Introducing a localised spatio-temporal LCI method with wheat production as exploratory case study

The use of dynamical information, which is temporally and spatially explicit, to quantify environmental impacts is gaining importance in recent years. Life Cycle Assessment has been applied to identify environmental impacts of, for example, wheat production. However, conventional Life Cycle Assessment is typically limited by its static nature and cannot explicitly consider temporal and spatial variability in its matrix-based mathematical structure. To address this limitation, a novel dynamical Life Cycle Assessment framework that applies spatio-temporal mathematical models. in Life Cycle Inventory is introduced. This framework employs the existing Enhanced Structural Path Analysis (ESPA) method paired with a spatial dispersion model to determine the localised emissions over time within the Life Cycle Inventory. The spatially explicit calculations consider emissions to the surrounding area of an origin. A case study was undertaken to demonstrate the developed framework using the production of wheat at the Helford area in Cornwall, UK. Results show the spatio-temporal dispersion for four example emissions atmosphere, soil, flowing and groundwater. These outcomes show that it is possible to implement both spatial and temporal information in matrix-based LCI. We believe this framework could potentially transform the way LCA is currently performed, i.e., in a static and spatially-generic way and will offer significantly improved understanding of life cycle environmental impacts and better inform management of processes such as agricultural production that have high spatial and temporal heterogeneity. (C) 2016 The Authors. Published by Elsevier Ltd.