to provide an analysis product that would be comparable with the earlier Aerosol Chemical Speciation Monitor (ACSM) PMF results for Delhi of Bhandari et al (2019). Additionally, it provides information on the association between the organic factors and 210 the ions that are normally associated with inorganic compounds.…”

Section: Source Apportionment 175mentioning

confidence: 99%

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Seasonal analysis of submicron aerosol in Old Delhi using high resolution aerosol mass spectrometry: Chemical characterisation, source apportionment and new marker identification

Cash¹,

Langford²,

Marco³

et al. 2020

Preprint

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Abstract. 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 ~ 600 µg m−3 during the most polluted period, the post-monsoon, where PM1 increased by 178 % over the pre-monsoon period. Using positive matrix factorisation (PMF) to perform source apportionment analysis, two burning-related factors 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 (PAH) 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 gasoline. 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. 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 (488 %) 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.

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Section: Inorganic and Organic Pm Concentrationssupporting

confidence: 85%

Section: Source Apportionment 175mentioning

confidence: 99%

Seasonal analysis of submicron aerosol in Old Delhi using high resolution aerosol mass spectrometry: Chemical characterisation, source apportionment and new marker identification

Cash¹,

Langford²,

Marco³

et al. 2020

Preprint

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“…This high relative contribution of OA has been observed in previous studies in India (Bhandari et al, 2019;Singla et al, 2019).…”

Section: Aerosol Concentrations and Compositionsupporting

confidence: 82%

“…In India, source apportionment studies using PMF have identified different OA sources, for instance, seasonal analysis in 2016-2017 in Mahabaleshwar, a high altitude site, identified hydrocarbon-like OA (HOA), biomass burning OA (BBOA) and two different types of OOA as the OA sources (Mukherjee et al, 2018;Singla et al, 2019). Similar OA factors were identified in a recent study performed in New Delhi, with the main OA sources being HOA, BBOA, and OOA from a 1 year analysis (Bhandari et al, 2019).…”

Section: Introductionmentioning

confidence: 62%

PM1 composition and source apportionment at two sites in Delhi, India across multiple seasons

Reyes-Villegas

Panda

Darbyshire

et al. 2020

Preprint

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Abstract. 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 result of anthropogenic activities. Organic aerosols (OA) 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 processes in urban environments is still limited. This is important particularly in India, as Delhi is a massive, inhomogeneous conurbation, which we would expect that the apportionment and concentrations will vary depending on where in Delhi the measurements/source apportionment is performed, indicating the need of multi-site 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, sulphate, chloride and organic aerosols) of four aerosol mass spectrometers were analysed. Collocated measurements of VOC, black carbon, NOx and CO were performed. Positive matrix factorization (PMF) analysis was performed to separate the organic fraction, identifying a number of conventional factors: hydrocarbon-like OA (HOA) related to traffic emissions, biomass burning OA (BBOA), cooking OA (COA) and secondary OA (SOA). A composition-based estimate of PM1 is defined by combining BC and NR-PM1 (C-PM1 = BC + NR-PM1). No significant difference was observed on C-PM1 concentrations between sites; OD (142 ± 117 µg m−3) compared to ND (123 ± 71 µg m−3), 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 emissions control offers the greatest opportunity. PMF-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.

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“…Since coagulation only affects particle number concentrations, and not mass concentrations, PM 0.56 increased into the night, possibly owing to a combination of increased sources (e.g., nocturnal truck traffic, biomass burning for cooking and heat) and decreasing ventilation (Guttikunda and Gurjar, 2012;Guttikunda and Calori, 2013;Bhandari et al, 2019). The PN concentrations dropped after the evening traffic rush hours and only increased again during the morning traffic rush hours.…”

Section: Coagulation Scavengingmentioning

confidence: 99%

Particle number concentrations and size distribution in a polluted megacity: The Delhi Aerosol Supersite study

Gani¹,

Bhandari²,

Patel³

et al. 2020

Preprint

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Abstract. The Indian national capital, Delhi, routinely experiences some of the world's highest urban particulate matter concentrations. While fine particulate matter (PM2.5) mass concentrations in Delhi are at least an order of magnitude higher than in many western cities, the particle number (PN) concentrations are not similarly elevated. Here we report on 1.25 years of highly time resolved particle size distributions (PSD) data in the size range of 12&#8211;560&#8201;nm. We observed that the large number of accumulation mode particles &#8211; that constitute most of the PM2.5 mass &#8211; also contributed substantially to the PN concentrations. The ultrafine particles (UFP, Dp&#8201;<&#8201;100&#8201;nm) fraction of PN was higher during the traffic rush hours and for daytimes of warmer seasons&#8212;consistent with traffic and nucleation events being major sources of urban UFP. UFP concentrations were found to be relatively lower during periods with some of the highest mass concentrations. Calculations based on measured PSD and coagulation theory suggest UFP concentrations are suppressed by a rapid coagulation sink during polluted periods when large concentrations of particles in the accumulation mode result in high surface area concentrations. A smaller accumulation mode for warmer months results in increased UFP fraction, likely owing to a comparatively smaller coagulation sink. We also see evidence suggestive of nucleation which may also contribute to the increased UFP proportion during the warmer seasons. Even though coagulation does not affect mass concentrations, it can significantly govern PN levels with important health and policy implications. Implications of a strong accumulation mode coagulation sink for future air quality control efforts in Delhi are that a reduction in mass concentration, especially in winter, may not produce proportional reduction in PN concentrations. Strategies that only target accumulation mode particles (which constitute much of the fine PM2.5 mass) may even lead to an increase in the UFP concentrations as the coagulation sink decreases.

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Sources and atmospheric dynamics of organic aerosol in New Delhi, India: Insights from receptor modeling

Cited by 17 publications

References 44 publications

Seasonal analysis of submicron aerosol in Old Delhi using high resolution aerosol mass spectrometry: Chemical characterisation, source apportionment and new marker identification

Seasonal analysis of submicron aerosol in Old Delhi using high resolution aerosol mass spectrometry: Chemical characterisation, source apportionment and new marker identification

PM<sub>1</sub> composition and source apportionment at two sites in Delhi, India across multiple seasons

Particle number concentrations and size distribution in a polluted megacity: The Delhi Aerosol Supersite study

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Sources and atmospheric dynamics of organic aerosol in New Delhi, India: Insights from receptor modeling

Cited by 17 publications

References 44 publications

Seasonal analysis of submicron aerosol in Old Delhi using high resolution aerosol mass spectrometry: Chemical characterisation, source apportionment and new marker identification

Seasonal analysis of submicron aerosol in Old Delhi using high resolution aerosol mass spectrometry: Chemical characterisation, source apportionment and new marker identification

PM&lt;sub&gt;1&lt;/sub&gt; composition and source apportionment at two sites in Delhi, India across multiple seasons

Particle number concentrations and size distribution in a polluted megacity: The Delhi Aerosol Supersite study

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PM<sub>1</sub> composition and source apportionment at two sites in Delhi, India across multiple seasons