A process-oriented life-cycle assessment (LCA) model for environmental and resource-related technologies (EASETECH)

Abstract

Purpose In life-cycle assessment (LCA), environmental technologies are often modelled as “black-box processes”, where inputs and outputs are typically not linked through physical and/or (bio) chemical relationships. This limits transparency and usability of environmental modelling of resource systems for which the conversion of materials and chemical substances in the materials is essential for the environmental performance. We introduce an advanced “process-oriented” modelling framework allowing quantitative and parameterised physical-chemical relationships between input material composition, conversion process units and subsequent output products, promoting mass and substance balanced conversion modelling and environmental assessment. Methods A dedicated LCA model, EASETECH, has been used to provide a user-friendly platform for performing advanced LCA of complex technologies, without the need for additional software/tools. In the modelling framework, the technology is subdivided into individual unit processes. In each process, the characterisation of the input feedstock material into biochemical, physical, chemical and nutritional properties is taken into consideration in each multi-output production flow. For each unit process, the processes governing the mass/energy/substance transition and transformation are described by mathematical equations (i.e. relationships between inputs and outputs) through the use of parameters. A range of new operators were developed to establish these relationships that allow for non-linear responses whereby changes in one flow can give a non-linear response in other flows. The modelling framework and the involved operators are explained and applied to a biorefinery case study. Results and discussion The model facilitates “tracking” of the feedstock material properties from the input to the final products, by establishing mass, substance and energy balances for each conversion unit process. In addition, the process-oriented modelling framework appropriately represents material/substance transition and transformations. The choice of process parameters has considerable importance for the overall results. This was illustrated by one-at-a-time changes in parameter values in two different biorefinery unit processes (i.e. hydrolysis, and fermentation and distillation). In addition, the relevance of feedstock characteristics for the performance of the individual unit processes was proved with fixed parameter sets with different feedstocks. The biorefinery case study demonstrated that the LCA model can be applied to technology cases with different process configurations (e.g. different efficiencies) and different input feedstock properties, where it automatically adjusts to these changes in properties. Conclusions The advanced process-oriented modelling framework offers more flexible modelling of the conversion technology than previously available, improved options for technology development in view of environmental performance, and potentially more accurate results. This provides a significantly improved basis for environmental modelling and decision-making in relation to resource systems.