by: Adam Pinchefsky
The goal of Environmental Impact assessment (EIA) is to assess the socio-economical / bio-physical impacts of proposed projects and offer ways to mitigate those impacts. One issue that many people have with EIA is the inherent uncertainty in almost every fabric of the process. EIA practitioners must make predictions based on the information available to them and the understanding of the environmental systems present in the project area. The information available to EIA practitioners is often incomplete and has uncertainty present in the way the data was collected and in the data itself. Environmental systems are not perfectly understood and possibly might never be, thus uncertainty exists in the models of these systems that practitioners use to make their decisions. Lastly, we come to the word “prediction”, which in itself eludes to uncertainty. The unavoidable uncertainty in EIA predictions is well-known among EIA practitioners and those familiar with EIA (1).
It has become very common that public policy decisions are heavily influenced by scientific expertise (2). Policy decisions in regards to EIA’s are no different. The science of the natural world is used to model the effects that projects will have on the environment and how these changes will subsequently affect us. These models are then used to generate various scenarios of the effects that the project will have and the data generated by these models are presented to decision makers, which they use to decide if the project should go ahead, go ahead with changes, or be denied. Uncertainty in EIA is generally not communicated or poorly communicated to decision makers, where it is assumed that decision makers know of the uncertainty in the information (2). Often times, when uncertainty is mentioned, the breakdown of the origin of the uncertainty or the justification for that uncertainty is missing (2).
The big question here is: Do decision makers REALLY want to know about the uncertainties in EIA? At first glance, I thought that this was a simple question, with the obvious answer being that decision makers would want all the available information and the uncertainty that goes along with it to make the best decision possible. However, after thinking about the question further, I started to doubt my initial answer to that question. The decision maker is accountable for their decision and too much information and uncertainty can complicate the decision-making process by increasing the effort required to fully understand the information that they are presented with. Decision makers when seeing that there is uncertainty in the predictions, might air on the side of caution and choose the safer option, even though it might not be the best option given the information presented because they might not fully understand what the uncertainty means.
A situation where there is too much information to process which hinders the ability to make sensible decisions is called “Information Overload” (3). By including all the uncertainty inherent in all the aspects of the EIA process, the complexity of the problem is expanded by adding on more information that the decision maker must take into account (3). This overload of information can lead to the decision maker being unable to come to the best decision. The uncertainty in the data that is presented to the decision maker will increase their own uncertainty about what is best with regards to the project.
At the end of the day, it comes down to whether or not the added benefit of knowing the uncertainty of the information presented in EIA documentation is worth the added complexities and difficulties that decision makers must work through to come to a decision. I personally believe that uncertainty should be included in EIA documents but should be stated in a simple and clear way, with an explanation of what the uncertainty means so that it is as easy as possible for decision makers to read and understand. Although uncertainty adds an extra layer of complexity to the decision-making process, projects can have significant effects on the environment and decision makers should have all pertinent information in order to come to a logical, well thought out decision. The possibility of making a wrong decision due to missing information is greater than the possibility of making a wrong decision with as much information as possible, even with the possibility of information overload.
1- Tenney, Aud, Kvaerner, Jens & Djerstad, Karl Idar, 2006. Uncertainty in environmental impact assessment predicitions: the need for better communication and more transparency. Impact Assessment and Project Appraisal. Volume 24, number 1, 45-56.
2- Hellström, Tomas & Jacob, Merle, 1996. Uncertainty and values: The case of environmental impact assessment. Knowledge and Policy. Volume 9, Issue 1, 70-84.
3- Infoengineering. Understanding Information Overload.
Pielke Jr., Roger. The Linear Model of Science and Decision Making, 14 June, 2010. http://rogerpielkejr.blogspot.ca/2010/06/linear-model-of-science-and-decision.html>
Stan, Tanya. Uncertainty Factors used to Ensure Protection of Public Health. Based on Chapter 14-4: Toxicity Assessment, 4 september, 2010. <Accessed January 19, 2014: http://risketm525.blogspot.ca/2010/09/uncertainty-factors-used-to-ensure.html>