A key tenet of the work to mitigate anthropogenic climate change is to reduce carbon emissions. An entity; be it individual, company, or nation state, is more able to reduce their carbon dioxide equivalent emissions if they can be monitored and attributed, and their effects measured. The current state of carbon accounting methods does not consistently meet the standards required to tackle this global challenge, therefore this study aimed to identify key methodological practices affecting carbon accounting models and to assess the use of the system boundary.
Models currently available are either input-output based, (using macro-economic analysis), process-based, (using specific carbon emissions attributes through a life-cycle), or a hybrid of the two. A detailed comparison was made and the findings applied to a case study assessing the carbon burden of copper wire. An industry-leading process-based model was analysed using gap analysis and system boundary selection, and identification methods assessed.
Key methodological factors were found to be the inclusion of multi-regional data and sensitivity to the economic situation embodied in the model. Multi-regional data was found to increase carbon accounting model accuracy by reducing the need to make methodological assumptions and increasing the models’ ability to represent real-world complexity. Economic sensitivity also enables the models to better represent complexity by describing differences in location, price volatility and market situations. System boundaries were identified as inadequately reported universally, the improvement of which is key to any future consumption-based carbon accounting accuracy, comparability and usefulness.