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Ports are essential and strategic nodes of international trade and economic activities. The integration of port resources helps enhance the optimal division of port functions to further promote economic development. This paper explores the evolutionary trends of port integration policy from 2011 to 2021 in China through a text-mining approach. We first used the Latent Dirichlet Allocation (LDA) topic analysis method to analyze the port integration policies and summarize the evolutionary trends of port policies. In addition, an association analysis was conducted to explore port integration policies' impacts by examining their relationships among the environmental protection, digitalization level, and port development scale. Our findings suggested that China's port integration policy has evolved from specific and simple to abstract and complicated at the managerial level. Port development has enriched from infrastructure construction to the ideology of economic development. Our findings show that China's port integration is gradually improving the port operation. The findings of the study contribute to the extant literature by analyzing the port integration policy evolution in China and can be referred to by other countries. • Text mining method was used to explore the port integration policy evolution. • Port integration policy evolved from specific and simple to abstract and complicated. • Port development enriched from basic infrastructure to the governance model. • The evolution of port integration policy was related to reducing carbon emissions in the port sector. • The evolution of port integration policy made the ports intelligent in association with digital technology such as big data and AI. [ABSTRACT FROM AUTHOR]

In response to the growing emphasis on green packing, e-commerce businesses actively pursue sustainable solutions that balance cost reduction with environmental conservation. Traditional research on three-dimensional bin packing has concentrated on maximizing spatial utilization under fixed box dimensions. However, in the practical context of e-commerce, packing boxes exhibit a wide range of sizes within a single warehouse. Customizing packing to prevent material and space wastage has become crucial for sustainable development. This paper innovates traditional three-dimensional packing research by introducing open dimensions instead of fixed ones. It addresses challenges in e-commerce packing, such as multiple orders and diverse bin shapes, to formulate a mixed-integer programming model. Focused on the carbon emission lifecycle's usage phase for packing boxes, the model aims to minimize associated costs while ensuring that items' weight, the center of gravity, sufficient support, and non-overlapping placement are maintained during the packing process. It also incorporates one-dimensional and two-dimensional fixed bin sizes. To solve this model, the paper proposes an improved hybrid genetic algorithm for stack sequence optimization. This algorithm systematically optimizes the dimensions for each box type. Building upon this, the study introduces an algorithm capable of estimating packing material consumption and the percentage reduction in carbon emissions during the packing process, given the known variability in packing box utilization. These two algorithms are integrated into an open-dimension packing box warehouse management ecological closed loop system designed for the B2B e-commerce context. In experiments with the proposed model and algorithms, the results demonstrate an average packing rate improvement of 10%–12% compared to alternative methods. Additionally, packing material consumption and carbon emissions are reduced by approximately 16.56%–19.85%, confirming the effectiveness of the proposed approach. • Open dimension model boosts green e-commerce packing efficiency. • Stacking algorithm lifts space use up to 12%. • Material and emissions cut 16%–20% on space gains. • Eco warehouse system enables box reuse and material recycle. [ABSTRACT FROM AUTHOR]

• A multi-objective model is proposed, which contains both the cost and carbon emission objectives. The sizing of the grid-connected converter is included. The carbon emission of the power from the grid is considered. The model can comprehensively describe the requirements of LVDC systems in the economy and environmental protection. • This paper considers the effect of EVs on the sizing of LVDC systems. Both the charging and discharging of EVs are fully used to reach better sizing and operation for the system. • A minimum fuzzy carbon emission method (MFCEM) is given to transform the multi-objective into a single objective. Compared with the linear weighting method, MFCEM is a useful method for finding a point on the Pareto front that balances cost and carbon emissions. Grid-connected low-voltage direct current (LVDC) systems offer a promising solution for achieving low-carbon buildings. However, a new challenge arises in sizing grid-connected LVDC systems, which is to fully utilize distributed renewable energy, energy storage, and load demand response to minimize both the economy and carbon emissions. To address this gap, this paper studies the sizing of grid-connected LVDC systems, considering the grid-connected converter, photovoltaic (PV), battery, and demand response of electric vehicles (EVs). Firstly, two objective functions are proposed, including the economy and carbon emissions. Secondly, constraints for sizing and operation are presented, with particular consideration given to the discharging of EVs and the corresponding cost of cycle-life loss. Finally, a minimum fuzzy carbon emission method (MFCEM) is proposed to solve the model, which can adaptively and objectively transform the multi-objective into a single objective. According to the case study, the proposed model comprehensively considers the cost and carbon emissions of grid-connected LVDC systems, and its feasibility and validity are verified. Compared with the linear weighting method, MFCEM is a useful method for finding a point on the Pareto front that balances cost and carbon emissions. [ABSTRACT FROM AUTHOR]

In the context of global warming and energy scarcity, regional integrated energy system (RIES) can effectively improve energy utilization efficiency and reduce carbon emissions. However, this leads to the increased complexity of the market transactions. To this end, based on the mixed game strategy, a multi-agent low-carbon optimal dispatch model of RIES is proposed in this paper. Firstly, to fully consider the low-carbon objective of the system, a reward and punishment ladder carbon trading mechanism and a ladder integrated demand response (IDR) model are developed. Then, the decision models of the energy management operator (EMO), multiple energy hub agents (EHAs) and the user load aggregator (ULA) are constructed respectively with the goal of economy, and carbon emission flows are introduced as constraints. The interactive trading process of various stakeholders is simulated by a mixed game with master-slave game nested bidding strategy. Finally, the economics and carbon emissions of the system in different scenarios are analyzed by examples, and the effectiveness of the proposed model is verified. Numerical simulation results show that the proposed method not only has good economic and low-carbon environmental protection benefits, but also ensures the interests of various stakeholders. • A multi-agent energy trading mechanism is proposed to realize low-carbon operation. • A ladder integrated demand respond model considering carbon compensation is developed. • A multi-agent optimization strategy based on mixed game is proposed. [ABSTRACT FROM AUTHOR]

• China's sustainable development relies on agricultural trade and carbon emissions. • Carbon emission transfer index in agricultural trade is measured. • Decoupling-recoupling model and integrated prediction model are constructed. • A unified framework for trade, environment and technology is established. Under the new development pattern of domestic and international "dual circulation" in China, studying the relationship among green technology innovation, agricultural trade deficit (ATD) and carbon emission transfer embodied in agricultural trade (ATCT) becomes crucial for achieving coordinated and unified high-quality economic development and efficient environmental protection. Based on this, the paper uses environmental input–output model, "two-stage" decoupling and recoupling model, panel vector auto-regressive model, spatial econometric model and "rolling" Grey-BP neural network prediction model to explore present status of ATD, ATCT and their relationship, driving role of green technology innovation, as well as whether that relationship will be improving in the future. The results reveal the following: (1) China's ATD and ATCT show an increasing trend year by year, and their inter-provincial differences are gradually significant over time. The overall relationship between ATD and ATCT does not display ideally, which makes it necessary to quickly transform that relationship into reasonable and ideal state. (2) Green technology innovation has significant positive "U-shaped" and inverted "U-shaped" local effects on ATD and ATCT respectively, with a reasonable range of ATD reduction while ATCT increase valuing from 0 to 0.290, and has significant positive "U-shaped" spatial spillover effect on both without any reasonable range. The short-term effect of green technology innovation on coordinated promotion between ATD and ATCT is superior to the long-term one. (3) Green technology innovation has a significant regional heterogeneity. Regional differences must be taken into consideration seriously, and the measures adapted to local conditions are crucial. The role of fundamental and progressive green technology innovation has heterogeneity, which means that targeted development and utilization of green technology products are important. (4) Regardless of the time horizon, the relationship between ATD and ATCT will improve, which can provide a key step for coordinated development of economy and environment in agricultural trade. Therefore, in order for China to implement and promote further opening-up, reduce agricultural trade dependence, ensure food security and important agricultural product supply, as well as achieve the unity of high-quality economic development and ecological efficient protection, it is necessary to reasonably reverse trade deficit and increase carbon emission transfer in agriculture. [ABSTRACT FROM AUTHOR]

With the current decreasing fossil resources and increasing carbon dioxide emissions, researchers are increasingly concerned about the development and utilization of biomass resources. The development of bio-based waterborne polyurethanes (BWPU) provides a new direction for the utilization of biomass resources and the protection of the environment. BWPU has attracted much attention from academia and industry due to their good physical and chemical properties, no volatile organic compounds (VOCs) emissions, exploitation of renewable substances, and structural design-ability. BWPU typically includes the polymerization of bio-based monomers, such as animal and vegetable oils, the addition of bio-based nanofillers, such as cellulose, lignin, and chitosan, and antimicrobial modifications, such silver nanoparticles and carvacrol, which can effectively replace traditional petroleum-based resources. At present, there are few reviews on the synthesis and applications of BWPU. Therefore, this paper reviews the recent progress in the synthesis of BWPU, and focuses on its applications in coatings, adhesives and antimicrobials, which is expected to provide reference and summarize research priorities and issues. [Display omitted] • Summarize bio-based waterborne polyurethanes (BWPU) recently produced from bio-based raw materials. • Summarize the current applications of BWPU, including coatings, adhesives and antimicrobials. • Suggestions are provided for further future research by BWPU in other areas. [ABSTRACT FROM AUTHOR]