ML103620077
ML103620077 | |
Person / Time | |
---|---|
Site: | Davis Besse ![]() |
Issue date: | 12/28/2010 |
From: | Luna R, Yoshimura H, Hoo M Sandia |
To: | NRC/SECY |
SECY RAS | |
Shared Package | |
ML103620074 | List: |
References | |
License Renewal 2, RAS 19324, 50-346-LR | |
Download: ML103620077 (7) | |
Text
Surn'Y or Costs Arising From Potl'ntiai Radionuclidl' Scatlt'ring [ "I'llts - 8147 Robert E. Llma, PhD, PE . Cousuilanl Albuquerque, NM 87 111 H. Richard Yoshimura and Mad: S. Soo Hoo Sandia National Laboratories*
Albuquerque, NM 87185 ABSTRACT The potential effects from scattering radioactive materials in public places include healdl, sociaL and economic consequences. These are substantial consequences relative 10 potentiaitelTor activities that include use ofradioactive material dispersal devices (RODs). Such an event with radionuclides released and deposited on surfaces outside and inside people's residences and places of work, conUllerce. and recreation will require decisions on how to recover from the event. Glle aspect of those decisions will be the cost to clean up the residua l radioactive contaminatiollto make the area functional again versus abandOlUllent and/or razing and rebuilding.
Development of cleanup processes have been the subject of experiment from dIe begiwling of the nuclear age. but fonnalized cost breakdowns are relatively rare and mostly applicable to long tenn releases in non-public sites. Pre-event cleanup cost estimation of cost for cleanup of radioactive materials released to dIe public environment is an issue that has seen sporadic activi£y over the lasl 20 to 30 years. l1Iis paper will briefly review several of the more important efforts to estimate die costs of remediation or razing and reconstruction of radioactively contaminated areas. The cost estimates for such recoveries will be compared in tenns of 2005 dollars for the sake of consistency. Dependence of cost estim ates on population density and needed degree of decontamination will be shown to be quite strong in the overall presentation of the data.
LITERATURE OVERVIEW Techniques used for cases of released radioactive materials in the event of an accident during transpoI1 have been a principal source of cost estimating teclllliques. These are contained in the RADTRAN transport risk assessment codes that were ftrst produced in 1974 for use in preparing NUREG-O170 (NRC, 1977). TImt version, RADTRAN I, had several revisions in succeeding issues of the code to the present version contained in RADTRAN VI. Two non-RADTRAN
- Saf'l(lia Is a multiprogram laboratory operated by Sandia Ccxporation. a lockllee<l Marlin company. lor the U n~ed Slates Department of Energy's National Nuclear Security Adrrinistration uf'l(ler Cootrad DE-AC04*94Al85000.
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methodologies are also notable. First. is an analysis completed to estimate the cost of cleaning up plutonitun scattered as a result of a nuclear weapons accident that was completed in 1996 (Chanin. 1996). Second is a computer code developed in the UK (and apparently only usable for UK govenunent purposes) called CONDO (Charnock, 2003). In additio n. some cleanup cost estimates have been put forward in a paper (Reichmuth, 2005) for the Depamnent of Homeland Secmlty that gives cleanup cost estimates for high population densi ty areas based on RADTRAN IV calculaliolls and acrual costs for remediation of the World Trade Center (WTC) site in New York C ity.
PROCESS USED The methodology for estimating cleanup costs uses 1\\'0 principal parameters. TIle first and most basic is the acceptable residual level of contamination detennined for each nuclide released that will avoid a given level of radiological dose to persons who will remain living/working in the contaminated area. TIle acceptable dose and, hence, the residual contamination level for each nuclide, is likely to be negotiated for each release event (DHS, 2007). TIle second parameter is the Decontamination Factor. OF. which can be rationalized in 1\\'0 ways:
- At any point at the site of the radioactive material release, it is the ratio of the local contamination level for a released nuclide to the acceptable residual contamination level.
(DFJ
- A measure of the capability of a given cleanup method (like water hosin g) to reduce the contamination level for a given surface material. Thus, it is the ra tio of contamination level before treatment 10 conlamination level after treatment, (OF...)
Specific cleanup tec1mologies applied to specific surfaces and nuclides are characterized by the maximum DFm ac hievable. If the OF. is less than the effects of all the cleanup processes that could be applied sequentially. OF. < [OFm, then cleanup is successftll. btu if the OF. is greater than the effects of all the cleanup processes that are applied sequentially, OF. > [ OF m. then other altematives. like razing and rebuilding, or interdiction must be app lied.
TIle methodologies used in the all oflhe cited literattll'e recognized the limitations of cleanup and employ razing 01' interdiction in the event that the required OF. fo r a given situation could not be achieved by standard cleanup processes. For most of the earl y cost eslimation teclUliques. it was asstuued that a OFm o f 50 was generally attainable, but more recent data, nicely Stunmallzed in the CONDO report , suggest that a OFm greater than 10 or so (with some isolated exceptions) is tuilikely to be attamed. TIlis suggests that the earlier cost estimates would be expected to be somewhat low, since cleanup costs are generally lower than raze and rebuild or interdiction methods.
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For the data presented below the original cleanup cost estimates presented in the source doclUuents were extracted and converted to 2005 costs using standard cost deflators (Williamson. 2006). hI general. costs were stratified by the initial level of contamination as represented by OF. values. Light contamination corresponded to a OF. <5: mediwn. 5< OF.
< 10; and heavy. OF. > 10. Costs in the RADTRAN reports were filf1her stratified by a specification relating to population density (mral, suburban, and urban) corresponding to mean population densities ofaboU! 10. 750, and 3800 persons per knl respectively. hI the Chanin report. the urban population density values were taken to be about 1350 personsi knl (corresponding to a mean population density in areas identified as urbanized by the census bureau). Reichmuth stated that population densities (PD in persolls/km2) were as follows:
Rural 0 < PO < 50 Urban 50 < PO < 3000 High Density Urban 3000 < PO < 10,000 Hyper Density Urban 10,000 < PO As is obvious from tile above, there is no strict translation of words describing population density tenllinology in quantitative tenus, but there is enough specificity to compare various costs estim ates as a ftmction of population density.
TIle SNL study (Chanin. 1996) provided a fairly detailed methodology in which to estimate costs. For an urban area. the overall results that came out of the effort are shown in Table I.
Table I. Urban Area (1344 persons/bu 2) Remediation Costs for Year 2005 in SMlkm2 from Appendix G (Chanin. 1996).
Cosu pn sq. kID Aru " 'd gbIHl C ons Ana Usa,. Li,bl Mod ...:II. Un,.,. An a Lip l ModH"2l. Un,")"
T ,,,. (2<DF,<S) (5< DF,10) FrxlioD (2<DF, <5) (5<OF,<10) (DF,>IO)
Residentia l' 172.4 1t63.9 SJ01.2 0.316 122.9 151.8 195.2 Commercial S195.3 S295.5 S851.2 0. 173 $33 .8 S5 1.1 S1 47. 3 Industria l S674.0 S704.2 S I,245.9 0.064 S43 .1 $45.1 S79.7 SIreeIS $15.9 $18.5 $247.7 0. 175 $2.8 S3.2 $4 3.3 Vacanl Land $81.1 $85.7 $95.2 0.272 $2 2.1 123.3 $25.9
$ 124 .6 1 174.5 $391. 4 Overall Cost per sq. krn
.mc.ludes lingle and multiple fmnily dwdlmgs and 1IpartnJ=1 houses Table I demonstrates the methodology used as well as results. Costs were estimated for generic land use areas and then weighted by the fraction of the overall area in that land use class. Short of repeati.n g the considerable effort in developing the report results, what options exist for esti.matiIlg the cleanup cost for higher population density areas? If data is available for the land use area frac tions iII the higher population area, then an estimate can be made by plugging in tbose va lues in the 51b cohmm of Table I. In addition, an adjustment for population density can Page 3/
be made by noting that higher poPldation density implies that there are more dwe1li.llg lUlits per km 2 and that the costs shown in Table I are based on individual dwellings. As a result.
l1udtiplyi.ng the residential costs by a ratio of population density should adjust for higher populations in the same area. In addition, since commercial space is likely to expand with population density. the commercial values would also be adjus ted in a similar Il13IUler. TIlese are approxin13te methods and usefhl Oldy for order of magnihlde estimates. TIle result of such adj ustments is shown in Table U.
Table U. Estimated Remediation Costs for New York City Reflecting Land Use Distribution and Population Density.
Arn " 'rig htrd Popu tulon I nd Arn W r ightrd Lo nd Us. A~, Lie hl Modu at .. H..a,.,. PD Lichl Mod .. ral.. Hn *.,.
Fraction' (2<DF, <~ (S< DF,<IO) (DF, >10) "'nllipl (2<DF, <S) (S<oF,<lO) (DF,>IO)
Residenti al 0 .287 $20 .3 1 $4 5.99 $84 .5 1 6.8 2 $138.55 $3 13.64 $576 .38 Commercial 0 . 164 $32 .09 $48 .55 $ 139.84 6.8 2 $2 18.84 $3 3 1.12 $953.80 Industria l 0 .068 $4 5.5 1 $47 .55 $84.1 2 LOO $45.5 1 $4 7.5 5 $84 .12 Streets 0 .250 $3.97 $4.62 $61.88 LOO $3.97 $4.62 $61.88 Vacant Land 0 .238 $ 19 .29 $20.38 $22.64 LOO $ 19 .29 $20.38 $22 .64 LOO Ovmlll Cost ($Mlkm $ 12 1.2 $167. 1 $393.0 $426 $7 17 $1 ,699
- dmved from New York City data ( httpJ !w....-w.nyc.goVlb tmllskpfpdfllandusefactsl!anduse tables.pdf )
~ ntlO of New York CIty populatton density to that m Table 1 (9 166' 1344 '" 6 .82)
The process used 10 produce Table II can be used to derive remediation cost estimates for other population density areas as shown by the triangle points in Figure I . Figure) also contains remediation cost data from the source doclUllellts discussed above.
TIle Legend in Figure I is quite large. but is color keyed for some addition clarity. Red lines and symbols are for (DF. > l O). orange for (5 < OF. < 10), and green for ( I < OF. < 5). Purple symbols are for estin13tes ti13t are unspecific about the DF. they app ly to, but the values could be as large as 50.
Figure 1 shows a fa ir amount of variability in the costs estin13ted by the various methods and sources covered in this ovelv iew. TIle thr ee straight lines penciled in on the plot are intended to suggest how the costs might valY with poPldation density and degree of contamination. TIle lines are a reasonable representation of much of the infOlmation, but some data points deviate substantially and will be discussed here. The 1\\'0 red disc points that are well above the Cluves are from the paper by Reiclulluth and are based on estin13tes of cost derived 10 clean up and restore (not rebuild) the 16 acre WTC site in New York City after 9/ 11 . The cost to replace the facilitie s is estimated to be an order of magnihlde larger (not shown on the plot),
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Figure I: Remediation Cost Estimates Compared.
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Since the estimated cost was based on the area of the wrc site, but the actua l expenditure covered actions made over the SUffOlUIding areas and included actions somewhat beyond what would be expected in response to an RDD event, the acnJaI cost/kIll could be overestimated by 50% to 60%.
The purple squares below ule curve represent the estimates that were done using RADTRAN I in the mid 1970 's with an lUlsophisticated methodology. Moreover, the estima tes are the oldest and most subject to lUlcertainty associated wiul selecting the best deflator statistic for updating costs.
The RADTRAN 6 estimates (purple diamonds) also are below the trend lines but not as pronounced an effect as wiul RADTRAN 6 (Osborn, 2(07). Note that the RADTRAN 6 values (squares with center crosses) fit much more closely with the other estimates and the trend lines.
The trend lines favor the cost values generated by the Sandia snldy (Chanin. 1996). because of the detail involved in the initial estimates and the ability to project the costs to other population densities and land use area fractions.
CONCLUSION TIle likelihood ofa " Dirty Bomb" attack in the US or elsewhere is unknown. Most sources suggest (e. g .. Karam. 2(05) that the radiological consequences of such an attack are unlikely to be life tlu-eatening and that the greatest mortal danger is to persous exposed to blast from the device (assmning that is its mode of operation). However, the expenditures needed to recover from a successftu attack using an RDD type device, as depicted in Figure I. are likely to be significallt from the standpoint of resources available to local or state govenunents. Even a device that contaminates an area of a few hw)(ired acres (a square kilometer) 10 a level that requires modest remediation is likely to produce costs ranging from S I OM to S300M or more depending 0 11 intensity of conunercialization, population density. and details of land use in the area. As a res\UI. it is important to put appropriate emphasis on the efforts 1I0W being taken by the Department of Energy. Nuclear Regulatory Commission, and the Department of Homeland Security 10 provide acco\U1tancy for radioactive materials used in the public and private sectors and to detect. as ftllly as possible. traffic in potential dirty bomb materials within and on the borders of the USA.
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REFERENCES (Chanin, 1996) : Chanin. David L and Murfin Walter B., "Site Restoration: Estimation of Attributable Costs From Plutonium-Dispersal Accidents". Sandia National Laboratories. Report SAND 96-0957. May 1996.
(Charnock, 2003): Chamock. T. et ai, "CONDO: Sofiv.'are for Estimating the Consequences of Decontanunatioll Options". National Radiological Protectiou Board. Report NRPB-W43. May 2003) .
(DRS, 2007) : Department of Homeland Security, Preparedness Directorate: "Protective Action Guides for Radiological Dispersal Device (ROD) and Improvised Nuclear Device (INDY', Federal Register, Vol. 71. No. I , January 3, 2006, pI 74-196.
(Kanlpt', 1992) :. Kanipe, F and Neuhauser, K. S., "RADTRAN 4: Volume 4 Programmers Manual", Sandia National Laboratories, Report SAND89-2370, July 1992.
(Kara m, 2005): Karam, Andrew, "Radiological Ten orislll," Hmuall and Ecological Risk Assessment. Vol. I L 2005 , pp. 50 1-523.
(Nt'uha ust'r, 1992) : Neuhauser. K. S. and Kanipe, F., " RADTRAN 4: Vollune 3 User Guide".
Sandia Nat ional Laboratories, Report SAND89-2370, January 1992.
(Nt'uh aust'r, 1993) : Neuhauser. K. S. and Kanipe, F. , "RADTRAN 4: Vollune 2 Technical Manual", Sandia National Laboratories, Report SAND89-2370. August 1993.
(OSb OI'U, 2007): Private Communication with Douglas Osborn, SNL relative to estimated cleauup cost estimated by RADTRAN VI, October 2007.
(pt'ulstt'o, 2007): Penistell, J. P.. and Weiner, R., " An Economic Model ofa Radioactive Materials Transportation Accident for the RADTRAN Risk Assessment Code", Proceedings of Waste Management 2005. Febmary 27-March 3, 2005, Tucson, AZ (SAND2oo5-3802C).
(1\'RC, 1977): "Final Environmental Statement on the Transportatioo of Radioactive Materials by Air and Other Modes", NUREG-O 170, US Nuclear Regulatory ConUlussioll. Washington, DC. December 1977.
(Rt'lr hmuth, 2005) : Reichmuth, B. , et aI, " Economic Consequences ofa RADINUC Altack:
Cleanup Standards Significantly Affect Cost", Proceedings of Working Together R&D Partnerships in Homeland Secmity, Boston, MA, April 2003 (Pacific NOIlhwesl National Laboratory. PNNL-SA-45256).
(Willia mson, 2006): Williamson, Samuel H. , "Five Ways to Compute the Relative Value of a U.S. Dollar Amount. 1790 - 2005," MeasuringWOllh.Com, 2006 Olttp:Ilwv.""'.measlmng\\'Ollh.com/calculators/uscompare/result.php .
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