• Energy Research
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Abstract Recharging infrastructure (RI) deployment plays a vital role in improving the public recharging availability for transport electrification. Decarbonizing transportation using low-emission electricity requires massive RI network. Even though the consumers are reluctant to purchase electric vehicles (EVs) until RIs are sufficiently placed, the investors are not willing to invest in RIs due to recharging demand uncertainties. Therefore, a scientific planning framework is needed to ensure the sustainable deployment of EV-RIs in complex networks. In this study, a lifecycle thinking-based multi-period infrastructure-planning framework is proposed to develop sustainable public EV-RIs in an urban context. This framework consists of a temporal model to find the dynamic EV-RI demands, a stochastic model to obtain travel distances, and a multi-objective optimization model to select the best desirable capacities and locations for potential EV-RIs. A case study of a typical medium-scale municipality in Canada was assessed using the proposed framework and validated using conventional infrastructure planning scenarios. The geo-processing data, regional travel behaviors, and recharging characteristics were used as model inputs. The results of the case study showed that the proposed framework can be used to estimate multi-period public recharging demands, minimize lifecycle costs, maximize service coverage and infrastructure utilization, and ensure reasonable paybacks compared to conventional planning approaches. Moreover, this framework can be used to compare different investment assistances, which are required in the early stages of the RI deployment process to encourage investors. Furthermore, government and private institutions can use this framework to identify recharging demands, permitting, and developing RIs in the long-run.

A key determinant and outcome of successful environmental education is ‘pro-environmental behavior’, i.e., behavior that involves conscious action to mitigate adverse environmental impacts at personal or community level, e.g., reducing resource consumption and waste generation, avoiding toxic substances, and organizing community awareness initiatives. However, some theorists have sought to move away from rationalist models of behavioral modification, towards holistic pedagogical initiatives that seek to develop action competence. In light of the global push towards achievement of the Sustainable Development Goals (SDGs), emerging evidence suggests that education initiatives should foster action competence so students may be equipped to contribute to sustainable development as part of their education. The UNESCO Education for Sustainable Development (ESD) Roadmap 2030 has also identified key priority areas to strengthen ESD in formal curricula. This article reports two informal environmental education initiatives for promoting action competence and pro-environmental behaviors in school-aged children. The authors recommend that formal education settings (e.g., schools) should incorporate self-directed, free-choice project-based learning to augment environmental education programs and promote students’ action competence for contribution to attainment of SDGs. To this end, we propose a Free-Choice Project-based Learning for Action Competence in Sustainable Development (ACiSD) Curriculum, comprising six implementation dimensions, namely: (1) project duration and teaming arrangements, (2) topic selection, (3) student support, (4) teacher support, (5) learning environments, and (6) digital access and equity. For each implementation dimension, we recommend action steps to help educators implement this curriculum in their own educational settings, with the aid of an illustrative worked example.

AbstractCellulose and lignin nanoparticles are high‐value‐added products obtained from lignocellulosic biomasses through several steps of cellulose purification and lignin extraction. These steps drastically reduce the potential feedstock revenue when carried out as stand‐alone methodologies. To increase biomass yields, we describe here a strategy to design a biorefinery focused on producing cellulose and lignin nanoparticles as main products, but also aim to recover and benefit from other biomass components using only water‐based processes. Sequential pressurized liquid extractions and diluted acid and alkaline treatments were carried out to fractionate elephant grass biomass, yielding (for every 100 g of biomass): 30 g of cellulose pulp (converted to 9 g of cellulose nanocrystals and 9 g of cellulose nanofibers); 10 g of lignin (used to produce 8.5 g of stable colloidal lignin nanoparticles by probe‐sonication in water); 7.5 g of extractives (e.g. sterols and phenolics) and 23 g of xylose (converted to 4.1 g of furfural). Alternatively, to allow for the flexible use of the cellulose fraction in the proposed biorefinery, 22 g of glucose could be produced by enzymatic hydrolysis. The results demonstrate that water‐based processes are suitable for a holistic use of biomass, providing a comprehensive set of high‐value‐added co‐products that are renewable and cost‐effective chemical, cosmetic, food, polymer and pharmaceutical solutions.

This paper presents a methodology to obtain a discrete-time state-space representation of an electrical network using the nodal [G] matrix of the Electromagnetic Transients Program (EMTP) solution. Compared with conventional state-space solutions, the nodal EMTP solution is computationally very efficient. Compared with the phasor solutions used in transient stability analysis, the proposed approach may capture a wider range of eigenvalues and system operating states. An important advantage of extracting the system eigenvalues from the EMTP solution is the ability of the EMTP to follow the characteristics of nonlinearities. In addition, the algorithm can be used as a tool to identify network partitioning subsystems suitable for real-time hybrid power system simulator environments, including the implementation of multi-time-scale solutions. The proposed technique can be implemented as an extension of an EMTP-based simulator. Within our research group at UBC, it is aimed at extending the capabilities of our real-time PC-cluster Object Virtual Network Integrator (OVNI) simulator.

Interest in biomass to produce heat, power, liquid fuels, hydrogen, and value-added chemicals with reduced greenhouse gas emissions is increasing worldwide. Gasification is becoming a promising technology for biomass utilization with a positive environmental impact. This review focuses speci-fically on woody biomass gasification and recent advances in the field. The physical properties, chemical structure, and composition of biomass greatly affect gasification performance, pretreatment, and handling. Primary and secondary catalysts are of key importance to improve the conversion and cracking of tars, and lime-enhanced gasification advantageously combines CO2 capture with gasification. These topics are covered here, including the reaction mechanisms and biomass characterization. Experimental research and industrial experience are investigated to elucidate concepts, processes, and characteristics of woody biomass gasification and to identify challenges.

In this paper, we consider the resource-allocation problem for energy efficiency (EE)–spectral efficiency (SE) tradeoff. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or on the achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a tradeoff parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then, we apply the generalized framework of the resource allocation for the EE–SE tradeoff to optimally allocate the subcarriers' power for orthogonal frequency-division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the tradeoff parameter and study the effect of the estimation error, transmission power budget, and channel-to-noise ratio on the multiobjective optimization.

AbstractThe state of California could play an important role in emerging markets for biochar, due in part to the availability of low‐value biomass resources and their potential for use in agriculture sector. In this study, we assess the scale of production and use, and comment on potential markets for biochar in California. We explore various sectors for the application of biochar produced from local biomass using surveys and a market‐sizing approach. A market‐oriented approach for biochar innovation and the ecosystem around a biochar producer is also discussed. Next, we identify barriers to biochar market success in the present and the near future based on a survey of local producers. Among the barriers analyzed, access to capital investment for scale‐up is the biggest barrier experienced by a majority of producers, followed by market and demand. When grouped under different categories, the extent of barriers decreased in the order: market > scale‐up > technical > socio‐political > environmental. Most producers anticipate that revenues from carbon offset credits would help them scale up their facilities and expand the biochar market. In the near future, soil‐based applications of biochar could be the most likely market for biochar, followed by filtration, livestock feed, and manure management. As the industry evolves, rewarding carbon credits, increasing awareness and improving production processes are expected to help commercialize biochar. Finally, we offer recommendations to promote the growth of biochar in California. © 2021 Society of Chemical Industry and John Wiley & Sons, Ltd

Abstract BackgroundMicroorganisms in biogas reactors are essential for degradation of organic matter and methane production. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository.ResultsHere, 134 publicly available metagenomes derived from different biogas reactors were used to recover 1,635 metagenome-assembled genomes (MAGs) representing different biogas bacterial and archaeal species. All genomes were estimated to be >50% complete and nearly half ≥90% complete with ≤5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth dynamics for microbes involved in different steps of the food chain. ConclusionsThe outcome of this study highlights a high flexibility of the biogas microbiome, allowing it to modify its composition and to adapt to the environmental conditions, including temperatures and a wide range of substrates. Our findings enhance our mechanistic understanding of the AD microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.