System dynamics as a tool to include time-dependent factors in environmental assessment modelling

Life Cycle Assessment (LCA), as conceived in ISO 14040 series, is based on a steady state and linear model. Time dimension is not considered and changes in time are not foreseen. Therefore, the oversimplified ISO LCA structure could fail to capture complex dynamics evolving over time, which in some cases can be crucial in providing a proper environmental assessment. Several attempts to introduce time dimension in LCA modelling, with particular regard to Life Cycle Inventory (LCI), have been proposed in the past, but dynamic approaches to LCA are still pioneering. On the other hand, system dynamics represents a well-established method for analysing the interrelationships and feedbacks existing within complex systems, thus exploring the non-linear and time dependent causalities and consequences reflective of real world behaviour. Our research group is studying the way for combining system dynamics and LCA to implement a dynamic LCI. The methodology proposed would find application within the European projects Star-Pro-Bio, aimed at the development of sustainability assessment tools for bio-based products, and TO-SYN-FUEL, aimed to demonstrate the conversion of biomass into advanced biofuels. The present work represents an exercise where a system dynamics modelling framework is built in order to implement a dynamic LCI. The main objective is to provide an example case of generation of inventory data for life cycle environmental assessment, considering their interrelationship with a multiplicity of time-dependent and case-specific environmental and economic variables in a unique comprehensive framework. In this way, complex dynamics can be managed and made explicit, allowing the study to highlight how they affect the assessment of environmental impacts. Starting from a marginal demand for biomass feedstock (e.g. maize) generated by the production of a novel bio-based product, the aim of the developed system dynamics model is to quantify the increased use of fertilizers and the consequent change in their stock in agricultural land, which is also mutually linked to the quantity of chemical compounds emitted into the environmental compartments. This way, varying the production of the novel bio-based product will provide a dynamic inventory of the fertilizer-derived emissions. Emissions generated over time can ultimately be converted into environmental impacts through conventional characterisation factors.