Assessing the role of top-down techniques for improving regional estimates of artisanal and small-scale gold mining mercury emissions

ASGM is the world’s largest source of anthropogenic Hg emissions and is common in Latin America, Sub-Saharan Africa, South Asia, and East Asia. However, the amount of mercury emitted from ASGM and contributing to global mercury emissions is subject to substantial uncertainty. Bottom-up studies have quantified sources of Hg, including ASGM, using data on underlying activities to estimate regional and global totals. In contrast, top-down studies have used atmospheric concentration measurements and models to constrain Hg emissions. However, no top-down estimates have yet been calculated for ASGM emissions. With GEOS-Chem’s global-scale chemical transport model for Hg, we investigate whether and how ASGM-related Hg emissions can be quantified from existing regional measurement sites for gaseous elemental mercury (GEM). By combining our top-down method with existing bottom-up data, we improve estimates of Hg emissions from ASGM activities, using Peru and the Madre de Dios region of South America as case studies. We find that quantitative constraints on ASGM emissions are better provided by information on the shape of the probability distribution of GEM concentrations, such as the interquartile range and the 95% range, suggesting possible design guidelines for monitoring networks. The model-based analysis offers insights into improving regional estimates of ASGM emissions.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Institute for Data, Systems, and Society

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2022

Author dc:creator

• Dlamini, Thandolwethu

Advisor dc:contributor.advisor

• Selin, Noelle

Statement dc:rights

• In Copyright - Educational Use Permitted
• Copyright MIT

Licence dc:rights.uri

• http://rightsstatements.org/page/InC-EDU/1.0/

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/147481

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/147481