Chemical composition and source-apportionment of sub-micron particles during wintertime over Northern India: New insights on influence of fog-processing

Prashant Rajput; Dharmendra Kumar Singh; Amit Kumar Singh; Tarun Gupta

doi:10.1016/j.envpol.2017.10.036

Chemical composition and source-apportionment of sub-micron particles during wintertime over Northern India: New insights on influence of fog-processing

Environ Pollut. 2018 Feb:233:81-91. doi: 10.1016/j.envpol.2017.10.036. Epub 2017 Oct 19.

Authors

Prashant Rajput¹, Dharmendra Kumar Singh², Amit Kumar Singh³, Tarun Gupta⁴

Affiliations

¹ Department of Civil Engineering and APTL at Center for Environmental Science and Engineering (CESE), Indian Institute of Technology Kanpur, Kanpur, 208 016, India; Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, University of Surrey, Guildford, GU2 7XH, UK.
² Department of Civil Engineering and APTL at Center for Environmental Science and Engineering (CESE), Indian Institute of Technology Kanpur, Kanpur, 208 016, India; NUS Environmental Research Institute (NERI), National University of Singapore, #02-01, T-Lab Building 5A Engineering Drive 1, 117411, Singapore.
³ Department of Civil Engineering and APTL at Center for Environmental Science and Engineering (CESE), Indian Institute of Technology Kanpur, Kanpur, 208 016, India.
⁴ Department of Civil Engineering and APTL at Center for Environmental Science and Engineering (CESE), Indian Institute of Technology Kanpur, Kanpur, 208 016, India. Electronic address: tarun@iitk.ac.in.

PMID: 29055838
DOI: 10.1016/j.envpol.2017.10.036

Abstract

A comprehensive study was carried out from central part of Indo-Gangetic Plain (IGP; at Kanpur) to understand abundance, temporal variability, processes (secondary formation and fog-processing) and source-apportionment of PM₁-bound species (PM₁: particulate matter of aerodynamic diameter ≤ 1.0 μm) during wintertime. A total of 50 PM₁ samples were collected of which 33 samples represent submicron aerosol characteristics under non-foggy condition whereas 17 samples represent characteristics under thick foggy condition. PM₁ mass concentration during non-foggy episodes varied from 24-393 (Avg.: 247) μg m^-3, whereas during foggy condition it ranged from 42-243 (Avg.: 107) μg m^-3. With respect to non-foggy condition, the foggy conditions were associated with higher contribution of PM₁-bound organic matter (OM, by 23%). However, lower fractional contribution of SO₄^2-, NO₃^- and NH₄⁺ during foggy conditions is attributable to wet-scavenging owing to their high affinity to water. Significant influence of fog-processing on organic aerosols composition is also reflected by co-enhancement in OC/EC and WSOC/OC ratio during foggy condition. A reduction by 5% in mineral dust fraction under foggy condition is associated with a parallel decrease in PM₁ mass concentration. However, mass fraction of elemental carbon (EC) looks quite similar (≈3% of PM₁) but the mass absorption efficiency (MAE) of EC is higher by 30% during foggy episodes. Thus, it is evident from this study that fog-processing leads to quite significant enhancement in OM (23%) contribution (and MAE of EC) with nearly equal and parallel decrease in SO₄^2-, NO₃^- and NH₄⁺ and mineral dust fractions (totaling to 24%). Characteristic features of mineral dust remain similar under foggy and non-foggy conditions; inferred from similar ratios of Fe/Al (≈0.3), Ca/Al (0.35) and Mg/Al (0.22). Positive matrix factorization (PMF) resolves seven sources: biomass burning (19.4%), coal combustion (1.1%), vehicular emission (3%), industrial activities (6.1%), leather tanneries (4%), secondary transformations (46.2%) and mineral dust (20.2%).

Keywords: Absorption property of EC; Composition; Fog processing; Indo-Gangetic Plain; PM(1); PMF.

MeSH terms

Aerosols / analysis
Air Pollutants / analysis*
Biomass
Carbon / analysis
Dust
Environmental Monitoring*
India
Particulate Matter / analysis*
Vehicle Emissions
Weather

Substances

Aerosols
Air Pollutants
Dust
Particulate Matter
Vehicle Emissions
Carbon