ORFA: introducing a method for maximizing social profit from soil remediation funds

Abstract

Purpose

Contaminated land is a major problem. The remediation cost of brownfields in Europe and the USA exceeds 550 billion €; however, rehabilitation is on a slow pace. It is estimated that the money spent so far correspond to just 5% of the required one to eliminate the problem. The high cost of remediation, along with the inefficiency of the available funds, gives rise to a need for a method to effectively allocate remediation funds.

Materials and methods

Risk assessment is often used to prioritize the rehabilitation of contaminated sites. Cost–benefit analysis, by means of environmental economics, is another step in the right direction. Optimum Remediation Funds Allocation method (ORFA), the new method presented in this paper, goes beyond that. Instead of simply deciding which sites should be cleaned up or not, the optimum remediation level is determined in each case in terms of the 3-D geographical boundaries of the soil mass that should be remediated. The method is based on the idea of considering contaminated soil as a “negative ore,” with an economic value that can be estimated using environmental economic methods. This approach enables the use of a sophisticated pit optimization software widely applied in mining like Minemax Planner, which is based on the push–relabel algorithm.

Results and discussion

ORFA can guide remediation starting from the soil blocks which are the most profitable for the society until the point that remediation produces no more social profit. The validation of the method is presented in the remediation project of the Lavrion Technological and Cultural Park (LTCP) case, Greece, one of the most heavily contaminated sites worldwide. ORFA achieved 99.4% remediation with a cost reduction of 17%. This means that, if remediation plans are guided by ORFA, for every five sites, as contaminated as LTCP, almost one site can be cleaned up for free. If the sites under remediation are less polluted, then ORFA can achieve even better results, saving money to clean up more sites.

Conclusions

ORFA succeeds in determining the socially optimum remediation level that produces the maximum net economic value. Alternatively, it gives the best remediation scheme under specific budget constraints. Ultimately, ORFA’s main contribution is that it can cause radical changes in the way we think and moreover realize rehabilitation of contaminated land.