Maëlys Kathy Courtat

PurposeEnvironmental rating ecolabels (ERE) are developing rapidly across Europe, intending to guide sustainable purchasing choices through performance ratings derived from life cycle assessment (LCA). Integrating robust data quality methods in the LCA modelling stage is essential for accurate and comparable ratings, but challenging as ERE must be feasible to generate with reasonable effort for broad adoption. The use of secondary life cycle inventory (LCI) datasets, alongside actual product information such as bills of materials, is inevitable. However, the selection process for secondary LCI datasets and its implications for environmental ratings have yet to be investigated.MethodsWe examine the context-dependent suitability of secondary LCI datasets (aka their representativeness), hypothesising that differing levels of representativeness could lead to differences in product ratings. In a case study involving 94 laundry detergent products, we investigate how different secondary dataset choices influence the resulting aggregated LCA results (single scores), relative product rankings, and environmental ratings. Four distinct data scenarios are defined, in which the production of 19 key ingredients is represented through datasets of varying representativeness (from most specific to most generic).ResultsOver 60% of the products studied obtained a different rating under at least one of the three lower representativeness (more generic) data scenarios explored as compared with the rating obtained when the highest representativeness (most specific) data scenario was used. Lower representativeness scenarios also led to wider distributions of product single scores, with scenarios which utilised LCI data representing the function of ingredients (e.g. alkalinity source) or generic LCI data (e.g. organic chemicals) showing the most significant deviations from the distributions under the specific data scenario. This highlights the importance of having clearly defined, consistent data quality management approaches for the LCA stage of ERE.ConclusionsProduct information (e.g. formulation and packaging specifications) from primary sources should be combined with representative LCI datasets from third party databases to obtain reliable product ratings. We demonstrate that the representativeness of secondary datasets can be evaluated through three contextual indicators of data quality (technological, geographical, and temporal representativeness) to help guide the data selection process aligned to defined data quality thresholds. Based on our findings, practical recommendations are provided for data quality management in ERE. Scheme developers are encouraged to embed these in their methodologies to underpin transparent, robust labelling for product comparison.

Environmental rating ecolabels (ERE) represent a new generation of consumer-oriented communication tools. They aim to derive product environmental ratings from the assessment of multiple environmental impacts, thereby facilitating comparison of the environmental performance of products. This type of ecolabel has developed rapidly in Europe in recent years. However, their fragmented development means that numerous ERE schemes now co-exist with nearly as many distinct methodologies underpinning them. While most approaches are based on Life Cycle Assessment (LCA) calculations, they differ significantly in key methodological aspects – e.g. LCA modelling assumptions, impact category selection, aggregation of LCA results (including addition of non-LCA information) and conversion of aggregated numerical results into (usually categorical) ratings. The lack of harmonisation and scientific scrutiny to which ERE schemes have so far been subject represents a threat to the fulfilment of their original purpose: fair and evidence-based product comparisons in support of sustainable consumption decisions.

The work presented in this thesis characterises the emerging ERE landscape and examines key methodological aspects of ERE which require further development and harmonisation to achieve increased scientific robustness and credibility. Through four interlinked papers, this thesis demonstrates that designing and developing ERE schemes is a complex undertaking. From the LCA modelling stage to the display of a product rating, multiple and interrelated methodological stages exist, combining both empirical and normative decisions. Chapters 3 to 5 demonstrate that these methodological choices – specifically the design of the rating approach (Chapter 3), product categorisation considerations (Chapter 4), and the selection of secondary LCI datasets (Chapter 5) – can have a substantial impact on the ratings awarded to products.

Methodological development must therefore be approached in a rigorous, transparent and evidence-based way if these instruments are to gain widespread traction, providing effective and trustworthy information to apprise consumption choices. A pioneering framework (Chapter 2) is provided to guide the development of robust ERE schemes. Additional research areas are identified, notably to better understand and manage uncertainty. The work presented in this thesis is grounded in sector specific case studies and provides relevant recommendations for ERE scheme developers, policy makers and industry actors.

Contact details: m.courtat@surrey.ac.uk (Maelys Courtat - Author), j.sadhukhan@surrey.ac.uk (Jhuma Sadhukhan - Supervisor), rj.murphy@surrey.ac.uk (Richard Murphy - Supervisor)

Contact details: m.courtat@surrey.ac.uk (Maelys Courtat - Author), j.sadhukhan@surrey.ac.uk (Jhuma Sadhukhan - Supervisor), rj.murphy@surrey.ac.uk (Richard Murphy - Supervisor)

The award of environmental rating ecolabels (ERE) to products involves the definition of a common rating scale on which products can be placed and compared. This process is essential to translate Life Cycle Assessment (LCA) results into relative performance ratings that can effectively orient consumers towards more sustainable consumption choices. Yet, limited evidence currently exists regarding the choices available to scheme developers within this process, and their implications for final ratings. Using the food sector as a case study, we explored the significance of various rating scale parameters for ERE schemes. Potential product ratings were established for 2253 products based on cradle-to-shelf environmental single scores derived from the Agribalyse 3.1 database. We investigated the effects of three distinct 'thresholding' scenarios for establishing the placement of products in five environmental performance classes (A-E) along the rating scale; these were the class width, the number of products per class, and a hybrid of the two. The effect of other methodological choices made prior to the rating stage (e.g., functional unit and data linearity) on final ratings were also considered and assessed. The choice of thresholding approach was a critical determining factor in the distribution of products across the A-E rating classes. Nearly 90 % of products experienced a shift of one class or more depending on the scenario chosen to define the class boundaries, with 50 % of products obtaining a different rating across the three scenarios investigated. The distribution curve of the single scores from which ratings were established was another major factor and was influenced by choices in the functional unit definition, the linearity of the data, as well as the sample dataset used to establish the rating scale. Overall, we demonstrate the rating approach to be a fundamental component of an environmental rating scheme's methodology, necessitating clear consideration from the earliest stages of methodological development and transparent, thorough documentation regarding its definition.

Environmental rating ecolabels are a new generation of ecolabels. They are intended to enable consumers to compare the environmental impacts of multiple products and make more sustainable consumption choices. Falling outside of the three types defined in the ISO 14020 environmental label and declarations series, the recent proliferation of these business-to-consumer communication instruments has resulted in the creation of a plethora of methodologies to derive product performance ratings. Interest from consumers wanting more information on the products they purchase, as well as the promise of policy instruments aiming to increase transparency and combat greenwashing, are fuelling further multiplication of schemes. A move towards more credible, evidence-based environmental rating ecolabels is therefore urgently needed to promote assessment based on scientific understanding, gain consumer trust, and realise policy objectives. We propose a framework based on four core principles-i) relevance, ii) scientific robustness, iii) trust and transparency, and iv) feasibility (scalability, affordability)-with 18 guidelines that can be followed by rating scheme developers. We characterise the rise of environmental rating ecolabels in geographical Europe and build an inventory of 33 existing schemes, at various stages of development and implementation, to which we apply the framework. This reveals the potential for significant improvement in current schemes, indicating important areas for development. The framework provides a valuable guide for the development of new schemes or an evaluation grid for existing initiatives.