Improved ecological network analysis for environmental sustainability assessment; a case study on a forest ecosystem

To assess the environmental sustainability of industrial products and services, tools such as life cycle assessment (LCA) have been developed. In LCA, the total environmental impact of resource extraction and emissions during a productʹs life cycle is quantified. To better quantify this impact, first the alteration of ecosystems induced by those processes needs to be accounted for. Second, the flow networks of ecosystems, responsible for the formation of the extracted resources, should be included in the productʹs life cycle. To achieve these two objectives, a tool was selected which studies the flow networks of ecosystems: ecological network analysis (ENA). In ENA, total system indicators are calculated which assess an ecosystemʹs functioning (e.g. cycling). Alterations of ecosystems can be represented by changes in the values of those indicators. ENA is based on the computational framework of input–output analysis (IOA). This framework is also used in LCA allowing for a possible extension of a productʹs life cycle in an LCA with the ecosystem flow networks of ENA. The ENA/IOA framework itself was revised and improved in this study to better fit in an LCA framework, prior to integration and application in LCA. The major adaptation was to enable physical compartmentalization of the surrounding environment of the studied (eco)system. This allows for a specification of destinations and sources of export and import flows, respectively, which is desired in LCA to assess the impact of these flows. Next to that, the adapted framework was made applicable to non-steady-state systems by applying Finnʹs concept (1976, 1977), in which increase, increment, and decrease, depletion, in stock are considered abstract export and import flows, respectively. As an example, the adapted ENA framework was applied to a forest ecosystem. However, there are no standards yet for the different choices in the ENA methodology, which can have an influence on the indicator values. Hence, defining such standards is a next important research step.