A method for analyzing energy-soil-carbon collaborative relationship of urban agglomeration under cross-regional perspective

Abstract

The application discloses a kind of urban agglomeration energy-soil-carbon synergistic relationship analysis methods under cross-region visual angle, including calculating urban agglomeration energy-soil-carbon direct flow;Urban agglomeration energy-soil-carbon implicit flow is calculated;Urban agglomeration energy-soil-carbon synergistic degree is obtained;Urban agglomeration energy-soil-carbon ecological network is constructed, and the control and dependent relationship of urban agglomeration energy-soil-carbon is analyzed and judged using the urban agglomeration energy-soil-carbon ecological network;Urban agglomeration energy-soil-carbon intermediate end data is obtained using intermediate model;The control and dependent relationship of urban agglomeration energy-soil-carbon obtained by analysis and judgment identifies the interaction between nodes in urban agglomeration energy-soil-carbon ecological network and the key path and node that influence urban agglomeration carbon emission change, from production end, consumption end, intermediate end multi-perspective data analysis energy-soil-carbon ecological network synergistic feature, and the synergistic degree relationship between each region and each department of urban agglomeration is analyzed from the obtained urban agglomeration energy-soil-carbon synergistic degree.

Description

Technical Field

[0001] The present invention relates to the technical field of collaborative analysis, and in particular to a method for analyzing the energy-soil-carbon collaborative relationship of urban agglomerations from a cross-regional perspective. Background Art

[0002] The overexploitation of energy and land during urbanization and industrialization has led to a surge in greenhouse gas emissions, placing enormous pressure on countries worldwide to reduce carbon emissions. Domestic and international scholars have conducted a series of studies on the impact of land-use change on carbon emissions and the relationship between energy consumption and carbon emissions. However, these studies focus on the interplay between individual factors and carbon emissions, lacking a systematic understanding of the "energy-land-carbon" metabolic network. Land resources and energy are two core factors closely linked to human economic and social activities. Furthermore, the influence of trade within urban agglomerations further complicates the carbon metabolism process. Therefore, analyzing the interregional synergy between energy, land resources, and carbon dioxide emissions at the urban agglomeration level is particularly important for carbon reduction. Summary of the Invention

[0003] The purpose of the present invention is to overcome the shortcomings of the existing technology and provide a method for analyzing the energy-soil-carbon synergistic relationship of urban agglomerations from a cross-regional perspective.

[0004] To achieve the above objectives, the technical solutions provided by the present invention are:

[0005] A cross-regional analysis method for the energy-soil-carbon synergy in urban agglomerations includes:

[0006] Calculate direct energy-soil-carbon flows in urban agglomerations;

[0007] Calculate the implicit energy-soil-carbon flows of urban agglomerations, including implicit flows between regions and sectors;

[0008] The energy-soil-carbon synergy of urban agglomerations is calculated by combining the calculated direct energy-soil-carbon flow and the implicit energy-soil-carbon flow of urban agglomerations.

[0009] Using each region and department of the urban agglomeration as nodes and the implicit flows between regions and departments as paths, we constructed an urban agglomeration energy-soil-carbon ecological network. This urban agglomeration energy-soil-carbon ecological network was then used to analyze and determine the control and dependency relationships between energy, soil, and carbon in the urban agglomeration.

[0010] Use the intermediate model to obtain data on the energy-soil-carbon intermediary of urban agglomerations;

[0011] By analyzing and judging the control and dependence relationships of energy, soil and carbon in urban agglomerations, we identify the interaction relationships between nodes in the energy-soil-carbon ecological network in urban agglomerations and the key paths and nodes that affect the changes in carbon emissions in urban agglomerations. We analyze the synergistic characteristics of the energy-soil-carbon ecological network from multiple perspectives, including production, consumption and intermediary data. We also analyze the synergy relationships between various regions and departments in urban agglomerations from the energy-soil-carbon synergy obtained in urban agglomerations.

[0012] Furthermore, the calculation of direct energy-soil-carbon flows in urban agglomerations includes:

[0013] Collect energy consumption data from various departments in each city to obtain the total energy consumption;

[0014] Land use data were collected, including land use types such as cultivated land, forest land, grassland, water area, urban land, rural land, transportation and mining land, and unused land. Statistical analysis was performed using ArcGIS software. The statistical analysis formula is as follows:

[0015]

[0016] Where S represents the area; n is the number of land use types before and after the transfer; u and v represent the land use types before and after the transfer, respectively; S uv It represents the area of ​​land type u before transfer and land type v after transfer;

[0017] Energy carbon emissions caused by energy consumption are calculated by multiplying the consumption of fossil energy, including coal, coke, crude oil, fuel oil, gasoline, kerosene, diesel and natural gas, by the emission factor. The calculation formula is:

[0018] C E =∑ i ∑ h C i，h =∑ i ∑ j e i，h ×NCV h ×CC h ×O i，h

[0019] Where C E Energy carbon emissions caused by energy consumption; C i，h NCV is the carbon emission of energy type h in sector i; h is the calorific value of h energy variety; CC h is the unit calorific value emission of h energy types; O i，h is the oxidation efficiency of energy type h in sector i;

[0020] The calculation formula for carbon emissions caused by land use is as follows:

[0021] C C =C E +C ER +C EF

[0022] C ER =k ER ×p i

[0023]

[0024] Where C C is the carbon emissions caused by land use; C ER Carbon emissions from human breathing and livestock farming; C EF is the carbon emission rate of farmland; k ER is the emission coefficient; p i The number of biological individuals carrying out activities is divided into urban population, rural population, and the number of large and medium-sized livestock raised in the livestock breeding industry; are the carbon emission rates of fertilizer application, mechanical tillage, and farmland irrigation, respectively; F is the amount of fertilizer applied; M is the total mechanical power; S1 is the irrigated area; k1, k2, and k3 are the corresponding conversion coefficients, respectively;

[0025] Calculate the carbon absorption C of natural land S , the calculation formula is as follows:

[0026] C s =∑K×S

[0027] Where S is the land use type area; K is the carbon sink coefficient.

[0028] Furthermore, the implicit energy-soil-carbon flows of urban agglomerations are calculated, including:

[0029] The energy, land resources and carbon emission intensities of each sector in each region are as follows:

[0030]

[0031] Where, X j represents the total investment amount of department j; e i is the energy intensity consumed per unit of economic output of sector i; c i is the carbon dioxide intensity per unit of economic output of sector i; is the direct land use matrix of unit economic output of sector i in land use type k; is the area occupied by land use type k in sector i; E i is the total energy consumption of sector i, C i is the carbon emissions of sector i;

[0032] Based on the final demand of each city in the inter-city input-output table, the implicit flow of energy, carbon, and land resources is calculated to explore the relationship between cities in the urban agglomeration and identify the main contributing cities, sectors, and links in the energy-land-carbon supply chain of the urban agglomeration. The calculation formula is:

[0033]

[0034] Where, is the implicit energy flow required for sector i to meet the final demand of sector j, is the carbon flow implied by sector i satisfying the final demand of sector j, is the implicit land resource flow required for sector i to meet the final demand of sector j, I is the n×n unit matrix, (IA) -1 is the inverse Leontief matrix, Y S is the final demand matrix.

[0035] Furthermore, the formula for calculating the energy-soil-carbon synergy of urban agglomerations is:

[0036]

[0037]

[0038]

[0039]

[0040] Where a e is the total energy consumption; a l is the total area of ​​land that has changed its land use type; a c is the total carbon emissions; is the implicit energy flow required for sector i to meet the final demand of sector j, is the carbon flow implied by sector i satisfying the final demand of sector j, The implicit flow of land resources required by sector i to meet the final demand of sector j; Represents the synergy between energy and land, Represents the degree of coordination between energy and carbon emissions, represents the degree of coordination between land and carbon emissions, Represents the comprehensive coordination between energy, land, and carbon emissions;

[0041] The calculation formula for the total carbon emissions ac is as follows:

[0042] a c =C E +C C -C S

[0043] Where C E is the carbon emissions caused by energy consumption, C C is the carbon emissions caused by land use, C S is the amount of carbon absorbed by natural land.

[0044] Furthermore, the energy-soil-carbon ecological network of urban agglomerations is constructed as follows:

[0045]

[0046] Where, f gh is the flow of urban energy, land, and carbon from node g to node h; z g is the input of the external environment to the node g in the network; y g is the output of node g in the network to the external environment; T g is the total metabolic rate of node g;

[0047] The control matrix is ​​defined by the system integral flow, and the control matrix is ​​used to reflect the impact of one department on another department in the overall system structure. The ecological network flow analysis method is used to calculate the system integral flow matrix:

[0048] N=(n gh )=G 0 +G 1 +G 2 +G 3 …G m +…=(IG) -1

[0049]

[0050] N′=(n′ gh ) = G′ 0 +G′ 1 +G′ 2 +G′ 3 …G′ m +…=(IG′) -1

[0051]

[0052] Where N is the output-oriented dimension-integral flow matrix; N′ is the input-oriented dimension-integral flow matrix; G 0 , G′ 0 It is a self-feedback matrix, reflecting the traffic of each node; G 1 , G′ 1 is the direct flow matrix, which represents the carbon flow transmitted between nodes; G m , G′ m is the indirect flow with node path length;

[0053] The control and dependency levels are formulated based on the control allocation coefficient CA and the dependency allocation coefficient DA based on the regional control matrix;

[0054]

[0055] Where CA is the control distribution coefficient, ca gh It represents the relative control relationship between the department at the production end and the department at the consumption end. DA is the control allocation coefficient, da gh It indicates the relative dependence of the department on the production side on the department on the consumption side;

[0056] The controlled energy, land and carbon flows are:

[0057]

[0058] Where, is the cross-border controlled energy flow triggered by final consumption in regions R1-Rm; are cross-border controlled land flows triggered by final consumption in regions R1-Rm; It is a cross-border controlled carbon flow triggered by final consumption in regions R1-Rm.

[0059] Furthermore, the calculation formula of the intermediate model is:

[0060]

[0061] Where, T = LA = AL = A + A 2 +A 3 ..., T is the complete consumption coefficient matrix, b q (l1, l2) is the total weight of the entire supply chain through industry q; where the number of upstream industries in the supply chain is l1, and the number of downstream industries is l2; f is the direct resource consumption coefficient; J is an n×n matrix with the (q, q) element being 1 and the rest being 0; Y is the final demand;

[0062] Obtain data on the energy-soil-carbon intermediary of urban agglomerations through the intermediate model: energy consumption data in the middle of industry Q Land use data and carbon emissions data

[0063] Compared with the existing technology, this technical solution has at least the following beneficial effects:

[0064] (1) This technical solution analyzes the mutual influence mechanism between land resources and energy resources carbon emissions, clarifies the interaction mechanism between multiple factors, and can effectively analyze the synergistic regulation effect of land, energy, and carbon from the perspective of the urban agglomeration complex system;

[0065] (2) This technical solution constructs the energy-soil-carbon ecological network of urban agglomerations and applies complex network analysis technology to deeply study the structure and characteristics of metabolic networks, clarify the key transmission nodes in the energy-soil-carbon ecological network of urban agglomerations, and help achieve efficient resource utilization and sustainable environmental development;

[0066] (3) This technical solution is based on the energy-soil-carbon synergy analysis in the context of urban agglomerations, and can meet the energy-soil-carbon synergy analysis needs of urban agglomerations with different development conditions and sizes. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the services required for use in the embodiments or the prior art descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0068] Figure 1 This is a principle flow chart of a method for analyzing the energy-soil-carbon synergistic relationship of urban agglomerations from a cross-regional perspective. DETAILED DESCRIPTION

[0069] The present invention will be further described below in conjunction with specific embodiments:

[0070] like Figure 1 As shown, the method for analyzing the energy-soil-carbon synergistic relationship of urban agglomerations from a cross-regional perspective described in this embodiment includes the following steps:

[0071] S1. Calculate the direct energy-soil-carbon flows of urban agglomerations;

[0072] This implementation calculates direct carbon emissions caused by energy consumption and land use changes, as well as carbon metabolism in natural land, including the carbon absorption process generated by natural land.

[0073] The first part is to collect energy consumption data of each city and each department in each city to obtain the total energy consumption.

[0074] The second part is to collect land use data, which includes eight land use types: cultivated land, forest land, grassland, water area, urban land, rural land, transportation and mining land, and unused land. Statistical analysis is performed using ArcGIS software. Its general form is as follows:

[0075]

[0076] Where S represents the area; n is the land use type before and after the transfer; u and v represent the land use type before and after the transfer respectively; S uv Represents the area where the land type before the transfer is u and the land type after the transfer is v.

[0077] In the third part, the carbon emissions caused by energy consumption are calculated by multiplying the consumption of 17 primary fossil energy sources such as coal, coke, crude oil, fuel oil, gasoline, kerosene, diesel and natural gas by the emission factor. The calculation formula is:

[0078] C E =∑ i ∑ h C i，h =∑ i ∑ j e i，h ×NCV h ×CC h ×O i，h

[0079] Where C E Energy carbon emissions caused by energy consumption; C i，h NCV is the carbon emission of energy type h in sector i; h is the calorific value of h energy variety; CC h is the unit calorific value emission of h energy types; O i，h is the oxidation efficiency of energy type h in sector i.

[0080] The fourth part is to calculate the carbon emissions from land use. The calculation formula is as follows:

[0081] C C =C E +C ER +C EF

[0082] C ER =k ER ×p i

[0083]

[0084] Where C C is the carbon emissions caused by land use; C ER Carbon emissions from human breathing and livestock farming; C EF is the carbon emission rate of farmland; k ER is the emission coefficient; p i The number of biological individuals involved in this activity is divided into urban population, rural population, and the number of medium and large livestock raised in the livestock breeding industry; are the carbon emission rates of fertilizer application, mechanical tillage and farmland irrigation respectively; F is the amount of fertilizer application; M is the total mechanical power; S1 is the irrigation area; k1, k2 and k3 are all conversion coefficients.

[0085] Part 5: Calculate the carbon absorption C of natural land S , the calculation formula is as follows:

[0086] C S =∑K×S

[0087] Where S is the land use type area; K is the carbon sink coefficient.

[0088] S2. Calculate the implicit energy-soil-carbon flow in urban agglomerations. The calculation process is as follows:

[0089] The energy, land resources and carbon emission intensities of each sector in each region are as follows:

[0090]

[0091] Where, X j represents the total investment amount of department j; e i is the energy intensity consumed per unit of economic output of sector i; c i is the carbon dioxide intensity per unit of economic output of sector i; is the direct land use matrix of unit economic output of sector i in land use type k; is the area occupied by land use type k in sector i; E i is the total energy consumption of sector i, C i is the carbon emissions of sector i;

[0092] Based on the final demand of each city in the inter-city input-output table, the implicit flow of energy, carbon, and land resources is calculated to explore the relationship between cities in the urban agglomeration and identify the main contributing cities, sectors, and links in the energy-land-carbon supply chain of the urban agglomeration. The calculation formula is:

[0093]

[0094]

[0095]

[0096] Where, is the implicit energy flow required for sector i to meet the final demand of sector j, is the carbon flow implied by sector i satisfying the final demand of sector j, is the implicit land resource flow required for sector i to meet the final demand of sector j, I is the n×n unit matrix, (IA) -1is the inverse Leontief matrix, Y S is the final demand matrix.

[0097] S3. Use the cosine similarity method to evaluate the coordinated control of energy, land use, and carbon emissions. The formula for calculating the energy-land-carbon synergy of urban agglomerations is:

[0098]

[0099]

[0100]

[0101]

[0102] Where a e is the total energy consumption; a l is the total area of ​​land that has changed its land use type; a c is the total carbon emissions; is the implicit energy flow required for sector i to meet the final demand of sector j, is the carbon flow implied by sector i satisfying the final demand of sector j, The implicit flow of land resources required by sector i to meet the final demand of sector j; Represents the synergy between energy and land, Represents the degree of coordination between energy and carbon emissions, represents the degree of coordination between land and carbon emissions, Represents the comprehensive coordination between energy, land, and carbon emissions;

[0103] Total carbon emissionsa c The calculation formula is as follows:

[0104] a c =C E +C C -C S

[0105] Where C E is the carbon emissions caused by energy consumption, C C is the carbon emissions caused by land use, C S is the amount of carbon absorbed by natural land.

[0106] S4. Using each region and department of the urban agglomeration as nodes and the implicit flows between regions and departments as paths, construct an urban agglomeration energy-soil-carbon ecological network. This urban agglomeration energy-soil-carbon ecological network is then used to analyze and determine the control and dependency relationships between energy, soil, and carbon in the urban agglomeration.

[0107] Specifically, the energy-soil-carbon ecological network of the urban agglomeration is constructed as follows:

[0108]

[0109]

[0110]

[0111] Where, f gh is the flow of urban energy, land, and carbon from node g to node h; z g is the input of the external environment to the node g in the network; y g is the output of node g in the network to the external environment; T g is the total metabolic rate of node g;

[0112] The control matrix is ​​defined by the system integral flow, and the control matrix is ​​used to reflect the overall structure of the system.

[0113] The impact of one department on another is analyzed using the ecological network flow analysis method to calculate the system integral flow matrix:

[0114] N=(n gh )=G 0 +G 1 +G 2 +G 3 …G m +…=(IG) -1

[0115]

[0116] N′=(n′ gh ) = G′ 0 +G′ 1 +G′ 2 +G′ 3 …G′ m +…=(IG′) -1

[0117]

[0118] Where N is the output-oriented dimension-integral flow matrix; N′ is the input-oriented dimension-integral flow matrix; G 0 , G′ 0 It is a self-feedback matrix, reflecting the traffic of each node; G 1 , G′ 1 is the direct flow matrix, which represents the carbon flow transmitted between nodes; G m , G′ m is the indirect flow with a node path length of m;

[0119] The control and dependency levels are formulated based on the control allocation coefficient CA and the dependency allocation coefficient DA based on the regional control matrix;

[0120]

[0121] In the formula, CA is the control allocation coefficient, cagh represents the relative control relationship of department g on the production side to department h on the consumption side, DA is the control allocation coefficient, dagh represents the relative dependence relationship of department g on the production side to department h on the consumption side;

[0122] The controlled energy, land and carbon flows are:

[0123]

[0124] Where, is the cross-border controlled energy flow triggered by final consumption in regions R1-Rm;

[0125] are cross-border controlled land flows triggered by final consumption in regions R1-Rm; It is a cross-border controlled carbon flow triggered by final consumption in regions R1-Rm.

[0126] S5. Use the intermediate model to obtain data on the energy-soil-carbon intermediary of urban agglomerations;

[0127] Specifically, the calculation formula of the intermediate model is:

[0128]

[0129] Where, T = LA = AL = A + A 2 +A 3 ..., T is the complete consumption coefficient matrix, b q (l1, l2) is the total weight of the entire supply chain through industry q; where the number of upstream industries in the supply chain is l1, and the number of downstream industries is l2; f is the direct resource consumption coefficient; J is an n×n matrix with the (q, q) element being 1 and the rest being 0; Y is the final demand;

[0130] Obtain data on the energy-soil-carbon intermediary of urban agglomerations through the intermediate model: energy consumption data in the middle of industry Q Land use data and carbon emissions data

[0131] S6. By analyzing and judging the control and dependence relationships of energy, soil and carbon in urban agglomerations, we can identify the interaction relationships between nodes in the energy-soil-carbon ecological network in urban agglomerations and the key paths and nodes that affect the changes in carbon emissions in urban agglomerations. We can analyze the synergistic characteristics of the energy-soil-carbon ecological network from multiple perspectives, including the production, consumption and intermediary ends. We can also analyze the synergy relationships between various regions and departments in urban agglomerations from the energy-soil-carbon synergy obtained in urban agglomerations.

[0132] The embodiments described above are only preferred embodiments of the present invention and are not intended to limit the scope of implementation of the present invention. Therefore, any changes made based on the shape and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A cross-regional analysis method for the energy-soil-carbon synergy relationship of urban agglomerations, characterized by: include: Calculate direct energy-soil-carbon flows in urban agglomerations; The direct energy-land-carbon flow of urban agglomerations refers to the direct carbon emissions caused by energy consumption and land use changes in various regions and sectors within the urban agglomeration, as well as the carbon absorption caused by natural land use; Calculate the implicit energy-land-carbon flows within urban agglomerations, including the implicit flows between regions and sectors. The implicit energy-land-carbon flows within urban agglomerations refer to the flows of implicit energy, land resources, and carbon emissions driven by final demand across regions and sectors within an urban agglomeration through cross-regional supply chains. The energy-soil-carbon synergy of urban agglomerations is calculated by combining the calculated direct energy-soil-carbon flow and the implicit energy-soil-carbon flow of urban agglomerations. Using each region and department of the urban agglomeration as nodes and the implicit flows between regions and departments as paths, we constructed an urban agglomeration energy-soil-carbon ecological network. This urban agglomeration energy-soil-carbon ecological network was then used to analyze and determine the control and dependency relationships between energy, soil, and carbon in the urban agglomeration. Use the intermediate model to obtain data on the energy-soil-carbon intermediary of urban agglomerations; By analyzing and judging the control and dependence relationships of energy, soil, and carbon in urban agglomerations, we identify the interactions between nodes in the energy, soil, and carbon ecological network within urban agglomerations, as well as the key paths and nodes that influence changes in carbon emissions within urban agglomerations. We analyze the synergistic characteristics of the energy, soil, and carbon ecological network from multiple perspectives, including production, consumption, and intermediary data. Furthermore, we analyze the synergy between various regions and sectors within urban agglomerations based on the energy, soil, and carbon synergy obtained. The constructed urban agglomeration energy-soil-carbon ecological network is as follows: Where, f gp is the flow of urban energy, land, and carbon from node g to node p; z g is the input of the external environment to the node g in the network; y g is the output of node g in the network to the external environment; T g is the total metabolic rate of node g; The control matrix is ​​defined by the system integral flow, and the control matrix is ​​used to reflect the impact of one department on another department in the overall system structure. The ecological network flow analysis method is used to calculate the system integral flow matrix: N=(n gp )=G 0 +G 1 +G 2 +G 3 …G m +…=(I-G) -1 N'=(n' gp )=G' 0 +G' 1 +G' 2 +G' 3 …G' m +…=(I-G') -1 Where N is the output-oriented dimension-integral flow matrix; N' is the input-oriented dimension-integral flow matrix; G 0 , G' 0 It is a self-feedback matrix, reflecting the traffic of each node; G 1 , G' 1 is the direct flow matrix, which represents the carbon flow transmitted between nodes; G m , G' m is the indirect flow with a node path length of m; The control and dependency levels are formulated based on the control allocation coefficient CA and the dependency allocation coefficient DA based on the regional control matrix; Where CA is the control distribution coefficient, ca gp It represents the relative control relationship between node g at the production end and node p at the consumption end. DA is the control allocation coefficient, da gp Indicates the relative dependency of node g on the production side on node p on the consumption side; The controlled energy, land and carbon flows are: Where, is the cross-border controlled energy flow triggered by final consumption in regions R1-Rm; are cross-border controlled land flows triggered by final consumption in regions R1-Rm; It is a cross-border controlled carbon flow triggered by final consumption in regions R1-Rm.

2. The method for analyzing the energy-soil-carbon synergy relationship of urban agglomerations from a cross-regional perspective according to claim 1 is characterized by: Calculation of direct energy-soil-carbon flows in urban agglomerations includes: Collect energy consumption data from various departments in each city to obtain the total energy consumption; Land use data were collected, including land use types such as cultivated land, forest land, grassland, water area, urban land, rural land, transportation and mining land, and unused land. Statistical analysis was performed using ArcGIS software. The statistical analysis formula is as follows: Where S represents the area; n is the number of land use types before and after the transfer; u and v represent the land use types before and after the transfer, respectively; S uv It represents the area of ​​land type u before transfer and land type v after transfer; Energy carbon emissions caused by energy consumption are calculated by multiplying the consumption of fossil energy, including coal, coke, crude oil, fuel oil, gasoline, kerosene, diesel and natural gas, by the emission factor. The calculation formula is: C E =∑ i ∑ h C i,h =∑ i ∑ j e i,h ×NCV h ×CC h ×O i,h Where C E Energy carbon emissions caused by energy consumption; C i,h NCV is the carbon emission of energy type h in sector i; h is the calorific value of h energy variety; CC h is the unit calorific value emission of h energy types; O i,h is the oxidation efficiency of energy type h in sector i; The calculation formula for carbon emissions caused by land use is as follows: C C =C E +C ER +C EF C ER =k ER ×p i Where C C is the carbon emissions caused by land use; C ER Carbon emissions from human breathing and livestock farming; C EF is the carbon emission rate of farmland; k ER is the emission coefficient; p i The number of biological individuals engaged in activities is divided into urban population, rural population, and the number of large and medium-sized livestock raised in the livestock breeding industry; are the carbon emission rates of fertilizer application, mechanical tillage, and farmland irrigation, respectively; F is the amount of fertilizer applied; M is the total mechanical power; S1 is the irrigated area; k1, k2, and k3 are the corresponding conversion coefficients, respectively; Calculate the carbon absorption C of natural land S , the calculation formula is as follows: C S =∑K×S Where S is the land use type area; K is the carbon sink coefficient.

3. The method for analyzing the energy-soil-carbon synergy relationship of urban agglomerations from a cross-regional perspective according to claim 2 is characterized by: Calculate the implicit energy-soil-carbon flows of urban agglomerations, including: The energy, land resources and carbon emission intensities of each sector in each region are as follows: Where, X j represents the total investment amount of department j; e i is the energy intensity consumed per unit of economic output of sector i; c i is the carbon dioxide intensity per unit of economic output of sector i; is the direct land use matrix of unit economic output of sector i in land use type k; is the area occupied by land use type k in sector i; E i is the total energy consumption of sector i, C i is the carbon emissions of sector i; Based on the final demand of each city in the inter-city input-output table, the implicit flow of energy, carbon, and land resources is calculated to explore the relationship between cities in the urban agglomeration and identify the main contributing cities, sectors, and links in the energy-land-carbon supply chain of the urban agglomeration. The calculation formula is: Where, is the implicit energy flow required for sector i to meet the final demand of sector j, is the carbon flow implied by sector i satisfying the final demand of sector j, is the implicit land resource flow required for sector i to meet the final demand of sector j, I is the n×n unit matrix, (IA) -1 is the inverse Leontief matrix, Y S is the final demand matrix.

4. The method for analyzing the energy-soil-carbon synergy relationship of urban agglomerations from a cross-regional perspective according to claim 3 is characterized by: The formula for calculating the energy-soil-carbon synergy of urban agglomerations is: Where a e is the total energy consumption; a l is the total area of ​​land that has changed its land use type; a c is the total carbon emissions; is the implicit energy flow required for sector i to meet the final demand of sector j, is the carbon flow implied by sector i satisfying the final demand of sector j, The implicit flow of land resources required by sector i to meet the final demand of sector j; Represents the synergy between energy and land, Represents the degree of coordination between energy and carbon emissions, represents the degree of coordination between land and carbon emissions, Represents the comprehensive coordination between energy, land, and carbon emissions; Total carbon emissionsa c The calculation formula is as follows: a c =C E +C C -C S Where C E is the carbon emissions caused by energy consumption, C C is the carbon emissions caused by land use, C S is the amount of carbon absorbed by natural land.

5. The method for analyzing the energy-soil-carbon synergy relationship of urban agglomerations from a cross-regional perspective according to claim 1 is characterized in that: The calculation formula of the intermediate model is: Where, T = LA = AL = A + A 2 +A 3 …, T is the complete consumption coefficient matrix, b q (l1,l2) is the total weight of the entire supply chain through industry q; where the number of upstream industries in the supply chain is l1, and the number of downstream industries is l2; f is the direct resource consumption coefficient; J is an n×n matrix with the (q,q) element being 1 and the rest being 0; Y is the final demand; Obtain data on the energy-soil-carbon intermediary of urban agglomerations through the intermediate model: energy consumption data in the middle of industry Q Land use data and carbon emissions data

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