Assessing Sites Contaminated with Unexploded Ordnance:  Statistical Modeling of Ordnance Spatial Distribution

• Published in: Environmental science & technology Vol. 40; no. 3; pp. 931 - 938
• Main Authors: Macdonald, Jacqueline A, Small, Mitchell J
• Format: Journal Article
• Language: English
• Published: Washington, DC American Chemical Society 01-02-2006
• Subjects: 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; United States; North America; America; United States > US; USA; Military installation; Spatial distribution; Decontamination; Decision support system; Risk assessment; Environment impact; Statistical model; Ammunition; Soil pollution; Armament; Military equipment
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/es051168t

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.