Research on Resource Carbon Emission Allocation Efficiency Based on Blockchain Consensus Algorithm

This paper takes the secondary low-carbon supply chain composed of a manufacturer and a retailer as the research object and takes the government subsidy strategy of low-carbon supply chain as the research theme, the government invests in the construction of blockchain technology application platform, and supply chain enterprises use blockchain technology for compensation. Under this background, considering consumers’ low-carbon preference and green trust, a three-stage game model dominated by the government and followed by manufacturers and retailers under the four scenarios of emission reduction technology input subsidy and low-carbon product output subsidy before and after the application of blockchain technology is established. By comparing the optimal social welfare, carbon emission reduction rate, and low-carbon product output under the four scenarios, the optimal problem of government low-carbon subsidy strategy is discussed. It is found that when the product of consumers’ low-carbon preference coefficient and green trust coefficient is greater than a certain fixed value, the government can obtain higher social welfare and promote enterprises’ emission reduction through output subsidies. The government can always promote the demand for low-carbon products through output subsidies. When the emission reduction cost coefficient approaches infinity, the demand for low-carbon products when the government implements output subsidies are four times that when the government implements technology subsidies. When the single cycle shared cost of the blockchain platform and the unit cost of enterprise application of blockchain technology are less than a certain threshold, the government’s construction of the blockchain platform can obtain higher social welfare, promote enterprise emission reduction, and improve consumers’ demand for low-carbon products.

A marine fungus efficiently degrades polyethylene

Plastics pollution has been a global concern. Huge quantities of polyethylene (PE), the most abundant and refractory plastic in the world, have been accumulating in the environment causing serious ecological problems. However, the paucity of microorganisms and enzymes that efficiently degrading PE seriously impedes the development of bio-products to eliminate this environmental pollution. Here, by screening hundreds of plastic waste-associated samples, we isolated a fungus (named Alternaria sp. FB1) that possessing a prominent capability of colonizing, degrading and utilizing PE. Strikingly, the molecular weight of PE film decreased 95% after the fungal treatment. Using GC-MS, we further clarified that a four-carbon product (named Diglycolamine) accounted for 93.28% of all degradation products after the treatment by strain FB1. We defined potential enzymes that involved in the degradation of PE through a transcriptomic method. The degradation capabilities of two representative enzymes including a laccase and a peroxidase were verified. Lastly, a complete biodegradation process of PE is proposed. Our study provides a compelling candidate for further investigation of degradation mechanisms and development of biodegradation products of PE.

A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty

With the increase in pollution and people’s awareness of the environment, reducing greenhouse gas (GHG) emissions from products has attracted more and more attention. Companies and researchers are seeking appropriate methods to reduce the GHG emissions of products. Currently, product family design is widely used for meeting the diverse needs of customers. In order to reduce the GHG emission of products, some methods for low-carbon product family design have been presented in recent years. However, in the existing research, the related GHG emission data of a product family are given as crisp values, which cannot assess GHG emissions accurately. In addition, the procurement planning of components has not been fully concerned, and the supplier selection has only been considered. To this end, in this study, a concurrence optimization model was developed for the low-carbon product family design and the procurement plan of components under uncertainty. In the model, the relevant GHG emissions were considered as the uncertain number rather than the crisp value, and the uncertain GHG emissions model of the product family was established. Meanwhile, the order allocation of the supplier was considered as the decision variable in the model. To solve the uncertain optimization problem, a genetic algorithm was developed. Finally, a case study was performed to illustrate the effectiveness of the proposed approach. The results showed that the proposed model can help decision-makers to simultaneously determine the configuration of product variants, the procurement strategy of components, and the price strategies of product variants based on the objective of maximizing profit and minimizing GHG emission under uncertainty. Moreover, the concurrent optimization of low-carbon product family design and order allocation can bring the company greater profit and lower GHG emissions than just considering supplier selection in low-carbon product family design.

Rice Husk Research: From Environmental Pollutant to a Promising Source of Organo-Mineral Raw Materials

Rice husk is a large-tonnage waste left from rice production. It is not subject to humification and therefore becomes a serious environmental pollutant. Due to the presence of two essential elements—carbon and silicon—in its composition, rice husk is a promising organo-mineral raw material. The known methods for processing of rice husk are associated with the formation of even more aggressive waste. The creation of a waste-free technology for processing this plant material requires a detailed study. Rice husk of yzylorda oblast was studied using IR, SEM, TA, TPD-MS, EPR, and TEM methods. It was determined that under a temperature up to 500 °C, the ligno-carbohydrate component of rice husk decomposes almost completely. Three main peaks are recorded during the decomposition: hemicellulose at 200 °C, cellulose at 265 °C, and lignin at 350–360 °C. This process is endothermic. However, above of 300 °C the exothermic reactions associated with the formation of new substances and condensation processes in the solid residue begin to prevail. This explains the increase in the concentration of paramagnetic centers (PMCs) in products of rice husk carbonization in the range of up to 450 °C. Further increase in temperature leads to a decrease in the number of PMCs as a result of carbon graphite-like structures formation. The silicon–carbon product of rice husk carbonization (nanocomposite) is formed by interconnected nanoscale particles of carbon and silicon dioxide, the modification of which depends on the temperature of carbonization. The obtained data allow management of the rice husk utilization process while manufacturing products in demand based on ecofriendly technologies.

Analysing the effect of low carbon product design on firm performance

PurposeThe purpose of this study is to analyze the effect of low carbon product design on firm's competitiveness and economic performance. It also examines the mediating role of the proactive environmental strategy and eco-innovation on low carbon product design, competitiveness and economic performance.Design/methodology/approachThrough a questionnaire-based survey, the data were collected from 69 Indian manufacturing firms and analyzed using a variance-based structural equation modeling (SEM) technique to test the proposed hypotheses.FindingsThe results show that the low carbon product design significantly improves firm's competitiveness and economic performance, and proactive environmental strategy significantly mediates the relationship between low carbon product design and firm's competitiveness.Practical implicationsThis study provides a framework for the adoption of low carbon product design. It demonstrates how manufacturing firms can implement environmental friendly product design. It also analyses the contextual factors that ensure a successful low carbon product design.Originality/valueThis article investigates the economic benefit of low carbon product design, thus filling lacuna in existing research.

An Extenics-Based Scheduled Configuration Methodology for Low-Carbon Product Design in Consideration of Contradictory Problem Solving

Low-carbon product design involves a redesign process that requires not only structural module modification, but more importantly, generating innovative principles to solve design contradictions. Such contradictions include when current design conditions cannot satisfy design requirements or there are antithetical design goals. On the other hand, configuration tasks in the reconfiguration process are interdependent, which requires a well-scheduled arrangement to reduce feedback information. This study proposes an effective configuration methodology for low-carbon design. Firstly, configuration tasks and configuration parameters are designated through quality characteristics, and the directed network along with the associated values of configuration tasks are transformed into the design structure matrix to construct the information flow diagram. Then, the Extenics-based problem-solving model is presented to address design contradictions: low-carbon incompatibility and antithetical problems are clarified and formulated with a basic-element model; extensible and conjugate analysis tools are used to identify problematic structures and provide feasible measures; the Gantt chart of measures execution based on the information flow diagram is constructed to reduce feedback and generate robust schemes with strategy models. The methodology is applied to the vacuum pump low-carbon design, the results show that it effectively solves contradictions with innovative design schemes, and comparative analysis verifies the performance of Extenics.

Biomass-Derived Carbonaceous Materials to Achieve High-Energy-Density Supercapacitors

Biomass-derived carbonaceous materials are considered as one of the most perspective electrodes for symmetric supercapacitors working with alkaline-basic electrolytes. However, they still exhibit lower energy density. Herein, we demonstrate the capacitance performance of the commercial carbon product (YP-50F, “Kuraray Europe” GmbH), obtained from coconuts, in symmetric supercapacitors by using lithium and sodium organic electrolytes. It is found that YP-50F delivers higher energy density when lithium electrolyte containing LiBF4 salt is employed. The sodium electrolyte with NaPF6 salt is less aggressive toward YP-50F than that of LiPF6 salt, as a result of which a good capacitance performance is observed in the sodium electrolyte. The contributions of surface functional groups of YP-50F, as well as its compatibility with non-aqueous lithium and sodium electrolyte, are discussed on the basis of post-mortem scanning electron microscopy (SEM)/energy-dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) data analyses. The obtained correlations could be of significance in order to design sustainable supercapacitors with high energy density.

Two-Stage Pricing Decision for Low-Carbon Products Based on Consumer Strategic Behaviour

The development of information technology has changed the pricing strategy of retailers, and consumers have also made strategic consumption behaviours accordingly. At the same time, changes in the environment have caused changes in the retailer’s products and raised consumers’ environmental awareness. This paper uses a two-stage pricing model to study the low-carbon product pricing decisions of retailers based on strategic consumers with low-carbon preferences in two situations. Through the analysis of low-carbon and ordinary products in two situations, the following conclusions can be drawn: (1) In a market where retailers only sell low-carbon products, product prices and profits increase as consumers’ green preference θ increases. (2) In the low-carbon product and ordinary product markets, the price and profit of low-carbon products increase with regard to consumers’ green preference θ . (3) In the second stage, when consumers’ intertemporal discount factor β for ordinary products is larger than that of low-carbon products, the retailer’s total profit is smaller. The research conclusion comprehensively analyses the impact of customer strategic behaviour on the two-stage pricing decision of green differentiated products, which provides a very important reference for retailers to make pricing optimization decisions.