Best options for large-scale production of liquid biofuels by value chain modelling: A New Zealand case study

Ian D. Suckling, Ferran de Miguel Mercader, Juan J. Monge, Steve J. Wakelin, Peter W. Hall, Paul J. Bennett, Barbara Höck, Nouri J. Samsatli, Sheila Samsatli and Muthasim Fahmy

Applied Energy, 2022, vol. 323, issue C, No S0306261922008510

Abstract: Biofuels are a promising low-carbon replacement for fossil fuels in the transport sector. However, how should a country without an existing biofuel industry, such as New Zealand, go about implementing large-scale production and use of biofuels? We used value chain modelling and optimisation to identify lowest-cost options to replace existing liquid fossil fuels used in New Zealand, and how to make the transition. Multiple scenarios, e.g. 5–50% biofuel substitution, different land use assumptions, were examined. Novel features were added to the Biomass Value Chain Model to consider the impacts of land quality on biomass production, land use competition, existing and new plantation forests, and replacements for multiple liquid fossil fuels used. Credible routes exist for large-scale biofuel production in New Zealand, which could contribute significantly to meeting its GHG reduction targets. Key results include (i) Lowest cost substitution of 30% of fossil fuel use by 2050 reduced GHG emissions by 80% at a levelized cost within the range of prices seen for imported fossil petrol and diesel over the last 10 years; (ii) Drop-in biofuels from non-food feedstocks, particularly forestry on non-arable land, are the most attractive in the long term; and (iii) Pyrolysis plus upgrading of lignocellulosic feedstocks and biodiesel from canola were amongst the lowest-cost conversion options. The most important contributors to the cost are the: conversion process capital and operating costs; delivered cost of feedstock(s) suitable for each process; conversion yields; and options for co-product sales and distributed processing. Land use decisions, conditioned by land prices, affected the preferred feedstocks, but also where biomass was grown and converted into fuels, fuel costs, and GHG reductions. Conversion plant locations were driven by feedstock availability and costs through time and existing infrastructure.

Keywords: Biofuel value chains; Optimisation; Scenario modelling; Plantation forests; Land use (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1016/j.apenergy.2022.119534

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