Optimization analysis of grain self-production and import structure based on carbon footprint

Zhang, Hua; Zhao, Fang; Han, Kexuan

doi:10.1108/caer-02-2022-0036

Cited by 4 publications

(3 citation statements)

References 22 publications

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“…The sharp decline in China's production has been unable to meet China's consumption demand for barley. China is highly dependent on imported barley [30,31], and the trade of barley characterized by a high concentration of import sources determines that China's barley import trade has a certain vulnerability [32,33] and is easily affected by the adjustment of import tariff policies [34]. Based on the above background, this study proposes the hypothesis that China's adjustment of tariffs on imports of Australian barley will affect China's barley import trade and bring the risk of a significant increase in domestic prices or a sudden decrease in imports.…”

Section: Introductionmentioning

confidence: 99%

China-Australia Trade Relations and China’s Barley Imports

Liu

Sun

2023

Agriculture

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The high concentration of China’s barley import sources determines that China’s barley import trade is vulnerable to the impact of tariff policy adjustment. In particular, in 2020, China implemented anti-dumping and anti-subsidy policies against Australia, the largest source of barley imports. Therefore, whether China’s barley import trade will face import risks due to the adjustment of tariff policy has become a question worth discussing. Based on the above background, this study uses the partial equilibrium model to explore the impact of China’s adjustment of tariff policy on imported barley from Australia on China’s barley industry under the changing trade relations between China and Australia. Through analyzing the feasibility of developing domestic barley industry and expanding barley import sources, further explore strategies to deal with barley import trade risks. The results show that: Under the three import tariff adjustment simulations, the total import volume of China’s barley shows a downward trend, and the import price increases to varying degrees. However, the relatively small increase in domestic production suggests that the domestic barley market is less able to cope with the risk of a sharp drop in imports. At the same time, affected by the adjustment of tariff policy, some Chinese consumer demand is difficult to satisfy. China can deal with trade risks by implementing an import diversification strategy.

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Section: Introductionmentioning

confidence: 99%

China-Australia Trade Relations and China’s Barley Imports

Liu

Sun

2023

Agriculture

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“…In the field of carbon emissions research, there are various analysis methods available. These include the use of Autoregressive Integrated Moving Average model (ARIMA) and neural network prediction models for forecasting carbon emissions [16][17][18][19], examining panel data onto different regions in China using spatial econometric models [20,21], studying the decoupling model between economic growth and carbon emissions, and identifying the driving factors that affect carbon emissions [22][23][24][25][26]. When considering carbon sequestration and analyzing issues related to carbon emissions, it is beneficial to combine multiple methods.…”

Section: Introductionmentioning

confidence: 99%

Study on the Relationship between Economic Growth of Animal Husbandry and Carbon Emission Based on Logarithmic Average Index Method and Decoupling Model: A Case Study of Heilongjiang Province

Lin

et al. 2023

Sustainability

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With the establishment of the action plan for the goal of “carbon peaking and carbon neutrality”, how to achieve high-quality agricultural development, help implement the construction of the green Longjiang River, reduce agricultural carbon emissions, and increase the level of agricultural carbon sink is a key problem that must be solved for Heilongjiang Province to achieve the goal of “double carbon”. This article uses the Life Cycle Assessment (LCA) method to estimate the carbon emissions of animal husbandry in Heilongjiang Province and 13 cities from 2000 to 2020. By constructing the Tapio decoupling model, Kaya identity, and the LMDI model, the relationship between animal husbandry economy and carbon emissions in Heilongjiang Province and the driving factors affecting animal husbandry carbon emissions are explored. The results indicate that: (1) From 2000 to 2020, the carbon emissions of animal husbandry in Heilongjiang Province showed an overall slightly upward trend. From the perspective of various emission links, the highest carbon emissions are from the gastrointestinal fermentation environment (42.49%), with beef cattle, cows, and live pigs being the main livestock and poultry in Heilongjiang Province with carbon emissions. (2) The Tapio decoupling model results indicated that from 2000 to 2020, the relationship between the economic development of animal husbandry in Heilongjiang Province and carbon emissions was mainly characterized by weak decoupling. (3) The main driving force behind the continuous increase in carbon emissions from animal husbandry in Heilongjiang Province is the changing factors of agricultural population returns and changes in the production structure of animal husbandry; The driving factors that suppress the increase in carbon emissions from animal husbandry in Heilongjiang Province are changes in animal husbandry production efficiency, population and urban development levels, and population mobility factors. Finally, based on the decoupling effect status and driving factors of decomposition between Heilongjiang Province and its various cities, it is recommended to implement countermeasures and suggestions for the transformation of animal husbandry in the province towards green and low carbon at the macro level. This can be achieved through the adoption of sustainable and eco-friendly practices such as the use of renewable energy sources and the reduction of greenhouse gas emissions. Additionally, promoting research and development in sustainable agriculture and animal husbandry can also contribute to the transformation towards a more environmentally friendly industry.

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“…This research advises on agricultural layout optimization, and hence building a modern agricultural industrial system and achieving the carbon peaking and neutrality goals. Zhang et al (2022) take a close look at grain trade and planting technology. It shows that the carbon footprint can be reduced by 3.29 million tons by adjusting the grain import structure.…”

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confidence: 99%

Guest editorial: Agricultural and rural development under the goal of carbon neutrality

Liao

2022

CAER

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Optimization analysis of grain self-production and import structure based on carbon footprint

Cited by 4 publications

References 22 publications

China-Australia Trade Relations and China’s Barley Imports

China-Australia Trade Relations and China’s Barley Imports

Study on the Relationship between Economic Growth of Animal Husbandry and Carbon Emission Based on Logarithmic Average Index Method and Decoupling Model: A Case Study of Heilongjiang Province

Guest editorial: Agricultural and rural development under the goal of carbon neutrality

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