Grantee Research Project Results
Final Report: Stratified Multilayer Algal-biofilm Reclamation Technology (SMART)
EPA Grant Number: SU839295Title: Stratified Multilayer Algal-biofilm Reclamation Technology (SMART)
Investigators: Zhang, Yongli , Roostaei, Javad , Asadi, Ali , Doosti, Zohreh , Ewing, Michael , Guan, Joanne , Uddin, Thanjila , Wagnen, James Van
Institution: Wayne State University
EPA Project Officer: Page, Angela
Phase: I
Project Period: November 1, 2017 through October 31, 2018
Project Amount: $14,954
RFA: P3 Awards: A National Student Design Competition for Sustainability Focusing on People, Prosperity and the Planet (2017) RFA Text | Recipients Lists
Research Category: P3 Awards , Sustainable and Healthy Communities , P3 Challenge Area - Safe and Sustainable Water Resources
Objective:
The overall objective of the Phase I work is to design a Stratified Multilayer Algal-biofilm Reclamation Technology (SMART) coupled with Internet of Things (IoT) sensing for efficient wastewater treatment and sustainable biofuel feedstock generation. The central hypothesis is that SMART is capable of harnessing the benefits of mixotrophic growth’s high efficiency, microalgae biofilm’s stress resistance and low harvesting costs, and IoT’s real-time monitoring and control for a more robust and cost-efficient system, as compared to current wastewater-algae approaches. SMART consists of microalgae biofilm ordered in multiple supporting layers under mixotrophic conditions. SMART harnesses the benefits of mixotrophic growth’s high efficiency, i.e. capable of subsisting on inorganic and organic carbons, thus unaffected by limited light like autotrophic cultivation. Additionally, microalgae biofilm has a high resistance to environmental stresses and, most importantly, the harvesting cost is low. At the same time, the utilization of IoT can help to automatically control multiple growth parameters in real time with low cost. This work is one pioneer study that would bring IoT to a novel algae-wastewater treatment for processing control and optimization. To achieve the overall objective, three research objectives are included: (i) developing a SMART pilot reactor for efficient wastewater treatment and sustainable biofuel feedstock generation; (ii) developing the IoT framework as a control tool for algae cultivation; and (iii) evaluating SMART and IoT technologies for nutrients recovery, emerging contaminants (ECs) removal, algal biofuel feedstock production, and environmental/economic cost. Collectively, this work helps to address sustainability challenges in people, prosperity and the planet via the innovative SMART technology for cost-efficient wastewater treatment and renewable bioenergy generation.
Summary/Accomplishments (Outputs/Outcomes):
First, we have proved the novel SMART technology coupled with IoT for cost-efficient wastewater treatment and bioenergy feedstock production. Our results, as one of the first studies of this type, demonstrate that the SMART technology can significantly improve wastewater treatment efficiency and algal bioenergy productivity: 2-3 times higher of biomass yield and nutrients recovery and 2-10 times higher of lipid accumulation when compared to other wastewater-algae systems. Second, our work have demonstrated the capacity of growing SMART algae in real wastewater, which indicates the applicability of integrating the novel SMART technology with wastewater treatment plants (WWTPs) for maximum efficiency. Third, we have developed a high-resolution spatially explicit life cycle assessment by integrating life cycle assessment with GIS to compare environmental footprint of wastewater-algae systems across the whole U.S. Finally, we have integrated our research efforts with educational and community engagement activities, including WSU STEM day, WSU Sustainable Engineering Certificate program for college students and working professionals, Michigan Science Center Expo, and USA Science and Engineering Festival.
Conclusions:
Our results prove that the innovative SMART technology can significantly improve wastewater treatment efficiency and biofuel feedstock productivity. Different from other wastewater-algae systems such as open ponds and photo-bioreactors, SMART is capable of harnessing the benefits of both mixotrophic growth’s high efficiency and biofilm’s low harvesting cost to achieve high productivity at low cost, which opens a new paradigm to solve long-lasting challenges of wastewater-algae systems (i.e., low productivity and high cost).
Journal Articles on this Report : 1 Displayed | Download in RIS Format
Other project views: | All 1 publications | 1 publications in selected types | All 1 journal articles |
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Type | Citation | ||
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Roostaei J, Wager Y, Shi W, Dittrich T, Miller C, Gopalakrishnan K. IoT-based edge computing (IoTEC) for improved environmental monitoring. SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS 2023;38(100870) |
SU839295 (Final) |
Exit |
Supplemental Keywords:
Algal Wastewater Treatment, Sustainable Design, Pollution Removal, Internet of Things (IoT)Relevant Websites:
Sustainable Water-Environment-Energy Technologies (SWEET) Laboratory Exit
Wayne State University EPA P3 Team, 2018 Youtube Exit
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Conclusions drawn by the principal investigators have not been reviewed by the Agency.