Method for quantifying planting industry carbon emission influence factors based on novel logarithmic mean Dirse index method model

Abstract

The invention discloses a method for quantifying carbon emission influence factors in the planting industry based on a novel logarithmic mean Dirse index method model, and relates to the technical field of environmental economy and policy analysis. Comprising the following steps: data acquisition: acquiring carbon emission data of the whole life cycle of the planting industry; accounting and analysis: carrying out accounting and preliminary analysis on the obtained full-life-cycle carbon emission data, and calculating the total carbon emission amount of each link; and factor decomposition: decomposing the total amount of carbon emission into a plurality of factors by using a novel logarithmic mean Dirse index method model, and respectively calculating the contribution of each factor to the carbon emission change. According to the method, a specific implementation path can be provided for formulating a carbon emission reduction strategy, the independence and synergistic effect of each factor on carbon emission change can be accurately analyzed, and a scientific tool for optimizing resource allocation and effectively reducing carbon emission is provided for planting industry policy formulators.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental economics and policy analysis, and more specifically to a method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirichlet index model. Background Art

[0002] As the global climate change problem intensifies, the control and reduction of greenhouse gas emissions has become the focus of attention of governments and the international community. As one of the important sources of carbon emissions, the carbon footprint of agriculture has received particular attention. Planting industry occupies an important position in agricultural carbon emissions because the fertilizer use, mechanical operation and straw management involved in its production process will produce a large amount of greenhouse gases. Therefore, how to accurately quantify and analyze the factors affecting carbon emissions in the planting industry and find the key emission reduction path has become the focus of current research.

[0003] As an advanced decomposition analysis method, the Logarithmic Mean Divisia Index (LMDI) has been widely used in the fields of energy economics and environmental science in recent years. The LMDI model solves the mathematical problems of the traditional Divisia index in dealing with zero and negative values ​​through the logarithmic mean method, and has the advantages of simple calculation and strong interpretability of results. It is mainly used to decompose the total change into the contribution of multiple influencing factors, so as to analyze in detail the role of each factor in the change process.

[0004] At present, the application of LMDI model in fields such as energy consumption and industrial carbon emissions has been relatively mature, but there are few studies on agricultural carbon emissions analysis. In addition, the current LMDI analysis of carbon emissions in the planting industry mainly focuses on the socio-economic level, analyzing the factors affecting carbon emissions from macro perspectives such as GDP, per capita GDP, and national industrial structure. Although these factors can provide an overall trend in carbon emissions, they have certain limitations in terms of refined analysis and are difficult to accurately reflect the impact of various factors in the specific production process.

[0005] The carbon emissions from the planting industry have their own particularities, such as the amount of fertilizer used per unit area, the energy consumption of mechanical operations, and the yield of different crops, which will all have an impact on carbon emissions. Therefore, it is necessary to build a full life cycle accounting system for carbon emissions from the planting industry based on the production, consumption, and straw processing characteristics of the planting industry, analyze various influencing factors in a refined manner, identify key emission units, optimize the decomposition and analysis methods of carbon emissions, and provide more accurate and detailed carbon emission data support.

[0006] The present invention is based on the theoretical basis and calculation method of the LMDI model proposed by Ang BW et al., and has innovated and improved it, which can conduct a refined analysis of the factors affecting carbon emissions in the entire life cycle of the planting industry from a micro level. The model decomposes the carbon emissions of the planting industry into five major factors: coefficient, technology, structure, demand and population, and conducts a detailed micro-level analysis of each factor for different processes, accurately quantifying the contribution of each factor to carbon emissions, which can provide a basis for formulating scientific and reasonable emission reduction strategies.

[0007] Therefore, it is an urgent problem for those skilled in the art to propose a method for quantifying the factors affecting carbon emissions from the agricultural industry based on a new logarithmic mean Dirichlet index model to solve the difficulties existing in the prior art. Summary of the invention

[0008] In view of this, the present invention provides a method for quantifying the influencing factors of carbon emissions from the planting industry based on a new logarithmic mean Dirichlet index model, which is used to solve the technical problems existing in the prior art.

[0009] In order to achieve the above object, the present invention provides the following technical solutions:

[0010] A method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirksen index model comprises the following steps:

[0011] Data acquisition: Obtain carbon emission data for the entire life cycle of the planting industry;

[0012] Accounting and analysis: Calculate and preliminarily analyze the acquired carbon emission data throughout the life cycle to calculate the total carbon emissions of each link;

[0013] Factor decomposition: Using the new logarithmic mean Dirichlet index method model, the total carbon emissions are decomposed into several factors, and the contribution of each factor to the change in carbon emissions is calculated separately.

[0014] Optionally, the entire life cycle includes the crop planting process, fertilizer application process, straw management process and energy consumption process.

[0015] Optionally, the total carbon emissions include: methane emissions from the crop planting process, nitrous oxide emissions from the fertilizer application process, methane and nitrous oxide emissions from the straw management process, and carbon dioxide emissions from the energy consumption process.

[0016] Optionally, the methane emissions generated during crop cultivation are calculated as:

[0017]

[0018] Among them, E cfIndicates the methane emissions generated during crop cultivation, D1 rice,r represents the rice planting area in province r, R1 r represents the methane emission factor of rice fields in province r;

[0019] The nitrous oxide emissions generated during fertilizer application are calculated using the following formula:

[0020]

[0021] Among them, E fu Indicates the amount of nitrous oxide emissions generated during fertilizer application, D2 r represents the nitrogen fertilizer application amount in province r, D3 r R2 represents the amount of compound fertilizer applied in province r. r represents the direct emission factor of nitrous oxide from fertilizer application in province r, and B represents the emission of NH3 and NO in the process of fertilizer application. x R3 is the proportion of nitrogen in synthetic fertilizers that volatilizes v R4 represents the indirect emission factor of nitrous oxide due to nitrogen deposition. r represents the nitrogen leaching and runoff rate in province r, R3 l&r represents the indirect emission factor of nitrous oxide due to nitrogen leaching and runoff;

[0022] The calculation formula for nitrous oxide emissions from straw reuse as fertilizer and discarding on farmland during straw management is:

[0023]

[0024] in, Indicates the nitrous oxide emissions from the straw management process, D4 n,r represents the crop yield of crop n in province r, G n represents the stalk-to-grain ratio of crop n, C n represents the straw collection coefficient of crop n, H fertilizer,r represents the proportion of straw used as fertilizer in province r, A n represents the nitrogen content of crop straw n, R2 r represents the direct emission factor of nitrous oxide from fertilizer application in province r, where r represents the province and n represents the crop type;

[0025] The methane emissions from open burning during straw management are calculated as follows:

[0026]

[0027] in, represents the methane emissions from straw management, D4 n,rrepresents the crop yield of crop n in province r, G n represents the stalk-to-grain ratio of crop n, C n represents the straw collection coefficient of crop n, H wasted,r represents the proportion of straw wasted by open burning in province r, R5 represents the methane emission factor of open burning of straw, r represents province, and n represents crop type;

[0028] The carbon dioxide emissions generated by the energy consumption process are calculated as follows:

[0029]

[0030] Among them, E ec Indicates the carbon dioxide emissions generated by the energy consumption process, D5 r represents the amount of diesel input for agricultural machinery in province r, R6 represents the carbon dioxide emission factor of diesel application, D1 n,r represents the sown area of ​​crop n in province r, F n Represents the power consumption coefficient for irrigating crop n, R7 r represents the carbon dioxide emission factor of China's regional power grid, r represents the province, and n represents the crop type.

[0031] Optionally, the total carbon emissions are decomposed into several factors including: coefficient factor CF, technical factor TF, structural factor SF, demand factor DF and population factor PF.

[0032] Optionally, carbon emission influencing factors include:

[0033] Crop planting process: coefficient factor CF analyzes carbon emissions per unit rice planting area, technical factor TF analyzes the rice planting area required for unit rice output, demand factor DF analyzes per capita rice demand, and population factor PF analyzes the impact of regional population size on carbon emissions;

[0034] Fertilizer application process: coefficient factor CF analyzes carbon emissions generated by unit nitrogen fertilizer input, technical factor TF analyzes nitrogen fertilizer application per unit area, demand factor DF analyzes the planting area corresponding to unit population, and population factor PF analyzes the impact of regional total population size on carbon emissions;

[0035] Straw management process: coefficient factor CF analyzes the carbon emissions per unit crop, technical factor TF analyzes the yield per unit planting area, structural factor SF analyzes the proportion of each crop area to the total area, demand factor DF analyzes the planting area of ​​each crop per unit population, and population factor PF analyzes the impact of the total population size of the region on carbon emissions;

[0036] Energy consumption process: The coefficient factor CF analyzes the carbon emissions generated by unit energy consumption, the technical factor TF analyzes the energy usage per unit area, the demand factor DF analyzes the crop planting area corresponding to the unit population, and the population factor PF analyzes the impact of the total population size of the region on carbon emissions.

[0037] Optionally, the factors affecting methane emissions during crop planting are decomposed into coefficient factors CF, technical factors TF, demand factors DF and population factors PF:

[0038]

[0039] ΔE=E t -E0=ΔE CF +ΔE TF +ΔE DF +ΔE PF

[0040]

[0041] Among them, r represents the province, E cf ' represents the carbon dioxide equivalent produced during the crop planting process in that year, in kilotons, E r1 represents the carbon dioxide equivalent produced by crop cultivation in province r in that year, in kilotons, S rice,r represents the rice planting area in province r in that year, in thousand hectares, V rice,r represents the rice production of province r in that year, in thousands of tons, P r It represents the total population of province r in that year, in thousands of people;

[0042] E r / S rice,r represents the coefficient factor, i.e., carbon emission intensity of rice cultivation, S rice,r / V rice,r represents the technical factor, i.e. the rice planting area required for unit rice output, V rice,r / P r represents the demand factor, i.e., the per capita rice demand, P r represents the demographic factor, i.e., population size;

[0043] △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively;

[0044] in, represents the carbon dioxide equivalent produced by crop planting in period t, represents the carbon dioxide equivalent produced by crop cultivation in the base period, and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

[0045] Optionally, the factors affecting nitrous oxide emissions during fertilizer application are decomposed into coefficient factors CF, technical factors TF, demand factors DF and population factors PF:

[0046]

[0047] ΔE=E t -E0=ΔE CF +ΔE TF +ΔE DF +ΔE PF

[0048]

[0049]

[0050] Among them, r represents the province, E fu ' represents the carbon dioxide equivalent produced during the application of fertilizers in that year, in kilotons, E r2 represents the carbon dioxide equivalent produced by fertilizer application in province r in that year, in kilotons, N r represents the fertilizer input of province r in that year, in thousands of tons, S r represents the crop planting area of ​​province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people;

[0051] E r / N r represents the coefficient factor, i.e., the carbon emission intensity of fertilizer application, N r / S r represents the technical factor, i.e. the amount of fertilizer applied per unit planting area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size;

[0052] △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DFand ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively;

[0053] represents the carbon dioxide equivalent produced by the application of fertilizer in period t, It represents the carbon dioxide equivalent produced by fertilizer application in the base period. and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

[0054] Optionally, the influencing factors of methane and nitrous oxide emissions in the straw management process are decomposed into coefficient factors CF, technical factors TF, structural factors SF, demand factors DF and population factors PF:

[0055]

[0056] ΔE=E t -E0=ΔE CF +ΔE TF +ΔE SF +ΔE DF +ΔE PF

[0057]

[0058]

[0059] Among them, r represents the province, n represents the crop type, E sm ' represents the carbon dioxide equivalent emissions generated by the straw management process in that year, in kilotons, E rn V is the carbon dioxide equivalent produced by crop straw management in province r in that year, in kilotons. rn represents the yield of crop n in province r in that year, in thousands of tons, S rn S represents the planting area of ​​crop n in province r in that year, in thousands of hectares. r represents the total planting area of ​​all crops in province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people;

[0060] E rn / V rn represents the coefficient factor, i.e., the carbon emission intensity of crop planting, V rn / S rn represents the technical factor, i.e., the crop yield per unit planting area, S rn / S rrepresents the structural factor, that is, the proportion of each crop planting area to the total planting area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size;

[0061] △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E SF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, structural factors, demand factors and population factors respectively;

[0062] represents the carbon dioxide equivalent produced by straw management in period t, represents the carbon dioxide equivalent produced by straw management during the base period, and They represent the coefficient factor, technical factor, structural factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, structural factors, demand factors and population factors respectively.

[0063] Optionally, the CO2 emission influencing factors of energy consumption are decomposed into coefficient factor CF, structural factor SF, demand factor DF and population factor PF:

[0064]

[0065] ΔE=E t -E0=ΔE CF +ΔE TF +ΔE DF +ΔE PF

[0066]

[0067] Among them, r represents the province, E ec ' represents the carbon dioxide equivalent produced by the energy consumption process in the year, in kilotons, E r3 represents the carbon dioxide equivalent produced by energy consumption in province r in that year, in kilotons, U r represents the energy consumption of province r in that year, with diesel in kilotons and electricity in megawatt-hours. r represents the total planting area of ​​all crops in province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people;

[0068] E r / U r represents the coefficient factor, i.e., energy carbon emission intensity, U r / S r Represents technical factors, i.e. energy consumption per unit area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size;

[0069] △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively;

[0070] represents the carbon dioxide equivalent produced by the energy consumption process in period t, represents the carbon dioxide equivalent produced by the energy consumption process in the base period, and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

[0071] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a method for quantifying the factors affecting carbon emissions in the planting industry based on a new logarithmic mean Digg index model, and its beneficial effects are:

[0072] (1) Comprehensive and detailed assessment: By decomposing the five key influencing factors of carbon emissions (coefficient, technology, structure, demand and population), we can comprehensively and detailedly assess the contribution of each factor to carbon emissions;

[0073] (2) Improved accounting accuracy: Innovatively combined with specific characteristics of the planting industry, such as fertilizer use per unit area and mechanical energy consumption, thereby improving the accuracy of carbon emission accounting;

[0074] (3) Broad application prospects: By applying the theoretical basis of the logarithmic mean Dirichlet index model to the analysis of carbon emissions from crop production, it provides a powerful tool for policymakers to support them in formulating more effective environmental policies and promote the development of sustainable agriculture.

[0075] (4) Supporting low-carbon agriculture and sustainable development: The present invention not only fills the gap in the existing technology in the fine analysis of carbon emissions from the planting industry at the micro level, but also provides strong support for achieving low-carbon agriculture and sustainable development goals through high-precision and targeted analysis methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0077] Figure 1 A flow chart of a method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirichlet index model provided by the present invention;

[0078] Figure 2 A system structure diagram for quantifying factors affecting carbon emissions from the crop industry based on a novel logarithmic mean Dirichlet index method model provided by the present invention. DETAILED DESCRIPTION

[0079] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0080] See also Figure 1 As shown, the present invention discloses a method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirichlet index model, comprising the following steps:

[0081] Data acquisition: Obtain carbon emission data for the entire life cycle of the planting industry;

[0082] Accounting and analysis: Calculate and preliminarily analyze the acquired carbon emission data throughout the life cycle to calculate the total carbon emissions of each link;

[0083] Factor decomposition: Using the new logarithmic mean Dirichlet index method model, the total carbon emissions are decomposed into several factors, and the contribution of each factor to the change in carbon emissions is calculated separately.

[0084] Furthermore, the whole life cycle includes the crop planting process, fertilizer application process, straw management process and energy consumption process.

[0085] Specifically, the entire life cycle of the planting industry includes the crop planting process, the energy consumption process (the types of energy consumed include electricity and diesel), the straw management process (the management process includes the reuse of straw as fertilizer, discarding on farmland and open burning) and the fertilizer application process (the fertilizer application process includes direct emissions, indirect emissions caused by nitrogen deposition and indirect emissions caused by nitrogen leaching and runoff).

[0086] The carbon emission data of the planting industry throughout its life cycle include: the application amount of nitrogen fertilizer and compound fertilizer, the direct emission factor of nitrous oxide during the application of chemical fertilizers, the direct emission factor of nitrous oxide during the application of chemical fertilizers, and the emission factor of nitrous oxide in terms of NH3 and NO x The proportion of nitrogen that volatilizes in the form of nitrogen in synthetic fertilizers, the indirect emission factor of nitrous oxide caused by nitrogen deposition during fertilizer application, nitrogen leaching and runoff rate, the indirect emission factor of nitrous oxide caused by nitrogen leaching and runoff during fertilizer application, the amount of diesel input for agricultural machinery, the carbon dioxide emission factor of diesel application, the planting area of ​​each crop, the electricity consumption coefficient of each crop irrigation, the carbon dioxide emission factor of China's regional power grid, the methane emission factor of rice fields, the crop yield of each province in different years, the straw-to-grain ratio of each crop, the straw collection coefficient of each crop, the proportion of straw used as fertilizer in each province, the nitrogen content of each crop straw, the proportion of straw wasted by open burning in each province, and the methane emission factor of open burning of straw.

[0087] Furthermore, the total carbon emissions include: methane emissions from the crop planting process, nitrous oxide emissions from the fertilizer application process, methane and nitrous oxide emissions from the straw management process, and carbon dioxide emissions from the energy consumption process.

[0088] Furthermore, the methane emissions generated during crop cultivation are calculated as follows:

[0089]

[0090] Among them, E cf Indicates the methane emissions generated during crop cultivation, D1 rice,r represents the rice planting area in province r, R1 r represents the methane emission factor of rice fields in province r;

[0091] The nitrous oxide emissions generated during fertilizer application are calculated using the following formula:

[0092]

[0093] Among them, E fu Indicates the amount of nitrous oxide emissions generated during fertilizer application, D2 r represents the nitrogen fertilizer application amount in province r, D3 r R2 represents the amount of compound fertilizer applied in province r.r represents the direct emission factor of nitrous oxide from fertilizer application in province r, and B represents the emission of NH3 and NO in the process of fertilizer application. x R3 is the proportion of nitrogen in synthetic fertilizers that volatilizes v R4 represents the indirect emission factor of nitrous oxide due to nitrogen deposition. r represents the nitrogen leaching and runoff rate in province r, R3 l&r represents the indirect emission factor of nitrous oxide due to nitrogen leaching and runoff;

[0094] The calculation formula for nitrous oxide emissions from straw reuse as fertilizer and discarding on farmland during straw management is:

[0095]

[0096] in, Indicates the nitrous oxide emissions from the straw management process, D4 n,r represents the crop yield of crop n in province r, G n represents the stalk-to-grain ratio of crop n, C n represents the straw collection coefficient of crop n, H fertilizer,r represents the proportion of straw used as fertilizer in province r, A n represents the nitrogen content of crop straw n, R2 r represents the direct emission factor of nitrous oxide from fertilizer application in province r, where r represents the province and n represents the crop type;

[0097] The methane emissions from open burning during straw management are calculated as follows:

[0098]

[0099] in, represents the methane emissions from straw management, D4 n,r represents the crop yield of crop n in province r, G n represents the stalk-to-grain ratio of crop n, C n represents the straw collection coefficient of crop n, H wasted,r represents the proportion of straw wasted by open burning in province r, R5 represents the methane emission factor of open burning of straw, r represents province, and n represents crop type;

[0100] The carbon dioxide emissions generated by the energy consumption process are calculated as follows:

[0101]

[0102] Among them, E ec Indicates the carbon dioxide emissions generated by the energy consumption process, D5 rrepresents the amount of diesel input for agricultural machinery in province r, R6 represents the carbon dioxide emission factor of diesel application, D1 n,r represents the sown area of ​​crop n in province r, F n Represents the power consumption coefficient for irrigating crop n, R7 r represents the carbon dioxide emission factor of China's regional power grid, r represents the province, and n represents the crop type.

[0103] Furthermore, the total carbon emissions are decomposed into several factors including coefficient factor CF, technical factor TF, structural factor SF, demand factor DF and population factor PF.

[0104] Furthermore, the factors affecting carbon emissions include:

[0105] Crop planting process: coefficient factor CF analyzes carbon emissions per unit rice planting area, technical factor TF analyzes the rice planting area required for unit rice output, demand factor DF analyzes per capita rice demand, and population factor PF analyzes the impact of regional population size on carbon emissions;

[0106] Fertilizer application process: coefficient factor CF analyzes carbon emissions generated by unit nitrogen fertilizer input, technical factor TF analyzes nitrogen fertilizer application per unit area, demand factor DF analyzes the planting area corresponding to unit population, and population factor PF analyzes the impact of regional total population size on carbon emissions;

[0107] Straw management process: coefficient factor CF analyzes the carbon emissions per unit crop, technical factor TF analyzes the yield per unit planting area, structural factor SF analyzes the proportion of each crop area to the total area, demand factor DF analyzes the planting area of ​​each crop per unit population, and population factor PF analyzes the impact of the total population size of the region on carbon emissions;

[0108] Energy consumption process: The coefficient factor CF analyzes the carbon emissions generated by unit energy consumption, the technical factor TF analyzes the energy usage per unit area, the demand factor DF analyzes the crop planting area corresponding to the unit population, and the population factor PF analyzes the impact of the total population size of the region on carbon emissions.

[0109] Furthermore, the factors affecting methane emissions during crop planting are decomposed into coefficient factors CF, technical factors TF, demand factors DF and population factors PF:

[0110]

[0111] ΔE=E t -E0=ΔE CF +ΔE TF +ΔE DF +ΔE PF

[0112]

[0113] Among them, r represents the province, E cf ' represents the carbon dioxide equivalent produced during the crop planting process in that year, in kilotons, E r1 represents the carbon dioxide equivalent produced by crop cultivation in province r in that year, in kilotons, S rice,r represents the rice planting area in province r in that year, in thousand hectares, V rice,r represents the rice production of province r in that year, in thousands of tons, P r It represents the total population of province r in that year, in thousands of people;

[0114] E r / S rice,r represents the coefficient factor, i.e., carbon emission intensity of rice cultivation, S rice,r / V rice,r represents the technical factor, i.e. the rice planting area required for unit rice output, V rice,r / P r represents the demand factor, i.e., the per capita rice demand, P r represents the demographic factor, i.e., population size;

[0115] △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively;

[0116] in, represents the carbon dioxide equivalent produced by crop planting in period t, represents the carbon dioxide equivalent produced by crop cultivation in the base period, and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

[0117] Furthermore, the factors affecting nitrous oxide emissions during fertilizer application are decomposed into coefficient factors CF, technical factors TF, demand factors DF and population factors PF:

[0118]

[0119] ΔE=E t -E0=ΔE CF +ΔETF +ΔE DF +ΔE PF

[0120]

[0121] Among them, r represents the province, E fu ' represents the carbon dioxide equivalent produced during the application of fertilizers in that year, in kilotons, E r2 represents the carbon dioxide equivalent produced by fertilizer application in province r in that year, in kilotons, N r represents the fertilizer input of province r in that year, in thousands of tons, S r represents the crop planting area of ​​province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people;

[0122] E r / N r represents the coefficient factor, i.e., the carbon emission intensity of fertilizer application, N r / S r represents the technical factor, i.e. the amount of fertilizer applied per unit planting area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size;

[0123] △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively;

[0124] represents the carbon dioxide equivalent produced by the application of fertilizer in period t, It represents the carbon dioxide equivalent produced by fertilizer application in the base period. and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

[0125] Furthermore, the influencing factors of methane and nitrous oxide emissions in the straw management process are decomposed into coefficient factors CF, technical factors TF, structural factors SF, demand factors DF and population factors PF:

[0126]

[0127] ΔE=E t -E0=ΔE CF +ΔE TF +ΔE SF +ΔE DF +ΔE PF

[0128]

[0129]

[0130] Among them, r represents the province, n represents the crop type, E sm ' represents the carbon dioxide equivalent emissions generated by the straw management process in that year, in kilotons, E rn V is the carbon dioxide equivalent produced by crop straw management in province r in that year, in kilotons. rn represents the yield of crop n in province r in that year, in thousands of tons, S rn S represents the planting area of ​​crop n in province r in that year, in thousands of hectares. r represents the total planting area of ​​all crops in province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people;

[0131] E rn / V rn represents the coefficient factor, i.e., the carbon emission intensity of crop planting, V rn / S rn represents the technical factor, i.e., the crop yield per unit planting area, S rn / S r represents the structural factor, that is, the proportion of each crop planting area to the total planting area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size;

[0132] △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E SF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, structural factors, demand factors and population factors respectively;

[0133] represents the carbon dioxide equivalent produced by straw management in period t, represents the carbon dioxide equivalent produced by straw management during the base period, and They represent the coefficient factor, technical factor, structural factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, structural factors, demand factors and population factors respectively.

[0134] Furthermore, the factors affecting carbon dioxide emissions from energy consumption are decomposed into coefficient factors CF, structural factors SF, demand factors DF and population factors PF:

[0135]

[0136] ΔE=E t -E0=ΔE CF +ΔE TF +ΔE DF +ΔE PF

[0137]

[0138] Among them, r represents the province, E ec ' represents the carbon dioxide equivalent produced by the energy consumption process in the year, in kilotons, E r3 represents the carbon dioxide equivalent produced by energy consumption in province r in that year, in kilotons, U r represents the energy consumption of province r in that year, with diesel in kilotons and electricity in megawatt-hours. r represents the total planting area of ​​all crops in province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people;

[0139] E r / U r represents the coefficient factor, i.e., energy carbon emission intensity, U r / S r Represents technical factors, i.e. energy consumption per unit area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size;

[0140] △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively;

[0141] represents the carbon dioxide equivalent produced by the energy consumption process in period t, represents the carbon dioxide equivalent produced by the energy consumption process in the base period, and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

[0142] In one embodiment, Figure 1 Corresponding to the method described above, the embodiment of the present invention also provides a system for quantifying the influencing factors of carbon emissions in the planting industry based on a new logarithmic average Dirichlet index method model, which is used to Figure 1 The specific implementation of the method in the embodiment of the present invention, the logarithmic mean Dirichlet index method model LMDI model can be applied to a computer terminal, and its system structure diagram is shown in FIG. Figure 2 As shown, it includes a start module, a data input module, a crop industry full life cycle carbon accounting module, a data integrity decision module, a crop industry full life cycle carbon accounting analysis module, a result rationality decision module, a LMDI decomposition analysis module, a LMDI analysis result output module and an end module.

[0143] Specifically, the output end of the start module is connected to the input end of the data input module; the output end of the data input module is connected to the input end of the crop industry full life cycle carbon accounting module; the output end of the crop industry full life cycle carbon accounting module is connected to the input end of the data integrity decision module; the data integrity decision module has two output ends, one indicates that the data is complete (Y), which is connected to the input end of the crop industry full life cycle carbon accounting analysis module; the other indicates that the data is incomplete (N), and returns to the input end of the data input module for data supplement; the output end of the crop industry full life cycle carbon accounting analysis module is connected to the input end of the result rationality decision module; the result rationality decision module also has two output ends, one indicates that the result is reasonable (Y), which is connected to the input end of the LMDI decomposition analysis module; the other indicates that the result is unreasonable (N), and returns to the input end of the data input module for data correction; the output end of the LMDI decomposition analysis module is connected to the input end of the LMDI analysis result output module; the output end of the LMDI analysis result output module is connected to the input end of the end module.

[0144] Furthermore, the following is a detailed description of the role of each module:

[0145] Start module: marks the beginning of the entire process, starts the process, and ensures that the system is ready for data input and processing;

[0146] Data input module: responsible for receiving and entering carbon emission data for the entire life cycle of the planting industry, including detailed data on fertilizer application, crop planting, energy consumption and straw management;

[0147] Planting industry full life cycle carbon accounting module: process and account for input carbon emission data, calculate the total carbon emission of each link, and ensure that all input data are processed and calculated correctly;

[0148] Data integrity decision module: Checks whether the data is complete. If the data is missing or incomplete, it returns to the data input module for supplementation. If the data is complete, it continues to the next step of analysis;

[0149] Planting industry full life cycle carbon accounting analysis module: further analyze and process the calculated data to ensure the rationality and accuracy of all data;

[0150] Result rationality decision module: evaluates the rationality of the analysis results. If the results are unreasonable, it returns to the data input module for correction. If the results are reasonable, it proceeds to the next step of decomposition analysis.

[0151] LMDI decomposition analysis module: using the logarithmic mean Dirichlet index (LMDI) model, the total carbon emissions are decomposed into five major factors: coefficient, technology, structure, demand and population, and the contribution of each factor to the change in carbon emissions is calculated in detail;

[0152] LMDI analysis result output module: output the results of LMDI decomposition analysis and generate the final analysis report or data file;

[0153] End module: marks the end of the entire process, confirms that all steps have been completed, closes the process, and saves all output results.

[0154] Through the collaborative work of the above modules, the invention can finely quantify the factors affecting carbon emissions in the agricultural industry and provide scientific carbon reduction strategies.

[0155] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0156] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirk index model, characterized in that: The following steps are involved: Data acquisition: Obtain carbon emission data for the entire life cycle of the planting industry; Accounting and analysis: Calculate and preliminarily analyze the acquired carbon emission data throughout the life cycle to calculate the total carbon emissions of each link; Factor decomposition: Using the new logarithmic mean Dirichlet index method model, the total carbon emissions are decomposed into several factors, and the contribution of each factor to the change in carbon emissions is calculated separately.

2. The method for quantifying the influencing factors of carbon emissions from crop production based on the novel logarithmic mean Dirk index model according to claim 1 is characterized in that: The entire life cycle includes the crop planting process, fertilizer application process, straw management process and energy consumption process.

3. The method for quantifying the influencing factors of carbon emissions from crop production based on the novel logarithmic mean Dirk index model according to claim 2 is characterized in that: The total carbon emissions include: methane emissions generated during crop planting, nitrous oxide emissions generated during fertilizer application, methane and nitrous oxide emissions generated during straw management, and carbon dioxide emissions generated during energy consumption.

4. The method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirk index model according to claim 3 is characterized in that: The methane emissions generated during crop cultivation are calculated as follows: Among them, E cf Indicates the methane emissions generated during crop cultivation, D1 rice,r represents the rice planting area in province r, R1 r represents the methane emission factor of rice fields in province r; The nitrous oxide emissions generated during fertilizer application are calculated using the following formula: Among them, E fu Indicates the amount of nitrous oxide emissions generated during fertilizer application, D2 r represents the nitrogen fertilizer application amount in province r, D3 r R2 represents the amount of compound fertilizer applied in province r. r represents the direct emission factor of nitrous oxide from fertilizer application in province r, and B represents the emission of NH3 and NO in the process of fertilizer application. x R3 is the proportion of nitrogen in synthetic fertilizers that volatilizes v R4 represents the indirect emission factor of nitrous oxide due to nitrogen deposition. r represents the nitrogen leaching and runoff rate in province r, R3 l&r represents the indirect emission factor of nitrous oxide due to nitrogen leaching and runoff; The nitrous oxide emissions from straw reuse as fertilizer and discarding on farmland during straw management are calculated as follows: in, Indicates the nitrous oxide emissions from the straw management process, D4 n,r represents the crop yield of crop n in province r, G n represents the stalk-to-grain ratio of crop n, C n represents the straw collection coefficient of crop n, H fertilizer,r represents the proportion of straw used as fertilizer in province r, A n represents the nitrogen content of crop straw n, R2 r represents the direct emission factor of nitrous oxide from fertilizer application in province r, where r represents the province and n represents the crop type; The methane emissions from open burning during straw management are calculated as follows: in, represents the methane emissions from straw management, D4 n,r represents the crop yield of crop n in province r, G n represents the stalk-to-grain ratio of crop n, C n represents the straw collection coefficient of crop n, H wasted,r represents the proportion of straw wasted by open burning in province r, R5 represents the methane emission factor of open burning of straw, r represents province, and n represents crop type; The carbon dioxide emissions generated by the energy consumption process are calculated as follows: Among them, E ec Indicates the carbon dioxide emissions generated by the energy consumption process, D5 r represents the amount of diesel input for agricultural machinery in province r, R6 represents the carbon dioxide emission factor of diesel application, D1 n,r represents the sown area of ​​crop n in province r, F n Represents the power consumption coefficient for irrigating crop n, R7 r represents the carbon dioxide emission factor of China's regional power grid, r represents the province, and n represents the crop type.

5. The method for quantifying the influencing factors of carbon emissions from crop production based on a novel logarithmic mean Dirichlet index model according to claim 1 is characterized in that: The total carbon emissions are decomposed into several factors including coefficient factor CF, technical factor TF, structural factor SF, demand factor DF and population factor PF.

6. A method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirichlet index model according to claim 3 or 5, characterized in that: The factors affecting carbon emissions include: Crop planting process: coefficient factor CF analyzes carbon emissions per unit rice planting area, technical factor TF analyzes the rice planting area required for unit rice output, demand factor DF analyzes per capita rice demand, and population factor PF analyzes the impact of regional population size on carbon emissions; Fertilizer application process: coefficient factor CF analyzes carbon emissions generated by unit nitrogen fertilizer input, technical factor TF analyzes nitrogen fertilizer application per unit area, demand factor DF analyzes the planting area corresponding to unit population, and population factor PF analyzes the impact of regional total population size on carbon emissions; Straw management process: coefficient factor CF analyzes the carbon emissions per unit crop, technical factor TF analyzes the yield per unit planting area, structural factor SF analyzes the proportion of each crop area to the total area, demand factor DF analyzes the planting area of ​​each crop per unit population, and population factor PF analyzes the impact of the total population size of the region on carbon emissions; Energy consumption process: The coefficient factor CF analyzes the carbon emissions generated by unit energy consumption, the technical factor TF analyzes the energy usage per unit area, the demand factor DF analyzes the crop planting area corresponding to the unit population, and the population factor PF analyzes the impact of the total population size of the region on carbon emissions.

7. The method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirichlet index model according to claim 6 is characterized in that: The factors affecting methane emissions during crop planting are decomposed into coefficient factors CF, technical factors TF, demand factors DF and population factors PF: ΔE=E t -E0=ΔE CF +ΔE TF +ΔE DF +ΔE PF Among them, r represents the province, E cf ' represents the carbon dioxide equivalent produced during the crop planting process in that year, in kilotons, E r1 represents the carbon dioxide equivalent produced by crop cultivation in province r in that year, in kilotons, S rice,r represents the rice planting area in province r in that year, in thousand hectares, V rice,r represents the rice production of province r in that year, in thousands of tons, P r It represents the total population of province r in that year, in thousands of people; E r / S rice,r represents the coefficient factor, i.e., carbon emission intensity of rice cultivation, S rice,r / V rice,r represents the technical factor, i.e. the rice planting area required for unit rice output, V rice,r / P r represents the demand factor, i.e., the per capita rice demand, P r represents the demographic factor, i.e., population size; △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively; in, represents the carbon dioxide equivalent produced by crop planting in period t, represents the carbon dioxide equivalent produced by crop cultivation in the base period, and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

8. The method for quantifying the factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirichlet index model according to claim 6 is characterized in that: The factors affecting nitrous oxide emissions during fertilizer application are decomposed into coefficient factors CF, technical factors TF, demand factors DF and population factors PF: ΔE=E t -E0=ΔE CF +ΔE TF +ΔE DF +ΔE PF Among them, r represents the province, E fu ' represents the carbon dioxide equivalent produced during the application of fertilizers in that year, in kilotons, E r2 represents the carbon dioxide equivalent produced by fertilizer application in province r in that year, in kilotons, N r represents the fertilizer input of province r in that year, in thousands of tons, S r represents the crop planting area of ​​province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people; E r / N r represents the coefficient factor, i.e., the carbon emission intensity of fertilizer application, N r / S r represents the technical factor, i.e. the amount of fertilizer applied per unit planting area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size; △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively; represents the carbon dioxide equivalent produced by the application of fertilizer in period t, It represents the carbon dioxide equivalent produced by fertilizer application in the base period. and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

9. The method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirk index model according to claim 6 is characterized in that: The influencing factors of methane and nitrous oxide emissions in the straw management process are decomposed into coefficient factors CF, technical factors TF, structural factors SF, demand factors DF and population factors PF: ΔE=E t -E0=ΔE CF +ΔE TF +ΔE SF +ΔE DF +ΔE PF Among them, r represents the province, n represents the crop type, E sm ' represents the carbon dioxide equivalent emissions generated by the straw management process in that year, in kilotons, E rn V is the carbon dioxide equivalent produced by crop straw management in province r in that year, in kilotons. rn represents the yield of crop n in province r in that year, in thousands of tons, S rn S represents the planting area of ​​crop n in province r in that year, in thousands of hectares. r represents the total planting area of ​​all crops in province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people; E rn / V rn represents the coefficient factor, i.e., the carbon emission intensity of crop planting, V rn / S rn represents the technical factor, i.e., the crop yield per unit planting area, S rn / S r represents the structural factor, that is, the proportion of each crop planting area to the total planting area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size; △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E SF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, structural factors, demand factors and population factors respectively; represents the carbon dioxide equivalent produced by straw management in period t, represents the carbon dioxide equivalent produced by straw management during the base period, and They represent the coefficient factor, technical factor, structural factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, structural factors, demand factors and population factors respectively.

10. The method for quantifying factors affecting carbon emissions from crop production based on a novel logarithmic mean Dirichlet index model according to claim 6, characterized in that: The factors affecting carbon dioxide emissions from energy consumption are decomposed into coefficient factors CF, structural factors SF, demand factors DF and population factors PF: ΔE=E t -E0=ΔE CF +ΔE TF +ΔE DF +ΔE PF Among them, r represents the province, E ec ' represents the carbon dioxide equivalent produced by the energy consumption process in the year, in kilotons, E r3 represents the carbon dioxide equivalent produced by energy consumption in province r in that year, in kilotons, U r represents the energy consumption of province r in that year, with diesel in kilotons and electricity in megawatt-hours. r represents the total planting area of ​​all crops in province r in that year, in thousand hectares, P r It represents the total population of province r in that year, in thousands of people; E r / U r represents the coefficient factor, i.e., energy carbon emission intensity, U r / S r Represents technical factors, i.e. energy consumption per unit area, S r / P r represents the demand factor, i.e., per capita crop planting area, P r represents the demographic factor, i.e., population size; △E represents the total change in carbon dioxide equivalent, E0 and E t They represent the base period emissions and the emissions in the tth period, △E CF , △E TF , △E DF and ∆E PF They represent the changes in carbon dioxide equivalent caused by coefficient factors, technical factors, demand factors and population factors respectively; represents the carbon dioxide equivalent produced by the energy consumption process in period t, represents the carbon dioxide equivalent produced by the energy consumption process in the base period, and They represent the coefficient factor, technical factor, demand factor and population factor of the tth period respectively. and They represent base period coefficient factors, technical factors, demand factors and population factors respectively.

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