Life cycle assessments (LCAs) are the means of the choice to empower facts-based decisions and drive eco-friendly innovation from the first bolt to the recycling bin. If you’ve ever wondered how tomorrow’s engineers and sustainability experts learn to measure the environmental impact of products, then we are already on the same wavelength. Our recent paper set out to answer a deceptively simple question: How are LCAs taught in universities, and what works best?
How it all began…: A story of fortunate coincidences
The initial impetus for our publication project was an email from Vasiliki Panagiotopoulou, who notified us authors from Graz that she would soon serve as a guest editor for a special issue titled “Reskilling and Upskilling of Workforce on Sustainability and Circular Economy”. As we know her through our collaboration in the IALF working group “Sustainability and Circular Economy in Learning Factories”, we immediately agreed, as our recent efforts to establish practical training in the field of carbon footprinting (Wolf et al., 2023; Rüdele & Wolf, 2024) provided a solid starting point.
It turned out that until that point, there had been hardly any review papers that dealt in detail with teaching approaches regarding LCAs. The only noteworthy contributions were led by Tobias Viere (Viere et al., 2021 & 2024), which prompted us to invite him to collaborate on the paper – and Tobias agreed without hesitation.
Subsequently, we began screening the relevant literature as well as the curricula of European universities. A little later, we gathered additional empirical data through an online survey, which brought us in contact with Sanni Väisänen, who supported our efforts and completed the author team.
The heart of the study: What, how, and why
LCAs are a critical tool for evaluating the environmental impacts of products and processes.
As sustainability becomes increasingly central, it is crucial for future decision-makers to be equipped with the knowledge and skills to conduct LCAs and draw the right conclusions. One must bear in mind that LCAs have evolved into a distinct scientific discipline. So, teaching it is no small feat: the field is complex, and the textbooks are hefty. This leads to the question of how students are currently educated in this matter and whether best practices have already been established. We wanted to map the landscape of LCA education, especially across Europe.
In order to attain a comprehensive overview, we evaluated publications and publicly accessible curricula and subsequently conducted a survey among LCA instructors. In total, the following datasets were compiled:
- 148 analyzable literature sources from the years 1997 to 2024
- Information about 162 courses at 77 universities from 15 European countries
- 109 sufficiently completed online questionnaires
The result? A comprehensive snapshot of how LCA is taught, who’s teaching it, and what students are actually doing in the classes.
What we discovered: Trends, triumphs, and trouble spots
The data was analyzed to provide an understanding of the global state of LCA teaching. Our analysis revealed some interesting patterns:
- Where and who: The results reveal that in the USA, LCA courses are primarily designed for undergraduate students, while comparable courses in Europe tend to be part of graduate programs. Currently, these courses primarily address engineering disciplines.
- How it’s taught: The vast majority (>70%) of the courses include practical exercises. Findings also indicate a trend towards active learning and group projects, which foster essential competencies.
- What’s missing: Usually, the most labor-intensive phase of an LCA is the collection of reliable data; therefore, it seems worthwhile to make students aware of the importance of not underestimating this task. Yet few courses require students to gather primary data themselves. This is a missed opportunity, as it’s where theory meets the messiness of reality.
- Best practices: Publications on flagship projects, along with the survey results, suggest that problem-/project-based learning is valued by educators. Real-life case studies conducted in collaboration with external organizations, typically local companies, are particularly promising.
Future research should focus on broader geographical exploration, longitudinal studies to track changes in LCA education, and assess the evolution of teaching methods and student outcomes over time.
What remains to be said
Our hope is that the paper will inspire LCA instructors to share their own best practices, collaborate across institutions, and maybe even work toward a joint syllabus or set of guidelines to enhance teaching quality. For this reason, we want to thank all respondents (we are still overwhelmed by the high response rate) and, at the same time, encourage researchers to continue this work.
In the end, teaching LCA isn’t just about methods and metrics - it’s about equipping the next generation to make smarter, greener decisions. And sometimes, all it takes to spark a research journey is a single, well-timed email.
References
Rüdele K, Wolf, M. Industrial management meets environmental reporting – how a learning factory for engineering education is used to teach accounting of greenhouse gas emissions. International Journal of Sustainability in Higher Education 25(9), 397-418 (2024) http://dx.doi.org/10.1108/IJSHE-04-2024-0301
Viere T, Amor B, Berger N, Fanous R, Arduin R, Keller R, Laurent A, Loubet P, Strothmann P, Weyand S, Wright L, Sonnemann G. Teaching life cycle assessment in higher education. International Journal of Life Cycle Assessment 26, 511-527 (2021) https://doi.org/10.1007/s11367-020-01844-3
Viere T, Lehmann J, Miao Z, Harding K, Strothmann P, Weyand S, Wright L, Chitaka T, Sonnemann G. Global state of the art of teaching life cycle assessment in higher education. International Journal of Life Cycle Assessment 29, 1290-1302 (2024) https://doi.org/10.1007/s11367-024-02319-5
Wolf M, Rüdele K, Ketenci A, Ramsauer C. Design of a teaching module for the determination of carbon footprints at learning factory assembly lines. Proceedings of the 13th Conference on Learning Factories (2023) https://doi.org/10.2139/ssrn.4470034