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China's rapid urbanization has led to the development of integrated transport networks, which requires the transport sector to pay particular attention to the integrated transport comprehensive carrying capacity (ITCCC). Concurrently, global climate change has focused the world community's attention on greenhouse gas concentrations like CO2. This study establishes an ITCCC measurement model of urban agglomerations (UAs) and measures the comprehensive carrying capacity from four factors: socio-economic, basic resources, transport facilities, and traffic environment. In particular, this paper takes carbon emission as a critical indicator of the traffic environment when considering the impact factors of ITCCC. Based on the data of China's five major UAs, this study estimates carrying capacity levels with the ITCCC model and analyses regional characteristics using the spatial-temporal differentiation method. The results show that the traffic environment significantly impacts the ITCCC. Further low-carbon transport policies and measures are recommended to achieve sustainable development of integrated transport in UAs. [ABSTRACT FROM AUTHOR]

The real-time dynamic coupling under the virtual-coupling technology guarantees running multi-group trains in different sections based on passenger flow's spatial and temporal distribution characteristics. It enables more flexible transport organization modes such as full-length and short-turn routing and the express/local stop mode. Utilizing the redundant capacity of the airport line to carry out coordinated transportation of passengers and goods is an essential means of relieving urban traffic pressure, saving energy, and protecting the environment. To promote urban rail transit to achieve the goal of "double-carbon," the optimization of passenger and freight cooperative transport schemes based on the virtual coupling technology for the airport line of the rail transit is investigated. Based on the train operation of full-length and short-turn routing under the virtual-coupling technology, according to the unbalanced distribution characteristics of passenger and freight flows in urban rail transit, this paper constructs an optimization model of urban rail transit capacity allocation to minimize passenger travel costs, enterprise operation costs, and carbon emission costs, and considering the constraints of the carbon emission policy, with the constraints such as the train operation safety, the constraints of the balance of the passenger flow and freight flow loading. The multi-objective model to solve the optimization problem has been designed. Given the complexity of the multi-objective model solution, an improved nondominated sorting genetic algorithm is designed, and the algorithm makes use of the screening function of the constraints during the initial population generation process, which effectively balances the relationship between the whole process of screening and time-consumption of the NSGA-II algorithm. Taking Wuxi Metro Line 3 as an example, the results show that: (i) Compared with the traditionally large and small crossing mode, full-length and short-turn routing of virtual coupling Trains proposed in this paper can reduce the average waiting time of passengers by about 2.01min, the cost of carbon emission by 15.7% and the cost of enterprise operation by 20.2%, and at the same time, improve the average total rate by about 50%, which verifies that the virtual formation technology is conducive to improving the efficiency of passenger travel and reducing the operating cost and the carbon cost. It is also beneficial for improving passenger traveling efficiency. (ii)The single-alignment fixed configuration mode, compared with the single-flow mode, can increase the average full-load rate by 26.6% while increasing the passenger travel cost by only 0.98% and reducing the carbon emission cost by a small margin; the virtual configuration technology based-on the large and smallalignment operation and transport scheme increases the passenger travel cost by about 0.3% and further reduces the carbon emission cost by 1.9%. They further reduced the carbon emission cost by 1.9% while increasing the average total occupancy rate by about 5.8%. The proposed models and algorithms provide some decision support for urban rail transit operators to optimize transport schemes under different carbon emission policies and the virtual coupling operation mode. [ABSTRACT FROM AUTHOR]

The determination of transport schemes represents a critical facet of operational management in express freight logistics and constitutes a significant scientific challenge within the domain of freight transportation. Globally, there is an escalating focus on adopting low-carbon transit strategies, and it has been established that multimodal transport methods can significantly diminish carbon emissions associated with freight transportation. Moreover, the scheduled arrival and departure times for railway and aviation are pivotal in shaping the selection of transport schemes. Regrettably, these critical considerations are frequently neglected in the prevailing body of research. This paper endeavors to bridge this research gap by advocating for a lowcarbon transport scheme for express freight through the utilization of an integrated transportation system. It undertakes a collaborative optimization study concerning transportation modes and routes. This document proposes an optimization framework for the selection of express freight transport schemes that incorporates considerations for carbon emissions and fixed timetables. A three-layer service network is developed, integrating the fixed schedules of railway and aviation to formulate a space-time shortest path problem aimed at minimizing the generalized transportation cost. Three models are formulated to reduce the transportation costs and carbon emissions of logistics enterprises, taking into account diverse carbon emission policies. Subsequently, a two-stage heuristic algorithm is introduced to address this complex problem. The findings reveal that by accounting for customers' transportation time constraints and judiciously selecting transportation modes and routes, it is feasible to effectively minimize transportation costs and carbon emissions. [ABSTRACT FROM AUTHOR]

Aiming at the problems of poor scheduling flexibility and insufficient carbon emission reduction capacity of the current integrated energy system, this paper proposes an optimization scheduling model of integrated energy demand response that combines source-load synergy with reward and punishment stepped carbon trading mechanism. Firstly, the integrated energy system operation architecture including electricity-heat-cooling energy was constructed to harmonize the energy generation side and consumption side and effectively improve the multi-energy complementary capability of the system. Secondly, the reward and punishment stepped carbon trading mechanism is established by combining the initial carbon quota allocation method and the actual carbon emission calculation theory, so that environmental friendliness and economic sustainability are effectively improved. Finally, to minimize the system operating cost, an integrated demand response optimal dispatch model that considers the characteristics of electric, thermal and cooling loads is constructed to determine the optimal dispatch scheme for the integrated energy system. The results of the calculation example indicate that the proposed integrated demand response model has the function of peak reduction and valley correction, energy conservation and carbon reduction, and provides a feasible solution for the integrated energy system optimal scheduling. [ABSTRACT FROM AUTHOR]

This paper purposes an optimal organization of route and transportation mode in a multimodal transportation network. It considers the uncertainties of freight volumes, expenses, time, and carbon emissions. Considering the above factors comprehensively, it establishes a multiobjective chance-constrained model which aims to minimize total transportation cost. Base on this, the corresponding NSGAâ...¢ is introduced to solve the model, and the distribution of the Pareto solutions under different parameters are discussed. Using Monte Carlo simulation techniques, the paper explores the solutions of each objective under different reliabilities, and found them to be in accordance with economic regularity. With an increase in reliability, each objective increases monotonously, and the results that correspond to an 80% reliability are the best choice. The corresponding cost is acceptable, and the transportation process completes with high reliability. The study provides a reference for similar studies. [ABSTRACT FROM AUTHOR]

Optimization of the travel paths is necessary to shorten travel time and reduce travel costs. This paper proposes the analysis theory of the travelers' low carbon route choice behavior based on improved prospect theory by analyzing the punctuality rate of travel time, the travelers' comfort level on the travelers' intermodal transport route optimization. Dual reference points are set according to the whether travelers have the prior experience as the judgment basis, constructing an optimization model of travelers' intermodal transport under bounded rationality. The results show that, in the travelers' intermodal transport route considering carbon emissions, the travel route selected by travelers will change with the road state. In this problem, the gain sensitivity coefficient α and the loss sensitivity coefficient β have influence on the decision. When traffic crowding or bad weather occurs, travelers tend to be more sensitive to time. The setting of each parameter has an important impact on the comprehensive prospect values. [ABSTRACT FROM AUTHOR]

In this paper we collect data of corporate bonds and government bonds issued from 2005 to 2019 from CSMAR database. Firstly, we make a stepwise regression analysis and research on the impact of climate risk, selling back and cross-market transaction on corporate bond yield. The impact of climate risk on corporate bond yield is positive because if carbon dioxide emission is more, the earth will be warmer and sea levels will be higher, then companies will face more climate risks and corporate bond yields will increase. The impact from the selling back on corporate bond yield is negative because if the bond can be resold, the risk will be lower and the bond yield will decrease. The impact of cross-market transaction on corporate bond yields is positive because if corporate bonds cannot be traded, the liquidity of corporate bonds will be low, and the risk will increase, then corporate bond yield will increase. Secondly, logarithmic regression analysis of climate risk factors shows that the climate risk is still significant and the model fits well. Selling back, cross-market trading and other factors are significant, and the pattern is more significant. Compared with the original model, it can better explain corporate bond yield. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed generator (DG) optimization framework based on an improved northern goshawk optimization (INGO) algorithm to install multiple DGs into the distributed system (DS) simultaneously. Various case studies are conducted in constant or varying load and generation models. The framework considers the power system's critical constraints while optimizing each DG's location, capacity, and power factor to minimize energy losses and voltage deviations and improve DG penetration levels and system voltage distribution. The effectiveness and stability of the INGO algorithm were first verified in two constant test systems, and the effect of the optimal power factor of the DG on the system was considered. The results of all case studies show that the INGO algorithm performs better than other existing methods in reducing active power losses and voltage deviations. When the three parameters of generator location, capacity, and power factor were optimized simultaneously, the active power losses of the two test systems were reduced by 93.96% and 98.11%, respectively. On this basis, photovoltaics (PVs) and wind turbines (WTs) as renewable energy DGs (REDGs) were also introduced in two changing test systems. The performance gap between two REDGs and conventional generators (CGs) is compared. The all-day active energy losses in the two tested systems were reduced by 88.27% and 94.74% after WTs installation. Much higher than 51.23% and 53.64% after installing PVs, almost as good as installing CGs. Therefore, WTs can replace CGs to reduce carbon emissions because the difference in energy loss and voltage deviation between the two is tiny. [ABSTRACT FROM AUTHOR]

To promote the consumption and development of new and green energy sources, we propose an economically optimal dispatch model to simulate virtual power plants (VPPs) in parks considering low-carbon objectives based on a dualcarbon background. First, individual models involved in the optimal dispatch of VPPs are introduced. A two-stage operation process of electricity-to-hydrogen transformation and hydrogen methanation of power-to-gas equipment is refined and analysed. Unstable wind power is converted into hydrogen and supplied to the hydrogen load during the electrolysis of the water-tohydrogen stage in conjunction with the development of hydrogen energy demands. Second, to minimise the sum of operating and carbon emission costs, an optimal dispatch model utilised by the virtual power plant considering a low-carbon objective is established. A simulation of the calculation case shows that the proposed model can achieve efficient energy utilisation and improved economic and carbon costs for a VPP in the park. Finally, a sensitivity analysis of the system cost is conducted by adding weighting coefficients; the optimal range of weighting coefficients for the VPP in the park proposed in this paper are derived for reference by considering economic benefits and environmental protection. [ABSTRACT FROM AUTHOR]

Aiming at the two-stage supply chain composed of manufacturers and retailers, it is assumed that all enterprises upstream and downstream strive to implement carbon emission reduction. Because of information asymmetry, manufacturers have a moral hazard in reducing carbon emissions. At the same time, the government decides whether to implement punishment or not by testing the carbon emission reduction standards of the product declared by manufacturers and retailers. This paper focuses on the impact of manufacturers' moral hazard probability and government punishment level on carbon emission reductions and profits of upstream and downstream enterprises. The study results show that when the government penalty intensity acts only on the retailer, the manufacturer must have an incentive for moral hazard behavior. The higher its moral hazard probability, the greater the retailer's expected profit loss. Therefore, a linear incentive contract design with fixed payments and adjustable incentive coefficients for retailers and an external loss-sharing contract design are investigated as a way to resolve the possible losses from moral hazards. The before and after comparison with the profit level and emission reductions also confirm the effectiveness of the contract design, which can ensure the manufacturer's expected profit. Achieve Pareto improvement of retailers' profits simultaneously. Linear incentive contracts have some limitations compared to external loss-sharing contracts. The analysis of examples further verifies the validity of the relevant conclusions. [ABSTRACT FROM AUTHOR]

This paper studies carbon management for optimisation of lot sizing in manufacturing under the stochastic make-to-order production planning environment, with an aim to maximise operational profit. It covers not only about the business benefits, but also about the ecological impingements involved with production planning. Our main concerns are focused on two primary green factors—carbon tax and public green awareness—to address their respective impacts on production planning, because carbon tax inevitably increases cost while public green awareness affects customers’ inclination towards green products and hence market demand. The result underscores the critical roles played by carbon management in manufacturing for achieving both ecological and economic benefits. It also provides managerial insight into operations optimisation in production planning to help firms abate ecological deterioration resulting from carbon emissions when achieving their economic performance. [ABSTRACT FROM AUTHOR]