Weighted Sensitivity Analysis of Emissions Inventory Data

Abstract

A technique is developed to compute precision requirements for component parts of an emissions inventory to ensure (at a given confidence level) an overall acceptable precision in the estimate of total emissions. Since the emissions inventory is a basic requirement of air quality control implementation plans and provides a valuable management tool for planning air pollution control activities, it isi appropriate to state in quantitative terms the confidence that can be associated with each inventory. The approach reported here uses weighted sensitivity analysis methods to distribute both percentage and physical errors in source class emissions according to their contribution to the total emissions, and utilizes Chebyshev’s inequality to establish confidence levels for total emissions. The analysis has been extended to cover the case where one or more of the error components in a given inventory source class can be fixed by the analyst. The utility of the technique is manifold and several practical applications are reported. In particular, it serves to establish percentage error requirements for source categories to satisfy given error bounds for the overall emissions inventory at a given level of statistical confidence. The weighted sensitivity analysis technique possesses a high degree of generality, being applicable to compute component error requirements for any kind of data inventory which exhibits a hierarchical (tree-like) structure, as exemplified by NEDS Emissions Summary Reports. This work should be of interest to air pollution control planners at all levels of government and to anyone responsible for the air pollution portion of environmental impact statements.