IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v26y2006i5p1363-1375.html
   My bibliography  Save this article

Uncertain Numbers and Uncertainty in the Selection of Input Distributions—Consequences for a Probabilistic Risk Assessment of Contaminated Land

Author

Listed:
  • Per Sander
  • Bo Bergbäck
  • Tomas Öberg

Abstract

Risks from exposure to contaminated land are often assessed with the aid of mathematical models. The current probabilistic approach is a considerable improvement on previous deterministic risk assessment practices, in that it attempts to characterize uncertainty and variability. However, some inputs continue to be assigned as precise numbers, while others are characterized as precise probability distributions. Such precision is hard to justify, and we show in this article how rounding errors and distribution assumptions can affect an exposure assessment. The outcome of traditional deterministic point estimates and Monte Carlo simulations were compared to probability bounds analyses. Assigning all scalars as imprecise numbers (intervals prescribed by significant digits) added uncertainty to the deterministic point estimate of about one order of magnitude. Similarly, representing probability distributions as probability boxes added several orders of magnitude to the uncertainty of the probabilistic estimate. This indicates that the size of the uncertainty in such assessments is actually much greater than currently reported. The article suggests that full disclosure of the uncertainty may facilitate decision making in opening up a negotiation window. In the risk analysis process, it is also an ethical obligation to clarify the boundary between the scientific and social domains.

Suggested Citation

  • Per Sander & Bo Bergbäck & Tomas Öberg, 2006. "Uncertain Numbers and Uncertainty in the Selection of Input Distributions—Consequences for a Probabilistic Risk Assessment of Contaminated Land," Risk Analysis, John Wiley & Sons, vol. 26(5), pages 1363-1375, October.
    • Handle: RePEc:wly:riskan:v:26:y:2006:i:5:p:1363-1375
    DOI: 10.1111/j.1539-6924.2006.00808.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.2006.00808.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1539-6924.2006.00808.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Charles N. Haas, 1997. "Importance of Distributional Form in Characterizing Inputs to Monte Carlo Risk Assessments," Risk Analysis, John Wiley & Sons, vol. 17(1), pages 107-113, February.
    2. Randy L. Maddalena & Thomas E. McKone & Michael D. Sohn, 2004. "Standardized Approach for Developing Probabilistic Exposure Factor Distributions," Risk Analysis, John Wiley & Sons, vol. 24(5), pages 1185-1199, October.
    3. John Bukowski & Leo Korn & Daniel Wartenberg, 1995. "Correlated Inputs in Quantitative Risk Assessment: The Effects of Distributional Shape," Risk Analysis, John Wiley & Sons, vol. 15(2), pages 215-219, April.
    4. George E. Apostolakis, 2004. "How Useful Is Quantitative Risk Assessment?," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 515-520, June.
    5. David E. Burmaster & Paul D. Anderson, 1994. "Principles of Good Practice for the Use of Monte Carlo Techniques in Human Health and Ecological Risk Assessments," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 477-481, August.
    6. Victor R. Vasquez & Wallace B. Whiting, 2005. "Accounting for Both Random Errors and Systematic Errors in Uncertainty Propagation Analysis of Computer Models Involving Experimental Measurements with Monte Carlo Methods," Risk Analysis, John Wiley & Sons, vol. 25(6), pages 1669-1681, December.
    7. Bruce S. Binkowitz & Daniel Wartenberg, 2001. "Disparity in Quantitative Risk Assessment: A Review of Input Distributions," Risk Analysis, John Wiley & Sons, vol. 21(1), pages 75-90, February.
    8. Kai Lessmann & Andreas Beyer & Jörg Klasmeier & Michael Matthies, 2005. "Influence of Distributional Shape of Substance Parameters on Exposure Model Output," Risk Analysis, John Wiley & Sons, vol. 25(5), pages 1137-1145, October.
    9. David M. Hassenzahl, 2006. "Implications of Excessive Precision for Risk Comparisons: Lessons from the Past Four Decades," Risk Analysis, John Wiley & Sons, vol. 26(1), pages 265-276, February.
    10. Brent Finley & Dennis Paustenbach, 1994. "The Benefits of Probabilistic Exposure Assessment: Three Case Studies Involving Contaminated Air, Water, and Soil," Risk Analysis, John Wiley & Sons, vol. 14(1), pages 53-73, February.
    11. Alexander I. Shlyakhter, 1994. "An Improved Framework for Uncertainty Analysis: Accounting for Unsuspected Errors," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 441-447, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Sarfraz Iqbal & Tomas Öberg, 2013. "Description and Propagation of Uncertainty in Input Parameters in Environmental Fate Models," Risk Analysis, John Wiley & Sons, vol. 33(7), pages 1353-1366, July.
    2. Monika Filipsson & Tomas Öberg & Bo Bergbäck, 2011. "Variability and Uncertainty in Swedish Exposure Factors for Use in Quantitative Exposure Assessments," Risk Analysis, John Wiley & Sons, vol. 31(1), pages 108-119, January.
    3. Yakov Ben‐Haim, 2012. "Doing Our Best: Optimization and the Management of Risk," Risk Analysis, John Wiley & Sons, vol. 32(8), pages 1326-1332, August.
    4. Martí Nadal & Vikas Kumar & Marta Schuhmacher & José L. Domingo, 2008. "Applicability of a Neuroprobabilistic Integral Risk Index for the Environmental Management of Polluted Areas: A Case Study," Risk Analysis, John Wiley & Sons, vol. 28(2), pages 271-286, April.
    5. Daniel J. Rozell & Sheldon J. Reaven, 2012. "Water Pollution Risk Associated with Natural Gas Extraction from the Marcellus Shale," Risk Analysis, John Wiley & Sons, vol. 32(8), pages 1382-1393, August.
    6. Lyda Zambrano & Kerry Sublette & Kathleen Duncan & Greg Thoma, 2007. "Probabilistic Reliability Modeling for Oil Exploration & Production (E&P) Facilities in the Tallgrass Prairie Preserve," Risk Analysis, John Wiley & Sons, vol. 27(5), pages 1323-1333, October.
    7. Guanghui Guo & Degang Zhang & Yuntao Wang, 2019. "Probabilistic Human Health Risk Assessment of Heavy Metal Intake via Vegetable Consumption around Pb/Zn Smelters in Southwest China," IJERPH, MDPI, vol. 16(18), pages 1-17, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martí Nadal & Vikas Kumar & Marta Schuhmacher & José L. Domingo, 2008. "Applicability of a Neuroprobabilistic Integral Risk Index for the Environmental Management of Polluted Areas: A Case Study," Risk Analysis, John Wiley & Sons, vol. 28(2), pages 271-286, April.
    2. Richard R. Lester & Laura C. Green & Igor Linkov, 2007. "Site‐Specific Applications of Probabilistic Health Risk Assessment: Review of the Literature Since 2000," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 635-658, June.
    3. Charles N. Haas, 1999. "On Modeling Correlated Random Variables in Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 19(6), pages 1205-1214, December.
    4. Maged M. Hamed & Philip B. Bedient, 1997. "On the Effect of Probability Distributions of Input Variables in Public Health Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 17(1), pages 97-105, February.
    5. Serkan Erbis & Zeynep Ok & Jacqueline A. Isaacs & James C. Benneyan & Sagar Kamarthi, 2016. "Review of Research Trends and Methods in Nano Environmental, Health, and Safety Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 36(8), pages 1644-1665, August.
    6. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    7. Monika Filipsson & Tomas Öberg & Bo Bergbäck, 2011. "Variability and Uncertainty in Swedish Exposure Factors for Use in Quantitative Exposure Assessments," Risk Analysis, John Wiley & Sons, vol. 31(1), pages 108-119, January.
    8. Olivier Chanel, 2022. "Impact of COVID‑19 Activity Restrictions on Air Pollution: Methodological Considerations in the Economic Valuation of the Long‑Term Effects on Mortality [Impact sur la pollution de l’air des restri," Working Papers hal-03778336, HAL.
    9. Charles N. Haas, 1997. "Importance of Distributional Form in Characterizing Inputs to Monte Carlo Risk Assessments," Risk Analysis, John Wiley & Sons, vol. 17(1), pages 107-113, February.
    10. Johnson, Caroline A. & Flage, Roger & Guikema, Seth D., 2021. "Feasibility study of PRA for critical infrastructure risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    11. Terje Aven, 2018. "An Emerging New Risk Analysis Science: Foundations and Implications," Risk Analysis, John Wiley & Sons, vol. 38(5), pages 876-888, May.
    12. Janssen, Hans, 2013. "Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 123-132.
    13. George E. Apostolakis & Douglas M. Lemon, 2005. "A Screening Methodology for the Identification and Ranking of Infrastructure Vulnerabilities Due to Terrorism," Risk Analysis, John Wiley & Sons, vol. 25(2), pages 361-376, April.
    14. Timothy M. Barry, 1996. "Recommendations on the Testing and Use of Pseudo‐Random Number Generators Used in Monte Carlo Analysis for Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 16(1), pages 93-105, February.
    15. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    16. Ken Silver & Richard Clapp, 2006. "Environmental Surveillance at Los Alamos: An Independent Reassessment of Historical Data," Risk Analysis, John Wiley & Sons, vol. 26(4), pages 893-906, August.
    17. Senderov, Sergey M. & Smirnova, Elena M. & Vorobev, Sergey V., 2020. "Analysis of vulnerability of fuel supply systems in gas-consuming regions due to failure of critical gas industry facilities," Energy, Elsevier, vol. 212(C).
    18. Luca Allodi & Fabio Massacci, 2017. "Security Events and Vulnerability Data for Cybersecurity Risk Estimation," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1606-1627, August.
    19. Olivier Chanel, 2022. "Impact of COVID-19 Activity Restrictions on Air Pollution: Methodological Considerations in the Economic Valuation of the Long-Term Effects on Mortality," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 534-35, pages 103-118.
    20. Tidwell, Vincent C. & Lowry, Thomas S. & Binning, David & Graves, Jenny & Peplinski, William J. & Mitchell, Roger, 2019. "Framework for shared drinking water risk assessment," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 37-47.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:26:y:2006:i:5:p:1363-1375. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.