Combination of LCA databases solves challenges for measuring environmental impacts satellite mission
The European Space Agency (ESA) is an organisation gathering knowledge about the earth, its immediate space environment, our solar system, and the universe. It also develops satellite-based technologies and services and promotes European industries.
ESA knows how important it is to understand how their activities impact the environment, and to minimise these impacts, which is why they started the Clean Space Initiative. Under this initiative, ESA requested a consortium consisting of VITO (The Flemish Institute for Technological Research), PRé Consultants and QinetiQ Space to do a life cycle assessment (LCA) of a satellite mission.
The Challenge Of Life Cycle Assessment For Specialist Missions
LCA is a powerful tool for assessing the environmental impact of products and services. Most LCAs use LCA process databases, containing products and processes that can be selected on basis of units such as mass or distance. Selecting one kilogram of a certain plastic, for instance, outputs a list of environmental flows such as the resources needed for its production and emissions to air, water and soil.
The power of these databases is that they contain many common, mass-produced products. The space industry, however, often uses specialist materials and custom-made components. Contrary to mass produced products, for custom-made components, a high proportion of production costs goes into activities such as research and testing rather than manufacturing. An average mass-produced component or material cannot be compared with custom-made components used in the space industry, which means we cannot use LCA process databases as single data source to do the analysis.
How To Accurately Estimate Impacts of Specialty Products?
From the very beginning of the project, the consortium realized that using process databases would underestimate the impact of a satellite mission. The materials and components used in the space industry need to satisfy stringent safety and quality requirements, and are subjected to more research and testing than average products. To cover these gaps in process databases, we decided to investigate the possibility of using Environmental Extended Input Output (EEIO or IO) databases, which cover specific economic sectors instead of products and processes.
Input Output databases describe the sale and purchase relationships between economic sectors such as agriculture, industrial sectors and services in relation to their environmental impact. Every purchase from a certain sector in an Input Output database is related to the impact caused by that sector.
The flow between sectors is expressed in monetary units such as euros or dollars. This way, the impact on climate change, for example, can be related to one euro or one dollar spent in that sector. If someone spends 100,000 euro on research, then their impact on climate change can be calculated by multiplying that sum with the impact per euro specific for the research sector. IO databases can be used to fill the data gaps in process databases, such as lack of information on extensive research and testing of space mission components, and their related flows.
Unlike process databases, IO-databases are developed top-down and give a complete picture of all environmental impacts (all inputs) throughout the complete supply chain in the various economic sectors of an economy. This can be a national economy or an economy of more countries together, like the EU.
A disadvantage of using IO databases is their low accuracy. A dataset for a particular sector most likely covers a broad range of industries, which are related in some way but do not all have the same impacts. Since, for example, our satellite’s solar panel cannot be found in a process database, we would have to look in the IO database. The IO database does not contain a specific dataset on the space solar panel industry, so we need to choose the much more general electronics sector, which covers – among many industries – photovoltaic cells and devices. However, since the estimated impact of our solar panel is derived from the average of the entire industry, we might still be over- or underestimating.
Solution – Getting the Big Picture With Hybrid LCA
In summary, doing an LCA on such a specialist project as a satellite mission is problematic because LCA process databases don’t contain custom-made products and IO databases only fill these gaps in inaccurate ways. The solution is a hybrid LCA, using data from process databases as well as data from IO databases.
We modelled components such as solar panels with process databases, adding the specific materials used in the space industry to the dataset. Research and testing of these components was accounted for using IO databases, where we added the estimated investments to a dataset specific to the research and development sector. We were able to follow this strategy for the whole study and managed to calculate the final environmental impact.
In this way, we used the best of both worlds: the accuracy and transparency of a process database and the completeness of an Input Output database. The consortium believes that the results derived by such a hybrid LCA give the most accurate estimation of the impacts caused by a satellite mission.