Grey Correlation Analysis of Transportation Carbon Emissions under the Background of Carbon Peak and Carbon Neutrality

Optimization and analysis of battery thermal management system structure based on flat heat pipes and biomimetic fins

As one of the key components of electric vehicles, the enhancement of the performance of the power battery is closely intertwined with an efficient Battery Thermal Management System (BTMS). In the realm of BTMS, Flat Heat Pipes (FHP) have garnered considerable attention due to their lightweight structure and excellent thermal conductivity. Thus, a BTMS configuration scheme based on FHP is proposed in this study. Utilizing orthogonal design and fuzzy grey relational analysis as the evaluation methods, coupled with numerical simulations, an investigation into the influence of four structural parameters of the novel biomimetic fins (namely, the diameter, height, spacing of protrusions, and height of cooling fins) on the temperature distribution of the battery pack is conducted. The research findings indicate that to maintain the battery within an optimal operational temperature range, the optimal dimensional parameters should be controlled at 17.5 mm, 4 mm, 13 mm, and 90 mm, respectively. Subsequent sensitivity analysis reveals that the height of the protrusions exhibits the most significant influence on the maximum temperature of the module, whereas the height of the cooling fins exerts a considerable impact on the consistency of the module temperature. The optimized maximum temperature is determined to be 36.52 °C, with a temperature difference of 2.65 °C.

Analysis of spatial spillover effects and influencing factors of transportation carbon emission efficiency from a provincial perspective in China

Globally, the transportation industry has become one of the leading sectors in carbon emission, and all countries are committed to environmental protection and energy conservation while experiencing rapid development. Under China's "dual-carbon" goal, the carbon emission problem hinders the construction of China's green transportation system and affects the high-quality development of transportation, so it is of great significance to study the spatial pattern of carbon emission efficiency in the transportation industry and the factors affecting it. Firstly, this paper measures the carbon emission value of transportation in 30 provinces in China from 2010 to 2020 based on the IPCC method and measures the carbon emission efficiency through the super-efficiency slack-based measurement model. Secondly, spatial autocorrelation analysis was conducted to determine the spatial clustering characteristics of the efficiency values. Finally, two spatial Durbin models are constructed to measure the spatial spillover effects and analyze the short-term immediate effects of each influencing factor on the static model and the long-term effects of the dynamic model considering the time lag of the transportation carbon emission efficiency. The results of the study show that (1) the average value of efficiency in the central and eastern regions is basically higher than 0.5; in the western and northeastern regions, it is basically lower than 0.3.The overall efficiency of carbon emission in the region shows a fluctuating upward trend but with increasing regional differences. (2) The number of regions with positive spatial correlation increased from 21 to 25 during the study period, and the degree of provincial transportation carbon emission efficiency agglomeration increased. (3) Although urbanization and energy intensity have a large detrimental influence on transportation carbon emission efficiency, environmental regulation has a major favorable effects on it both long and short term. Population scale, opening level, and urbanization all have significant spatial spillover effects. Accordingly, relevant policy recommendations are put forward to provide theoretical guidance for promoting the realization of low-carbon transportation.

The mechanism of China's renewable energy utilization impact on carbon emission intensity: Evidence from the perspective of intermediary transmission

Renewable energy (RE) plays a crucial role in global energy transformation, and a thorough study of the potential impact of RE on regional carbon emissions is of great significance. This is particularly relevant to China, which needs to clarify its path to carbon reduction. Using the sample data of 30 provinces in China from 2000 to 2021, this paper uses the Granger causality test to verify the causal relationship between carbon emission intensity (CEI) and other factors. It builds a mediation effect model on this basis to explore the direct impact effect and indirect transmission path of renewable energy utilization (REU) on CEI. The results show that REU has a one-way causal relationship with CEI. REU can directly and indirectly reduce CEI by improving social wealth and changing the direction of energy investment. In addition, REU indirectly increases CEI through the transmission paths of investment in the energy industry - social affluence and industrial level-social affluence. The CEI is indirectly reduced through the conduction paths of (social affluence-Urbanization rate), (Investment in the energy industry-Urbanization rate), (Industrial level-Urbanization rate), and (Industrial level-Investment in the energy industry). These conclusions will assist policymakers in exploring targeted pathways for low-carbon power development, providing a reference for strategic and sustainable carbon reduction policies.

A novel fractional-order grey prediction model: a case study of Chinese carbon emissions

Objective and accurate prediction of carbon emissions can provide a basis for the country to achieve carbon emission reduction targets and can also comprehensively and scientifically predict the peak of carbon emissions effectively, providing valuable reference information for the implementation of specific emission reduction policies and measures at each stage. In this paper, a novel fractional-order grey multivariate forecasting model is established to analyze and forecast China's carbon emissions, reflecting the principle of new information priority. The model adds fractional-order cumulative sequences to the traditional integer-order cumulative sequences, uses the Gamma function to represent the fractional-order sequences and the time-response equation, and uses the particle swarm algorithm to find the optimal order of the cumulative sequence. Finally, the modeling steps of the model are given. Then, the new model is analyzed for its effectiveness from three different perspectives using 21 years of Chinese carbon emission data. The results of the first and second cases show that the newly established particle swarm optimization fractional-order model is superior to the grey multivariate comparison model. The results of the third case show that the new model is superior to the three classical grey prediction comparison models. It has stable characteristics for both simulation and prediction and also shows high accuracy, and all three cases fully illustrate the effectiveness of the new model. Finally, this new model is applied to forecast China's carbon emissions from 2022-2026, analyze the forecast results, and make relevant recommendations.

Analysis of environmental sustainability and economic development from electricity consumption based on the modified spatial Durbin model

The study investigates the impacts of financial development, electricity use, and technology innovation on CO2 emissions. International trade also plays an essential role in the economic development of Pakistan. Studying the relationship between ecological parameters, technological innovation, electricity use, and CO2 emissions is necessary to formulate the country's reasonable and practical energy policies. Based on the study's use of data from 292 Pakistani firms from 2006 to 2021, the paper investigates the mechanism of the role between financial development, electricity use, technological innovation, international trade, and CO2 emissions using the spatial Durbin model. The results reveal that the effect of economic growth, electricity use, and technological innovation on CO2 emissions has a spatial spillover effect. The results verify that international trade and the transport sector promote the country's carbon emissions. The typical speculation spike on technology innovation enhanced and financial development should concentrate more on protective ecological parameters. The research provides theoretical guidance for solving the contradictory problem of renewable energy use growth and CO2 emission limitation while promoting green and low-carbon development in the country.

Pricing decisions of risk averse logistic companies with carbon cap and trade under Stackelberg game

With the implementation of the double carbon plan, this paper considers the delivery fees of two risk averse logistics companies under carbon cap and trade mechanism. We establish logistics company Stackelberg (MS) model and retailer Stackelberg (RS) model under mean variance (MV) framework, respectively. We obtain the optimal delivery fees and retail prices. We find out that the higher degree of risk aversion can lead to a lower delivery fee. We also show that a higher carbon trading price or a higher cross price sensitivity will increase delivery fees. Moreover, we indicate that the performances of logistics companies under MS scenario are higher than that RS scenario. In addition, we suggest that under the carbon cap and trade rules, in order to obtain higher profits, logistics companies should use fuel vehicle for transportation under certain conditions, and use electric vehicle in other cases.

A systematic review of transportation carbon emissions based on CiteSpace

Transportation sector has become a major contributor to the escalation of carbon emissions and subsequent climate change. In this study, a bibliometric analysis was conducted using CiteSpace on published papers (1991-2022). Then a theoretical framework was proposed through traditional content analysis from three aspects: measurement, mechanism analysis, and low-carbon pathways analysis. The clustering results show that the research topics have involved mainly factor analysis, evaluation, system analysis, control measurement and pollutants. A further summary of the content of the relevant literature shows that there are five main accounting methods for measuring transportation carbon emissions (TCEs), which can be applied to different scenarios. Studies involving the spatio-temporal distribution of TCEs is limited and mainly focus on macroperspectives. The mechanism of TCEs involves three main aspects: system assessment, efficiency measurement, and driver analysis, which serve to identify the internal patterns of TCEs. Finally, the outlook regarding TCEs is presented.

Research on the Carbon Credit Exchange Strategy for Scrap Vehicles Based on Evolutionary Game Theory

In this article, we construct a game model that uses government regulators and scrap vehicle owners as the main parties to investigate the carbon credit exchange strategy of scrap vehicles using evolutionary game theory. The results were validated using Matlab simulation analysis to reveal the dynamic evolution process of the strategy of both sides of the game. A sensitivity analysis of the key parameters was conducted to explore the influence of each parameter on the evolution process and the stabilization trends. The study shows that (1) The time for the game system to reach a steady state is inversely related to the size of the initial willingness of the parties to cooperate. (2) In the mixed steady-state scenario, when the overall return differential between the positive and negative regulatory verification by government departments is positive, the steady state is participation and positive scrapping. (3) When the probability of the government verifying and being successful in verifying the punishment of the owner's negative scrapping behavior increases, both parties of the game will eventually choose the strategy of participation and positive scrapping. When the cost of the government participation strategy and the cost of the government verification strategy increase, both sides of the game will eventually choose the strategy combination of no participation and positive scrapping. (4) When the owner's reward for cooperating with the strategy, the owner's cost of scrapping the vehicle, and the benefits of the owner's negative cooperation strategy change, they will not change the strategy stability results but will affect the time it takes for the game system to reach a stable state. This study has theoretical implications for government policies in the scrapping industry and how to guide vehicle owners to actively scrap their vehicles.

Water Ecotourism Route Recommendation Model Based on an Improved Cockroach Optimization Algorithm

Aiming to address the problems of the current research on water ecotourism routes, a water ecotourism route recommendation model based on an improved cockroach optimization algorithm is proposed. The aim is to recommend the tour routes with the lowest exhaust emissions. Firstly, depending on tourists’ once-visited water scenic spots, a scenic spot recommendation model based on the improved item-based collaborative filtering algorithm is set up. Then, by combining the recommended scenic spots and integrating the random transportation modes selected by tourists, a tour route recommendation model based on an improved cockroach optimization algorithm is constructed, which can output the tour route that produces the lowest exhaust emissions. Finally, The sample experiment shows that, on the basis of combining with the multivariate random transportation modes, the proposed algorithm has greater advantages than the tour routes planned by the traditional electronic maps, as it can output the tour routes with the lowest exhaust emissions, reduce the damage exhaust emissions cause in the urban water environments and to water resources, and effectively protect the urban water ecological environments.