Life Cycle Assessments & the Fashion Industry – The good, the bad, the potential.
Big fashion brands are under fire, receiving fees- or even sued for greenwashing claims. In this commotion, a lot of well-deserved attention goes to the credibility of environmental data. Where does this data come from? How reliable is it? How reliable are the measurement methods? In this article we go through the good, the bad and the potential of Life Cycle Assessments as environmental impact measurement method for the fashion industry.
With the recent increase in greenwashing claims for big names like H&M, Boohoo, Asos, Asda, Life Cycle Assessments (*LCA for short) as a measurement method for the environmental impact of products – has come under quite a lot of critique.
These brands are often accused of showing inaccurate environmental data and untransparent/bad sustainability reporting. Of course, we want to know how these brands acquired their ‘environmental data’. And that’s where LCA comes to the surface.
In this article, we dive into the 3 most common critiques on Life Cycle Assessment and share our views as an LCA software provider.
What’s a Life Cycle Assessment?
Life Cycle Assessments or LCA is one of the main scientific environmental impact assessment methods available. It allows you to measure the footprint of your product. LCA assesses the environmental impact of a product throughout every phase of its life- the so-called product life cycle. Think of:
Fashion brands and textile manufacturers can choose which different life cycle phases they want to include in their LCA. For example, the lifecycle model Gradle-to-gate focuses only on the footprint of your production until your product leaves the factory. Therefore including everything in your ‘upstream’ value chain e.g. the raw material extraction, transport of raw materials, and production processes.
LCA offers the use of environmental impact databases made from scientifically researched and approved impact references of materials and processes – such as EcoInvent or Gabi. These average impact references are called ‘secondary data’, and help companies start up their measurements if they don’t have all the raw primary data on their processes and materials yet. Your primary and secondary data input for your product results in a certain amount of emissions. These emissions are then translated into impact outcomes in LCA.
The LCA results: 15+ impact outcomes on your product, which include carbon emissions, land use, water pollution, health damage, etc.
The 3 main critiques on LCA in fashion + our response
We summarized the critique on LCA in Fashion into three main critiques.
1. Many brands use average data, this is bad.
Average data here refers to the use of impact databases in LCA such as EcoInvent. Usually, average data is associated with ‘quick and dirty’ LCAs. Companies only use and rely on average data from databases, which isn’t specific to their product. Why? Because it’s faster and easier than gathering primary data from suppliers – and diving into relevant materials and processes on-site- or in the value chain. It ‘does the deed’ so to say.
The result: average footprints that might give you a good indication of where your biggest impact comes from. But don’t give an accurate depiction of your product. How can you make sustainability claims – if your footprint results aren’t true to your product’s reality?
1.1 Our response:
Average data isn’t inherently inaccurate, as it’s based on previous scientific research. But it does have both negative and positive associations to it.
a. The negative: The use of average data is often not communicated transparently and simply used to say ‘Voila this is my actual impact! We are doing a great job’. Moreover, many companies don’t work on actually gathering the primary data necessary to improve the quality of their footprint results – after their initial measurements. Still, this isn’t a problem related to LCA, but how companies and researchers use the method.
The main solutions here are increasing LCA knowledge within companies, strict legislation, and punishment for brands practicing greenwashing.
b. The positive: The purpose of LCI databases in LCA, is so companies are able to start with impact measurements. It allows for filling the gaps where companies lack primary data. Primary data is more accurate raw data that is directly collected from main sources. However, a lot of this data lies with manufacturers, suppliers, or distributors. Making it difficult to already have all primary data ready, when companies start their first LCA. The more fragmented, intransparent, and complex supply chains are – the bigger the hurdle (associated with high costs) to collect this primary data.
Therefore, average data is a great means to start your measurements. It gives a good indication of which processes or materials cause the biggest impact. The result: focus on where to invest your sustainability efforts and which suppliers should be prioritized for requests of raw primary data (inventory data or LCA’s of their products).
Plainly said: the higher the quality of data you put into your LCA, the more accurate its results. The more in-depth primary data you gather, the more credible your results will be. But this does require time and effort.
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2. LCA isn’t nuanced enough.
Often companies use very specific materials in their products. But as soon as they start looking for the corresponding impact references, they can’t find the ones specific to their product. So, brands that are putting in the extra work to really create innovative, sustainable processes or materials – can’t be rewarded for it.
2.1 Our response:
This is a very relevant issue a lot of companies face. Their product is different from the average impact reference (e.g. their cotton was produced differently or comes from a very specific place), so their LCA results won’t be specific enough to their product.
But, there’s a solution. Multiple impact references can be tweaked and combined together to create a reference for a company’s specific process or product. Say, you use an energy mix that doesn’t exist in an LCI database. In that case, you can use the background data behind the individual references of these energy types- and combine them. This creates an LCA reference that better resembles your product’s production process and supply chain.
Still, even without all primary data available, background processes can be adjusted with the data a company did already gather. Enabling a more realistic data model and increasing the overall data quality and reliability of your LCA (i.e. less insecurity of the outcomes). The more layers and specific reference combinations you add to your LCA, the more accurate the results will be. And the more useful it is for companies purchasing your products – to make their LCA’s more credible too.
Creating these in-depth references isn’t always easy. That’s why offer specialist support to our software users to help them modify data behind the environmental database references. Ensuring companies have the most realistic LCA for their specific case.
3. ‘Comparing’ the impact of products based on…what?
Quite some brands want to prove they are more sustainable than similar products. To show the difference, they want to compare their product to an average one. But how do you know what a standard product looks like? The fashion industry currently doesn’t have an ‘industry standard’ for any kind of product, but they still make these claims. Potentially creating their own industry standard that could make their own products look better and mislead consumers.
3.1 Our response:
To create a clear level-playing field in product footprint comparisons – we need better industry standards available to measure the impact of textile products. The European Commission’s PEF standard (Product Environmental Footprint) will be the way forward to harmonize impact measurements and enable our users to make LCAs according to the same standards.
The PEF is still being developed, but will be a standard way of measuring and reporting LCA – also for different product groups (using the PEF’s Product Category Rules, also PEFCR’S). These PEFCRs create industry average products, that enable benchmark values for companies. This allows for better comparisons between brands and their products. Finally, leading to a better regulated and transparent way of measuring environmental impacts in the textile industry.
What brands can do until the PEF has arrived:
Our final conclusion on LCA in fashion
The quality of LCA results truly depends on the quality of the data that goes in. Having accurate and credible LCA results comes down to the amount of effort companies want to put into it. And sadly, many companies who have the resources to gather the raw data necessary for accurate LCA’s – don’t invest/or apply them properly and transparently.
A proper LCA takes time and requires the right knowledge and skillset to really understand what you are looking at (e.g. LCI databases, average data, LCA results, etc). That’s why it’s crucial we share knowledge between LCA researchers and professionals in specific industries. One of the reasons we share free LCA knowledge on our website as well.
We shouldn’t forget sustainability is a journey that requires effort. It’s okay if a company starting its sustainability journey, might not have all the data sourced necessary for a 100% accurate LCA. That’s exactly why environmental databases such as Ecoinvent exist. It helps companies to get started with measuring and quantifying their environmental impact. However, plainly ‘having environmental data’ should never be the end stop of sustainability efforts. Companies ALWAYS need to be transparent on:
LCA is one of the most trustworthy impact measurement methods currently existing. Instead of breaking it down, let’s increase attention to greenwashing, stimulate the market to use primary data, and adopt newly developed standards & methods to increase comparability and credibility (such as PEF).