Rare earth elements (REEs) are essential for advanced manufacturing (e.g., renewable energy, military equipment, electric vehicles); hence, the recovery of REEs from low-grade resources has become ...increasingly important to address their growing demand. Depending on specific mining sites, its geological conditions, and sociodemographic backgrounds, mining waste has been identified as a source of REEs in various concentrations and abundance. Yttrium, cerium, and neodymium are the most common REEs in mining waste streams (50 to 300 μg/L). Biomining has emerged as a viable option for REEs recovery due to its reduced environmental impact, along with reduced capital investment compared to traditional recovery methods. This paper aims to review (i) the characteristics of mining waste as a low-grade REEs resource, (ii) the key operating principles of biomining technologies for REEs recovery, (iii) the effects of operating conditions and matrix on REEs recovery, and (iv) the sustainability of REEs recovery through biomining technologies. Six types of biomining will be examined in this review: bioleaching, bioweathering, biosorption, bioaccumulation, bioprecipitation and bioflotation. Based on a SWOT analyses and techno-economic assessments (TEA), biomining technologies have been found to be effective and efficient in recovering REEs from low-grade sources. Through TEA, coal ash has been shown to return the highest profit amongst mining waste streams.
In this study, we consider the combination of clustering and resource allocation based on game theory in ultra-dense networks that consist of multiple macrocells using massive multiple-input ...multiple-output and a vast number of randomly distributed drones serving as small-cell base stations. In particular, to mitigate the intercell interference, we propose a coalition game for clustering small cells, with the utility function being the ratio of signal to interference. Then, the optimization problem of resource allocation is divided into two subproblems: subchannel allocation and power allocation. We use the Hungarian method, which is efficient for solving binary optimization problems, to assign the subchannels to users in each cluster of small cells. Additionally, a centralized algorithm with low computational complexity and a distributed algorithm based on the Stackelberg game are provided to maximize the network energy efficiency (EE). The numerical results demonstrate that the game-based method outperforms the centralized method in terms of execution time in small cells and is better than traditional clustering in terms of EE.
Data corroborated in this study highlights laundry wastewater as a primary source of microfibers (MFs) in the aquatic environment. MFs can negatively impact the aquatic ecosystem via five possible ...pathways, namely, acting as carriers of other contaminats, physical damage to digestive systems of aquatic organisms, blocking the digestive tract, releasing toxic chemicals, and harbouring invasive and noxious plankton and bacteria. This review shows that small devices to capture MFs during household laundry activities are simple to use and affordable at household level in developed countries. However, these low cost and small devices are unrealiable and can only achieve up to 40 % MF removal efficiency. In line filtration devices can achieve higher removal efficiency under well maintained condition but their performance is still limited compared to over 98 % MF removal by large scale centralized wastewater treatment. These results infer that effort to increase sanitation coverage to ensure adequate wastewater treatment prior to environmental discharge is likely to be more cost effective than those small devices for capturing MFs. This review also shows that natural fabrics would entail significantly less environmental consequences than synthetic materials. Contribution from the fashion industry to increase the share of natural frabics in the current textile market can also reduce the loading of plastic MFs in the environment.
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•Laundry and textile industry are the main source of plastic microfiber pollution.•Washing conditions and fabrics material significantly influence microfibers release.•Microfibers pollution can direct and indirectly harm the aquatic environment.•Fashion industry should reverse to natural fabrics to phase out synthetic materials.•Microfiber removal by centralized treatment is preferred over passive devices.
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•Yields of starch and PHB can be increased through culture with nutrient starvation.•Cyanobacteria are a suitable source of PHB during cultivation and harvesting.•Inconsistency in the ...polysaccharide composition of seaweed affects yield extraction.•Carrageenan is a good additive for the production of edible food packaging.•Membrane photobioreactor could be a sustainable production of algal derivatives.
Improper use of conventional plastics poses challenges for sustainable energy and environmental protection. Algal derivatives have been considered as a potential renewable biomass source for bioplastic production. Algae derivatives include a multitude of valuable substances, especially starch from microalgae, short-chain length polyhydroxyalkanoates (PHAs) from cyanobacteria, polysaccharides from marine and freshwater macroalgae. The algae derivatives have the potential to be used as key ingredients for bioplastic production, such as starch and PHAs or only as an additive such as sulfated polysaccharides. The presence of distinctive functional groups in algae, such as carboxyl, hydroxyl, and sulfate, can be manipulated or tailored to provide desirable bioplastic quality, especially for food, pharmaceutical, and medical packaging. Standardizing strains, growing conditions, harvesting and extracting algae in an environmentally friendly manner would be a promising strategy for pollution control and bioplastic production.
An effective pretreatment is the first step to enhance the digestibility of lignocellulosic biomass – a source of renewable, eco-friendly and energy-dense materials – for biofuel and biochemical ...productions. This review aims to provide a comprehensive assessment on the advantages and disadvantages of lignocellulosic pretreatment techniques, which have been studied at the lab-, pilot- and full-scale levels. Biological pretreatment is environmentally friendly but time consuming (i.e. 15–40 days). Chemical pretreatment is effective in breaking down lignocellulose and increasing sugar yield (e.g. 4 to 10-fold improvement) but entails chemical cost and expensive reactors. Whereas the combination of physical and chemical (i.e. physicochemical) pretreatment is energy intensive (e.g. energy production can only compensate 80% of the input energy) despite offering good process efficiency (i.e. > 100% increase in product yield). Demonstrations of pretreatment techniques (e.g. acid, alkaline, and hydrothermal) in pilot-scale have reported 50–80% hemicellulose solubilisation and enhanced sugar yields. The feasibility of these pilot and full-scale plants has been supported by government subsidies to encourage biofuel consumption (e.g. tax credits and mandates). Due to the variability in their mechanisms and characteristics, no superior pretreatment has been identified. The main challenge lies in the capability to achieve a positive energy balance and great economic viability with minimal environmental impacts i.e. the energy or product output significantly surpasses the energy and monetary input. Enhancement of the current pretreatment techno-economic efficiency (e.g. higher product yield, chemical recycling, and by-products conversion to increase environmental sustainability) and the integration of pretreatment methods to effectively treat a range of biomass will be the steppingstone for commercial lignocellulosic biorefineries.
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•Cost-competitiveness remains the challenge for full-scale lignocellulosic biorefinery.•Pretreatment techniques have shown great efficiency in lab-scale investigations.•Combined pretreatment techniques create a synergistic effect on sugar conversion.•Recycling chemicals and enzymes from lignocellulosic pretreatment enhance cost benefits.•Pretreatment is an integral part of breakthrough lignocellulosic biofuel plants in operation.
Ciprofloxacin (CIP) is an antibiotic that is widely used to treat bacterial infections and is poorly biodegraded during wastewater treatment. In this study, a CIP-degrading bacterial strain (GLC_01) ...was successfully retrieved from activated sludge by enrichment and isolation. The obtained bacterial strain shares over 99% nucleotide identity of the 16S rRNA gene with Bradyrhizobium spp. Results show that Bradyrhizobium sp. GLC_01 degraded CIP via cometabolism with another carbon substrate following a first-order kinetics degradation reaction. CIP degradation by Bradyrhizobium sp. GLC_01 increased when the concentration of the primary carbon source increased. The biodegradability of the primary carbon source also affected CIP degradation. The use of glucose and sodium acetate (i.e. readily biodegradable), respectively, as a primary carbon source enhanced CIP biotransformation, compared to starch (i.e. relatively slowly biodegradable). CIP degradation decreased with the increase of the initial CIP concentration. Over 70% CIP biotransformation was achieved at 0.05 mg L−1 whereas CIP degradation decreased to 26% at 10 mg L−1. The phylogenetic identification and experimental verification of this CIP-degrading bacterium can lead to a bioengineering approach to manage antibiotics and possibly other persistent organic contaminants during wastewater treatment.
•Bradyrhizobium sp. GLC_01 was isolated from activated sludge.•GLC_01 removed CIP via cometabolism with primary carbon source.•High concentration of the primary carbon source induced better removal of CIP.•The primary carbon source degradability affected CIP removal.•GLC_01 could remove 70% of CIP at environmentally relevant concentration.
We consider the downlink of a cell-free massive multiple-input multiple-output (MIMO) network, where numerous distributed access points (APs) serve a smaller number of users under time division ...duplex operation. An important issue in deploying cell-free networks is high power consumption, which is proportional to the number of APs. This issue has raised the question as to their suitability for green communications in terms of the total energy efficiency (bits/Joule). To tackle this, we develop a novel low-complexity power control technique with zero-forcing precoding design to maximize the energy efficiency of cell-free massive MIMO considering the Backhaul power consumption and the imperfect channel state information.
Transportation projects are increasingly complex. A systematic approach for measuring and evaluating complexity in transportation projects is imperative. Thirty six project complexity factors were ...identified specifically for transportation construction. Using factor analysis, this study deduced the six components of project complexity, namely sociopolitical, environmental, organizational, infrastructural, technological, and scope complexity. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method was employed to determine the weights of the components and parameters of project complexity. Sociopolitical complexity was the most defining component of complexity in transportation construction. A complexity level (CL) was proposed to measure the overall project complexity. The application of the proposed approach was demonstrated in a case study of three transportation projects performed by a heavy construction company. As a quantitative measure CL enables managers to better anticipate potential difficulties in complex transportation projects. As a result, scarce resources will be allocated efficiently among transportation projects in a company’s portfolio.
•This study identified complexity factors specifically for transportation projects.•We deduced the components and parameters of complexity in transportation projects.•A Fuzzy AHP-based approach was proposed to measure the overall project complexity.•The complexities of three transportation projects were measured as a case study.•The measure enables managers to better navigate complex transportation projects.
Device-to-device (D2D) communication is an emerging technology in the evolution of the 5G network enabled vehicle-to-vehicle (V2V) communications. It is a core technique for the next generation of ...many platforms and applications, e.g. real-time high-quality video streaming, virtual reality game, and smart city operation. However, the rapid proliferation of user devices and sensors leads to the need for more efficient resource allocation algorithms to enhance network performance while still capable of guaranteeing the quality-of-service. Currently, deep reinforcement learning is rising as a powerful tool to enable each node in the network to have a real-time self-organising ability. In this paper, we present two novel approaches based on deep deterministic policy gradient algorithm, namely "distributed deep deterministic policy gradient" and "sharing deep deterministic policy gradient", for the multi-agent power allocation problem in D2D-based V2V communications. Numerical results show that our proposed models outperform other deep reinforcement learning approaches in terms of the network's energy efficiency and flexibility.
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