Auditing the Assessment of the Environmental Impacts of Planning Projects

This paper presents the results from a post-auditing study-a comparison of the predictions of environmental impacts of projects made in environmental statements prior to developmentwith those that actually occurred upon or after development. The purpose of post-auditing is to provide an analysis of prediction performance in environmental impact assessment and thus to improve future practice by learning from experience. By means of a combination of site visits, interviews and document scrutiny, 865 predictions from 28 UK projects granted planning permission were examined. Of these, 488 (56%) were auditable, of which 383 (79%) were deemed 'accurate' or 'nearly accurate' and 105 (21%) 'inaccurate'. The remaining 377 (44%) predictions were not auditable, the main reasons being lack of data, vague or ambiguous predictions and time dependency.There were only six unpredicted impacts. The study reveals some encouraging findings, but also a number of discouraging ones, which indicate the need to increase both enthusiasm for, and implementationof, post-auditing activities. Several suggestions are made to help achieve these objectives.     

Monitoring and Post-auditing in Environmental Impact Assessment: A Review

Environmental impact assessment (EIA) is a procedure for predicting environmental impacts of projects prior to their development, while post-auditing seeks to assess the accuracy of such predictions. A literature review examines the need for post-auditing, highlighting several benefits to EIA performance that could arise if the results were effectively used. This reveals that, in practice, post-auditing activities are not widespread, and suggests reasons why this is so. An overview of post-audit findings from a survey of published studies is then presented, and it is concluded that there is much scope for raising the profile of post-auditing in EIA world-wide. Preliminary results from a recent UK post-auditing study based on eight projects are described. Information on impact predictions was gathered and compared with actual impacts. A total of 366 impact predictions were made of which 78% were qualitative in nature; 57% of the predictions were auditable and of these nearly three-quarters were accurate. Reasons for inauditability were ascertained including, for all cases, a lack of data or unsuitable information.