In current LCA studies, the environmental footprint of transport processes is calculated using the weight of the product and the distance travelled. This cannot be considered accurate for returnable packagings that reduce in volume when empty. The weight of the freight as well as the number of trips needed varies and is not taken into account in that calculation. In this research an Excel tool is developed based on an existing CO2 calculation tool created by Partners for Innovation where reduction in volume is taken into account for the environmental calculation of the transportation processes. A factor of reduction of volume is created, which describes to what extent the packaging nests or folds when empty. Next, a calculation is performed that states whether and how many extra trips are needed because of inefficient stacking, or how many trips are saved because of efficient stacking. All of the aforementioned data is used to create a final factor which is in turn multiplied by the amount of ton kilometre in the original calculation. Applying data of fictitious scenarios to the tool shows that the new calculation gives a more precise result regarding CO2 emissions. Furthermore, it shows that nesting of packagings makes a significant positive impact on the CO2 emission as it reduces the number of trips needed to transport the packagings. Lastly, a real-life scenario validates the applicability of the tool in a real situation.

Climate change is a large and global concern. The healthcare sector contributes between 6% and 10% to national carbon emissions in developed countries. Within the healthcare sector, operation rooms are very resource-intensive. A lot of energy, medical products, equipment and pharmaceuticals are required to perform surgery on a daily basis. This report explores methods to calculate the carbon footprint of Dutch operation rooms. Based on these, a tool is developed to calculate total carbon footprint and identify contributing processes. A data collection trial is completed during this development, identifying difficulties in the data collection and calculation process as well as generating some emission results. A tool is designed from the results of this trial. It is based on life cycle analysis, while also including emission factors calculated from sector carbon disclosures. Differences from either one of these carbon emission calculation methods are evaluated and if possible, compared. A final selection of calculation methods for each process is selected and used in the tool. The tool is capable of both internally monitoring carbon emissions over different time periods and comparing emission results with other hospitals. Both these functions can be used to identify emission hotspots, inspire improvements and monitor changes in emissions. Sensitivity of the model to different characterization methods and scope definitions is tested. Ultimately, this tool is aimed to aid in reducing CO2-eq emissions within operation rooms. Recommendations are made to further improve this tool and its data collection procedure.