Comparative life cycle assessment of wastewater treatment in Denmark including sensitivity and uncertainty analysis - Niero, Monia; Pizzol, Massimo; Bruun, Henrik Gundorph; Thomsen, Marianne (Journal of cleaner production, 2014)
Wastewater treatment has nowadays multiple functions and produces both clean effluents and sludge, which is increasingly seen as a resource rather than a waste product. Technological as well as management choices influence the performance of wastewater treatment plants (WWTPs) on the multiple functions. In this context, Life Cycle Assessment (LCA) can determine what choices provide the best environmental performance. However, the assessment is not straightforward due to the intrinsic space and time-related variability of the wastewater treatment process. These challenges were addressed in a comparative LCA of four types of WWTPs, representative of mainstream treatment options in Denmark. The four plant types differ regarding size and treatment technology: aerobic versus anaerobic, chemical vs. combined chemical and biological. Trade-offs in their environmental performance were identified considering system expansion to model the avoided impacts achievable in different end-of-life scenarios for sludge: combustion with energy production versus agricultural application. To account for the variability in quality of effluents and sludge, and to address the related uncertainties, Monte Carlo simulation and sensitivity analysis were applied. Uncertainties related to the choice of Life Cycle Impact Assessment (LCIA) method and to the use of different data sources were also discussed. The results showed that, for the climate change and fossil depletion impact categories, recycling phosphorus to agricultural soils appear as a more sustainable alternative compared to the incineration of sludge. However, the uncertainty and sensitivity analysis showed that robust conclusions could not be drawn on the eutrophication and toxicity-related impact categories. •We compared 4 different types of Danish Wastewater Treatment Plant.•We used Life Cycle Assessment methodology including system expansion.•Agricultural sludge application emerged as best option for final sludge destination.•We used sensitivity analysis to increase the robustness of our findings.•We assessed input data variability through Monte Carlo uncertainty analysis.