An interval parameter fuzzy relation analysis (IPFRA) model is proposed for environmental risk assessment of petroleum contaminated acquifers due to leakage from underground storage tanks. The model can effectivelv incorporate effects of different pollutants and different remediation techniques within a general framework. Also. it can directly reflect uncertainties presented as inexact intervals for a number of modelling inputs. Results of a case study indicate that reasonable solutions for risk assessment under different system conditions have been generated Four potential site remediation strategies are analyzed. They have different environmental/economic characteristics with lower risks generally corresponding to higher, costs. Tradeoffs between environmental and economic objectives are then analyzed In general. the JPFRA approach is useful for comprehensively evaluating risks within a system containing many factors with complicated interrelationship.


Development of petroleum industry is one of the major economic sectors in the North America. Its development is currently associated with a number of environmental concerns. Among them, problem of leakage from underground storage tanks (USTs) has been paid significant attention 1–3. The number of USTs for petroleum products in the North America was estimated to be between 1.5 and 2 millions4. Tejada reported that as much as 23% of all the tanks leak5, The main causes of leakage are corrosion (for steel USTs) and breakage (for fiberglass USTs)5–6.

The leakage problem has led to a variety of impacts, risks and liabilities. It became such an important concern that the U.S. Environmental Protection Agency created the Office of Underground Storage Tanks in 1985. The leakage represents an increasing danger to groundwater resources and public health7,8. Therefore, effective environmental risk assessment of groundwater contamination due to leaking USTs is important for evaluating necessity of site remediation actions and providing support for decisions related to prevention, detection and correction of the leakage and contamination problems.

There have been some studies of environmental risk assessment for petroleum waste management. For example, Lo proposed an oil spill risk simulation model based on an probabilistic approach9. Hallenbeck and Flowers undertook a study of risk assessment for worker exposure to benzene10. Rundmo studied occupational accidents and objective risks on North Sea offshore installations11. Generally, most of the previous risk analysts argued that risk should be measured through probability (relative likelihood) of possible contamination and magnitude (seriousness) of consequences from the contamination. Thus, risk could be expressed as a probability distribution over a number of adverse consequences. However, when applied to diverse problems, probability theory often retains a fundamental assumption about the subject area involved. Specifically, it assumes that there exists a historical run for the observations of events. In fact, when attempting to model behaviors of environmental processes, analysts often suffer from a lack of data or imperfect knowledge about the processes. This may frustrate rigorous probabilistic studiesl2. Another problem with the probability theory is its law of excluded middle [p(A ∪AC) = I] and contradiction [p(A ∩AC) = 0]. For instance, rotating a dice, the results will be 6, 5, 4, 3, 2 or I, but never 4.5 or 2.1.

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