Reducing Mercury Emission Uncertainty from Artisanal and Small-Scale Gold Mining Using Bootstrap Confidence Intervals: An Assessment of Emission Reduction Scenarios

Abstract

Atmospheric mercury emission scenarios from artisanal and small-scale gold mining for 56 tropical and subtropical countries have been elaborated and assessed for their comparative significance. A multi-step quantitative method that yields narrow and robust confidence intervals for mercury emission estimates was employed. Firstly, data on gold production for different years, the ratio of mercury used in the different amalgamation processes, and ancillary input parameters were retrieved from official and unofficial sources, and their potential for emission reduction examined. Then, a Monte Carlo method to combine the data and generate mercury emission samples was used. These samples were processed by a non-parametric re-sampling method (bootstrap) to obtain robust estimates of mercury emissions, and their 95% confidence intervals, both for the current state and for the emission scenarios designed in this study. The artisanal and small-scale gold mining mercury emission (to the atmosphere) estimates agree with those reported in the Global Mercury Assessment 2018; however, the overall uncertainty is reduced from roughly 100% in the Global Mercury Assessment (779.59 tons/y; uncertainty range: 361.07–1197.97) to 27% (1091.93 tons/y; confidence interval at 95% level of confidence: 964.54–1219.77) in this study. This is a substantial outcome since the narrowing of the confidence intervals permits a more meaningful evaluation of the different emission scenarios investigated, which otherwise, given the broad uncertainty of other estimates, would have led only to vague conclusions in a study of this nature.