Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China

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%~13%, −13%~37%, −11%~38%, −14%~45%, −17%~54%, −25%~136%, and −40%~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