China’s transport carbon emissions are increasing quickly and the issue of emission reduction is urgent. This article aims to calculate and decompose China’s transport carbon emissions during 2001–2019. It first calculates the China’s transport carbon emissions by IPCC carbon emission factor method, and then applies the Logarithmic Mean Divisia Index (LMDI) model for decomposition analysis. The conclusion indicates that: (1) Diesel, gasoline, kerosene, and fuel oil are the major energy sources used in China’s transport sector, with the combined consumption of diesel and gasoline exceeding 70%, and the annual growth rate of energy consumption reached 8.92% during 2000–2019. Among them, natural gas and liquefied petroleum gas (LPG) have the fastest growth rate, while the only one showing a downward trend is raw coal, indicating that China’s transportation energy structure is being optimized. (2) Although China’s transport carbon emissions have been increasing, the growth rate has declined since 2013. The proportion of carbon emissions from kerosene, diesel, natural gas, and LPG increased from 2000 to 2019, while that of raw coal, gasoline, and fuel oil decreased. This suggests that the use of clean energy, air transportation, and large-scale transportation is increasing, while the use of heavily polluting fuels and small-scale road transportation is decreasing. (3) Per capita GDP is the driving factor that has the most influence on the increase of China’s transport carbon emissions. Population positively influences transportation carbon emissions too, but issues such as aging, low fertility rates, and insufficient labor force may change the direction of the impact in the next 30 years. (4) The negative effect of energy intensity on transport carbon emissions is the greatest, followed by industrial structure and energy structure. The development of highways, new energy vehicles, railway electrification, multimodal transportation, third-party logistics, and logistics information technology in China has improved the energy structure, reduced energy intensity, and brought China’s transport sector into an important stage of innovation driven and pursuit of coordinated development with the environment.

In agricultural production, chemical fertilizers and pesticides are being used in large quantities; the residues of these substances have some negative impact on the quality of agricultural products and soil, and they produce a large amount of carbon emissions. Green agricultural products are popular for their low carbon, quality, and safety, and they flow from the production side to consumers through a traceable supply chain. Therefore, ensuring the reliable and stable operation of the traceable supply chain for green, low-carbon agricultural products is an important issue. In view of the difficulty of obtaining information in previous coordination mechanisms in multi-person cooperative games, this article proposes an optimal pricing decision and constructs a profit-distribution model based on an improved Raiffa value to make the profit-distribution mechanism more conducive to the stability and sustainable development of the supply chain, and empirical analysis was carried out. The empirical analysis shows the following: (1) The centralized decision-making selling price of green and low-carbon agricultural products based on the quantitative cost–benefit analysis and demand function can realize the optimal profit of the supply chain. (2) Using the improved Raiffa value, considering the investment cost and risk to allocate the optimal profit of centralized decision-making, optimizes the profit distribution of supply chain members and overcomes the problem of the difficulty in acquiring information in multi-player cooperative games. (3) For investment costs and risks, the corresponding profit-distribution adjustment value weight vector can be obtained using the AHP; for risks that are difficult to quantify, the fuzzy comprehensive evaluation method and the risk-factor-based method can be used to determine the risk coefficient of each member of the supply chain. The optimized profit-distribution mechanism of supply chain members is more reasonable than decentralized decision-making, which has a significant reference for promoting the sustainable development of a traceable supply chain of green and low-carbon agricultural products.

Currently, a large amount of greenhouse gas emissions has caused a series of problems such as serious environmental degradation, and China is facing enormous pressure to reduce emissions. In terms of meeting the needs of people’s lives, cold chain logistics has undergone faster development, and its carbon emissions are relatively high. In response to the government’s advocacy for green and low-carbon concepts, some technical measures taken will increase the cost of carbon emissions. Identifying measures to reduce carbon emissions using management methods is an ongoing problem that this paper intends to solve. To address the shortcomings of the traditional cost method that cannot accurately account for the cost of each calculation object and ignores the carbon emission cost, this paper constructs an activity-based cost model for cold chain logistics enterprises to more comprehensively account for the operation cost and carbon emission cost. Then, a typical enterprise YS cold chain logistics company is used as a case study for an empirical calculation and analysis. The following conclusions are drawn: (1) the results identify the main activity centers that affect the operating costs and carbon emission costs of different customers; (2) a comparison among the total cost of each project helps to identify high-quality customers; (3) clarifying the carbon emission cost of wasting resources is beneficial for further optimizing the match between production capacity and business volume. This paper provides a path reference for enterprises to efficiently implement logistics cost management and carbon emission control, which can help enterprises cope with cost reduction and efficiency enhancement in a low-carbon environment and promote the long-term development of the logistics industry and environmental protection.

As the economy develops, the level of logistics required means many activities become increasingly dependent on transportation, which leads to the deterioration of the ecological environment, aggravates air pollution, causes urban traffic jams, and has a negative influence on sustainable development. Therefore, in the context of sustainable development, how to coordinate the development of the logistics industry and regional economy has become a governmental and academic focus. The coupling coordination degree model and spatial autocorrelation analysis model were applied to empirically analyze the coupling and coordination of the logistics industry and economy in each city in YRDR and the relationship of mutual influence. The research results show that, for economically developed cities, economic development had more influence on the coupled and coordinated degree of the two, and for the less developed cities, the development of logistics drove the improvement of the coupled and coordinated degree of the two. The analysis of the Anhui Province showed that the coupling and coordination degree of its own logistics industry and economy was driven by strong radiation, and the impact on that degree of the logistics industry and economy of cities in Jiangsu, Zhejiang, and Shanghai was not significant. The development of the coupling and coordination degree of the two variables of cities in Jiangsu Province was more balanced. The divergence degree of that of the logistics industry and economy of cities in Zhejiang Province exhibited a tendency to increase, and the divergence mainly came from the endogenous development of each city. The variability was mainly due to the endogenous dynamics of each city’s development. Finally, suggestions for the coordinated and sustainable development of the logistics industry and regional economy are provided.

To address the issue where information asymmetry in third-party logistics (3PL)-led low-carbon supply chain coordination undermines coordination efficiency, thereby threatening the sustainability and resilience of supply chain cooperation, this paper develops a Stackelberg dynamic game model with the 3PL as the leader. This model is constructed within the context where consumers’ low-carbon preferences influence product demand, and a government carbon cap policy is implemented. By comparing decentralized and centralized equilibria, we verify that centralized collaboration achieves dual gains: higher carbon reduction levels and greater overall supply chain profits, which strengthens sustainability and resilience. To address efficiency losses from three types of information asymmetry, we propose a two-stage dynamic coordination mechanism adapted to evolving cooperation transparency. At the initial stage with opaque information, a bargaining-power-weighted profit-sharing contract is adopted, where negotiation weights are quantified by enterprise scale, resource control and industry influence. After data transparency improves, the system switches to a Nash bargaining framework supported by blockchain carbon data sharing to realize stable long-term collaboration. Numerical cases and sensitivity analysis demonstrate that manufacturer cost information asymmetry is the primary constraint on coordination efficiency. The proposed dynamic coordination scheme effectively mitigates systemic complexity, balancing economic benefits and carbon reduction targets. This study provides practical pathways for supply chain participants to navigate complex low-carbon environments and advance sustainable, resilient supply chain operation.