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Enhancing the Sustainability of Asphalt Mixtures: A Focus on Operational Factors and Dataset for Environmental Product Declarations

Author

Listed:
  • Rita Kleizienė

    (Road Research Institute, Vilnius Gediminas Technical University, Saulėtekio Av. 11, 10223 Vilnius, Lithuania)

  • Gabriella Buttitta

    (Department of Engineering, University of Palermo, Viale delle Scienze Ed.8, 90128 Palermo, Italy
    National Sustainable Mobility Center (Centro Nazionale per la Mobilità Sostenibile-CNMS), 20158 Milano, Italy)

  • Nicolás Carreño

    (VINCI Construction Shared Services GmbH, Forschung & Technik, Rheinbabenstraße 75, 46240 Bottrop, Germany)

  • Davide Lo Presti

    (Department of Engineering, University of Palermo, Viale delle Scienze Ed.8, 90128 Palermo, Italy
    National Sustainable Mobility Center (Centro Nazionale per la Mobilità Sostenibile-CNMS), 20158 Milano, Italy)

Abstract

The demand for reliable Environmental Product Declarations (EPDs) of asphalt mixtures is growing, particularly as they are increasingly used in public road construction tenders across Europe. However, the reliability and comparability of EPDs remain limited due to two main challenges: (i) significant variability in dataset selection for key materials such as bitumen and aggregates, and (ii) uncertainty regarding the influence of operational factors, including aggregate moisture, mixing temperature, and transportation. The objective of this research is to assess the influence of dataset selection and operational parameters on the environmental performance of an asphalt mixture, focusing on improving the reliability of EPDs. Within this research, a Life Cycle Assessment (LCA) was conducted using a cradle-to-gate approach (A1–A3), including modules C1–C4 and D, in compliance with EN 15804:2019+A2:2020. Primary data were collected from an asphalt plant in Lithuania, while secondary data were obtained from the Ecoinvent database. The sensitivity analyses were performed to investigate the variation of data set choices and key operational factors that influence the environmental impact. The assessment was carried out using the Simapro 9.6 software and the EF 3.1 impact assessment method. The results indicate significant sensitivity to dataset selection, particularly for bitumen and dolomite production, leading to environmental impact variations of up to 41.8% and 35.3%, respectively. Among operational factors, reducing aggregate moisture from 5% to 3% by sheltering stockpiles helps achieve the highest environmental impact reduction (3.2% under the Aggregate Single Score), while lowering mixing temperatures to 130 °C resulted in a 1.6% decrease. Transportation mode selection contributed to emission variations between 1.8% and 6.7%, with long-distance aggregate transport increasing emissions by up to 14.6%. The research findings underscore the critical need for harmonizing dataset selection and optimizing operational processes to improve asphalt sustainability. Standardizing datasets is essential for ensuring fair and transparent EPD generation for asphalt mixtures, particularly when used in road construction tenders, as seen in several European countries. Future research should explore the integration of reclaimed asphalt (RA) and assess its potential environmental benefits.

Suggested Citation

  • Rita Kleizienė & Gabriella Buttitta & Nicolás Carreño & Davide Lo Presti, 2025. "Enhancing the Sustainability of Asphalt Mixtures: A Focus on Operational Factors and Dataset for Environmental Product Declarations," Sustainability, MDPI, vol. 17(20), pages 1-22, October.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:20:p:9349-:d:1776348
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    References listed on IDEAS

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    5. Mayara S. Siverio Lima & Mohsen Hajibabaei & Sina Hesarkazzazi & Robert Sitzenfrei & Alexander Buttgereit & Cesar Queiroz & Viktors Haritonovs & Florian Gschösser, 2021. "Determining the Environmental Potentials of Urban Pavements by Applying the Cradle-to-Cradle LCA Approach for a Road Network of a Midscale German City," Sustainability, MDPI, vol. 13(22), pages 1-14, November.
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