A causal network approach using a community well-being framework for an initial impact assessment of large-scale energy infrastructure projects.

Impact assessment as a discipline continues to evolve and search for ways to address challenges that are wicked, systemic, and unconventional. More guidance however is required on integrating multi-disciplinary and novel approaches without losing the richness of impact assessments. This paper explores integrating the causal network approach, underpinned by a community well-being framework, into environmental and social impact assessments. We do this by using a hypothetical scenario of large-scale green hydrogen industry in Australia and engage an interdisciplinary team of experts representing a broad experience across the social, economic, and environmental sectors, via interviews and a workshop. The result is a complex detailed causal network, depicting both environmental and social risks and opportunities associated with the hydrogen industry. We discuss using simple and complex versions of causal networks as both are needed to when communicatng with all relevant stakeholders. We found that the causal network approach is useful for the initial scoping of potential social and environmental impacts, especially for a multi-disciplinary team. Three areas were identified to further strengthen such an approach to facilitate a fully-fledged impact assessment in a real case. First, causal relationships need to be evaluated to assess the magnitude of the impacts and identify mitigation measures and incentives. Second, stakeholders, including local communities, should be involved throughout the assessment process, beginning from the conceptualisation of such assessments. Third, the causal network approach presented in this paper is likely to benefit from incorporating ecological frameworks (or similar) to expand environmental pathways in the network. • Structured mapping of cause-and-effect relationships of complex systems. • Use of a community well-being framework for social and biophysical dimensions. • Value in developing complex and simplified representations of reality. [ABSTRACT FROM AUTHOR]