Quantification of Agricultural Land Use Changes in Consequential Life Cycle Assessment Using Mathematical Programming Models Following a Partial Equilibrium Approach

Abstract

Conventional Life Cycle Inventories (LCIs) are static models not considering any mechanism of revenue maximization and price equilibrium under external constraints. The underlying assumption is that demand of a given commodity, irrespective of the amount, can always be supplied by the average supplier (fully elastic market). This constitutes a recognized limitation for the application of Life Cycle Assessment (LCA) to  the evaluation of complex systems, like agro-systems. In the Consequential LCI, the relationships between the activities and processes of a life-cycle are no longer seen as essentially technical connections, based on average data; instead the relevant socio-economic mechanisms are considered via market information and economic models (partial or computable general equilibrium). The paper presents two  partial equilibrium (PE) models of the agricultural sector of the Grand Duchy of Luxembourg, to calculate the LCI and the Indirect Land Use Change (ILUC) effects related to the introduction of a given demand for biomass (in particular maize) for biogas generation. The model is market-based and has farmers’ revenue maximization as the driver, represents the first step of a Consequential Life Cycle Assessment (CLCA) for biogas production in Luxembourg.

Keywords: biofuels, consequential LCA, crops rotation, land use change, linear programming, Luxembourg, partial equilibrium model, positive mathematical programming