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Advancing Integrated Systems Modelling Framework for Life Cycle Sustainability Assessment

doi: 10.3390/su3020469
The need for integrated methodological framework for sustainability assessment has been widely discussed and is urgent due to increasingly complex environmental system problems. These problems have impacts on ecosystems and human well-being which represent a threat to economic performance of countries and corporations. Integrated assessment crosses issues; spans spatial and temporal scales; looks forward and backward; and incorporates multi-stakeholder inputs. This study aims to develop an integrated methodology by capitalizing the complementary strengths of different methods used by industrial ecologists and biophysical economists. The computational methodology proposed here is systems perspective, integrative, and holistic approach for sustainability assessment which attempts to link basic science and technology to policy formulation. The framework adopts life cycle thinking methods—LCA, LCC, and SLCA; stakeholders analysis supported by multi-criteria decision analysis (MCDA); and dynamic system modelling. Following Pareto principle, the critical sustainability criteria, indicators and metrics (i.e., hotspots) can be identified and further modelled using system dynamics or agent based modelling and improved by data envelopment analysis (DEA) and sustainability network theory (SNT). The framework is being applied to development of biofuel supply chain networks. The framework can provide new ways of integrating knowledge across the divides between social and natural sciences as well as between critical and problem-solving research.
- University of Queensland Australia
- University of Maine System United States
- University of Maine United States
- University of Maine United States
- University of Maine System United States
690, life cycle thinking, Integrated sustainability assessment, Monitoring, multi-criteria decision making, TJ807-830, integrated sustainability assessment, TD194-195, Renewable energy sources, Complexity dynamics, network theory, Multi-criteria decision making, Data envelopment analysis, GE1-350, Life cycle thinking, integrated sustainability assessment; life cycle thinking; multi-criteria decision making; stakeholders analysis; data envelopment analysis; agent based modelling; network theory; complexity dynamics; biofuels, Planning and Development, Sustainability and the Environment, Policy and Law, complexity dynamics, Environmental effects of industries and plants, 3305 Geography, Agent based modelling, Stakeholders analysis, stakeholders analysis, agent based modelling, biofuels, 2105 Renewable Energy, Environmental sciences, Biofuels, Network theory, 2308 Management, data envelopment analysis, jel: jel:Q, jel: jel:Q0, jel: jel:Q2, jel: jel:Q3, jel: jel:Q5, jel: jel:O13, jel: jel:Q56
690, life cycle thinking, Integrated sustainability assessment, Monitoring, multi-criteria decision making, TJ807-830, integrated sustainability assessment, TD194-195, Renewable energy sources, Complexity dynamics, network theory, Multi-criteria decision making, Data envelopment analysis, GE1-350, Life cycle thinking, integrated sustainability assessment; life cycle thinking; multi-criteria decision making; stakeholders analysis; data envelopment analysis; agent based modelling; network theory; complexity dynamics; biofuels, Planning and Development, Sustainability and the Environment, Policy and Law, complexity dynamics, Environmental effects of industries and plants, 3305 Geography, Agent based modelling, Stakeholders analysis, stakeholders analysis, agent based modelling, biofuels, 2105 Renewable Energy, Environmental sciences, Biofuels, Network theory, 2308 Management, data envelopment analysis, jel: jel:Q, jel: jel:Q0, jel: jel:Q2, jel: jel:Q3, jel: jel:Q5, jel: jel:O13, jel: jel:Q56
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).217 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
