Emad Yaghmaei

Dr. Emad Yaghmaei


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 June 2026 in Applied Sciences
Verified
Journal Article
Open access
PDF file
DNDavid F. Nettleton
David F. Nettleton
DGDavid Fernández Gutiérrez
David Fernández Gutiérrez
Hasler IglesiasHasler Iglesias
Hasler Iglesias
DSDaniele Spinelli
Daniele Spinelli
MMMatteo Maccanti
Matteo Maccanti
EYEmad Yaghmaei
Emad Yaghmaei
Background: This paper presents the development of digital tools created within the BIORADAR European project to improve user access to Life Cycle Assessment (LCA) results from the project’s use cases and to enable users to upload, benchmark and analyze their own data. The work addresses common challenges in circularity and environmental impact assessment, particularly data availability and expert-assisted self-assessment for users such as small- and medium-sized enterprises. Methods: The LCA data for the project use cases is calculated using the Environmental Footprint methodology. Benchmarking compares bio-approach use cases with traditional approaches across three key sectors selected by the BIORADAR project: fertilizer, textile and packaging. These sectors are recognized by the European Commission as three of the most important sectors in terms of environmental impact. Case impact factor data are normalized using a reference statistic, and a weighting is assigned to each key performance indicator to calculate the global score. Individual impact factor values can also be used for benchmarking. Synthetic data are generated through an advanced statistical decomposition algorithm. Advanced data analytics are provided with clustering and a decision tree algorithm using supervised machine learning. Results: Two examples of decision-oriented case studies are used to illustrate how the platform can support the interpretation and use of already computed LCA results in realistic settings. The web-based expert-assisted self-assessment tool, developed in JavaScript, allows users to input their data, benchmark them against project results and perform multidimensional data analysis. The resulting digital tools provide access to LCA data for each use case, generate realistic synthetic datasets preserving key statistical properties, support benchmarking of both project and user-uploaded cases, and perform data analytics, which complement the benchmarking module with a structural and exploratory interpretation of the data. Conclusions: Overall, the tools integrate use case benchmarking, data processing, advanced analytics and user interfaces to facilitate environmental self-assessment and comparison within the BIORADAR framework.