There’s an increasing demand for LCA – in scale and urgency

The LCA world is moving away from static snapshots to dynamic models with a focus on providing applicable industry insights. This sometimes means moving away from hard science to feasible and usable solutions. Many presenters focused on scalability, reducing resources through automation, artificial intelligence or machine learning, and tooling solutions that turn complex scientific models into easily digestible user experiences.

We are at an interesting crossroads of evolving science, increased understanding, fast large-scale uptake and simplification. This includes involving life cycle actors outside of a company’s direct control – such as communities in the supply chain, small-scale entrepreneurs and users of products. Equally important is having transparent value chains which share information and also provide investors with information about the sustainability of products and services.

Sustainability solutions involve more than traditional environmental LCA

Another trend in the LCA world is moving away from LCA studies on existing products. Instead, anticipatory studies are on the rise: predicting the impacts of emerging technologies, for example. Assessments now require that a single set of information is used for multiple purposes – from basic carbon footprints to entire life cycle sustainability assessments.

More often these days, the questions that LCA answers require to integrate system thinking and consequential effects outside of the product scope. Sometimes only quantitative information is not the most representative and pairing an assessment with qualitative information can give much more meaning to results. For example, biodiversity footprinting alone does not tell the entire picture but paired with a qualitative assessment, it can unlock many more insights.

Lastly, companies want to focus on solutions: clarity about the actions companies can take to include and increase positive impacts.

Sector-specificity is important

Sector-specific guidelines can help to uncover relevant impacts and solutions for specific industries, product groups and products. For example, the agriculture sector will always have high land use and therefore biodiversity impacts, the plastics industry will have large effects at end-of-life with emissions into air, water and soil and the mining sector will always have high energy use and therefore high climate change impacts. These insights can help to focus efforts while not burden-shifting the impacts.

Regulations in different parts of the world are also often specific to different sectors. The responsiveness of the LCA community should align with the most urgently needed solutions.

A large role for new technologies in LCA

To scale up the use of LCA, automation is indispensable. Take two often manual and tedious tasks: collecting data and matching bills of materials (BOMs) to background datasets. New technologies such as artificial intelligence (AI) and the internet of things (IoT) can reduce the time these take through call and response from software, or extracting and sorting information.

To make LCAs truly scalable, there are still several challenges that need to be addressed. For example, most of the current methods are not yet mature enough to provide reliable outcomes. While there’s a vast amount of data out there, it comes in a variety of formats, which makes it difficult to automate collection and consolidation. Additionally, ensuring transparency and traceability in using AI for sustainability assessments is essential to providing a trustworthy basis for decision-making.

A huge facilitatory role for life cycle networks

Life cycle networks have a huge responsibility to aid in connecting the many stakeholders involved in the sustainability transition. This can involve developing consensus-built knowledge, sharing knowledge between researchers and industry, providing a platform to exchange ideas, publications and opportunities and connecting the broader sustainability field with the LCA community.

For this to be effective, networks need to be able to communicate what results mean and work towards solutions-oriented outcomes for the challenges companies face. This takes a broader view than only providing LCA solutions. The networks have the opportunity to link policy and regulation development with science-based LCA methods and metrics. It’s also important that they focus on the evolution of the LCA community to solve future needs.

Conclusions from another great LCM event

These are big topics and important questions. Is there a silver bullet? Probably not, but many people are working on it with incredible drive. Once again, we learned a lot from all the talented speakers. Events like LCM 2023 motivate us to keep working on solutions to embed LCA in organizations to provide credible, trustworthy and specific data. Getting to scale is a combination of having the resources (capacity building, methodological guidance) and using them efficiently through software and sharing models.

Most of all, we need our ethical compass to do what’s right. The quality of LCA is under pressure, with the increasing complexity of assessments, the large demand and the need for quick and easy solutions. We need to find the right balance – and that’s a responsibility we all have within this ecosystem.