Environmental Science and Pollution Research

, Volume 25, Issue 17, pp 17216–17222 | Cite as

Assessing the external benefits of contaminated soil remediation in Korea: a choice experiment study

  • Seul-Ye Lim
  • Hyo-Jin Kim
  • Seung-Hoon YooEmail author
Short Research and Discussion Article


Korean government has made and will continue to make a considerable investment in contaminated soil remediation to rectify the problems that arise from soil pollution. Quantitative information on the benefits of contaminated soil remediation is widely demanded by the public as well as the government. This article aims to assess the external benefits of contaminated soil remediation. A survey of 1000 randomly selected households was undertaken in Korea. The results show that the marginal willingness to pay values for a 1% decrease in human health hazard, a 1% improvement in biodiversity restoration, and 1000 new job creation by contaminated soil remediation are estimated to be KRW 204 (USD 0.17), 593 (0.50), and 238 (0.20) per household per year. The findings can provide policy-makers with useful information for both evaluating and planning the contaminated soil remediation.


Contaminated soil remediation External benefit Choice experiment Mixed logit model Willingness to pay 



This subject is supported by Korea Ministry of Environment (MOE) as “GAIA Project (Geo-Advanced Innovative Action Project) (No. 015000560003).”


  1. Adamowicz W, Louviere J, Williams M (1994) Combining revealed and stated preference methods for valuing environmental amenities. J Environ Econ Manag 26:271–292CrossRefGoogle Scholar
  2. Adamowicz W, Louviere J, Williams M (1999) Stated-preference methods for valuing environmental amenities. In: Bateman IJ, Willis KG (eds) Valuing environmental preferences: theory and practice of the contingent valuation method in the US, EU, and developing countries. Oxford University Press, New York, pp 460–479Google Scholar
  3. Ahn J, Shin J, Lee J, Shin K, Park H (2014) Consumer preferences for telemedicine devices and services in South Korea. Telemedicine and e-Health 20:1–7CrossRefGoogle Scholar
  4. Aizaki H, Sato K, Osari H (2006) Contingent valuation approach in measuring the multifuctionality of agriculture and rural areas in Japan. Paddy Water Environ 4:217–222CrossRefGoogle Scholar
  5. Alriksson S, Öberg T (2008) Conjoint analysis for environmental evaluation. Environ Sci Pollut Res 15:244–257CrossRefGoogle Scholar
  6. Banfi S, Filippini M, Horehájová A (2012) Using a choice experiment to estimate the benefits of a reduction of externalities in urban areas with special focus on electrosmog. Appl Econ 44:387–397CrossRefGoogle Scholar
  7. Ben-Akiva M, Lerman S (1985) Discrete choice analysis: theory and application to travel demand. Cambridge. MIT Press, MassGoogle Scholar
  8. Colombo S, Calatrava-Requena J, Hanley N (2003) The economic benefits of soil erosion control: an application of the contingent valuation method in the Alto Genil basin of southern Spain. J Soil Water Conserv 58:367–371Google Scholar
  9. Damigos D, Kaliampakos D (2003) Assessing the benefits of reclaiming urban quarries: a CVM analysis. Landsc Urban Plan 64:249–258CrossRefGoogle Scholar
  10. Hensher DA, Rose JM, Greene WH (2015) Applied choice analysis, 2nd edn. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  11. Hole AR, Kolstad JR (2012) Mixed logit estimation of willingness to pay distributions: a comparison of models in preference and WTP space using data from a health-related choice experiment. Empirical Economics 42 (2):445–469Google Scholar
  12. Jianjun J, Chong J, Thuy TD, Lun L (2013) Public preferences for cultivated land protection in Wenling City, China: a choice experiment study. Land Use Policy 30:337–343CrossRefGoogle Scholar
  13. Jin J, Wang W, He R, Gong H (2017) Valuing health risk in agriculture: a choice experiment approach to pesticide use in China. Environ Sci Pollut Res 24:17526–17533CrossRefGoogle Scholar
  14. Johnston RJ, Boyle KJ, Adamowicz W(V), Bennett J, Brouwer R, Cameron TA, Hanemann WM, Hanley N, Ryan M, Scarpa R, Tourangeau R, Vossler CA (2017) Contemporary guidance for stated preference studies. J Assoc Environ Resour Econ 4:319–405Google Scholar
  15. Keane M, Wasi N (2013) Comparing alternative models of heterogeneity in consumer choice behavior. J Appl Econ 28:1018–1045Google Scholar
  16. Lee JS, Yoo SH, Kwak SJ (2006) Consumers’ preferences for the attributes of post PC: results of a contingent ranking study. Appl Econ 38:2327–2334CrossRefGoogle Scholar
  17. Lim SY, Lim KM, Yoo SH (2014) External benefits of waste-to-energy in Korea: a choice experiment study. Renew Sust Energy Rev 34:588–595CrossRefGoogle Scholar
  18. Lim SY, Min SH, Yoo SH (2016) The public value of contaminated soil remediation in Janghang copper smelter of Korea. Resour Policy 50:66–74Google Scholar
  19. Lizin S, Passel SV, Schreurs E (2015) Farmer’s perceived cost of land use restrictions: a simulated purchasing decision using discrete choice experiments. Land Use Policy 46:115–124CrossRefGoogle Scholar
  20. Louviere JJ, Hensher DA, Swait JD (2000) Stated choice methods: analysis and applications. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  21. McFadden D (1974) Conditional logit analysis of qualitative choice behavior. In: Zarembka P (ed) Frontiers in econometrics. Academic Press, New York, pp 105–140Google Scholar
  22. McFadden D (1978) Modeling the choice of residential location. In: Karlquist A, Lundquist L, Snikars F, Weibull JW (eds) Spatial interaction theory and planning models. Amsterdam, pp 75–96Google Scholar
  23. Pimentel K, Harvey C, Resosudarmo P, Sinclair K, Kurz D, McNair M, Crist S, Shpritz L, Fitton L, Saffouri R, Blair R (1995) Environmental and economic costs of soil erosion and conservation benefits. Science 267:1117–1123CrossRefGoogle Scholar
  24. Shin J, Woo JR, Huh SY, Lee J, Jeong G (2014) Analyzing public preferences and increasing acceptability for the renewable portfolio standard in Korea. Energy Econ 42:17–26CrossRefGoogle Scholar
  25. Song Q, Wang Z, Li J (2016) Exploring residents’ attitudes and willingness to pay for solid waste management in Macau. Environ Sci Pollut Res 23(16):16456–16462CrossRefGoogle Scholar
  26. Tarfasa S, Brouwer R (2013) Estimation of the public benefits of urban water supply improvements in Ethiopia: a choice experiment. Appl Econ 45:1099–1108CrossRefGoogle Scholar
  27. Train KE (2003) Discrete choice methods with simulation. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  28. Train K, Sonnier G (2005). Mixed logit with bounded distributions of correlated partworths. Applications of simulation methods in environmental and resource economics. Springer, Netherlands, pp. 117–134Google Scholar
  29. van Wezel AP, Franken ROG, Drissen E, Versluijs KCW, Van den Berg R (2007) Societal cost-benefit analysis for soil remediation in the Netherlands. Integr Environ Assess Manag 4:61–74CrossRefGoogle Scholar
  30. Willison JHM, Li R, Yuan XZ (2013) Conservation and ecofriendly utilization of wetlands associated with the Three Gorges Reservoir. Environ Sci Pollut Res 20:6907–6916CrossRefGoogle Scholar
  31. Woo JR, Choi JY, Shin J, Lee J (2014) The effect of new media on consumer media usage: an empirical study in South Korea. Technol Forecast Soc Chang 89:3–11CrossRefGoogle Scholar
  32. Yekeen TA, Xu X, Zhang Y, Wu Y, Kim S, Reponen T, Dietrich KN, Ho SM, Chen A (2016) Assessment of health risk of trace metal pollution in surface soil and road dust from e-waste recycling area in China. Environ Sci Pollut Res 23:17511–17524CrossRefGoogle Scholar
  33. Yoo SH, Kwak SJ, Lee JS (2008) Using a choice experiment to measure the environmental costs of air pollution impacts in Seoul. J Environ Manag 86:308–318CrossRefGoogle Scholar
  34. Yuan MH, Lo SL, Yang CK (2017) Integrating ecosystem services in terrestrial conservation planning. Environ Sci Pollut Res 24:12144–12154CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Research Strategy Department, Frontier Research & Training InstituteYonginRepublic of Korea

Personalised recommendations