Waste battery disposal and recycling behavior: a study on the Australian perspective

What determines the batteries recycling behavior of e-bike citizens in Guangzhou?: Integrating place identity and environmental concern into the extended norm activation model

Battery recycling is viewed in China as an important means of achieving primary sustainability goals and greater economic and environmental development. With the notice of high battery recycling intentions through relevant investigations, this study examine the influencing factors of these recycling behaviors of e-bikes citizens by incorporating the place identity and environmental concern into the Extended Normative Activation Model (NAM), which fill the research gap on how place identity and environmental concern affect the batteries recycling behavior. This study proposes that the consequence awareness, personal norms, and attitudes have mediating effect on place identity to the recycling behavior, and the environmental concern has moderating effect on consequence awareness, personal norms, and attitudes to the recycling behavior, respectively. Based on 1068 valid surveys, hypotheses were examined using partial least square structural equation modeling (PLS-SEM). The results show that personal norms and awareness of consequences positively impact e-bike users' intentions to recycle waste batteries, and environmental concerns have no moderating effect on attitude, recycling intention, personal norms, and recycling intention. Theoretical and practical implications are discussed at last.

The optimization of an EV decommissioned battery recycling network: A third-party approach

In this paper, we solve the urgent problem to construct a recycling network of decommissioned batteries of Electric Vehicles (EVs) and clarify the recycling entities that will be responsible for its reverse logistics (RL) process. We consider the third-party recycling entities to develop a recycling network and conduct a case-study of Xi'an, a key industry of EVs in China to provide a reference for the government and enterprises to develop recycling plans. We scientifically optimize our recycling network, which will have a significant impact on the environmental and economic benefits of electric vehicles (EVs) in Xi'an in the future. Specifically, we consider the costs of transportation, construction, operation, recycling, packaging, and emission, as well as the profits achieved through sales revenue and subsidy offerings. We collect the actual data of potential facility locations in Xi'an, predict the quantity of decommissioned batteries in the future, and develop a fuzzy-based model to solve the optimal results of battery traveling path and distribution in the recycling process network. Our results show that with the rapid growth of the number of decommissioned batteries, third-party revenues will reach about 53.08 billion by 2035. When the facilities split the recycling process load appropriately, the network has increase in revenue while the utilization rate of facilities will decrease. We expect that splitting will be a major trend in the future development of recycling network in Xi'an. Finally, a sensitivity analysis finds that with the environmentally conscious and safe operation of recycling, the negative impact on the third-party enterprises' revenue will be small. Our proposed methodology can serve as a critical framework for other cities and governments to plan their recycling networks and formulate regulations, reflecting on the realistic projection of the scale of decommissioned batteries of EVs and the potential siting and sizing of the recycling facilities.

Putative Protein Discovery from Microalgal Genomes as a Synthetic Biology Protein Library for Heavy Metal Bio-Removal

Simple Summary

Nowadays, heavy metal polluted wastewater is one of the global challenges that leads to an insufficient supply of clean water. Taking advantage of what nature has to offer, several organisms, including microalgae, can natively bioremediate these heavy metals. However, the effectiveness of such processes does not meet expectations, especially with the increasing amount of pollution in today’s world. Therefore, with the goal of creating effective strains, synthetic biology via bioengineering is widely used as a strategy to enhance the heavy metal bio-removing capability, either by directly engineering the native ability of organisms or by transferring the ability to a more suitable host. In order to do so, a list of genes or proteins involved in the processes is crucial for stepwise engineering. Yet, a large amount of information remains to be discovered. In this work, a comprehensive library of putative proteins that are involved in heavy metal bio-removal from microalgae was constructed. Moreover, with the development of machine learning, the 3D structures of these proteins are also predicted, using machine learning-based methods, to aid the use of synthetic biology further.

Abstract

Synthetic biology is a principle that aims to create new biological systems with particular functions or to redesign the existing ones through bioengineering. Therefore, this principle is often utilized as a tool to put the knowledge learned to practical use in actual fields. However, there is still a great deal of information remaining to be found, and this limits the possible utilization of synthetic biology, particularly on the topic that is the focus of the present work—heavy metal bio-removal. In this work, we aim to construct a comprehensive library of putative proteins that might support heavy metal bio-removal. Hypothetical proteins were discovered from Chlorella and Scenedesmus genomes and extensively annotated. The protein structures of these putative proteins were also modeled through Alphafold2. Although a portion of this workflow has previously been demonstrated to annotate hypothetical proteins from whole genome sequences, the adaptation of such steps is yet to be done for library construction purposes. We also demonstrated further downstream steps that allow a more accurate function prediction of the hypothetical proteins by subjecting the models generated to structure-based annotation. In conclusion, a total of 72 newly discovered putative proteins were annotated with ready-to-use predicted structures available for further investigation.

Lithium-Ion Battery Recycling in the Circular Economy: A Review

Lithium-ion batteries have become a crucial part of the energy supply chain for transportation (in electric vehicles) and renewable energy storage systems. Recycling is considered one of the most effective ways for recovering the materials for spent LIB streams and circulating the material in the critical supply chain. However, few review articles have been published in the research domain of recycling and the circular economy, with most mainly focusing on either recycling methods or the challenges and opportunities in the circular economy for spent LIBs. This paper reviewed 93 articles (66 original research articles and 27 review articles) identified in the Web of Science core collection database. The study showed that publications in the area are increasing exponentially, with many focusing on recycling and recovery-related issues; policy and regulatory affairs received less attention than recycling. Most of the studies were experiments followed by evaluation and planning (as per the categorization made). Pre-treatment processes were widely discussed, which is a critical part of hydrometallurgy and direct physical recycling (DPR). DPR is a promising recycling technique that requires further attention. Some of the issues that require further consideration include a techno-economic assessment of the recycling process, safe reverse logistics, a global EV assessment revealing material recovery potential, and a lifecycle assessment of experiments processes (both in the hydrometallurgical and pyrometallurgical processes). Furthermore, the application of the circular business model and associated stakeholders’ engagement, clear and definitive policy guidelines, extended producer responsibility implications, and material tracking, and identification deserve further focus. This study presents several future research directions that would be useful for academics and policymakers taking necessary steps such as product design, integrated recycling techniques, intra-industry stakeholder cooperation, business model development, techno-economic analysis, and others towards achieving a circular economy in the LIB value chain.