| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1746068 | Journal of Cleaner Production | 2011 | 14 Pages |
Activities in offshore oil and gas (OOG) that cause environmental impacts can be systematically managed through an environmental management system (EMS). Environmental performance evaluation (EPE) is an essential part of an EMS. However, previous studies on EPE indicate that existing lists of indicators little insight into how indicators are modified to more accurately assess environmental performance.In this paper, a way is proposed to identify and define specific environmental performance indicators on a case-by-case basis, which consists of five steps: (1) describing environmental requirements; (2) determining favourable outcomes corresponding to the requirements; (3) identifying required activities or issues to achieve the outcomes; (4) searching for proper measures of the activities or issues; and (5) generating a list of key indicators. Based on these steps, a quality function deployment (QFD) approach is developed to determine key indicators and evaluate environmental performance. To handle uncertainties in QFD, the decision makers’ evaluations are quantified through rough numbers using the concept of rough sets. The outputs of the proposed approach are different environmental performance indices. Using these indices, decision makers can easily determine whether an improved performance has been achieved through an EMS. The proposed approach is transparent and promising for use as a unified tool for EPE. An application of the proposed approach is demonstrated through a numerical example.
► A new methodology is proposed to identify and define specific environmental performance indicators for environmental management system. ► Based on the methodology, a quality function deployment (QFD) approach is developed to determine key indicators to evaluate environmental performance. ► A rough set theory is integrated in QFD to handle uncertainties in the data/information. ► An application of the proposed approach is demonstrated through a numerical example of environmental management system for offshore oil and gas operation.
