An inverse Gaussian plume approach for estimating atmospheric pollutant emissions from multiple point sources

TL;DR

This paper introduces an inverse Gaussian plume method to estimate atmospheric pollutant emissions from multiple sources using ground deposition data, validated with real industrial data, offering a robust estimation approach.

Contribution

It presents a novel inverse modeling approach based on Gaussian plume solutions for estimating emissions from multiple point sources using ground deposition measurements.

Findings

The method accurately estimates total emissions in a real industrial setting.

The approach is robust against measurement and meteorological variability.

It effectively handles multiple sources in complex environments.

Abstract

A method is developed for estimating the emission rates of contaminants into the atmosphere from multiple point sources using measurements of particulate material deposited at ground level. The approach is based on a Gaussian plume type solution for the advection-diffusion equation with ground-level deposition and given emission sources. This solution to the forward problem is incorporated into an inverse algorithm for estimating the emission rates by means of a linear least squares approach. The results are validated using measured deposition and meteorological data from a large lead-zinc smelting operation in Trail, British Columbia. The algorithm is demonstrated to be robust and capable of generating reasonably accurate estimates of total contaminant emissions over the relatively short distances of interest in this study.