Chemical composition and source-apportionment of sub-micron particles during wintertime over Northern India: New insights on influence of fog-processing
2018
Rajput, Prashant | Singh, Dharmendra Kumar | Singh, Amit Kumar | Gupta, Tarun
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 SO₄²⁻, 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 SO₄²⁻, 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%).
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