Browsing by Author "Anastasopoulou, Aikaterini"

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    Conceptual environmental impact assessment of a novel self-sustained sanitation system incorporating a Quantitative Microbial Risk Assessment approach
    (Elsevier, 2018-05-26) Anastasopoulou, Aikaterini; Kolios, Athanasios; Somorin, Tosin; Sowale, Ayodeji; Jiang, Ying; Fidalgo, Beatriz; Parker, Alison; Williams, Leon; Collins, Matt; McAdam, Ewan; Tyrrel, Sean
    In many developing countries, including South Africa, water scarcity has resulted in poor sanitation practices. The majority of the sanitation infrastructures in those regions fail to meet basic hygienic standards. This along with the lack of proper sewage/wastewater infrastructure creates significant environmental and public health concerns. A self-sustained, waterless “Nano Membrane Toilet” (NMT) design was proposed as a result of the “Reinvent the Toilet Challenge” funded by the Bill and Melinda Gates Foundation. A “cradle-to-grave” life cycle assessment (LCA) approach was adopted to study the use of NMT in comparison with conventional pour flush toilet (PFT) and urine-diverting dry toilet (UDDT). All three scenarios were applied in the context of South Africa. In addition, a Quantitative Microbial Risk Assessment (QMRA) was used to reflect the impact of the pathogen risk on human health. LCA study showed that UDDT had the best environmental performance, followed by NMT and PFT systems for all impact categories investigated including human health, resource and ecosystem. This was mainly due to the environmental credits associated with the use of urine and compost as fertilizers. However, with the incorporation of the pathogen impact into the human health impact category, the NMT had a significant better performance than the PFT and UDDT systems, which exhibited an impact category value 4E + 04 and 4E + 03 times higher, respectively. Sensitivity analysis identified that the use of ash as fertilizer, electricity generation and the reduction of NOx emissions were the key areas that influenced significantly the environmental performance of the NMT system.
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    Probabilistic performance assessment of complex energy process systems - The case of a self-sustained sanitation system
    (Elsevier, 2018-02-22) Kolios, Athanasios; Jiang, Ying; Somorin, Tosin; Sowale, Ayodeji; Anastasopoulou, Aikaterini; Anthony, Edward J.; Fidalgo, Beatriz; Parker, Alison; McAdam, Ewan; Williams, Leon; Collins, Matt; Tyrrel, Sean
    A probabilistic modelling approach was developed and applied to investigate the energy and environmental performance of an innovative sanitation system, the “Nano-membrane Toilet” (NMT). The system treats human excreta via an advanced energy and water recovery island with the aim of addressing current and future sanitation demands. Due to the complex design and inherent characteristics of the system’s input material, there are a number of stochastic variables which may significantly affect the system’s performance. The non-intrusive probabilistic approach adopted in this study combines a finite number of deterministic thermodynamic process simulations with an artificial neural network (ANN) approximation model and Monte Carlo simulations (MCS) to assess the effect of system uncertainties on the predicted performance of the NMT system. The joint probability distributions of the process performance indicators suggest a Stirling Engine (SE) power output in the range of 61.5–73 W with a high confidence interval (CI) of 95%. In addition, there is high probability (with 95% CI) that the NMT system can achieve positive net power output between 15.8 and 35 W. A sensitivity study reveals the system power performance is mostly affected by SE heater temperature. Investigation into the environmental performance of the NMT design, including water recovery and CO2/NOx emissions, suggests significant environmental benefits compared to conventional systems. Results of the probabilistic analysis can better inform future improvements on the system design and operational strategy and this probabilistic assessment framework can also be applied to similar complex engineering systems.