Developing large scale microbial electrolysis cells (MECs) for the treatment of sludge return liquors
Developing large scale microbial electrolysis cells (MECs) for the treatment of sludge return liquors
批准号:
2447145
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --
中文摘要
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英文摘要
Microbial electrolysis cells can simultaneously treat wastewater and recover energy in the form of value-added products such as hydrogen. The system utilises a biofilm on an anode consisting of electrogenic microbes which anaerobically break down organic matter into electrons and H+ which react at a cathode to produce hydrogen when an external voltage of >0.14V is applied1. The technology's performance at lab-scale has been proven, however, pilot-studies have demonstrated major limitations that need to be overcome to enable its commercial application in the areas of energy recovery and treatment performance, system variability and costs. This research project aims to optimize performance against these barriers and move the technology into position to critically assess its feasibility as an energy neutral or positive wastewater treatment asset at a larger scale.Energy recovery and treatment performanceTo date, few of the pilot-trials have produced sufficient hydrogen to achieve net-positive energy performance, with electrical recovery efficiencies reported to be as low as 3%2. This has been attributed to hydrogen scavenging microbes in the cathode compartment2-4. Hence, this research project will investigate modes of sterilization (e.g H2O2 generation) and electrolyte recirculation within the MEC to inhibit microbial competition and assess their benefits on hydrogen generation and energy efficiency. Additionally, an input voltage optimization experiment on a pilot MEC using real wastewater will be considered to assess the influence of varying voltage on hydrogen recovery and volumetric treatment rates at a larger scale. The novelty here is that input voltages have only been optimized at lab-scale, where studies have used synthetic wastewater and neglect the challenges of increasing overpotentials on performance at scale.Reactor design will be explored to optimize performance using scenarios tested by an existing computational flow dynamics (CFD) model. Hence, the real effect of narrowing channel width on current, H2 production and treatment rates will be investigated using the pilot MEC at Howdon Sewage Treatment works or the BEWISE MEC facility (Northumbrian Water Ltd/Newcastle University) which allows for electrode cassettes to be adjusted. Sludge return liquors will be further explored as an avenue for MEC application as they provide sufficient COD to minimize concentration limitations on current and hydrogen production. Cost savings between MEC and activated sludge treatment of the liquor line will also be compared with ongoing reactor optimization. System Variability Performance variability within pilot-MECs has been observed in a number of trials which raises questions about its ability to produce consistent hydrogen2-4. Hence, another expect of this research will focus on reducing this variability by first identifying its origins in the MEC system by verifying if differences in biofilm development, cell internal resistance or both causes it. This will be tested by operating a high number of replica reactors under identical conditions and using microbial analysis and electrochemical impedance spectroscopy (EIS) to understand the differences between good and bad performing reactors. Following this, strategies for seeding reactors during start up and re-seeding those that fail will be developed. CostsAiken et al highlighted anode and current collector material costs need to be reduced by 90% along with other targets to make MECs financially viable5. Therefore, this research will aim to test the practicalities of using low-cost recycled carbon fibre as an anode material by monitoring material degradation in wastewater and treatment performance overtime at larger scales. This, along with the treatment and variability optimizations, will enable a full market analysis to be undertaken for the MEC.
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