Quantifying the uncertainties of China's emission inventory for industrial sources: From national to provincial and city scales

A comprehensive uncertainty analysis was conducted on emission inventories for industrial sources at national (China), provincial (Jiangsu), and city (Nanjing) scales for 2012. Based on various methods and data sources, Monte-Carlo simulation was applied at sector level for national inventory, and at plant level (whenever possible) for provincial and city inventories. The uncertainties of national inventory were estimated at -17-37% (expressed as 95% confidence intervals, CIs), -21-35%, -19-34%, -29-40%, -22 -47%, -21-54%, -33-84%, and -32-92% for SO2, NOx, CO, TSP (total suspended particles), PM10, PM25, black carbon (BC), and organic carbon (OC) emissions respectively for the whole country. At provincial and city levels, the uncertainties of corresponding pollutant emissions were estimated at -15-18%, -18 -33%, -16-37%, -20-30%, -23-45%, -26-50%, -33-79%, and -33-71% for Jiangsu, and -17 -22%, -10-33%, -23-75%, -19-36%, -23-41%, -28-48%, -45-82%, and -34-96% for Nanjing, respectively. Emission factors (or associated parameters) were identified as the biggest contributors to the uncertainties of emissions for most source categories except iron & steel production in the national inventory. Compared to national one, uncertainties of total emissions in the provincial and city-scale inventories were not significantly reduced for most species with an exception of SO2. For power and other industrial boilers, the uncertainties were reduced, and the plant-specific parameters played more important roles to the uncertainties. Much larger PM10 and PM2.5 emissions for Jiangsu were estimated in this provincial inventory than other studies, implying the big discrepancies on data sources of emission factors and activity data between local and national inventories. Although the uncertainty analysis of bottom-up emission inventories at national and local scales partly supported the top-down estimates using observation and/or chemistry transport models, detailed investigations and field measurements were recommended for further improving the emission estimates and reducing the uncertainty of inventories at local and regional scales, for both industrial and other sectors. (C) 2017 Elsevier Ltd. All rights reserved.