The U.S. Geological Survey Mineral Resources Program Five-Year Plan, 2006-2010
Research and Assessments
Long-term goal 2: Ensure availability of up-to-date geoenvironmental assessments of priority Federal lands
- Develop protocols for geoenvironmental models and complete geoenvironmental models for priority deposit types (approximately $1 million in FY 2006, decreasing to $750,000 thereafter)
- Complete prototype geoenvironmental assessment of priority lands identified by Federal land managers (approximately $1 million/year)
- Conduct research targeted at reducing uncertainty in geoenvironmental models and assessments (approximately $2.7 million in FY 2006, decreasing to $2 million by FY 2010)
In their short report titled Mineral Resources and Sustainability, the National Research Council identified seven key challenges for earth scientists. One of those challenges is To use basic science to improve environmental management and restoration ecology associated with mining and mineral processing (National Research Council, 1996b). The discussion specifically identifies environmental ore-deposit models as the tool required to meet this challenge. USGS scientists have begun the process of developing models of this type.
Remediation priorities for abandoned mine sites in the Animas Basin, Colorado were based on empirical studies of characteristics such as dump size and leach chemistry (among others). New research on geoenvironmental models will provide a framework for this kind of analysis, as well as permitting prediction of future states of mined and unmined lands (modified from Fey and others, 2000).
During the life of this plan, MRP will develop priority geoenvironmental models, test them in a prototype assessment, and conduct research necessary to reduce uncertainties arising from lack of understanding of the processes that occur when mineral deposits are exposed at the earth's surface, whether by natural erosion or by mining.
Models describing the environmental geochemistry of unmined and mined mineral deposits and mine wastes provide a powerful tool to anticipate environmental challenges with unmined deposits and to characterize environmental challenges associated with abandoned mines. Such insights are invaluable to land management agencies with responsibility for permitting new mines, reclamation of abandoned mine lands, and contributing to the maintenance of sustainable mineral supplies at minimal costs to the environment. At present, geoenvironmental models are largely empirical and descriptive. The lack of quantification and the limited number of completed case studies inhibit their predictive capability.
The potential environmental challenges associated with new mine development and the environmental impacts of abandoned mines result from the complex interplay of a variety of chemical and physical processes, many of which are mediated by micro-organisms. To plan for improved mitigation of future mines and to remedy existing threats to human health, ecosystems, and water resources, a thorough understanding of the underlying processes and their interactions is required. Increased understanding of necessary processes and links between them can best be addressed by focused studies involving investigations into the release, transport, and fate of metals and related compounds, by the use of multidisciplinary approaches, and by the use of emerging techniques to trace the behavior of metals and related compounds throughout the cycle of release, transport, and fate. Within the USGS, several programs in the Water and Biologic Resources Disciplines have parallel interests, including Toxic Substances Hydrology, Biological Contaminants, the National Water-Quality Assessment, and the National Research Program. None of these programs focuses directly on metals and associated compounds related to mineral resources, but each has goals, skills, and capabilities that complement MRP's work. Therefore, the results of this research will contribute to activities within the Water Resources and Biologic Resources disciplines. Some projects will be accomplished through collaboration with researchers working with related programs elsewhere in USGS' Geology, Water Resources, and Biologic Resources Disciplines.
Environmental challenges associated with as-yet undeveloped deposits and abandoned mines begin with the complex oxidative weathering of sulfide minerals, which releases metals and acid to the environment. The current understanding of these processes is dominated by laboratory studies of selected minerals conducted under highly controlled conditions, or by case studies of complex, individual field sites, for which a variety of processes may be occurring simultaneously. Increased understanding of these processes, particularly the ability to predict their significance under conditions outside the laboratory or closely monitored field sites, will require integrated approaches. New research will target additional mineral systems or their components, in the laboratory under a greater variety of conditions, additional field systems of selected ore-deposit types in selected climatic settings, and the development of methods to relate quantitatively laboratory studies to field settings.
The greatest limitation of an empirical approach as a predictive tool is the lack of data for all relevant deposit types in all of the relevant climatic or hydrologic settings. To overcome this obstacle, the primary climatic factors controlling these environmental signatures, such as temperature and amount of precipitation, must be identified and their roles must be more completely understood to enable predictions beyond the confines of the empirical database of selected deposit types and climatic settings. The database currently under construction for the geoenvironmental models effort should incorporate quantitative climatologic and hydrologic data for specific sites included in the database to facilitate the identification of the links between hydrologic and climatic setting to environmental response. This activity is essential for building quantitative predictive models from the current set of empirical descriptive models.