Life cycle assessment-based multiobjective optimisation of synthetic natural gas supply chain: A case study for the Republic of Ireland.

This article provides a novel designing tool that integrates life cycle and techno-economic analysis in a spatially-explicit optimisation model for the supply chain for biomass-derived synthetic natural gas production from forestry residues, identifying the configurations, including number of plants, locations, sizes, that minimise the environmental and investment associated, necessary for a sustainable transition to a decarbonised gas network. Results show the conversion stage having the highest negative single-score environmental impact with 1725 μPt/MWh, mostly due to the use of rapeseed-oil methyl esters, collection of feedstock with 858 μPt/MWh, then feedstock transport with a maximum of 103 μPt/MWh. The use of rapeseed-oil methyl esters instead of mineral oil, the substitution of biomass-derived synthetic natural gas and co-produced electricity to the natural gas and electricity grids and their end-use provide a net environmental benefit of −1716 μPt/MWh in the conversion stage. However, the benefit is limited to climate change, ionising radiation, ozone depletion and resource depletion, while eutrophication and acidification potentials, photochemical ozone formation and particulate matter categories are damaged. The environmental impact of the supply chain per unit of MWh of biomass-derived synthetic natural gas produced is minimised when increasing the number of the plants and minimising their sizes, reducing the impact of transport. However, when the environmental impact is coupled to its cost, a single plant is the one that presents Pareto optimal solutions. Maps of the configurations that minimise the environmental impact per unit euro expended varying the number of plants are produced, confirming a 67.6 MW single plant as best solution. Image 1 • Bio-SNG production is beneficial for 4 out of 10 of the considered impact categories. • The environmental impact is minimised for small multiple plants. • The single-plant configuration represents the Pareto optimal frontier. • The multiobjective optimisation suggests that large capacities are favoured. • The conversion stage is the source of major impact, because of the use of RME. [ABSTRACT FROM AUTHOR]