| contributor author | Aaron Leininger | |
| contributor author | Wing-Mei Ko | |
| contributor author | Mark Ramirez | |
| contributor author | Birthe V. Kjellerup | |
| date accessioned | 2019-09-18T10:39:03Z | |
| date available | 2019-09-18T10:39:03Z | |
| date issued | 2019 | |
| identifier other | %28ASCE%29EE.1943-7870.0001531.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4259823 | |
| description abstract | Microbial fuel cells are bioelectrochemical devices that use exoelectrogenic biofilms to convert organic matter into electric energy. Recent research of microbial fuel cells has occurred because of their potential to perform energy net-positive degradation and transformation of wastewater constituents. However, most studies have focused on small-scale (<1 L) batch systems with simple and homogenous feedstocks such as acetate. These studies are useful for identification of isolated variables in a controlled environment, but the system architectures are not scaleable to wastewater treatment applications and the feedstocks do not reflect the heterogeneity of real domestic wastewater. The emerging research evaluating scaled-up microbial fuel cells operating with domestic wastewater substrate has described new and different biofilm characteristics and associated transformations other than those seen in bench studies. Scale-up of wastewater microbial fuel cells presents challenges including feedstock variability, changing environmental conditions, and biofouling. To advise the design of pilot-scale systems, this review discusses process stream selection and system architecture with the aim to maximize net energy benefit, defined as the sum of treatment energy savings and direct energy recovery. | |
| publisher | American Society of Civil Engineers | |
| title | Implementation of Upscaled Microbial Fuel Cells for Optimized Net Energy Benefit in Wastewater Treatment Systems | |
| type | Journal Paper | |
| journal volume | 145 | |
| journal issue | 5 | |
| journal title | Journal of Environmental Engineering | |
| identifier doi | 10.1061/(ASCE)EE.1943-7870.0001531 | |
| page | 04019020 | |
| tree | Journal of Environmental Engineering:;2019:;Volume ( 145 ):;issue: 005 | |
| contenttype | Fulltext | |