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With the continuous development of global economic and trade activities, environmental problems have become an important factor restricting the sustainable development of all countries. How to realize the coordinated development of international trade and environmental protection has become a major issue facing the international community. Since China joined the WTO, its share of international trade has been increasing continuously. In order to deeply analyze the influence of international carbon emission trading policy on domestic carbon emissions, we use an input–output model and a GTAP analysis method to theoretically calculate the carbon emissions of the international trade of various departments in Shandong Province. At the same time, the implicit carbon emission index of various industries in 2022 is calculated through the direct energy consumption coefficient. The results show that there are significant differences in the impact of the carbon tariff system on different industries. In terms of the carbon emission index, the food processing industry showed a decrease of 18.99 Mt, while the implied carbon emission of the tobacco, textile and leather manufacturing industry reached 30.56 Mt due to the continuous expansion of trade scale. In contrast, the implied carbon emission level of the metal product processing industry reached 5.3 Mt, while the carbon emission of traditional trading industries such as coal mining was almost unaffected by international trade, and its carbon emission index reached the highest level of 5.89 in 2020. In terms of trade impact, high-trade industries such as the food processing industry are significantly affected by the carbon tariff policy, and their share has dropped from 5.89% to 3.95% in the past decade. The carbon emissions generated by GDP growth established by the GTAP model are more convincing. This model can directly reflect the energy efficiency of a region from the side. Based on the present situation of international trade, this paper analyzes the inequality of the current carbon tariff system, and puts forward some policies to optimize the energy structure to reduce carbon emissions and expand domestic demand to reduce the dependence on international trade. Through the GTAP model, we put forward policy suggestions to optimize the energy structure to reduce carbon emissions and the dependence on international trade by expanding domestic demand. [ABSTRACT FROM AUTHOR]

The continuously increasing demands of food, feed and various corn-derived products accelerate the concern about the corn production on environment. Nevertheless, few researches simultaneously address the issue from different perspectives of carbon, water and energy as well as their temporal variations. Herein, a systematic cradle-to-gate life cycle assessment of maize production was conducted with a case study in Shandong, China. Different midpoint and endpoint indices including 10-year average data from 2011 to 2020 and their temporal variations were investigated. The contribution analysis of different processes to these indices revealed that irrigation dominated the midpoint of water scarcity, whereas the sum of direct consumption, fertilizer and diesel production contributed more than 80% to all the other indices. The sensitivity analysis also illustrated that these environmental indices can be reduced by as high as 4% when the aforementioned inputs were individually decreased by 5%. The temporal variation of the global warming potential, aquatic eutrophication and fossil depletion demonstrated that all the three indices were decreased by about 25.0%–31.7% over the last decade. Further persistent efforts to enhance mechanized operation efficiency and explore green and efficient methods for fertilizer and diesel production were highlighted. Moreover, implementations of rational agricultural management such as scientific fertilization and water-efficient irrigation were suggested, in order to have an eco-friendly maize production system. [ABSTRACT FROM AUTHOR]

Legal requirements and consumer demands have motivated the development and application of traceability technology. Farming practices are the starting point of the agri-food supply chain and the destination of the agri-food traceability system (AFTS). The amount of resource information and the complexity of the production process of agri-food become the main obstacles to the wide application of AFTS. This study introduces an integrated machine-to-machine system that allows collecting field operation information automatically. This system includes an IoT-based integrated hardware system, a smart farm cloud (SFC) platform, and a mobile application, which accomplished the collection, upload, and storage of operation information. This system had been used in "BSD" organic apple orchard in Qixia, Shandong Province, China for about one year. The effectiveness of the system was evaluated by managing 270 apple trees in one plot of the orchard. Finally, a label with a QR code was successfully generated to provide consumers to query traceability information from a single tree to a fruit tray. This work was a background of a blockchain traceability system. Moreover, the future extendibility of the system was also discussed and prospected. [ABSTRACT FROM AUTHOR]