Automatic accounting method for carbon emission factors in regional food production stage

Abstract

The invention discloses a regional food production stage carbon emission factor automatic accounting method, and relates to the field of food system greenhouse gas emission, and the method comprises the steps: constructing an accounting framework of regional food production functional unit carbon emission factors; extracting an emission coefficient and activity data from the accounting framework; based on the emission coefficient and the activity data, constructing a multi-dimensional food production stage carbon emission factor system, and accounting carbon emission factors of food production stages in different regions; carrying out weight optimization on the carbon emission factors by utilizing a particle swarm optimization algorithm; based on the dynamic change of the multi-dimensional food production stage carbon emission factor system, the carbon emission factors of different regional food production periods are summarized to form a regional food production functional unit carbon emission factor automatic accounting system. According to the method, the carbon emission factors of the regional food production stage are automatically calculated based on the input data of the regional production stage, and the method can serve agricultural production carbon management and control of different regions and construction of an inter-region carbon compensation system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of food system greenhouse gas emissions, in particular to a method for automatically accounting carbon emission factors of regional food production stages. BACKGROUND

[0002] Due to economic growth, population growth and rapid urbanization, the total amount of food production and consumption and its consumption structure in China is undergoing tremendous changes. The food system supply chain, including food production, planting, and livestock grain and feed planting, feed processing, energy consumption and manure excretion, is also undergoing rapid transformation. The resulting greenhouse gas emissions have become a major challenge in addressing and mitigating climate change emissions while ensuring food security in China.

[0003] The Joint Research Centre (JRC) of the European Commission has calculated the greenhouse gas emissions of the food system according to the IPCC emission inventory decomposition method, but this inventory only accounts for national-level food system greenhouse gas emissions from an industry perspective. The results are difficult to guide the development of regionally differentiated food system emission reduction policies and to identify key food types and their production processes. Most previous carbon emission factor calculations for the food system were based on single food type production stages in a single department, and the results were difficult to reflect the overall level of regional food system carbon emission factors, and could not support the development of regional-scale food system carbon emission mitigation policies.

[0004] In view of the problems in the related art, no effective solutions have been proposed so far. SUMMARY

[0005] In view of the problems in the related art, the present application proposes a method for automatically accounting carbon emission factors of regional food production stages to overcome the above technical problems existing in the prior art.

[0006] To this end, the specific technical solutions adopted by the present application are as follows: The present application provides a method for automatically accounting carbon emission factors of regional food production stages, comprising: constructing an accounting framework for carbon emission factors of regional food production functional units; and extracting emission coefficients and activity data from the accounting framework; based on the emission coefficients and activity data, constructing a multi-dimensional food production stage carbon emission factor system, and accounting for carbon emission factors of different regions of food production stages; using a particle swarm optimization algorithm to optimize the weights of the carbon emission factors; Based on the dynamic change of the multi-dimensional food production stage carbon emission factor system, the carbon emission factors of different regional food production cycles are summarized to form an automatic accounting system of regional food production function unit carbon emission factors.

[0007] Further, the accounting framework includes research objectives, functional units and system boundaries; The research objectives include: analyzing the greenhouse gas emission factors generated by the regional food production function unit, and determining the key processes that have the greatest impact on the greenhouse gas emissions of the regional food system; The functional units include: the greenhouse gas emission equivalent generated by each unit mass of food in the production process of the regional food system; The system boundaries include: the whole process of planting and breeding food production in the region.

[0008] Further, extracting emission coefficients and activity data from the accounting framework further includes: The emission coefficients include: the emission coefficients of different planting and breeding foods in the production process in the region; The activity data includes: the production quantity and production material input quantity of different foods in the region.

[0009] Further, based on the emission coefficients and activity data, a multi-dimensional food production stage carbon emission factor system is constructed, and the carbon emission factors of different regional food production stages are calculated, including: Using the multi-dimensional food production stage carbon emission factor system, the carbon emission factors of the planting and breeding food production stages in any region are calculated.

[0010] Further, the carbon emission factors of the planting food production stage in any region include the agricultural material production stage and the food planting stage; The agricultural material production stage includes: obtaining carbon emission efficiency by the ratio of input activity data of agricultural emission sources to activity data of food production in any region; The product of the emission factor of the unit emission source and the carbon emission efficiency is combined, and a summation symbol is added to obtain the total carbon emission of the agricultural material production stage; The food planting stage includes: obtaining diesel energy utilization efficiency by the ratio of input activity data of agricultural machinery using diesel to activity data of food production in any region, combining the product of diesel consumption emission factor; The activity data of irrigation power consumption is added to the ratio of activity data of food production in any region, to obtain the power utilization efficiency, combine the product of power input emission factor, and add the carbon emissions of rice field methane emission in any region and the carbon emissions generated by straw burning process in any region. Carbon emissions during the use of fertilizers in any region, to obtain the total carbon emissions of the food planting stage.

[0011] Further, the carbon emission factor of the food production stage of any region food breeding type food includes the feed planting stage, the feed processing stage, the feeding energy consumption stage, the intestinal fermentation stage and the feces management stage; Wherein, the feed planting stage: through the ratio of the input activity data of the livestock emission source to the activity data of the meat, egg and milk production stage in any region, the resource utilization efficiency is obtained; The product of the emission factor of the feed planting and the resource utilization efficiency is combined, and a summation symbol is added to obtain the total carbon emission of the feed planting stage; The feed processing stage: based on the resource utilization efficiency of the feed planting stage, the product of the emission factor of the feed processing and the resource utilization efficiency is combined, and a summation symbol is added to obtain the total carbon emission of the feed processing stage; The feeding energy consumption stage: based on the resource utilization efficiency of the feed planting stage, the product of the emission factor of the feeding process and the resource utilization efficiency is combined, and a summation symbol is added to obtain the total carbon emission of the feeding energy consumption stage; The intestinal fermentation stage: through the ratio of the methane emission factor of the intestinal fermentation of meat, egg and milk to the activity data of the meat, egg and milk production stage in any region, the environmental efficiency of intestinal fermentation methane emission is obtained, and the product of the environmental efficiency of intestinal fermentation methane emission and the preset value is combined to obtain the carbon emission generated in the intestinal fermentation stage; The feces management stage: through the ratio of the methane emission factor of the feces management of meat, egg and milk to the activity data of the meat, egg and milk production stage in any region, the environmental efficiency of feces methane emission is obtained, and the product of the environmental efficiency of feces methane emission and the preset value is added; The product of the methane emission factor of the feces management of meat, egg and milk and the activity data of the meat, egg and milk production stage in any region is combined to obtain the environmental efficiency of feces methane emission, and the product of the environmental efficiency of feces methane emission and the preset value is added to obtain the carbon emission generated in the feces management stage.

[0012] Further, the weight optimization of the carbon emission factor is carried out by using the particle swarm optimization algorithm, including: Through literature data, the carbon emission factor of each process of planting type food and breeding type food is obtained, and the actual value exists deviation; By using the particle swarm optimization algorithm, the optimal solution is searched in the weight space by simulating particles, and the carbon emission total value calculated by the adjusted factor is as close as possible to the true value by combining the fitness function; Through particle iteration optimization, the speed and position are adjusted according to the optimal position and global optimal position of itself, so that the particle position is continuously updated.

[0013] Further, the formula of the fitness function is: ; In the formula, F Fitness Represents the fitness function n express N One particle; W i This represents the weight adjustment factor, generated by the algorithm. E i This represents the initial calculated value of the emission factor; Measured Emission || indicates emission values ​​from references or field measurements; || indicates the absolute value symbol. The summation symbol is used.

[0014] Furthermore, the particle position update formula is as follows: ; In the formula, Indicates the particle's first t +1 update position; Indicates the particle's first t The location of the next update; Indicates the particle's first t +1 time for speed optimization.

[0015] Furthermore, based on the dynamic changes in the carbon emission factor system across life stages, the carbon emission factors of different regions' food production cycles are aggregated to form an automated accounting system for carbon emission factors of regional food production functional units, including: Based on a multidimensional carbon emission factor system for food production stages, the emission coefficients for regional differences, differences between planted and raised foods, and differences in years are dynamically optimized. The greenhouse gases generated by regional differences, differences in planted and raised foods, and differences in years are classified and statistically analyzed to form an automated accounting system for carbon emission factors of regional food production functional units.

[0016] The beneficial effects of this invention are as follows: 1) This invention automatically calculates the carbon emission factor of the regional food production stage based on regional production stage input data, which can better serve the carbon management of agricultural production in different regions and the construction of inter-regional carbon compensation system; this invention formulates optimized management measures for food production functional units with low carbon as the goal; this invention provides technical support for special projects derived from this method, providing basic data services and methodological support for carbon emission accounting in agricultural production.

[0017] 2) Compared with the current top-down emission inventory obtained by decomposing departments, the present invention uses a bottom-up life cycle food system carbon emission factor accounting method, which can more clearly and accurately understand and trace the key emission factors of the regional food system, as well as the food types involved in the emission factors, their production processes and other element information.

[0018] 3) Compared with the current relatively singular calculation of carbon emission factors from agricultural production sources, this invention covers the life cycle emissions of 14 types of food production systems (8 types of planted food and 6 types of livestock food), including grain planting and production, and livestock feed planting, feed processing, feeding energy consumption, intestinal fermentation and manure management, which more comprehensively reflects the differences in emission factors of food system production stages in different regions. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of an automated calculation method for carbon emission factors in the regional food production stage according to an embodiment of the present invention; Figure 2 This is a framework for calculating carbon emission factors of regional food production functional units according to an embodiment of the present invention. Detailed Implementation

[0021] To further illustrate the various embodiments, the present invention provides accompanying drawings, which are part of the disclosure of the present invention. These drawings are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these drawings, those skilled in the art should be able to understand other possible implementation methods and the advantages of the present invention.

[0022] According to an embodiment of the present invention, an automated accounting method for carbon emission factors in the regional food production stage is provided.

[0023] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments, such as... Figure 1 As shown, an automated calculation method for carbon emission factors in the regional food production stage according to an embodiment of the present invention includes: Step S1: Construct an accounting framework for carbon emission factors of regional food production functional units; and extract emission coefficients (i.e. emission factor accounting) and activity data (i.e. input-output dataset) from the accounting framework. Step S2: Based on emission coefficients and activity data, construct a multi-dimensional carbon emission factor system for food production stages, and calculate the carbon emission factors for food production stages in different regions. Step S3: Use the particle swarm optimization algorithm to optimize the weights of the carbon emission factors; Step S4: Based on the dynamic changes of the carbon emission factor system in the multidimensional food production stage, the carbon emission factors of different regions in the food production cycle are summarized to form an automated accounting system for carbon emission factors of regional food production functional units.

[0024] In this optional embodiment, the accounting framework includes research objectives, functional units, and system boundaries; The research objectives include: analyzing greenhouse gas emission factors generated by regional food production functional units and identifying the key processes that have the greatest impact on greenhouse gas emissions from regional food systems; The functional unit includes: the greenhouse gas emission equivalent generated per unit mass of food during the production process of food systems in each region; The system boundary includes the entire process of producing both planted and farmed foods within the region.

[0025] It should be noted that 1) the research objective is to analyze the greenhouse gas emission factors generated during the regional food production stage and identify the key processes that have the greatest impact on greenhouse gas emissions from the regional food system; 2) Functional unit refers to the greenhouse gas emission equivalent generated by a unit mass of food in various food system production processes, expressed in kg of CO2. -1 The greenhouse gases mentioned include: carbon dioxide, methane, and nitrous oxide. These three greenhouse gases, when converted to carbon dioxide equivalents, CO 2 :1, CH 4 28, N 2 O :265; 3) The system boundary refers to the entire production process of planted and raised foods within the region. Planted foods include rice, wheat, corn, soybeans, vegetables, potatoes, oilseeds, and sugar crops, while raised foods include pork, beef, mutton, poultry, eggs, and milk.

[0026] In this optional embodiment, extracting emission factors and activity data from the accounting framework further includes: Emission coefficients include: emission coefficients of different types of planted and raised foods during the production process within the region; The activity data includes: the production volume of different foods and the input of production materials in the region.

[0027] It should be noted that the data required for carbon emission accounting of functional units in the regional food production stage should be identified and collected, including emission factors and activity data; 1) Emission coefficients include: emission coefficients of different types of planted and raised foods in the production process within the region; 2) Activity data include: production volume of different foods and input of production materials within the region.

[0028] In this optional embodiment, a multidimensional carbon emission factor system for food production stages is constructed based on emission coefficients and activity data, and the carbon emission factors for food production stages in different regions are calculated, including: Step S21: Calculate the carbon emission factors for the food production stages of any region, including both crop-based and livestock-based food production stages, using a multidimensional food production stage carbon emission factor system.

[0029] It should be noted that this invention constructs a multi-dimensional carbon emission factor system for the food production cycle, calculating carbon emission factors for food production processes in different regions. The food includes both planted and raised foods. Compared to the previous generalized calculation of carbon emissions from agricultural production, this invention further refines the classification of production input data. Planted food production inputs include N, P, K fertilizers, agricultural films, seeds, pesticides, and the electricity and fuel consumed in the production process. Raised food feed types include corn, rice, wheat, and soybeans. Furthermore, this invention further improves the food production cycle, calculating the production cycle to include the agricultural resource planting stage, the grain production stage, and the livestock grain and feed planting, feed processing, feeding energy consumption, and manure management processes.

[0030] In this optional embodiment, the carbon emission factor for any food production stage of food cultivation in any region includes both the agricultural input production stage and the food cultivation stage. Among them, step S211, the agricultural input production stage, includes: obtaining carbon emission efficiency by comparing the input activity data of agricultural emission sources with the activity data of grain production in any region. By combining the emission factor of a unit emission source with the carbon emission efficiency and adding a summation sign, the total carbon emissions generated during the agricultural input production stage are obtained. It should be noted that the formula for carbon emissions during the production stage of A1, agricultural production materials for plant-based foods, is: ; In the formula, E AProductioni,j grain per unit i exist j Carbon emissions during the production stage of regional agricultural inputs are... j The total carbon emissions generated by agricultural inputs required to produce one kilogram of grain in a region; where, ckEmissions from agricultural inputs include a1 nitrogen, a2 phosphorus, a3 potash fertilizer, a4 agricultural mulch film, a5 seeds, and a6 pesticides. IN ck,j For emission sources ck Input activity data (unit: kg / mu). A Productioni,j For food i exist j Regional production process activity data, i.e., output (unit: kg / mu); f ck Agricultural input per unit ck Emission factors (unit: kg CO2e kg) -1 ); Step S212, the food planting stage includes: obtaining the diesel energy utilization efficiency by comparing the input activity data of diesel use in agricultural machinery with the activity data of food production process in any region, and combining the product of diesel consumption emission factors. By adding data on electricity consumption for irrigation to the ratio of data on food production activities in any region, the electricity utilization efficiency is obtained. This efficiency is then combined with the product of electricity input emission factors. Finally, by adding methane emissions from paddy fields in any region, carbon emissions from straw burning in any region, and carbon emissions from fertilizer use in any region, the total carbon emissions generated during the food cultivation stage are obtained.

[0031] It should be noted that the formula for the carbon emission factor during the planting stage of A2, plant-based foods, is: ; In the formula, E GProductioni,j Indicates unit grain i exist j Carbon emissions during the crop cultivation stage in the region are j The total carbon emissions generated during the crop cultivation stage of producing one k of food in a region; IN fuel,j This represents input data for agricultural machinery that directly uses diesel fuel (unit: liters / acre). A Productioni,j Indicates grain i exist j Regional production process activity data, i.e., output (unit: kg / mu). f fuelc Indicates A7 diesel consumption fuel Emission factors (unit: kg CO2e kg) -1 ), IN ele,j Activity data representing electricity consumption for irrigation (unit: kWh / acre). f elecIndicates A8 power input ele Emission factors (unit: kg CO2e kg) -1 ), E Rice,j express j Methane emissions from paddy fields in the region (unit: t / mu), E Res,j express j Carbon emissions from straw burning in the region (unit: kg CO2e) E Fer,j Indicates unit grain i exist j Carbon emissions from the use of chemical fertilizers in the region (unit: kgCO2e).

[0032] unit grain j The formula for methane emissions from paddy fields in the region is: ; In the formula, f rice,j This indicates the use of greenhouse gas emissions from provincial greenhouse gas emission inventories in China (2006). CH 4 Emission coefficients (kg / hectare) calculated by the MOD model. A Productioni,j Indicates grain i exist j Regional production process activity data, i.e., output (unit: kg / mu).

[0033] unit grain i exist j The formula for carbon emissions generated by the burning of straw in the region is: ; In the formula, UA Res,i,j express j area i The straw burning rate (kg / mu) for grain-related crops is the product of the production amount of different types of grain, the corresponding straw-to-grain ratio, and the burning ratio. A Productioni,j Indicates grain i exist j Regional production process activity data, i.e., output (unit: kg / mu). f Res Emissions from straw combustion (unit: kg CO2e kg) -1 ).

[0034] unit grain i exist j The formula for carbon emissions from the use of chemical fertilizers in a region is: ; ; ; ; In the formula, UA N,i,j This represents the amount of nitrogen fertilizer applied per unit crop yield of grain i in region j. A Productioni,j Indicates grain i exist j Regional production process activity data, i.e., output (kg / mu). R N This indicates the nitrogen content of nitrogen fertilizer. f ND , f NL ,and f NV These represent the emission coefficients (kg N2O-N / kg nitrogen input) for direct emissions, nitrogen leaching, and ammonia volatilization during nitrogen fertilizer application. EF N express j Direct emission factor of N2O in the region (kg N2O-N / kg nitrogen input). EF L It represents the indirect emission factor of N2O caused by nitrogen leaching and runoff (kg N2O-N / kg nitrogen input). EF V This represents the indirect emission factor of N2O caused by volatilization (kg N2O-N / kg nitrogen input). f dry The dry weight ratio of grain. f eco Indicates the economic coefficient of grain. f ret Indicates the rate of straw return to the field. f rn Indicates the nitrogen content of straw. f ratio This indicates the root-to-crown ratio of grain.

[0035] Table 1. Calculation of Carbon Emission Factors in Grain Production In this optional embodiment, the carbon emission factor of any region’s food production stage includes feed planting stage, feed processing stage, feeding energy consumption stage, intestinal fermentation stage and manure management stage. Among them, step S221, feed planting stage: obtain resource utilization efficiency by comparing the input activity data of livestock emission sources with the production activity data of meat, eggs and milk in any region. By combining the emission factors of forage planting with the resource utilization efficiency and adding a summation sign, the total carbon emissions of the forage planting stage are obtained. It should be noted that the carbon emissions for B1, the planting stage of livestock feed, are calculated using the following formula: ; In the formula, EM Productioni,j Indicates the unit of meat, eggs and milk i exist j Carbon emissions during the regional forage planting stage are j Regional production of meat, eggs and milk per kilogram i The total carbon emissions during the required feed production stages; mk This indicates feed emission sources for livestock inputs, including b3 corn, b4 soybeans, b5 wheat, and b6 rice. IN mk,j Indicates emission source ck Input activity data (kg / kg) A Productioni,j This represents the production data (kg / head) of meat, eggs, and dairy products i in region j. f mkg Emissions from forage crop cultivation (kg CO2e kg) -1 ); Step S222, Feed Processing Stage: Based on the resource utilization efficiency of the feed planting stage, the emission factor of feed processing is multiplied by the resource utilization efficiency, and a summation symbol is added to obtain the total carbon emissions of the feed processing stage. It should be noted that the formula for carbon emissions during the B2 stage of livestock feed processing is as follows: and units of meat, eggs and milk i exist j Carbon emissions generated during the regional feed processing stage are calculated using the following formula: ; In the formula, EM processi,j Indicates the unit of meat, eggs and milk i exist j Carbon emissions generated during the regional feed processing stage. mk The sources of emissions from livestock inputs include b3 corn, b4 soybeans, b5 wheat, and b6 rice. IN mk,j Indicates emission source mk Input activity data (kg / kg) A Productioni,j Indicates meat, eggs, and dairy i exist jRegional production process activity data, i.e., output (kg / head). f mkp Emissions from feed processing (kg CO2e kg) -1 ).

[0036] Step S223, Feeding Energy Consumption Stage: Based on the resource utilization efficiency of the feed planting stage, combined with the product of the emission factor of the feeding process and the resource utilization efficiency, and with the addition of a summation symbol, the total carbon emissions of the feeding energy consumption stage are obtained. It should be noted that the formula for calculating carbon emissions during the B3 stage of livestock farming is as follows: The carbon emissions generated by raising a unit of meat, egg, and dairy product i in region j are calculated using the following formula: ; In the formula, EM Breedi,j Indicates the unit of meat, eggs and milk i exist j Carbon emissions generated during the regional breeding stage. mk 1 represents the emission sources of livestock inputs, including b1 electricity and b2 fuel power consumed in feeding. IN mk1,j For emission sources mk Input activity data for 1 (kWh / kg, kg / kg, liters / kg). A Productioni,j Indicates meat, eggs, and dairy i exist j Regional production process activity data, i.e., output (kg / head). f mkb Emissions during the feeding process (kg CO2e kg) -1 ).

[0037] Step S224, Intestinal Fermentation Stage: By comparing the methane emission factor of meat, egg and dairy products in the intestinal fermentation stage with the activity data of meat, egg and dairy products in any region, the environmental efficiency of methane emissions from intestinal fermentation is obtained. The carbon emissions generated in the intestinal fermentation stage are obtained by multiplying the environmental efficiency of methane emissions from intestinal fermentation with a preset value. Step S225, Fecal Management Stage: Obtain the environmental efficiency of fecal methane emissions by comparing the methane emission factor of meat, egg and dairy fecal management with the activity data of meat, egg and dairy production in any region, and add the product of the environmental efficiency of fecal methane emissions and the preset value. It should be noted that the formula for intestinal fermentation of B4-type farmed foods is: ; In the formula, EM Fermentationi,j Indicates the unit of meat, eggs and milki exist j Carbon emissions from gut fermentation in the region EF Enteric,i Indicates meat, eggs, and dairy i Intestinal fermentation CH 4 Emission factor (kg / head / year) A Productioni,j Indicates meat, eggs, and dairy i exist j Regional production process activity data, i.e., output (kg / head).

[0038] By combining the nitrous oxide emission factor of meat, egg and dairy manure management with the ratio of meat, egg and dairy production activity data in any region, the environmental efficiency of nitrous oxide emissions from manure is obtained. Then, by multiplying the environmental efficiency of nitrous oxide emissions from manure by a preset value, the carbon emissions generated during the manure management stage are obtained.

[0039] The formula for carbon emissions during the waste management phase is: ; In the formula, EM Manurei,j For units of meat, eggs and dairy i exist j Carbon emissions (kgCO2e) generated during the local sewage management process. EF CH4,Manure,i meat, eggs and dairy i fecal management CH 4 Emission factor (kg CO2e / head / year) EF N2o,Manure,i meat, eggs and dairy i N2O emission factor from fecal management (kg CO2e / head / year).

[0040] Table 2. Calculation of Carbon Emission Factors from Livestock Food Production The formula for the animal methane emission factor is: ; In the formula, Indicates the first i Animals in j Methane emission factor of the region (kg / head / year). GE i This represents the total energy (m) ingested by an animal. j ( / head / year) Y m,i The methane conversion rate is the proportion of total energy in feed that is converted into methane; 55.65 is the methane energy conversion factor (m). j kg CH4 ).

[0041] The formula for animal feces management emission factors is: ; In the formula, EM Manureijk Indicates animal species i Fecal management methods j Climate zones k methane emission factor (kg) CH 4 / Year); VS i Indicates animal species i Daily volatile solids emissions (kg dm³) 3 vs / day); 0.67 represents the mass-volume density of methane (kg / m³). 3 ); B 0i Indicates animal species i Maximum methane production capacity of feces (m 3 / kg dm 3 vs); MCF jk Indicates fecal management methods j Climate zones k methane conversion coefficient; MS ijk Indicates animal species i Climate zones k Fecal management methods j The proportion of.

[0042] Table 3 shows the grass-to-grain ratio. Table 4 shows the proportion of straw burning. Table 5 shows the root-to-shoot ratio. In this optional embodiment, optimizing the weights of the carbon emission factor using a particle swarm optimization algorithm includes: Step S31: Through literature data, it was found that the carbon emission factors of each process of planted and farmed foods deviated from the actual values; Step S32: Using the particle swarm optimization algorithm, the optimal solution is searched in the weight space by simulating particles, and combined with the fitness function, so that the total carbon emission calculated by the adjusted factors is as close as possible to the actual value. Step S33: Through particle iterative optimization, adjust the velocity and position according to the particle's own optimal position and the global optimal position to make the particle position continuously updated.

[0043] It should be noted that in the calculation of carbon emission factors for the food production life cycle in the aforementioned regions, the carbon emission factors for each process of planted and farmed foods were based on literature data and lacked dynamic and personalized adjustments. However, actual emission data are often affected by various factors (regional climate, planting / farming techniques, and agricultural management levels), so the resulting carbon emission factors may deviate from the actual values. To improve the accuracy of the calculation, the optimal solution was searched in the weight space by simulating particles, so that the total carbon emission value calculated by the adjusted factors is as close as possible to the measured value.

[0044] Step S34: In this optional embodiment, the formula for the fitness function is: ; In the formula, F Fitness Represents the fitness function n express N One particle; W i This represents the weight adjustment factor, generated by the algorithm. E i This represents the initial calculated value of the emission factor; Measured Emission || indicates emission values ​​from references or field measurements; || indicates the absolute value symbol. The summation symbol is used.

[0045] It should be noted that, firstly, it is randomly generated. N Particles V i Each particle's dimension is a weight vector [w1, w2, ..., w n The initial particle velocity is set to a small random value (-0.1 to 0.1); the initial range for each weight is [0.5, 1.5] (±50% adjustment space). In each iteration, each particle adjusts its velocity and position based on its own optimal position and the global optimal position. The particle velocity update formula is: ; In the formula, Indicates the particle's first t +1 times the optimization speed, where ω represents the inertia factor. C 1 , C 2 They represent acceleration factors, R 1 , R 2 These represent the introduced random numbers (0-1). P iThis represents the optimal position of an individual particle, that is, the best position the particle encounters throughout all iterations. g This represents the global optimal position, which is the optimal position encountered in all particle iterations.

[0046] Step S35: In this optional embodiment, the particle position update formula is: ; In the formula, Indicates the particle's first t +1 update position; Indicates the particle's first t The location of the next update; Indicates the particle's first t +1 time for speed optimization.

[0047] In this optional embodiment, based on the dynamic changes in the carbon emission factor system during the production stage, the carbon emission factors of different regions' food production cycles are aggregated to form an automated accounting system for carbon emission factors of regional food production functional units, including: Step S41: Based on the multidimensional food life stage carbon emission factor system, dynamically optimize the emission coefficients of regional differences, differences between planted and raised foods, and differences in years; Step S42: Classify and statistically analyze the greenhouse gases generated by regional differences, differences between planted and raised foods, and differences in years to form an automated accounting system for carbon emission factors of regional food production functional units.

[0048] It should be noted that, based on the dynamic changes of life cycle factors, carbon emission factors of different types of food production processes are aggregated. Emission coefficients are dynamically optimized according to regional differences, differences in planting and breeding types, and year differences. Furthermore, greenhouse gases generated by different production processes are categorized and statistically analyzed, forming an automated accounting system for carbon emission factors of regional food production functional units. This system covers the overall greenhouse gas emission factors of regional food production processes. CO 2 Emission factors, CH 4 Emission Factors and N 2 O Emission factors.

[0049] In summary, by utilizing the above-described technical solution of this invention, the objectives to be achieved by this invention are described. Accurate accounting of carbon emissions from agricultural production is a crucial means to support the achievement of my country's proposed goals for controlling greenhouse gas emissions, and it also injects momentum into improving my country's capacity to address climate change. By implementing carbon control over different types of food production processes, both "dual carbon" goals can be achieved while promoting coordinated regional development.

[0050] Against this backdrop, this study constructs an automated accounting method for carbon emission factors at the regional food production stage. This method aims to clearly and accurately understand and trace the emission factors at each stage of the regional food system's production, as well as the information on production processes, food types, and other related elements involved in these emission factors. It explores ways to optimize agricultural production patterns towards carbon neutrality. Therefore, this automated accounting method for carbon emission factors at the regional food production stage will contribute to the spatial management of carbon effects in agricultural production. This invention, based on an automated accounting framework for carbon emission factors of regional food production functional units, combines food emission factors and activity data from these units to calculate carbon emission factors for different types of food. This provides a foundational data basis for carbon control in agricultural production, supports the formulation of low-carbon agriculture carbon reduction and carbon sequestration policies, and has significant practical implications.

[0051] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automated method for calculating carbon emission factors during regional food production, characterized in that, include: Construct an accounting framework for carbon emission factors of regional food production functional units; And extract emission factors and activity data from the accounting framework; Based on emission coefficients and activity data, a multidimensional carbon emission factor system for food production stages was constructed, and the carbon emission factors for food production stages in different regions were calculated. The carbon emission factor is optimized by using the particle swarm optimization algorithm. Based on the dynamic changes of the carbon emission factor system in the multidimensional food production stage, the carbon emission factors of different regions in the food production cycle are summarized to form an automated accounting system for carbon emission factors of regional food production functional units.

2. The automated calculation method for carbon emission factors in the regional food production stage according to claim 1, characterized in that, The accounting framework includes research objectives, functional units, and system boundaries; The research objectives include: analyzing greenhouse gas emission factors generated by regional food production functional units and identifying the key processes that have the greatest impact on greenhouse gas emissions from regional food systems; The functional unit includes: the greenhouse gas emission equivalent generated per unit mass of food during the production process of each regional food system; The system boundary includes the entire production process of both planted and raised food within the region.

3. The automated calculation method for carbon emission factors in the regional food production stage according to claim 1, characterized in that, The extraction of emission factors and activity data from the accounting framework also includes: The emission coefficients include: emission coefficients of different types of planted and farmed foods during the production process within the region; The activity data includes: the production volume of different foods and the input of production materials within the region.

4. The automated calculation method for carbon emission factors in the regional food production stage according to claim 1, characterized in that, The aforementioned system of carbon emission factors for different food production stages, based on emission coefficients and activity data, is used to construct a multidimensional carbon emission factor system for different food production stages, and to calculate the carbon emission factors for different food production stages in different regions, including: Using a multidimensional food production stage carbon emission factor system, the carbon emission factors of food crop production stage and livestock production stage in any region can be calculated.

5. The automated calculation method for carbon emission factors in the regional food production stage according to claim 4, characterized in that, The calculation of carbon emission factors for any region's food production stage includes both the agricultural input production stage and the food planting stage. Among them, the agricultural input production stage includes obtaining carbon emission efficiency by comparing the input activity data of agricultural emission sources with the activity data of grain production in any region. By combining the emission factor of a unit emission source with the carbon emission efficiency and adding a summation sign, the total carbon emissions generated during the agricultural input production stage are obtained. The food cultivation stage includes: obtaining the diesel energy utilization efficiency by comparing the input activity data of diesel use in agricultural machinery with the activity data of food production in any region, and combining the product of diesel consumption emission factors; By adding data on electricity consumption for irrigation to the ratio of data on food production activities in any region, the electricity utilization efficiency is obtained. This efficiency is then combined with the product of electricity input emission factors. Finally, by adding methane emissions from paddy fields in any region, carbon emissions from straw burning in any region, and carbon emissions from fertilizer use in any region, the total carbon emissions generated during the food cultivation stage are obtained.

6. The automated calculation method for carbon emission factors in the regional food production stage according to claim 5, characterized in that, The calculation of carbon emission factors for any food production stage in any region includes the feed planting stage, feed processing stage, feeding energy consumption stage, intestinal fermentation stage, and manure management stage. Among them, in the feed planting stage: resource utilization efficiency is obtained by comparing the input activity data of livestock emission sources with the production activity data of meat, eggs and milk in any region. By combining the emission factors of forage planting with the resource utilization efficiency and adding a summation sign, the total carbon emissions of the forage planting stage are obtained. Feed processing stage: Based on the resource utilization efficiency of the feed planting stage, combined with the product of the emission factor of feed processing and the resource utilization efficiency, and with the addition of a summation sign, the total carbon emissions of the feed processing stage are obtained. Energy consumption stage of feeding: Based on the resource utilization efficiency of the feed planting stage, combined with the product of the emission factor of the feeding process and the resource utilization efficiency, and with the addition of a summation sign, the total carbon emissions of the energy consumption stage of feeding are obtained. Intestinal fermentation stage: The environmental efficiency of methane emissions from intestinal fermentation is obtained by comparing the methane emission factor of meat, eggs and dairy products with the production activity data of meat, eggs and dairy products in any region. The carbon emissions generated during the intestinal fermentation stage are obtained by multiplying the environmental efficiency of methane emissions from intestinal fermentation with a preset value. Fecal management stage: The environmental efficiency of fecal methane emissions is obtained by comparing the methane emission factor of meat, egg and dairy fecal management with the production activity data of meat, egg and dairy in any region, and the product of the environmental efficiency of fecal methane emissions and the preset value is added. By combining the nitrous oxide emission factor of meat, egg and dairy manure management with the ratio of meat, egg and dairy production activity data in any region, the environmental efficiency of nitrous oxide emissions from manure is obtained. Then, by multiplying the environmental efficiency of nitrous oxide emissions from manure by a preset value, the carbon emissions generated during the manure management stage are obtained.

7. The automated calculation method for carbon emission factors in the regional food production stage according to claim 1, characterized in that, The step of using particle swarm optimization algorithm to optimize the weights of carbon emission factors includes: Based on literature data, it was found that the carbon emission factors for each process of plant-based and livestock-based foods deviate from the actual values; By using the particle swarm optimization algorithm, the optimal solution is searched in the weight space by simulating particles, and combined with the fitness function, so that the total carbon emissions calculated by the adjusted factors are as close as possible to the actual values. Through particle iterative optimization, the velocity and position are adjusted based on the particle's own optimal position and the global optimal position, so that the particle position is continuously updated.

8. The automated calculation method for carbon emission factors in the regional food production stage according to claim 7, characterized in that, The formula for the fitness function is: ； In the formula, F Fitness Represents the fitness function n express N One particle; W i This represents the weight adjustment factor, generated by the algorithm. E i This represents the initial calculated value of the emission factor; Measured Emission || indicates emission values ​​from references or field measurements; || indicates the absolute value symbol. The summation symbol is used.

9. The automated calculation method for carbon emission factors in the regional food production stage according to claim 8, characterized in that, The particle position update formula is as follows: ； In the formula, Indicates the particle's first t +1 update position; Indicates the particle's first t The next update location; Indicates the particle's first t +1 time for speed optimization.

10. The automated calculation method for carbon emission factors in the regional food production stage according to claim 1, characterized in that, The dynamic changes of the carbon emission factor system based on the multidimensional food production stage, which summarizes the carbon emission factors of different regions' food production cycles to form an automated accounting system for regional food production functional unit carbon emission factors, include: Based on the life stage carbon emission factor system, the emission coefficients of regional differences, differences between planted and raised foods, and differences in years are dynamically optimized; The greenhouse gases generated by regional differences, differences in planted and raised foods, and differences in years are classified and statistically analyzed to form an automated accounting system for carbon emission factors of regional food production functional units.

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