Exposure to ambient black carbon derived from a unique inventory and high-resolution model

Abstract : Black carbon (BC) is increasingly recognized as a significant air pollutant with harmful effects on human health, either in its own right or as a carrier of other chemicals. The adverse impact is of particular concern in those developing regions with high emissions and a growing population density. The results of recent studies indicate that BC emissions could be underestimated by a factor of 2–3 and this is particularly true for the hot-spot Asian region. Here we present a unique inventory at 10-km resolution based on a recently published global fuel consumption data product and updated emission factor measurements. The unique inventory is coupled to an Asia-nested (∼50 km) atmospheric model and used to calculate the global population exposure to BC with fully quantified uncertainty. Evaluating the modeled surface BC concentrations against observations reveals great improvement. The bias is reduced from −88% to −35% in Asia when the unique inventory and higher-resolution model replace a previous inventory combined with a coarse-resolution model. The bias can be further reduced to −12% by downscaling to 10 km using emission as a proxy. Our estimated global population-weighted BC exposure concentration constrained by observations is 2.14 μg⋅m−3; 130% higher than that obtained using less detailed inventories and low-resolution models.
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Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2014, 111 (7), pp.2459-2463. 〈10.1073/pnas.1318763111〉
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Soumis le : lundi 17 novembre 2014 - 16:42:29
Dernière modification le : mercredi 31 janvier 2018 - 12:14:57

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R. Wang, S. Tao, Y. Balkanski, P. Ciais, Olivier Boucher, et al.. Exposure to ambient black carbon derived from a unique inventory and high-resolution model. Proceedings of the National Academy of Sciences of the United States of America , National Academy of Sciences, 2014, 111 (7), pp.2459-2463. 〈10.1073/pnas.1318763111〉. 〈hal-01083676〉

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