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Abstract Title: Global Estimate of Mercury Use in Artisanal Gold Mining: Value, Quality of Field-level Data, Remaining Gaps
Presenter Name: Kevin Telmer
Company/Institution: Artisanal Gold Council
Session: Mercury in Artisanal Gold Mining
Day and Session: Wednesday 27th July - SessionTwo
Start Time: 11:30 UTC
Co-Authors: Kevin Telmer

Abstract Information :

Artisanal and small-scale gold mining (ASGM) provides livelihoods for upwards of 10 million people directly and supports around 100 million people in total through its secondary economy in at least 81 countries. This army of gold miners produces approximately 20% of the world?s gold annually, making it a significant economic contributor for the rural poor. ASGM is also the world?s largest source of anthropogenic mercury emissions to the atmosphere. To inform the Minamata Convention on Mercury for it to prioritize actions and expenditures, efforts to estimate mercury emitted by the ASGM sector have been made. However, obtaining accurate and field representative estimates of mercury use that can be scaled up to regional and global numbers has remained a significant challenge due to difficulties in executing standardized data collection methods in the field. This has led to a perpetual paucity of quality data. Quantifying illegal mercury and gold trade in the informal artisanal mining communities remains a barrier for formal instruments like the Minamata Convention to overcome. For these reasons, estimates of annual ASGM mercury emissions to the atmosphere, which have apparently risen from 350 tonnes in 1997 to 675 -1000 tonnes in 2018 remain poorly constrained. The increase can be attributed to either sector growth or improved assessment techniques but the separation of these two has not been adequately investigated, despite the essential importance of doing so. We propose a classification of emission estimates based on the methodology used to make estimates in ASGM annually at a national scale, and verify the accuracy of the estimates based on factors such as gold grade, gold extraction practices used (e.g. whole ore amalgamation or concentrate amalgamation) and annual gold production, and critique the dataset generated in order to create a new estimate that recognizes the fundamental gaps in data collection

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