Probabilistic Life Cycle Assessment of the Nano Membrane Toilet

Authors: A. Anastasopoulou, A. Kolios, T. Somorin, A. Sowale, Y. Jiang, B. Fidalgo, A. Parker, L. Williams, M. Collins, E. J. McAdam, S. Tyrrel

Abstract:

Developing countries are nowadays confronted with great challenges related to domestic sanitation services in view of the imminent water scarcity. Contemporary sanitation technologies established in these countries are likely to pose health risks unless waste management standards are followed properly. This paper provides a solution to sustainable sanitation with the development of an innovative toilet system, called Nano Membrane Toilet (NMT), which has been developed by Cranfield University and sponsored by the Bill & Melinda Gates Foundation. The particular technology converts human faeces into energy through gasification and provides treated wastewater from urine through membrane filtration. In order to evaluate the environmental profile of the NMT system, a deterministic life cycle assessment (LCA) has been conducted in SimaPro software employing the Ecoinvent v3.3 database. The particular study has determined the most contributory factors to the environmental footprint of the NMT system. However, as sensitivity analysis has identified certain critical operating parameters for the robustness of the LCA results, adopting a stochastic approach to the Life Cycle Inventory (LCI) will comprehensively capture the input data uncertainty and enhance the credibility of the LCA outcome. For that purpose, Monte Carlo simulations, in combination with an artificial neural network (ANN) model, have been conducted for the input parameters of raw material, produced electricity, NO_X emissions, amount of ash and transportation of fertilizer. The given analysis has provided the distribution and the confidence intervals of the selected impact categories and, in turn, more credible conclusions are drawn on the respective LCIA (Life Cycle Impact Assessment) profile of NMT system. Last but not least, the specific study will also yield essential insights into the methodological framework that can be adopted in the environmental impact assessment of other complex engineering systems subject to a high level of input data uncertainty.

Keywords: Sanitation systems, nano membrane toilet, LCA, stochastic uncertainty analysis, Monte Carlo Simulations, artificial neural network.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1317216

References:

[1] World Health Organisation, “The International Decade for Action Water for Life - 2005-2015 Coping with Water Scarcity,” 2007.
[2] M. K. Daud et al., “Drinking Water Quality Status and Contamination in Pakistan.: EBSCOhost,” Biomed Res. Int., vol. 2017, pp. 1–18, 2017.
[3] G. McGranahan, “Household environmental problems in low-income cities. An overview of problems and prospects for improvement*,” Habitat Int., vol. 17, no. 2, pp. 105–121, 1993.
[4] D. P. Hanak et al., “Conceptual energy and water recovery system for self-sustained nano membrane toilet,” Energy Convers. Manag., vol. 126, pp. 352–361, 2016.
[5] T. Onabanjo et al., “Energy recovery from human faeces via gasification: A thermodynamic equilibrium modelling approach,” Energy Convers. Manag., vol. 118, pp. 364–376, 2016.
[6] T. Onabanjo et al., “An experimental investigation of the combustion performance of human faeces,” Fuel, vol. 184, pp. 780–791, 2016.
[7] T. Onabanjo, A. J. Kolios, A. Parker, E. McAdam, L. Williams, and S. Tyrrel, “Faecal-wood biomass co-combustion and ash composition analysis,” Fuel, vol. 203, pp. 781–791, 2017.
[8] E. Friedrich, S. Pillay, and C. A. Buckley, “Carbon footprint analysis for increasing water supply and sanitation in South Africa: a case study,” J. Clean. Prod., vol. 17, pp. 1–12, 2009.
[9] H. Gao, C. Zhou, F. Li, B. Han, and X. Li, “Economic and environmental analysis of five Chinese rural toilet technologies based on the economic input-output life cycle assessment,” J. Clean. Prod., vol. 163, pp. S379–S391, 2017.
[10] C. Remy and M. Jekel, “Sustainable wastewater management: Life Cycle Assessment of conventional and source-separating urban sanitation systems,” Water Sci. Technol., vol. 58, no. 8, pp. 1555–1562, 2008.
[11] P. Roux, C. Boutin, E. Risch, and A. Heduit, “Life Cycle environmental Assessment ( LCA ) of sanitation systems including sewerage : Case of Vertical Flow Constructed Wetlands versus activated sludge” in 12th IWA International Conference on Wetland Systems for Water Pollution Control, 2010, pp. 879–887.
[12] A. Flores, A. Rosemarin, and R. Fenner, “Evaluating the Sustainability of an Innovative Dry Sanitation (Ecosan) System in China as Compared to a Conventional Waterborne Sanitation System” in Proceedings of the Water Environment Federation, 2009, pp. 6734–6751.
[13] Kohler Co., “Environmental Product-Declaration: Persuade ® K-4353” 2014.
[14] M. Kulak, N. Shah, N. Sawant, N. Unger, and H. King, “Technology choices in scaling up sanitation can significantly affect greenhouse gas emissions and the fertiliser gap in India,” J. Water Sanit. Hyg. Dev., vol. 7, no. 3, pp. 466–476, 2017.
[15] C. Thibodeau, F. Monette, C. Bulle, and M. Glaus, “Comparison of black water source-separation and conventional sanitation systems using life cycle assessment,” J. Clean. Prod., vol. 67, pp. 45–57, 2014.
[16] A. Anastasopoulou et al., “Conceptual environmental impact assessment of a novel self-sustained sanitation system incorporating a quantitative microbial risk assessment approach” Sci. Total Environ., vol. 639, pp. 657–672, 2018
[17] A. Genty, M. Kowalska, and O. Wolf, “Developing an evidence base on flushing toilets and urinals. Preliminary Report,” 2014.
[18] A. Azapagic and R. Clift, “Allocation of environmental burdens in multiple-function systems” J. Clean. Prod., vol. 7, no. 2, pp. 101–119, 1999.
[19] C. Lazcano et al., “Environmental benefits of compost use on land through LCA – a review of the current gaps” in 9th International Conference on Life Cycle Assessment in the Agri-Food Sector Environmental, 2014, pp. 674–682.
[20] C. Rose, A. Parker, B. Jefferson, and E. Cartmell, “The Characterization of Feces and Urine: A Review of the Literature to Inform Advanced Treatment Technology” Crit. Rev. Environ. Sci. Technol., vol. 45, no. 17, pp. 1827–1879, 2015.
[21] A. P. Engelbrecht, Computational Intelligence-An Introduction. WILEY, 2002.
[22] J. Wang and A. Kusiak, Computational Intelligence in Manufacturing Handbook. CRC Press LLC, 2000.