A multi-objective extended input–output model for a regional economy

© 2019 Institution of Chemical Engineers Economies are constrained by a variety of economic, social, and political factors to attempt a reduction in environmental impacts such as global warming. While improvements in technology are commonly the expected general solution, lifestyle changes and modifications on consumption are also necessary to effectively reduce pollution. Such regulations may modify production activities, thus altering economic and social stability. Therefore, analyses need to consider numerous different aspects to locate suitable sectors in the economy in which emission reduction can be accomplished with the least socio-economic impact. Through an extended input–output analysis, this paper gives an insight into the intricate relationship of the sectors of an economic region and their respective greenhouse gas (GHG) emissions. Taking both a producer and a consumer-based perspective, sectors are analysed and categorised through various socio-economic and environmental indicators. The descriptive approach discerns between emission inventories of production activities and embodied emissions of consumption patterns, thus assigning a different responsibility to the carbon footprint of industrial activities. Further, an innovative multi-objective optimisation model is developed with consideration of Gross Domestic Product (GDP), GHG emissions, and employment. This methodology enables mapping an optimised space of scenarios for emission reduction through consumption limitation with a minimal socio-economic loss. The Australian economy was used as a case study. Results show a substantial difference in the allocation of emissions from a producer and a consumer perspective, indicating that many sectors rely on a small number of emissions-intensive sectors for their activities. Through the optimisation, all possible emission reductions are linked to consumption limit scenarios of minimised economic and employment losses. The model is effective in showing areas of interest for further scrutiny in consumption modification to meet a national agenda. Additionally, because of its adjustable and scalable configuration, the model can serve as the basis for future tailored analysis involving simultaneous multiple socio-economic and environmental impacts