In this work, we studied a novel algae cultivation strategy, mixotrophic microalgae biofilm, to improve the productivity and cost-efficiency of algal biofuel production. In contrast to previous methods, this improved approach can achieve high productivity at low cost by harnessing the benefits of mixotrophic growth’s high efficiency, i.e., capable of subsisting on inorganic and organic carbons thus unaffected by limited light, and microalgae biofilm’s low harvesting cost. Our results, as one of the first studies of this type, proved that microalgae biofilms under mixotrophic condition exhibited significantly higher productivity and quality of biofuel feedstock: 2–3 times higher of biomass yield, 2–10 times higher of lipid accumulation, and 40–60% lower of ash content when compared to microalgae biofilms under autotrophic condition. In addition, we investigated the impact of cell-surface properties (hydrophobicity and roughness) on the growth activities of microalgae biofilms and found that the productivity of mixotrophic biofilms was significantly correlated with the surface hydrophobicity. Finally, our work demonstrated the applicability of integrating this novel cultivation method with wastewater for maximum efficiency. This study opens a new possibility to solve the long-lasting challenges of algal biofuel feedstock production, i.e., low productivity and high cost of algal cultivation.

This work presented a Spatially-Explicit-High-Resolution Life Cycle Assessment (SEHR-LCA) model for wastewater-based algal biofuel production, by integrating life cycle assessment, GIS analysis, and site-specific Wastewater Treatment Plants (WWTPs) data analysis. Wastewater resources, land availability, and meteorological variation were analyzed for algae cultivation. Three pathways, Microwave Pyrolysis, hydrothermal liquefaction, and lipid extraction were modeled for bio-oil conversion. This model enables the assessment of seasonal and site-specific variations in productivity and environmental impacts of wastewater-based algal bio-oil across the whole U.S. Model results indicate that wastewater-based algal bio-oil can provide an opportunity to increase national biofuel output. The potential production of algal bio-oil can reach to 0.98billiongallon/yr, nearly 20% of advanced biofuel projection as outlined in the U.S. Energy Independence and Security Act (EISA) of 2007. LCA results shows significant variations among different locations, WWTPs, and operational seasons. Although not competitive to conventional fossil fuel in energy efficiency, wastewater-based algal biofuel could offer significant benefit in controlling GHG emissions. However, spatial analysis shows that only 61% of the total wastewater could be used, based on current land use efficiency for algae cultivation and land availability around each WWTP in a radius where algal biofuel production is energy positive (energy output>energy input). These results indicate that land availability could be a significant challenge for wastewater-based algal biofuels that have not been considered in previous studies. They also suggest that improvement should be made in technological development and system design to increase energy and land use efficiency for full potential of wastewater as a promising resource for algal biofuel production. Although focusing on the U.S. as the case study, the developed methodology could be used for spatially explicit analysis of algal biofuel integrated with wastewater on macro-scale in other regions as well

The objective of this study was to examine the sensor response characteristics of three commercial Internet of Things (IoT) compatible metal oxide (MOx) sensors in preparation for the development of field-scale sensor networks for the real-time monitoring of volatile organic compounds (VOCs) in indoor environments located in proximity to brownfield sites. Currently, there is limited examination of such sensor responses to relevant mixtures of target VOCs, such as the common petrochemicals benzene, toluene, ethylbenzene, and xylene (BTEX), as well as chlorinated aliphatic hydrocarbon (CAH) contaminants such as tetrachloroethylene (PCE) and trichloroethylene (TCE) which are frequently associated with deterioration of indoor air quality. To address this, a study of three commercial metal oxide (MOx) sensors (SGP30, BME680, and CCS811) was undertaken to examine the sensor response characteristics of individual components as well as mixtures of each of the target BTEX and CAH chemicals over relevant indoor air concentrations within the operating range of the MOx sensors (0–6000 ppb). Our investigation revealed similar response patterns to those previously reported for the thick film MOx sensor to most individual target VOCs, however, response trends for mixtures were more difficult to discern. In general, the MOx sensors we examined demonstrated similar magnitude responses to the CAHs as BTEX compounds indicating reliable detection of CAHs.