Research on the Implementation Path of Agricultural Carbon Reduction in Heilongjiang Province

: This article calculates the agricultural carbon emissions in Heilongjiang Province, analyzes the factors affecting agricultural carbon emissions using grey theory, and proposes strategies for reducing agricultural carbon emissions in Heilongjiang Province. Research shows that the main influencing factors of agricultural carbon emissions in Heilongjiang Province, in descending order, include: agricultural industrial structure; Urbanization rate of permanent population; Per capita arable land area for agricultural practitioners; Rural population; Agricultural energy intensity; Rural per capita disposable income; Rural per capita GDP. The suggestions proposed mainly include: further improving the quality of urbanization; Further optimize the agricultural industrial structure; Vigorously developing low-carbon agriculture; Increase the pace of large-scale agricultural development; Further improve the use efficiency of agricultural means of production.


Introduction
Since the implementation of the reform and opening up policy, China's agricultural development has made great progress. Agricultural production efficiency has improved, but overall it is still at a relatively low level, with low technical efficiency being the main factor restricting the improvement of production efficiency. The progress of agricultural technology in China, coupled with various policies that attach great importance to agricultural development, has led to a trend of overall shift from "weak decoupling" to "growth connection" between agricultural energy consumption and carbon emissions and agricultural economic growth [1]. However, the stability of the decoupling state between the two has gradually deteriorated, indicating that China's agricultural development is still affected by some uncertain factors [2].
The Chinese government attaches great importance to the development of low-carbon agriculture. After efforts, the overall carbon emission efficiency of agricultural energy in China has been improved, but it still shows significant regional differences. This is mainly because there are differences in economic development level, agricultural fiscal expenditure, agricultural technology innovation, and urbanization level among different regions [3]. From a regional perspective, the improvement of carbon emission efficiency in the eastern region is mainly driven by technological progress, while the central and western regions mainly rely on the improvement of technological efficiency [4].
Cui Yongfu et al. (2023) studied the spatial evolution of carbon emissions from county-level agriculture in Hebei Province and proposed corresponding countermeasures. These measures mainly include: improving the efficiency of agricultural material utilization and improving the soil environment; The government strengthens the promotion of low-carbon agriculture and increases financial support for low-carbon agriculture; Develop the integration mode of agricultural tourism in combination with the characteristics of the county; Fully utilize spatial spillover effects and synergistically promote the process of agricultural carbon reduction [5].
Chen Jianxue et al. (2023) studied the impact mechanism of agricultural insurance development on agricultural carbon emissions from the perspective of mesomeric effect from the perspective of behavior change. The research results indicate that the development of agricultural insurance can have a inhibitory effect on agricultural carbon emissions; The inhibitory effect of agricultural insurance development on agricultural carbon emissions is mainly concentrated in the central and western regions; Agricultural insurance can reduce agricultural carbon emissions by adjusting agricultural planting structure and expanding agricultural business scale [6].
Xu Yue et al. (2023) studied the spatiotemporal characteristics and decoupling effect of agricultural carbon emissions in Xuzhou City. The research results indicate that agricultural carbon emissions in Xuzhou City have become more reasonable with the continuous deepening of carbon reduction concepts, and agricultural economic development has also achieved certain results [7].
Based on the research results of scholars, this article will use grey correlation theory to analyze the influencing factors of carbon emissions from agricultural production in Heilongjiang Province, and propose corresponding suggestions.

Material selection and model application 2.1 Calculation of Agricultural Carbon Emissions
Agricultural carbon emissions mainly come from the carbon emissions generated in various links of agricultural production activities. Including the following.
One is the carbon emissions generated by diesel; The second is the carbon emissions generated by fertilizers; The third is the carbon emissions generated by pesticides; The fourth is the carbon emissions caused by agricultural film; The fifth is the carbon emissions caused by land tillage; The sixth is the carbon emissions generated by agricultural electricity use. The calculation formula for carbon emissions from agricultural production in this article is as follows Among them, E represents the total amount of agricultural carbon emissions, Ei represents the carbon emissions of various carbon sources, and Ti represents the number of various carbon sources, λ I represents the carbon emission coefficient of various carbon sources. Fertilizer 0.8956 (kg/kg), agricultural film 5.18 (kg/kg), agricultural irrigation 20.476 (kg/hm2), agricultural diesel 0.5927 (kg/kg), tillage 212.6 (kg/km2), pesticide 4.9341 (kg/kg).results are shown in table 1. According to the above formula and combined with the data from the "Statistical Yearbook of Heilongjiang Province 2011-2020", the carbon emissions from agricultural production in Heilongjiang Province are calculated, and the results are shown in the table 2 .

Grey correlation theory
Traditional analysis methods, due to the difficulty of collecting data information, cannot accurately measure the analysis results. The grey correlation analysis method can compensate for this deficiency. The modeling steps for grey correlation dynamic analysis are as follows.

Perform dimensionless processing on the original sequence
This is to eliminate the impact of different orders of magnitude, making it easier to calculate and compare. The initialization method, averaging method, and interval method can be used, and the calculation formulas are: The difference sequence is: Maximum difference: △ maxmax _ X 0 (k') -X i (k') _ (i=1,2,3,…,n), Minimum difference:

Calculation of grey correlation coefficient
L (k) 0i Is the correlation coefficient between the sub sequence and the parent sequence,Usually takenδ=0.5

Calculating Grey Correlation Degree
To obtain the overall correlation, it is necessary to consider the importance of different observation points in the overall observation, and therefore determine the weights of each point. Generally, the method of arithmetic mean is used to calculate the grey correlation degree. R 0i =[r 0i (1)+ r 0i (2)+ r 0i (3)+…+ r 0i (n)]/n (6) R 0i represent the correlation degree between the parent sequence and each subsequence.

Ranking of correlation degree
Sort the correlation degree based on the size of R0i. The closer the correlation degree is to 1, the greater the degree of correlation. Based on experience, when δ= 0.5, a correlation greater than 0.6 is considered significant [8] - [10].

Indicator selection
Drawing on the research viewpoints of scholars, this article intends to divide the influencing factors of carbon emissions from agricultural production in Heilongjiang Province into three parts.
One is population indicators. Select two indicators: rural population and urbanization rate. The second is technical indicators. Select two indicators of agricultural energy intensity and industrial structure. The third is economic indicators. Select three indicators: per capita GDP in rural areas, per capita arable land area of rural employees, and per capita disposable income in rural areas.
This article takes the carbon emissions from agricultural production in Heilongjiang Province as the parent sequence, denoted as X0 (unit: 10000 tons), and other influencing factors are: rural population (denoted as X1, unit: 100 million people); Urbanization rate of resident population (denoted as X2, unit:%); Agricultural energy intensity (recorded as X3, unit: ton/10000 yuan); Agricultural industrial structure (denoted as X4, unit:%); Rural per capita GDP (recorded as X5, unit: 10000 yuan); Rural per capita disposable income (recorded as X6, unit: 10000 yuan); The per capita arable land area of agricultural workers (recorded as X7, unit: hectares).the results are shown in table 3.

Data processing
Based on the above steps and calculations, the results are shown in table 4.

Conclusion and Suggestions
Through the above calculations, the following conclusions can be found. First, the carbon emission of agricultural production in Heilongjiang Province has reached its peak and is moving towards carbon neutrality.
The use of fertilizers and diesel is the main internal source of carbon emissions from agricultural production in Heilongjiang Province The urbanization rate of the permanent population and agricultural structure are the main external influencing factors of carbon emissions from agricultural production in Heilongjiang Province.
From the above conclusion, it can be seen that in order to achieve the "dual carbon" goal of agricultural production in Heilongjiang Province, the following aspects should be focused on.
(1) Further improve the quality of urbanization and reasonably control the development speed of urbanization. In order to further achieve the goal of carbon neutrality agricultural production in Heilongjiang Province, efforts should be made to improve the quality of urbanization. The relevant departments of the country should continue to improve the unified planning in the urbanization process, and make detailed plans for the scale of urbanization in the coming years, the use of resources and energy in the urbanization process, the urban-rural coordination, urbanrural integration development, and low-carbon development in the urbanization process, in order to ensure the improvement of urbanization quality.
(2) Further optimize the agricultural industrial structure. In the future, comprehensive planning should be carried out to scientifically predict the demand for agricultural products, forestry products, and aquaculture products in the coming years, and formulate long-term plans. The proportion of agricultural products, forestry products, and aquaculture products should be well divided, truly achieving the independent and high-quality development of each component while also coordinating with each other.
(3) Vigorously develop low-carbon agriculture. From the above analysis, it can be seen that agricultural energy intensity has a significant impact on agricultural production carbon emissions. The use of agricultural energy directly leads to significant carbon emissions. The construction of ecological civilization has deeply rooted in people's hearts, and how to achieve low-carbon in agricultural production is a question worth considering.
One is to vigorously develop agricultural technology, invest more manpower and resources in the research and development and use of modern agricultural machinery, and produce and use more advanced agricultural production equipment.
The second is to do a good job in seed research and development. Because high-quality seeds can increase yield while also reducing the consumption of agricultural production resources, such as water and fertilizer.
The third is to strengthen the training of agricultural practitioners and improve their quality. Agricultural production requires technology, and only by improving the quality of agricultural practitioners can we achieve the conservation and intensive use of energy resources in all aspects of agricultural production.
(4) Increase the pace of large-scale agricultural development. From the above data in this article, it can be seen that the per capita arable land of agricultural workers in Heilongjiang Province is about 2 hectares, which is still a significant gap compared to the per capita arable land of agricultural workers in developed countries. There are still many job requirements in this area. The government should introduce more active and scientific policies to provide greater incentives in land transfer, land compensation, market information provision, agricultural product sales, personnel training, agricultural machinery matching, and different types of seeds and fertilizers, in order to further promote the scale development of agriculture in Heilongjiang Province.
(5) Further improve the use efficiency of agricultural means of production. From the above analysis, it can be seen that the main sources of carbon emissions from agricultural production in Heilongjiang Province are the use of fertilizers and diesel fuel. To improve the efficiency of fertilizer use, on the one hand, it is necessary to combine the scale production mentioned above, on the other hand, start from the market side, and improve the market value of green food by market means, so that agricultural products with less or no fertilizer will have a higher profit margin, which can help agricultural practitioners to consciously reduce the use of fertilizer. The reduction of diesel consumption should also be combined with the large-scale production of agriculture and the improvement of the quality of agricultural workers.