Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, and Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China.
Proc Natl Acad Sci U S A. 2014 Feb 18;111(7):2459-63. doi: 10.1073/pnas.1318763111. Epub 2014 Jan 27.
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.
黑碳(BC)作为一种重要的空气污染物,其对人类健康的有害影响日益受到关注,无论是其本身的影响,还是作为其他化学物质的载体。在排放量大、人口密度不断增长的发展中地区,这种不利影响尤其值得关注。最近的研究结果表明,BC 的排放量可能被低估了 2-3 倍,特别是在热点亚洲地区。在这里,我们根据最近发表的全球燃料消耗数据产品和更新的排放因子测量结果,提供了一个独特的 10 公里分辨率清单。该独特清单与亚洲嵌套(~50 公里)大气模型相结合,用于计算具有完全量化不确定性的全球人口对 BC 的暴露量。评估模型表面 BC 浓度与观测结果的对比表明,这方面有了很大的改进。当独特清单和高分辨率模型替代以前的清单与粗分辨率模型结合使用时,亚洲的偏差从-88%减少到-35%。通过使用排放作为代理将分辨率降低到 10 公里,可以将偏差进一步减少到-12%。我们根据观测结果估计的全球人口加权 BC 暴露浓度为 2.14μg⋅m(-3);比使用较不详细的清单和低分辨率模型获得的结果高 130%。