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Title: A Framework for Quantitative Assessment of Impacts Related to Energy and Mineral Resource Development

Abstract

Natural resource planning at all scales demands methods for assessing the impacts of resource development and use, and in particular it requires standardized methods that yield robust and unbiased results. Building from existing probabilistic methods for assessing the volumes of energy and mineral resources, we provide an algorithm for consistent, reproducible, quantitative assessment of resource development impacts. The approach combines probabilistic input data with Monte Carlo statistical methods to determine probabilistic outputs that convey the uncertainties inherent in the data. For example, one can utilize our algorithm to combine data from a natural gas resource assessment with maps of sage grouse leks and pinon-juniper woodlands in the same area to estimate possible future habitat impacts due to possible future gas development. As another example: one could combine geochemical data and maps of lynx habitat with data from a mineral deposit assessment in the same area to determine possible future mining impacts on water resources and lynx habitat. The approach can be applied to a broad range of positive and negative resource development impacts, such as water quantity or quality, economic benefits, or air quality, limited only by the availability of necessary input data and quantified relationships among geologic resources, developmentmore » alternatives, and impacts. In conclusion, the framework enables quantitative evaluation of the trade-offs inherent in resource management decision-making, including cumulative impacts, to address societal concerns and policy aspects of resource development.« less

Authors:
 [1];  [1];  [2];  [1];  [3];  [4];  [5];  [6];  [1];  [7];  [8];  [1];  [9];  [10];  [1];  [11];  [9];  [12];  [1];  [13] more »;  [14];  [1] « less
  1. U.S. Geological Survey, Denver, CO (United States)
  2. U.S. Geological Survey, Seattle, WA (United States)
  3. U.S. Geological Survey, Denver, CO (United States); U.S. Dept. of Energy, Washington, D.C. (United States)
  4. Univ. of Miami, Miami, FL (United States)
  5. Univ. of California, Berkeley, CA (United States)
  6. U.S. Geological Survey, Menlo Park, CA (United States)
  7. Stanford Univ., Stanford, CA (United States)
  8. Arizona State Univ., Tempe, AZ (United States)
  9. U.S. Geological Survey, Reston, VA (United States)
  10. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  11. U.S. Fish and Wildlife Service, Denver, CO (United States)
  12. Southwest Statistical Consulting, LLC, Cortez, CO (United States)
  13. U.S. Dept. of Interior, Washington, D.C. (United States)
  14. Bureau of Land Management, Denver, CO (United States); National Park Service, Wellfleet, MA (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1390035
Report Number(s):
NREL/JA-6A20-70102
Journal ID: ISSN 1520-7439
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Natural Resources Research
Additional Journal Information:
Journal Volume: 23; Journal Issue: 1; Journal ID: ISSN 1520-7439
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
29 ENERGY PLANNING, POLICY, AND ECONOMY; energy resources; mineral resources; impact assessment; integrated assessment; environmental

Citation Formats

Haines, Seth S., Diffendorfer, Jay E., Balistrieri, Laurie, Berger, Byron, Cook, Troy, DeAngelis, Don, Doremus, Holly, Gautier, Donald L., Gallegos, Tanya, Gerritsen, Margot, Graffy, Elisabeth, Hawkins, Sarah, Johnson, Kathleen M., Macknick, Jordan E., McMahon, Peter, Modde, Tim, Pierce, Brenda, Schuenemeyer, John H., Semmens, Darius, Simon, Benjamin, Taylor, Jason, and Walton-Day, Katie. A Framework for Quantitative Assessment of Impacts Related to Energy and Mineral Resource Development. United States: N. p., 2013. Web. doi:10.1007/s11053-013-9208-6.
Haines, Seth S., Diffendorfer, Jay E., Balistrieri, Laurie, Berger, Byron, Cook, Troy, DeAngelis, Don, Doremus, Holly, Gautier, Donald L., Gallegos, Tanya, Gerritsen, Margot, Graffy, Elisabeth, Hawkins, Sarah, Johnson, Kathleen M., Macknick, Jordan E., McMahon, Peter, Modde, Tim, Pierce, Brenda, Schuenemeyer, John H., Semmens, Darius, Simon, Benjamin, Taylor, Jason, & Walton-Day, Katie. A Framework for Quantitative Assessment of Impacts Related to Energy and Mineral Resource Development. United States. doi:10.1007/s11053-013-9208-6.
Haines, Seth S., Diffendorfer, Jay E., Balistrieri, Laurie, Berger, Byron, Cook, Troy, DeAngelis, Don, Doremus, Holly, Gautier, Donald L., Gallegos, Tanya, Gerritsen, Margot, Graffy, Elisabeth, Hawkins, Sarah, Johnson, Kathleen M., Macknick, Jordan E., McMahon, Peter, Modde, Tim, Pierce, Brenda, Schuenemeyer, John H., Semmens, Darius, Simon, Benjamin, Taylor, Jason, and Walton-Day, Katie. Wed . "A Framework for Quantitative Assessment of Impacts Related to Energy and Mineral Resource Development". United States. doi:10.1007/s11053-013-9208-6. https://www.osti.gov/servlets/purl/1390035.
@article{osti_1390035,
title = {A Framework for Quantitative Assessment of Impacts Related to Energy and Mineral Resource Development},
author = {Haines, Seth S. and Diffendorfer, Jay E. and Balistrieri, Laurie and Berger, Byron and Cook, Troy and DeAngelis, Don and Doremus, Holly and Gautier, Donald L. and Gallegos, Tanya and Gerritsen, Margot and Graffy, Elisabeth and Hawkins, Sarah and Johnson, Kathleen M. and Macknick, Jordan E. and McMahon, Peter and Modde, Tim and Pierce, Brenda and Schuenemeyer, John H. and Semmens, Darius and Simon, Benjamin and Taylor, Jason and Walton-Day, Katie},
abstractNote = {Natural resource planning at all scales demands methods for assessing the impacts of resource development and use, and in particular it requires standardized methods that yield robust and unbiased results. Building from existing probabilistic methods for assessing the volumes of energy and mineral resources, we provide an algorithm for consistent, reproducible, quantitative assessment of resource development impacts. The approach combines probabilistic input data with Monte Carlo statistical methods to determine probabilistic outputs that convey the uncertainties inherent in the data. For example, one can utilize our algorithm to combine data from a natural gas resource assessment with maps of sage grouse leks and pinon-juniper woodlands in the same area to estimate possible future habitat impacts due to possible future gas development. As another example: one could combine geochemical data and maps of lynx habitat with data from a mineral deposit assessment in the same area to determine possible future mining impacts on water resources and lynx habitat. The approach can be applied to a broad range of positive and negative resource development impacts, such as water quantity or quality, economic benefits, or air quality, limited only by the availability of necessary input data and quantified relationships among geologic resources, development alternatives, and impacts. In conclusion, the framework enables quantitative evaluation of the trade-offs inherent in resource management decision-making, including cumulative impacts, to address societal concerns and policy aspects of resource development.},
doi = {10.1007/s11053-013-9208-6},
journal = {Natural Resources Research},
number = 1,
volume = 23,
place = {United States},
year = {2013},
month = {5}
}

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