Characterisation framework development for the SIMPASS (Singapore IMPact ASSessment) methodology

Life cycle assessment (LCA) practitioners in Singapore currently rely on foreign life cycle impact assessment (LCIA) methodologies when conducting studies, despite the fact that foreign methodologies may not be relevant, adaptable and sensitive to Singapore's circumstances. As a result, work has been undertaken to develop the Singapore IMPact ASSessment (SIMPASS) methodology by adapting and modifying existing LCIA methodologies to suit the Singaporean context. It is envisioned that the use of SIMPASS will improve the accuracy of LCA studies conducted for industries operating in Singapore.

The development is initiated by a compendious review of the available LCIA methodologies, in order to familiarise state-of-the-art developments and best available practice for LCIA in the world. Subsequently, five key design considerations are discussed. Firstly, six impact categories (climate change, acidification, eutrophication, fossil fuel depletion, water use and land use) are identified and prioritised for detailed analysis in this project, in view of their relevance and criticality to Singapore. Subsequently, user issues and the type of LCIA approach are considered. Following which, four areas of protection (namely Human Health, Natural Environment, Natural Resources and Man-made Environment) are selected for consideration in the SIMPASS methodology.

With the development approach in mind, extensive research is conducted in the six selected impact categories to construct the characterisation framework for SIMPASS. The characterisation framework is strongly based on current best practices in LCIA characterisation, while the characterisation models are chosen based on their extent of comprehensiveness, scientific sophistication, as well as specificity to Singapore.

SIMPASS proposes an attractive and feasible LCIA methodology that is highly specific to Singapore. Feasible recommendations are drawn to further develop and operationalise the characterisation framework.