Abstract

This study presents a simulation-based inversion model to estimate the quantitative contribution of Pb from different source materials to aerosols using a set of environmental proxies (206Pb/207Pb and 208Pb/206Pb). The proposed model uses location-specific dataset (206Pb/207Pbaerosol and 208Pb/206Pbaerosol) and a model parameter (a priori) that includes Pb isotopic composition of source materials and their fractional contribution to aerosol. Variability of Pb sources often causes a large spread in a priori values, resulting in erroneous interpretation. The proposed inversion model provides a means to obtain error-optimized and statistically best-fit values for the model parameter (a posteriori) thereby improving our understanding of source apportionment. As an example, the inverse model was appliedin eastern India, where it estimated that Pb-ores, coal, and unleaded petroleum produced up to 46%, 39%, and 36% of atmospheric Pb, respectively. Counter to general belief, the model revealed that a greater proportion of petroleum-derived Pb in the atmosphere was supplied by bituminous road (mechanical abrasion of road material) rather than direct usage of petrol and diesel as fuel. Increasing vehicle density and their activities on Indian roads (from 22 to 44 vehicles km−1 between the years 2005–2017) intensified Pb emissions from road materials to the atmosphere. The inversion model additionally exposed the enormity of Pb contamination in the Indian atmosphere, where the sources such as vehicular emissions, road dust, and industrial emissions (petroleum and Pb-ores) contributed up to 65% of atmospheric Pb. Together, model-derived results (ca. 90% anthropogenic Pb in aerosol), increased use of Pb-emitting raw materials and road vehicles, and the temporal distribution of Pb in aerosols confirm unrestrained Pb emissions continue in India despite the phasing-out of leaded petroleum.

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