• Natalya Tsoy
  • Valentina Prado
  • Aike Wypkema
  • Jaco Quist
  • Maurice Mourad

Environmental analysis should be performed early in the Research and Development (R&D) phases of new technologies to timely determine potential impact and, thereby, include prevention and minimization of unfavorable ecological impact into the innovation process. Here, we demonstrate the application of anticipatory Life Cycle Assessment (LCA) on novel anti-reflective coatings used for greenhouses in the Netherlands. Currently, these coating technologies are developed at the laboratory scale (lab-scale), but they have the potential to be transferred to commercial scale on the short term. What-if scenarios have been used to scale-up the coating production process to pilot and industrial scales. The scenarios were developed by optimizing the laboratory scale coating production parameters. A cradle-to-grave LCA has been done to compare novel coatings with conventional coatings. The functional unit has been defined as the production of 1692.30 kg of tomatoes in greenhouses during 30 years. Results indicate that the novel coating manufactured at industrial scale can compete with conventional coatings in terms of the environmental performance. Furthermore, LCA shows that the novel coating assessed does not bring environmental benefits as compared to employing uncoated glass. However, the use of the glass coating in the greenhouse may bring economic benefits during functional lifetime by means of increased yield of crop (e.g. tomatoes). Different pathways of the technological development of the novel coating have been considered in the sensitivity analysis. The option that includes glass manufacturing in the Netherlands rather than China has led to the best environmental impact results.

Original languageEnglish
Pages (from-to)365-376
Number of pages12
JournalJournal of Cleaner Production
Volume221
DOIs
Publication statusPublished - Jun 2019

    Research areas

  • Anti-reflective coating, Anticipatory LCA, Dip coating, Greenhouse glass, Scale-up, Scenarios

ID: 52763869