ausblenden:
Schlagwörter:
Air pollution, Particulate matter, Source apportionment, National clean air programme
Zusammenfassung:
Particulate matter (PM) pollution is a major challenge in India. The Ministry of Environment, Forest and Climate Change, Government of India has launched the National Clean Air Programme for monitoring, assessment and control of air pollution. The action plan envisions reduction in air pollution on the basis of source apportionment studies in all the non-attainment cities. Source apportionment (SA) using receptor modelling is important for understanding the PM sources, pollution outflow and larger scale regional impacts. This review presents current status of offline and online measurement based SA studies focusing on PM10 and finer fractions of PM, where receptor modelling on chemical species has been used to apportion contributions from different sources. While a good database is available on chemical characterization of ambient aerosols, only 49 offline and 16 online SA studies could qualify this criterion. Out of all offline studies reviewed here, only 41% studies measured all chemical signatures. State of the SA studies over different geographical divisions [Indo-Gangetic plain (IGP), Delhi NCR, western, eastern and central India] over India reveal that more than 50% of the studies are focused on the Delhi National Capital Region (NCR) and IGP. The most studied size fractions are PM10 (34%) and PM2.5 (28%) followed by 11% studies on PM1 and only 5% on size segregated SA of aerosols. The meta-analysis of available data on percentage contribution of major sources viz. secondary sources, biomass burning, combustion, vehicular emissions, industrial sources from these locations present a composite picture of major sources of ambient aerosols in India. This work also presents detailed discussion on different steps of SA viz. sampling design, analytical techniques and receptor modelling. The evolution from offline filter-based techniques to real time SA techniques has been discussed and recommendations for robust SA studies have been proposed.
