Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China
Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China
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DOI：
10.5194/acp-11-2295-2011
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发表时间：
2011-01-01
影响因子：
6.3
通讯作者：
Hao, J.
中科院分区：
文献类型：
--
作者：
Zhao, Y.;Nielsen, C. P.;Hao, J.
首次采用蒙特卡罗模拟方法，对中国人为SO2、NOx和不同粒径颗粒物（PM）排放量的自下而上的国家级清单的不确定性进行了全面量化。该清单由七个主要部门组成：燃煤电力，水泥，钢铁，其他工业（锅炉燃烧），其他工业（非燃烧过程），交通运输和住宅。对于与排放系数或活动水平计算有关的每一个参数，以概率分布表示的不确定性，或者使用国内实地测试的结果进行统计拟合，或者在缺乏这些结果的情况下，根据外国或其他国内数据进行估计。不确定性（即，2005年中国SO2、NOx、总PM、PM10、PM2.5、黑碳（BC）和有机碳（OC）的排放量估计为-14%相似于13%，-13%相似于37%，-11%相似于38%，-14%相似于45%，-17%相似于54%，-25%相似于136%，-40%相似于121%。活动水平的变化（例如。例如，在一个实施例中，能源消费或工业生产）不是排放不确定性的主要来源。由于源类型的分类范围窄，样本量大，数据质量相对较高，估计燃煤发电部门除BC和OC外，所有物种的排放不确定性最小。水泥生产和锅炉燃烧产生的NOx和PM的排放因子具有较大的不确定性，而生物质燃烧是BC和OC的最大排放源，其排放因子的概率分布是基于国内有限的现场实测数据拟合的，因此在解释这些排放不确定性时应特别谨慎。虽然蒙特卡罗模拟产生缩小估计的不确定性相比，以前的自下而上的排放研究，结果并不总是与卫星观测得出的一致。因此，这些结果代表了一个渐进的研究进展;虽然分析为研究中国和全球大气传输和化学的研究人员提供了当前的不确定性估计，但它也确定了数据收集和分析方面的具体需求，以改进这些需求。加强对所包括的物种和其他密切相关物种的排放量的量化--特别是主要由相同的过程产生的、因此受到许多相同参数不确定性影响的CO2--不仅对科学至关重要，而且对在地方、区域和全球范围内制定消除重大大气环境危害的政策也至关重要。
The uncertainties of a national, bottom-up inventory of Chinese emissions of anthropogenic SO2, NOx, and particulate matter (PM) of different size classes and carbonaceous species are comprehensively quantified, for the first time, using Monte Carlo simulation. The inventory is structured by seven dominant sectors: coal-fired electric power, cement, iron and steel, other industry (boiler combustion), other industry (non-combustion processes), transportation, and residential. For each parameter related to emission factors or activity-level calculations, the uncertainties, represented as probability distributions, are either statistically fitted using results of domestic field tests or, when these are lacking, estimated based on foreign or other domestic data. The uncertainties (i.e., 95% confidence intervals around the central estimates) of Chinese emissions of SO2, NOx, total PM, PM10, PM2.5, black carbon (BC), and organic carbon (OC) in 2005 are estimated to be -14%similar to 13%, -13%similar to 37%, -11%similar to 38%, -14%similar to 45%, -17%similar to 54%, -25%similar to 136%, and -40%similar to 121%, respectively. Variations at activity levels (e. g., energy consumption or industrial production) are not the main source of emission uncertainties. Due to narrow classification of source types, large sample sizes, and relatively high data quality, the coal-fired power sector is estimated to have the smallest emission uncertainties for all species except BC and OC. Due to poorer source classifications and a wider range of estimated emission factors, considerable uncertainties of NOx and PM emissions from cement production and boiler combustion in other industries are found. The probability distributions of emission factors for biomass burning, the largest source of BC and OC, are fitted based on very limited domestic field measurements, and special caution should thus be taken interpreting these emission uncertainties. Although Monte Carlo simulation yields narrowed estimates of uncertainties compared to previous bottom-up emission studies, the results are not always consistent with those derived from satellite observations. The results thus represent an incremental research advance; while the analysis provides current estimates of uncertainty to researchers investigating Chinese and global atmospheric transport and chemistry, it also identifies specific needs in data collection and analysis to improve on them. Strengthened quantification of emissions of the included species and other, closely associated ones - notably CO2, generated largely by the same processes and thus subject to many of the same parameter uncertainties - is essential not only for science but for the design of policies to redress critical atmospheric environmental hazards at local, regional, and global scales.