Participatory Modelling for Carbon Footprint Analysis : A Case Study at DeLava

Abstract: Because of global warming, companies have started to tackle sustainability issues within their operations, but major uncertainties exist on how to establish a quantitative baseline of the current environmental performance of companies. Numerous investigations have been made to assess the carbon footprint of companies with a variety of methods, tools and strategies. However, the lack of transparency in the methods used and the assumptions made could prevent companies to replicate methods and to analyse the results. Because of this, we will investigate how participatory modelling could be used to create a model of the carbon emissions of a company, but also how this method enables the company to understand the methods used and the results from the investigation. By doing this, we also aim to clarify how the process could be set up, which stakeholders that need to be involved and what data sources that could be used. The thesis was conducted as a single case study at a manufacturing company named DeLaval. A participatory modelling process with three major phases was carried out according to proposed methodologies in previous research. In the first phase, a conceptual model of the system accounting for the emissions was created. In the second phase, a quantitative model of the system was developed by gathering data and validating the calculation methodologies with operational stakeholders within the company. In the third phase, the results were verified, and the company could set up sustainability targets based on the findings. The outcomes of the case study showed that there are major benefits with applying participatory modelling because different perspectives throughout the organisation could be gathered efficiently to create a representable model of the company. The modelling strategy had more benefits in organisational areas characterised by high complexity with numerous of different stakeholders with different roles or by geographical distribution. To create the model, primary data consisting of master product data and transactional data was used, together with secondary data, consisting of carbon emission coefficients and gap filling data created by the modellers. By basing the calculations on the methodology set up by the GHG protocol and anchoring the root definition of the system with strategic stakeholders, the results were trusted by the organisation.