Beyond carbon: what about the water footprint of surgical pathology departments?
- Journal
- American journal of clinical pathology (Q1)
- Published
- 4 November 2026
- Study design
- Unclassified
- Evidence level
- Level 5, Expert Opinion (CEBM 5)
- Authors
- Tanguy Fenouil, Béatrice Nadaud, Sylvain Guinde, Karine Hutin, Lucie Gaillot-Durand, Alexis Trecourt
- PMID
- 42981493
- DOI
- 10.1093/ajcp/aqag121
Why clinicians should know about it
- Picked for Histology (top studies of the week, 8 November 2026): Evaluates routine stain quality while optimizing histology technique
Abstract
OBJECTIVES: We assessed the water footprint of preparing standard (hematoxylin, phloxine, and saffron [HPS]) and special stains, routinely used in surgical pathology, with the aim of reducing water consumption without compromising the quality of the analysis. METHODS: The water footprint of HPS and special stains was first calculated using water meters and the number of stains prepared per day. Then, the quality of HPS stains at different tap positions and flow rates (35.4, 28.3, and 18.5 mL/s) was compared to reduce the tap flow rate (protocol optimization). Finally, the number of water liters saved using the optimized protocol was estimated. RESULTS: For automated HPS stains, the mean number of slides prepared per day was 545.8 (range, 310-851), and the mean amount of water consumed daily was 1003.8 L (range, 807-1286). This represented an average of 1.8 L per HPS slide. For special stains, the mean amount of water consumed daily was 236.3 L (range, 39-1167), representing between 20.1 and 21.2 L per slide, depending on the staining procedure (manual or automated). Then, when comparing the HPS stain according to different tap positions, no difference in stain quality was noticed. Finally, setting the tap flow rate at 28.3 mL/s for the automated HPS staining procedure allowed us to reduce water consumption from 1.8 to 1.5 L per HPS slide, representing a 16.7% reduction. CONCLUSIONS: Reducing water consumption of staining procedures is feasible and easy to implement in practice without affecting the quality of the analyses.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.