Environmentally extended input-output analysis (EEIOA) is an important assessment tool that quantifies how demand for goods and services leads to resource use and emissions across the economy. Application are most common in carbon footprinting at regional, national and global scales where full sectoral coverage is required. However, a major limitation arises when EEIOA is used to investigate resource use and emissions that require spatially-explicit impact assessment for meaningful interpretation (e.g. water use; ISO14046:2014). This is because conventional input-output tables are usually produced at the scale of political units, which are typically not well aligned with environmentally relevant spatial units.
In new research by CSIRO and Deakin University, a high spatial resolution water use account and spatially-explicit water scarcity characterization factors were used to develop water footprint extensions for 26 agricultural and 75 industrial sectors in Australia. These extensions were subsequently coupled with a multi-regional (Australia and rest of world) input-output model. The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally, which is a significant advancement from previous EEIOA studies that report water use without impact assessment. The example shown in this study, whereby LCA impact category indicator results are used to augment the input-output model (rather than satellite data sets based on inventory-level accounting of natural resource use or emissions), is viewed as a feasible general approach for incorporating spatially-explicit impact assessment in EEIOA, thereby bringing EEIOA more into line with best practice impact assessment in LCA and extending the application of EEIOA to environmental concerns where regionalized impact assessment is necessary.
Access the study here. Ridoutt, B.G., Hadjikakou, M., Nolan, M., and Bryan, B.A. 2018. From water-use to water-scarcity footprinting in environmentally extended input-output analysis. Environ Sci Technol DOI: 10.1021/acs.est.8b00416