Assessing Sites Contaminated with Unexploded Ordnance: Statistical Modeling of Ordnance Spatial Distribution
More than 40 000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much as $140 billion. The amount of contaminated acreage and total costs are likely to increase as the U.S. Department of Defense (DOD) follows t...
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Published in: | Environmental science & technology Vol. 40; no. 3; pp. 931 - 938 |
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01-02-2006
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Abstract | More than 40 000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much as $140 billion. The amount of contaminated acreage and total costs are likely to increase as the U.S. Department of Defense (DOD) follows through on recently announced plans to close an additional 22 domestic military bases. The U.S. Environmental Protection Agency (EPA) and DOD disagree on how these sites should be characterized to assess their risks and plan for cleanup. As a result, much potentially valuable land remains idle while remediation decisions are pending. One of the sources of disagreement is how the locations of UXO should be characterized, given that the exact spatial distribution of UXO is unknown in advance of cleanup. In this paper, we propose and test a new model to represent the spatial distribution of UXO. Unlike existing DOD models, the new model accounts for the tendency of UXO to cluster, presumably around targets at which soldiers aimed during training. We fit the cluster model to geographic data on UXO locations at two former military installations and show that it describes key characteristics of the data more accurately than the existing DOD model. We discuss how the choice of a UXO spatial distribution model could affect important decisions about cleaning up and reusing UXO-affected property. |
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AbstractList | More than 40 000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much as $140 billion. The amount of contaminated acreage and total costs are likely to increase as the U.S. Department of Defense (DOD) follows through on recently announced plans to close an additional 22 domestic military bases. The U.S. Environmental Protection Agency (EPA) and DOD disagree on how these sites should be characterized to assess their risks and plan for cleanup. As a result, much potentially valuable land remains idle while remediation decisions are pending. One of the sources of disagreement is how the locations of UXO should be characterized, given that the exact spatial distribution of UXO is unknown in advance of cleanup. In this paper, we propose and test a new model to represent the spatial distribution of UXO. Unlike existing DOD models, the new model accounts for the tendency of UXO to cluster, presumably around targets at which soldiers aimed during training. We fit the cluster model to geographic data on UXO locations at two former military installations and show that it describes key characteristics of the data more accurately than the existing DOD model. We discuss how the choice of a UXO spatial distribution model could affect important decisions about cleaning up and reusing UXO-affected property. Using statistical modeling, sites contaminated with unexploded ordnance were explored. Experiments were conducted at two former military training ranges namely, Fort Ord, California, and Tobyhanna State Park, Pennsylvania. In each case, goal was to determine whether the CSR model or the cluster model better characterized the spatial distribution of UXO. It was found that most UXO contamination was the result of the failure of munnitions to detonate after they were fired. The Department of Defence (DOD) and Environmental Protection Agency (EPA) were unable to agree on how to address the uncertainties associated with the distribution of UXO across the site, the associated risk and different cleanup strategies. It is concluded that the factors other than spatial distribution namely, the depth at which the ordnance would be found, the probability that the civilians would encounter UXO, and the probability that the UXO would detonate, must be considered. More than 40 000 km super(2) of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much as $140 billion. The amount of contaminated acreage and total costs are likely to increase as the U.S. Department of Defense (DOD) follows through on recently announced plans to close an additional 22 domestic military bases. The U.S. Environmental Protection Agency (EPA) and DOD disagree on how these sites should be characterized to assess their risks and plan for cleanup. As a result, much potentially valuable land remains idle while remediation decisions are pending. One of the sources of disagreement is how the locations of UXO should be characterized, given that the exact spatial distribution of UXO is unknown in advance of cleanup. In this paper, we propose and test a new model to represent the spatial distribution of UXO. Unlike existing DOD models, the new model accounts for the tendency of UXO to cluster, presumably around targets at which soldiers aimed during training. We fit the cluster model to geographic data on UXO locations at two former military installations and show that it describes key characteristics of the data more accurately than the existing DOD model. We discuss how the choice of a UXO spatial distribution model could affect important decisions about cleaning up and reusing UXO-affected property. More than 40 000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much as $140 billion. The amount of contaminated acreage and total costs are likely to increase as the U.S. Department of Defense (DOD) follows through on recently announced plans to close an additional 22 domestic military bases. The U.S. Environmental Protection Agency (EPA) and DOD disagree on how these sites should be characterized to assess their risks and plan for cleanup. As a result, much potentially valuable land remains idle while remediation decisions are pending. One of the sources of disagreement is how the locations of UXO should be characterized, given that the exact spatial distribution of UXO is unknown in advance of cleanup. In this paper, we propose and test a new model to represent the spatial distribution of UXO. Unlike existing DOD models, the new model accounts for the tendency of UXO to cluster, presumably around targets at which soldiers aimed during training. We fit the cluster model to geographic data on UXO locations at two former military installations and show that it describes key characteristics of the data more accurately than the existing DOD model. We discuss how the choice of a UXO spatial distribution model could affect important decisions about cleaning up and reusing UXO-affected property. [PUBLICATION ABSTRACT] More than 40,000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much as 140 billion dollars. The amount of contaminated acreage and total costs are likely to increase as the U.S. Department of Defense (DOD) follows through on recently announced plans to close an additional 22 domestic military bases. The U.S. Environmental Protection Agency(EPA) and DOD disagree on how these sites should be characterized to assess their risks and plan for cleanup. As a result, much potentially valuable land remains idle while remediation decisions are pending. One of the sources of disagreement is how the locations of UXO should be characterized, given that the exact spatial distribution of UXO is unknown in advance of cleanup. In this paper, we propose and test a new model to represent the spatial distribution of UXO. Unlike existing DOD models, the new model accounts for the tendency of UXO to cluster, presumably around targets at which soldiers aimed during training. We fit the cluster model to geographic data on UXO locations at two former military installations and show that it describes key characteristics of the data more accuratelythan the existing DOD model. We discuss how the choice of a UXO spatial distribution model could affect important decisions about cleaning up and reusing UXO-affected property. |
Author | Macdonald, Jacqueline A Small, Mitchell J |
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References_xml | – volume-title: SERDP Project UX-1200: Bayesian Approach to UXO Site Characterization with Incorporation of Geophysical Information year: 2003 ident: es051168tb00026/es051168tb00026_1 contributor: fullname: McKenna S. A. – ident: es051168tb00001/es051168tb00001_1 – volume-title: Handbook on the Manage ment of Ordnance and Explosives at Closed, Transferred, and Transferring Ranges year: 2001 ident: es051168tb00009/es051168tb00009_1 contributor: fullname: Environmental Protection Agency – volume-title: Fact Sheet year: 2003 ident: es051168tb00027/es051168tb00027_1 contributor: fullname: Army Corps of Engineers. – volume-title: Spatial Cluster Modeling year: 2002 ident: es051168tb00022/es051168tb00022_1 contributor: fullname: Moller J. – volume-title: Statistical Analysis of Spatial Point Patterns year: 2003 ident: es051168tb00018/es051168tb00018_1 contributor: fullname: Diggle P. J. – ident: es051168tb00014/es051168tb00014_1 – ident: es051168tb00005/es051168tb00005_1 – volume: 1958 start-page: 20 ident: es051168tb00020/es051168tb00020_1 publication-title: J. R. Stat. Soc. contributor: fullname: Neyman J. – volume-title: Statistics for Spatial Data year: 1993 ident: es051168tb00017/es051168tb00017_1 doi: 10.1002/9781119115151 contributor: fullname: Cressie N. A. C. – volume-title: Development of a Database for Ordnance-Related Civilian Accidents: Final Report year: 2003 ident: es051168tb00007/es051168tb00007_1 contributor: fullname: Army Corps of Engineers. – volume-title: Progress in Metal-Detection Techniques for Detecting and Identifying Landmines and Unexploded Ordnance year: 2000 ident: es051168tb00010/es051168tb00010_1 contributor: fullname: Heberlein D. C. – volume-title: Final Report: Spatial Statistical Models and Optimal Survey Design for Rapid Geophysical Characterization of UXO Sites year: 2003 ident: es051168tb00023/es051168tb00023_1 contributor: fullname: Ostrouchov G. – volume: 25 start-page: 39 issue: 7 year: 2001 ident: es051168tb00006/es051168tb00006_1 publication-title: Military Technol contributor: fullname: Lauritzen E – volume-title: Estimating the spatial distribution of UXO from limited data using geostatistics. Presented at the UXO Countermine Forum year: 2002 ident: es051168tb00025/es051168tb00025_1 contributor: fullname: McKenna S. A. – ident: es051168tb00028/es051168tb00028_1 – volume-title: Report of the Defense Science Board Task Force on Unexploded Ordnance year: 2003 ident: es051168tb00003/es051168tb00003_1 contributor: fullname: Defense Science Board – volume-title: Statistical Tools for Designing Initial and Post-Removal UXO Characterization Surveys ident: es051168tb00029/es051168tb00029_1 contributor: fullname: Pulsipher B. – volume-title: Alternatives for Landmine Detection year: 2003 ident: es051168tb00012/es051168tb00012_1 contributor: fullname: MacDonald J. A. – volume-title: Evaluation of U. S. Army Corps of Engineers Statistical UXO Sampling and Characteriza tion Methodologies year: 2000 ident: es051168tb00016/es051168tb00016_1 contributor: fullname: Engelhardt M. – volume-title: UXO Cleanup Costs: Implica tions of Alternative Clearance Protocols year: 2005 ident: es051168tb00008/es051168tb00008_1 contributor: fullname: MacDonald J. A. – ident: es051168tb00011/es051168tb00011_1 – volume: 35 start-page: 376A issue: 17 year: 2001 ident: es051168tb00013/es051168tb00013_1 publication-title: Environ. Sci. Technol doi: 10.1021/es012463q contributor: fullname: MacDonald J. A – volume-title: AL year: 1999 ident: es051168tb00015/es051168tb00015_1 contributor: fullname: Fanning A. UXO – volume-title: The Challenge of Transferring Army BRAC Lands Containing Unexploded Ordnance: Lessons Learned and Options for the Future year: 2004 ident: es051168tb00002/es051168tb00002_1 contributor: fullname: MacDonald J. A. – volume-title: Defense Environmental Programs Annual Report to Congress Fiscal Year 2004 year: 2005 ident: es051168tb00004/es051168tb00004_1 contributor: fullname: Department of Defense. – volume-title: Office of Solid Waste and Emergency Response year: 1999 ident: es051168tb00019/es051168tb00019_1 contributor: fullname: Fields T. – volume-title: Spatial Cluster Modeling year: 2002 ident: es051168tb00021/es051168tb00021_1 doi: 10.1201/9781420035414 contributor: fullname: Lawson A. B. – volume-title: International Association of Mathematical Geology Annual Meeting, Cancun, September 6−12 year: 2001 ident: es051168tb00024/es051168tb00024_1 contributor: fullname: McKenna S. A. |
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Snippet | More than 40 000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much... More than 40,000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much... More than 40 000 km2 of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total as much... Using statistical modeling, sites contaminated with unexploded ordnance were explored. Experiments were conducted at two former military training ranges... More than 40 000 km super(2) of former military land in the United States are contaminated with unexploded ordnance (UXO). Cleanup costs are estimated to total... |
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SubjectTerms | Applied sciences Bioremediation Decontamination. Miscellaneous Earth sciences Earth, ocean, space Engineering and environment geology. Geothermics Environmental cleanup Environmental Monitoring - methods Environmental science Exact sciences and technology Explosions Explosives Military bases Models, Statistical Pollution Pollution, environment geology Refuse Disposal Risk Assessment Soil and sediments pollution Statistical analysis United States United States Environmental Protection Agency Warfare |
Title | Assessing Sites Contaminated with Unexploded Ordnance: Statistical Modeling of Ordnance Spatial Distribution |
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