Edge computing moves data and storage to one end of edge nodes. The advantages of direct data collection and intelligent analysis are gradually being considered as disruptive technologies to promote social progress. Many fields and industries are exploring the use of edge technologies. To achieve the goal of improving efficiency and optimizing business models, the supply chain is one of the areas where edge computing technology can be prioritized. Therefore, the organization and coordination of the supply chain must take into account both energy saving and emission reduction and intelligent decision-making effects. This paper establishes a basic decision-making model for the supply chain under the carbon tax constraint and compares and analyzes the optimal decision-making problem of the supply chain between the centralized and decentralized decisions of producers and retailers under the carbon tax constraint. Then, the supply chain optimization under the three conditions of considering the repurchase contract, the subsidy policy and the joint strategy of both the repurchase and the subsidy under the constraint of carbon tax are discussed. Research shows that carbon tax can play a role in reducing carbon emissions, but for some industries with smaller profit margins, relying solely on carbon tax policy may lead to reduced benefits and make business development difficult. Therefore, considering the combined strategy of repurchase and subsidy at the same time, the dual goals of emission reduction and economic benefits can be achieved. INDEX TERMS Edge computing, carbon tax constraint, low carbon supply chain, intelligent decision.

Affected by the Internet, computer, information technology, etc., building a smart city has become a key task of socialist construction work. The smart city has always regarded green and low-carbon development as one of the goals, and the carbon emissions of the auto parts industry cannot be ignored, so we should carry out energy conservation and emission reduction. With the rapid development of the domestic auto parts industry, the number of car ownership has increased dramatically, producing more and more CO2 and waste. Facing the pressure of resources, energy, and environment, the effective and circular operation of the auto parts supply chain under the low-carbon transformation is not only a great challenge, but also a development opportunity. Under the background of carbon emission, this paper establishes a decision-making optimization model of the low-carbon supply chain of auto parts based on carbon emission responsibility sharing and resource sharing. This paper analyzes the optimal decision-making behavior and interaction of suppliers, producers, physical retailers, online retailers, demand markets, and recyclers in the auto parts industry, constructs the economic and environmental objective functions of low-carbon supply chain management, applies variational inequality to analyze the optimal conditions of the whole low-carbon supply chain system, and finally carries out simulation calculation. The research shows that the upstream and downstream auto parts enterprises based on low-carbon competition and cooperation can effectively manage the carbon footprint of the whole supply chain through the sharing of responsibilities and resources among enterprises, so as to reduce the overall carbon emissions of the supply chain system.

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The carbon footprint of the cold chain logistics system refers to the greenhouse gas emissions directly or indirectly caused in each link of the cold chain logistics activities. Because cold chain logistics is the main carbon emitter in the field of logistics, research on how to reduce carbon emissions in the field of cold chain logistics plays an important role in energy conservation and emission reduction. Based on the in-depth analysis of the carbon footprint of cold chain logistics, this paper introduces the distance coefficient and freshness parameters into the optimization model innovatively and uses the life cycle assessment method and input-output method to determine the calculation range of the carbon footprint of fresh products of each link in the cold chain logistics. The system calculates the carbon emissions generated by the production and operation activities of each place of origin, distribution center, retailer, and waste disposal during the circulation of fresh products. This paper establishes a carbon footprint optimization model to discuss how to balance carbon constraints and minimized costs. Through the analysis of the simulation results, from the perspective of the government and enterprises, corresponding countermeasures are put forward to more effectively achieve the goal of energy conservation and emission reduction and guide the cold chain logistics industry to sustainable development.