Errors in top-down estimates of emissions using a known source

Abstract

Air pollutant emissions estimates by top-down methods are subject to a variety of errors and uncertainties. This work uses a known source, a coal-fired power plant, to explore those errors. The known emissions amount and location remove two major types of error, facilitating understanding of other types. Biases and random errors are distinguished. A Lagrangian dispersion model (HYSPLIT) is run forward in time from the known source, and virtual measurements of the resulting tracer plume are compared to actual measurements from research aircraft. Four flights in different years are used to illustrate a variety of conditions. The measurements are analyzed by a mass-balance method, and the assumptions of that method are discussed. Some of those assumptions can be relaxed in analysis of the modeled plume, allowing testing of their validity. Meteorological fields to drive HYSPLIT are provided by the European Centre for Medium-Range Weather Forecasts Fifth Reanalysis (ERA5). A unique feature of this work is the use of an ensemble of meteorological fields intrinsic to ERA5. This analysis supports reasonably large (30 %–40 %) uncertainties on top-down analyses.