• Energy Research
• 2021-2025close
• 6. Clean water close
• Frontiers in Energy Research close

Microalgae offer a great potential to contribute significantly as renewable fuels and documented as a promising platform for algae-based bio refineries. They provide solutions to mitigate the environmental concerns posed by conventional fuel sources; however, the production of microalgal biofuels in large scale production system encounters few technical challenges. High quantity of nutrients requirements and water cost constrain the scaling up microalgal biomass to large scale commercial production. Crop protection against biomass losses due to grazers or pathogens is another stumbling block in microalgal field cultivation. With our existing technologies, unless coupled with high-value or mid-value products, algal biofuel cannot reach the economic target. Many microalgal industries that started targeting biofuel in the last decade had now adopted parallel business plans focusing on algae by-products application as cosmetic supplements, nutraceuticals, oils, natural color, and animal feed. This review provides the current status and proposes a framework for key supply demand, challenges for cost-effective and sustainable use of water and nutrient. Emphasis is placed on the future industrial market status of value added by products of microalgal biomass. The cost factor for biorefinery process development needs to be addressed before its potential to be exploited for various value-added products with algal biofuel.

Pharmaceutical and personal care products (PPCPs) are discharged into receiving water bodies mainly from sewage treatment plants. Due to the inefficient removal in conventional wastewater treatment facilities, PPCPs have become a major concern to aquatic ecosystems, water quality, and public health worldwide since they cause harmful effects on aquatic life and human even at low doses. Among the PPCPs, carbamazepine (CBZ) is one of the most commonly prescribed anticonvulsant drugs and consumed more than 1,000 tons per year. Due to its structural complexity, CBZ is known as recalcitrant compound highly stable during wastewater treatment. Consequently, it has become one of the most frequently detected pharmaceuticals in waste water, surface water, and even drinking water. In this study, Korean indigenous microalgae strains were tested as eco-friendly and cost-effective solutions for CBZ removal. Based on the preliminary biological CBZ degradation tests, Tetradesmus obliquus KNUA061 demonstrating the best CBZ removal rate was selected for further experiments. In order to increase strain KNUA061's CBZ removal efficiency, NaOCl, which is widely accepted in the water purification process, was used as an additional stimulus to induce stress conditions. At around 20 μg L−1 CBZ, addition of 1.0 mg NaOCl resulted in approximately 20% of removal rate increase without suppressing cells growth. Roughly 90% of CBZ remained its original form and the composition of the transformed secondary metabolites was less than 10% during the biodegradation process by the microalga. Based on the results of the antioxidant enzyme activities, degree of lipid oxidation, and amino acid contents, it was concluded that the redox-defence system in microalgal cells may have been activated by the NaOCl treatment. Biomass analysis results showed that higher heating value (HHV) of strain KNUA061 biomass was higher than those of lignocellulosic energy crops suggesting that it could be utilized as a possible renewable energy source. Even though its biodiesel properties were slightly below the international standards due to the high PUFA contents, the biodiesel produced from T. obliquus KNUA061 could be used as a blending resource for transportation fuels. It was also determined that the microalgal biomass has acceptable feasibility as a sustainable dietary supplement feedstock due to its high essential amino acid contents.

Marine reactors are subjected to additional motions due to ocean conditions. These additional motions will cause large fluctuation of flow rate and change the coolant flow field, making the system unstable. Therefore, in order to understand the effect of oscillating motion on the flow characteristics, a numerical simulation of fluid flow is carried out based on a full-scale three-dimensional oscillating marine reactor. In this study, the resistance coefficients of the lattice, rod buddle and steam generator are fitted, and the distribution of flow rate, velocity as well as pressure in different regions is investigated through the standard model. After additional oscillation is introduced, the flow field in an oscillating reactor is presented and the effect of oscillating angle and elevation on the flow rate is investigated. Results show that the oscillating motion can greatly change the flow field in the reactor; most of the coolant circulates in the downcommer and lower head with only a small amount of coolant entering the core; the flow fluctuation period is consistent with the oscillating period, and the flow variation patterns under different oscillating conditions are basically the same; since the flow amplitude is related to oscillating speed, the amplitude of flow rate rises when decreasing the maximum oscillating angle; the oscillating elevation has little effect on the flow rate.

Ever-increasing anthropogenic CO2 emissions have required us to develop carbon capture, utilization, and storage (CCUS) technologies, and in order to address climate change, these options should be at scale. In addition to engineered systems of CO2 capture from power plants and chemical processes, there are emerging approaches that include the Earth (i.e., air, Earth, and ocean) within its system boundary. Since oceans constitute the largest natural sink of CO2, technologies that can enhance carbon storage in the ocean are highly desired. Here, we discuss alkalinity enhancement and biologically inspired CO2 hydration reactions that can shift the equilibrium of ocean water to pump more carbon into this natural sink. Further, we highlight recent work that can harvest and convert CO2 captured by the ocean into chemicals, fuels, and materials using renewable energy such as off-shore wind. Through these emerging and innovative technologies, organic and inorganic carbon from ocean-based solutions can replace fossil-derived carbon and create a new carbon economy. It is critical to develop these ocean-based CCUS technologies without unintended environmental or ecological consequences, which will create a new engineered carbon cycle that is in harmony with the Earth’s system.

Significant volumes of wastewater are routinely generated during agro-industry processing, amounting to millions of tonnes annually. In line with the circular economy concept, there could be a possibility of simultaneously treating the wastewater and recovering bio-energy resources such as bio-hydrogen. This study aimed to model the effect of different process parameters that could influence wastewater treatment and bio-energy recovery from agro-industrial wastewaters. Three agro-industrial wastewaters from dairy, chicken processing, and palm oil mills were investigated. Eight data-driven machine learning algorithms namely linear support vector machine (LSVM), quadratic support vector machine (QSVM), cubic support vector machine (CSVM), fine Gaussian support vector machine (FGSVM), binary neural network (BNN), rotation quadratic Gaussian process regression (RQGPR), exponential quadratic Gaussian process regression (EQGPR) and exponential Gaussian process regression (EGPR) were employed for the modeling process. The datasets obtained from the three agro-industrial processes were employed to train and test the models. The LSVM, QSVM, and CSVM did not show an impressive performance as indicated by the coefficient of determination (R2) < 0.7 for the prediction of hydrogen produced from wastewaters using the three agro-industrial processes. The LSVM, QSVM, and CSVM models were also characterized by high prediction errors. Superior performance was displayed by FGSVM, BNN, RQGPR, EQGPR, and EQGPR models as indicated by the high R2 > 0.9, an indication of better predictability with minimized prediction errors as indicated by the low root mean square error (RMSE), mean square error (MSE), and mean absolute error (MAE).

Pumping stations play an important role in China’s South-to-North Water Diversion, agricultural irrigation, and municipal drainage. Some pumping station units have been put into operation for long periods with improper operation and require maintenance. Moreover, the surfaces of the flow components have been worn and corroded, leading to an increase in the relative roughness and a decrease in the hydraulic performance efficiencies of pumping station units. In this work, we performed field measurements and numerical simulations to study the influence of the wall roughness on the hydraulic performance of slanted axial-flow pump devices under multiple working conditions. The effects of the wall roughness of the impeller chamber on the hydraulic performance of the pump, the guide vane chamber, and the inlet and outlet flow channel were investigated. Wall roughness had the largest influence on the hydraulic performance of the pump and the smallest influence on the inlet and outlet flow channels. For devices with different roughness values on the impeller chamber wall under different flow rate conditions, the performance of the pump device worsened under the large-flow-rate condition, and the device performance was better under the small-flow-rate and designed flow conditions. The efficiency of the slanted axial-flow pump device decreased significantly as the flow rate increased. Under the same flow rate condition, the performance of the device with Ra = 5 μm was similar to that with a smooth wall, where Ra is the roughness of the wall. With the increase in the roughness, the uniformity of the axial velocity distribution coefficient decreased, and the velocity-weighted average drift angle increased. External characteristic parameters, such as the torque and the static pressure, on the blade pressure surface gradually decreased with the increase in the wall roughness. A large roughness could induce instability of the wall flow and enhance the turbulent kinetic energy near the blade surface.

Re-fracturing treatments of horizontal wells are increasingly gaining popularity to address the issue of rapid production decline and low recovery ratio for the conglomerate reservoir of the Mahu Oilfield. How to effectively select the horizontal wells with potentiality for re-fracturing and conduct the re-fracturing operation to achieve the purpose is the key problem that needs to be investigated urgently. However, the conventional methods for vertical wells are not in our consideration, and some methods for horizontal wells have their limits for the Mahu reservoir. To cope with problems mentioned above, fourteen factors from geology parameters, engineering parameters, and production performance parameters are considered to establish a multi-level evaluation model to quantify the potentiality of each horizontal well for re-fracturing in the Mahu Oilfield. First, the analytic hierarchy process (AHP) is used to obtain the weights of various factors affecting the productivity of horizontal wells, and on this basis, the subordination degree and evaluation matrix are then calculated, and finally, the fuzzy synthetic determination is obtained to determine the candidate wells for re-fracturing. The results have shown that the weights corresponding to engineering parameters obtained by the AHP method are the largest, followed by geology parameters, and the weights of production performance parameters are the minimal relatively; the number of fractures and the sand quantity of single cluster are the main controlling factors in engineering factors, and the initial formation pressure is the main controlling factor in geological factors; there is obvious correlation between the cumulative oil production after 90 days of primary fracturing with final cumulative production. Wells M15, M13, and M7 rank top three among the candidate wells. Through re-fracturing treatment by temporary plugging, the daily oil production of well M15 has increased significantly and is even higher than that of the primary hydraulic fracturing stimulation, confirming the reliability of the proposed selection method.

CO2 flooding and burial efficiency can be improved by establishing a standard for screening suitable CO2 flooding reservoirs for the Daqing Oilfield. Moreover, the influencing factors of CO2 flooding can be classified into geological factors, fluid properties, and development factors. An evaluation index system and hierarchical structure are created based on the importance of multiple factors. The subjective analysis error of human beings is quite large when establishing the evaluation index system, especially in the fitting curves that are drawn by different analysts. Based on the geological characteristics of block Bei14 in the Daqing Oilfield, a typical CMG model is presented in this article. A total of 15 factors in the 72 models are used as independent variables, and the recovery factor is used as a dependent variable for multiple linear regression calculations. In addition to sensitivity tests based on how much significance is indicated by the t value in the results, a unique result can be calculated using standard statistical methods when analyzing the calculation results of the multiple linear regression model. The results of the screening standard evaluation system are consistent with the production history of the oilfield based on the mathematical understanding of multiple factors of CO2 flooding. Around the high-score well group, oil saturation decreases significantly, and the cumulative production is generally higher than that of the low-score well group. The calculation results of block Bei 14 show that 74% of well groups have an evaluation value greater than 0.50, and 72% of well groups have an annual oil exchange ratio above 40%, which means that over 70% of well groups can benefit from CO2 flooding. Thus, CO2 flooding can be applied in the Daqing Oilfield, and multiple linear regression can provide effective guidance for the Daqing Oilfield’s development.