M
Michael D. Gerst
Researcher at University of Maryland, College Park
Publications - 28
Citations - 723
Michael D. Gerst is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Climate change & Scenario analysis. The author has an hindex of 10, co-authored 25 publications receiving 636 citations. Previous affiliations of Michael D. Gerst include Yale University & Dartmouth College.
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In-use stocks of metals: status and implications.
TL;DR: Comparison of the per capita stocks in more-developed countries with those in less- Developed countries suggests that if the total world population were to enjoy the same per capita metal stock levels as the more- developed countries, using a similar suite of technologies, the amount of global in-use metal stocks required would be 3-9 times those existing at present.
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Agent-based modeling of climate policy
Michael D. Gerst,P. Wang,Andrea Roventini,Giorgio Fagiolo,Giovanni Dosi,Richard B. Howarth,Mark E. Borsuk +6 more
TL;DR: This paper introduces a multi-level model framework, called ENGAGE, that relaxes some common modeling assumptions by adopting an agent-based approach of international climate policy and plans to use the ENGAGE model to simulate the two-way dynamic feedback between international agreements and domestic policy outcomes.
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Linking Material Flow Analysis and Resource Policy via Future Scenarios of In-Use Stock: An Example for Copper
TL;DR: Under a scenario of no material substitution or technological change in copper products, global in-use stock in 2100 will be about as large as currently known copper resources, however, current scrap recycling trends and exploration will alleviate absolute supply pressure but not environmental impacts from decreasing copper are grades.
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Revisiting the Cumulative Grade-Tonnage Relationship for Major Copper Ore Types
TL;DR: In this paper, a grade-tonnage density function model was developed for four major copper ore types and the model was used to create cumulative grade-level curves, representing 1,778 million metric tons (Mt) of mineable copper, which were validated against 70 years of historical world average ore grade using production input by ore type from 1800 to 2000.
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Discovering plausible energy and economic futures under global change using multidimensional scenario discovery
TL;DR: A scenario discovery method is described that is multidimensional in the outcome space, thus precluding the need for users to agree on a single performance threshold or set of tradeoff weights, and applied to the results of ENGAGE, an agent-based model of economic growth, energy technology, and carbon emissions.