Quantitative Uncertainty Analysis in Air Pollutant Emission Inventories: Methodology and Case Study

Air pollutant emission inventories are often uncertain due to unavoidable measurement errors,random errors,data gap,non-representativeness of sample data,and other factors.Uncertainty in emission inventories refers to the lack of knowledge of the true emissions.On the basis of introducing the current methodological framework for quantifying uncertainty in emission inventories,it is demonstrated how uncertainty in emission inventories is quantified by using a real-world case study with continuous emission monitoring NO_x data of power plants.The results show that the NO_x emission inventory from power plants in this case study has about(±15%) uncertainty though the inventories are generally believed to be less uncertain.Quantification of uncertainty in emission inventories helps decision-makers determine the likelihood of complying with emission reduction objectives,and more properly make air pollution control strategies.Identification of key sources of uncertainty helps guide future emission inventory improvement and further data collection.Also,suggestions are made regarding how to initiate uncertainty analysis in emission inventory development in China.