How can you conduct a life cycle assessment with ease?

Conducting a life cycle assessment efficiently involves gathering data on resource use, emissions, and impacts across a product's life stages. Utilize software tools specifically designed for life cycle assessment to streamline data collection and analysis. Collaborate with stakeholders and experts to ensure comprehensive data accuracy. Prioritize key impact areas based on environmental significance and focus efforts accordingly. Regularly review and update assessments to reflect changes in processes, materials, and technology for continuous improvement in sustainability performance.

The goal of an LCA can for example be product optimization (e.g. through weak point analysis/comparison of different possible options) or advertising. This also determines the audience. The scope includes, among other things, the definition of - analyzed systems - a functional unit (for easier comparison, e.g. pen: per 100 meters written) and the respective reference flows - system boundaries (what is taken into account) - assumptions made - data sources and their quality - allocation methods (distribution of environmental impacts to various existing process products) - impact categories (e.g. global warming potential, eutrophication potential, ...)

Conducting a Life Cycle Assessment (LCA) with ease involves: 1.Define Scope: Clearly outline the goals, boundaries, and functional unit of the assessment. 2. Gather Data: Collect data on inputs, outputs, and processes throughout the product's life cycle. 3. Use Software Tools: Utilize LCA software for streamlined data analysis and modeling. 4. Apply Simplified Methods: Employ simplified LCA methodologies for quicker assessments when detailed data is limited. 5. Interpret Results: Analyze findings to identify hotspots and improvement opportunities. 6. Iterate: Refine the assessment based on feedback and evolving knowledge. 7. Communicate: Clearly communicate results to stakeholders for informed decision-making.

Self-collected primary data is obviously ideal, as you can be sure of its quality and specificity. The required sub-processes are recorded as precisely as possible, then respective inputs and outputs are measured, surveyed, researched or similar. As this may not always be possible or only with too much effort, secondary data may have to be used (even if only as a supplement), e.g. from published studies or existing databases. In this case, the data's origin definitely needs to be checked: When is the data from? Are the system boundaries appropriate? How specific is the data? Are the process and assumptions similar to your own case? The geographical origin is also important here, as the results may differ across local standards, laws, etc.

The product life from raw material extraction to final disposal (life cycle) is divided into basic processes for which each input and output is documented (see above). These "flows" can go from one process to another within the system (e.g. production and utilisation of a component) - raw materials/resources and emissions, however, come from or go into the environment. This is your Life Cycle Inventory. These elementary flows are then each summed up and combined into impact categories, e.g. all climate-relevant emissions to the global warming potential, measured in CO2 equivalents. This can be done using various methods. Other impact categories include fossil primary energy consumption, eutrophication, acidification, land and water use,...

The achieved results must be checked. Are goal and scope achieved? Are system boundaries correct? What were difficulties and uncertainties? Do the results fit to each other and maybe similar studies? Additionally, different scenarios can be set up in which different factors are varied. On the one hand, this can show how the results would change with slightly different assumptions (uncertainties). On the other hand, the optimization potential can be specified. Generally, a differentiated evaluation is important. Results may e.g. differ depending on the impact category. Also, limitations must be taken into account. Especially when publishing an LCA, a critical review may make sense. In the case of comparative LCAs, it is mandatory.

Other than a report, for communication, especially to non-experts (consumers and often producers), diagrams may be useful. For example, bar charts can illustrate: - Different process steps next to each other/in different colors in one bar (or broadly next to each other & more detailed by color) to show impacts - Different scenarios next to each other to show uncertainties/possible optimization In a product comparison, line diagrams (impact over lifetime) may be possible to show the break-even point. All impact categories should be considered. Tables can be used for this purpose; diagrams could be shown proportionally. It can also help to offer comparative values (e.g: How far would you have to drive for this global warming potential)