WIT Press
Surface Mining Operations in Oil Sands

Surface Mining Operations in Oil Sands

Establishing Sustainable Development Indicators (SDIs)

Authors: C.A. Poveda and M.G. Lipsett, University of Alberta, Canada


$124.00 (free shipping)











The creation of the World Commission on Environment and Development (WCED) – commonly known as the Brundtland Commission – and the publication in 1987 of its report, "Our Common Future", marked a turning point towards finding the balance among society, economy, and environment.

Since then, governments have improved regulations; new standards have been developed; management and process practices have addressed potential gaps; public and private organisations have taken initiative through the creation of committees and programs; and research covering all areas of sustainable development has become a priority for academics and practitioners. These different sources serve as the basis for a pre-selection process of sustainable development indicators (SDIs).

While some sources do not specifically address certain industries, the pre-selection process suggested in this book studies and analyses each SDI’s resource and the possible applicability of already-identified indicators. An assertive set of SDIs is not solely based on regulatory systems, as measuring sustainability cannot become a bureaucratic process, and neither can any other SDI’s source single-handedly determine or mandate the final set of indicators, as the real objective is to assist decision-makers and effectively engage stakeholders.

This book presents an analysis of six different sources for pre-selecting SDIs, accompanied by a methodology to then finalise with a set of SDIs for the surface mining operations in oil sands projects. Surface mining projects are complex operations with several social, economic, environmental, and health impacts. As the government and oil sands developers are turning towards increasing productivity with a more conscious sustainable development approach, a pre-selection of SDIs is required to assist further formal multi-criteria selection processes.

Data Mining VI
Data Mining IV