Uncertainty in policy transfer across contaminated land management regimes: examining the Nigerian experience

Kabari Sam*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Weak and developing contaminated land management regimes have continued to transfer perceived effective contaminated land management policies into their regimes, without considering the effects of variability in risk perceptions, available scientific data, expertise, and contextual differences in the implementation process of such policies. Such transferred policy is a foundation for faulty contaminated land management decisions and potentially exposes receptors to higher levels of risk and affects confidence in decisions and future land use. In addition, because the technical capacity to interpret and implement the transferred policy are often lacking, it becomes difficult to justify contaminated land management decisions and to involve local communities and other stakeholders in the decision-making process. It is argued that too much emphasis has been placed on policy transfer, without attention to contextualization and this results in uncertainties linked to lack of capacity, expertise, data, risk perception and human factor, during the implementation of transferred policies particularly in developing regimes. This article examines uncertainties related to policy transfer using the Nigerian experience of contaminated land management. The study concludes that uncertainty affects confidence in contaminated management decision-making, exposes receptors to unacceptable risks and threatens future land use. Developing contaminated land management regimes intending to transfer policy from effective regimes should consider country-specific peculiarities and use effective regimes as guidance rather than stark transfer of policy without consideration of contextual differences.

Original languageEnglish
Article number106645
Number of pages7
JournalLand Use Policy
Volume129
Early online date21 Mar 2023
DOIs
Publication statusPublished - 1 Jun 2023

Keywords

  • human error
  • knowledge gap
  • remediation
  • risk assessment
  • risk perception

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