Method and system for evaluating full-life-cycle cross-medium influence of carbon emission

Abstract

The invention discloses a pollution carbon emission full life cycle cross-medium influence assessment method and system, and particularly relates to the technical field of environment management. According to the evaluation target, determining a spatialized full-life-cycle carbon emission data list; obtaining a spatialization pollution carbon emission cross-medium influence factor data set based on the spatialization model of the pollution carbon emission full life cycle cross-medium influence factors; and according to the spatialization full-life-cycle dirt carbon emission data list and the spatialization dirt carbon emission cross-medium influence factor data set with the same resolution, obtaining a spatialization dirt carbon emission full-life-cycle cross-medium influence data set. By adopting the technical scheme of the invention, the problem that the existing influence assessment method is insufficient to be compatible with spatial multiple scales is solved, and the method is widely applied to the field of environmental influence assessment of atmospheric pollutants and carbon emission.

Description

Technical Field

[0001] The present invention relates to the field of environmental management technology, and in particular to a method and system for assessing the cross-media impact of carbon emissions over the entire life cycle. Background Art

[0002] Since the Industrial Revolution, intensive human activities have increasingly interfered with the earth system, and environmental problems such as environmental pollution and ecological damage have become prominent. Carrying out carbon emission accounting is a basic work to deal with environmental problems. Generally speaking, carbon emission accounting focuses on a series of quantitative indicators, such as atmospheric pollutants (sulfur dioxide, nitrogen oxides and volatile organic compounds, etc.), water pollutants (chemical oxygen demand, five-day biochemical oxygen demand and ammonia nitrogen, etc.) and solid waste emissions. The degree of interference of human activities on the earth system is identified by calculating the environmental emissions of pollutants and carbon, but the cross-media environmental impact caused by carbon emissions is not associated. Cross-media environmental impact refers to the interactive impact caused by environmental problems in different media such as the atmosphere, water and soil. For example, the precipitation of heavy metals produced during coal combustion will bring risks to the ecosystem and human health, and the excessive application of nitrogen fertilizers and phosphate fertilizers in farmland will cause eutrophication of water bodies. Therefore, strengthening cross-media impact assessment and coordinated governance is of great significance to improving regional environmental quality. At present, the cross-media impact assessment of carbon emissions is based on the perspective of the entire life cycle to avoid the transfer of environmental problems between different stages of the life cycle.

[0003] The cross-media environmental impact caused by carbon emissions focuses on identifying the actual interference mechanism of environmental emissions on the earth system, such as climate change, photochemical smog, acidification, eutrophication and toxicity. Since spatialized environmental characteristic data are difficult to obtain, traditional cross-media impact assessment methods develop cross-media impact factors at the global or national scale at the average level. However, the environmental impact potential caused by the same environmental emission level in different geographical regions varies greatly. This practice leads to insufficient geographical representativeness and spatial resolution of cross-media impact assessment of carbon emissions. In addition, different impact assessment methods may produce completely different results. The cross-media impact factors and assessment methods of carbon emissions in countries or regions with different environmental characteristics cannot provide scientific support for sustainable development and clean production decisions in other countries or regions around the world (especially developing countries with intensive carbon emissions). It can be seen that the existing impact assessment methods are actually not enough to be compatible with the cross-media impact assessment of carbon emissions at multiple spatial scales, and their applicability is greatly reduced. A comprehensive, accurate and high-spatial-resolution cross-media impact assessment method and system for the entire life cycle of carbon emissions is needed. Summary of the invention

[0004] The present invention aims to provide a method and system for cross-media impact assessment of carbon emissions over the entire life cycle, which solves the problem that existing impact assessment methods are not sufficient to be compatible with cross-media impact assessment of carbon emissions at multiple spatial scales.

[0005] In order to achieve the above-mentioned purpose, the present invention provides a technical solution as follows: a method for assessing the cross-media impact of carbon emissions throughout their life cycle, comprising the following steps:

[0006] S1. According to the accounting object, determine the spatial resolution requirements of the assessment and obtain a spatialized full life cycle carbon emission data list that meets the quality assessment requirements;

[0007] S2. Based on the spatialization model of the universal cross-media impact factor of carbon pollution emissions, the spatialized cross-media impact factor data of carbon pollution emissions is obtained according to the spatialized environmental characteristic data or the sensitive factor data that significantly affects the cross-media impact factor of carbon pollution emissions;

[0008] S3. Based on the universal spatialized model of cross-media impact of carbon emissions, the spatialized cross-media impact dataset of carbon emissions is obtained according to the spatialized full life cycle carbon emissions data inventory and the spatialized cross-media impact factor dataset of carbon emissions with the same spatial resolution.

[0009] Furthermore, the method of step S1 is as follows:

[0010] S1.1. According to the accounting object, determine the spatial resolution requirements for the assessment, determine the real-life data source, and collect the initial spatial full-life cycle pollution carbon emission real-life data inventory;

[0011] S1.2. Check and evaluate the data quality of the initial spatialized full-life cycle carbon emission real-life data inventory. If it does not meet the pre-set quality evaluation requirements, proceed to S1.1 to re-determine the real-life data source. Otherwise, proceed to S1.3.

[0012] S1.3. Extract the background data set from the international mainstream database corresponding to the spatialized full life cycle pollution carbon emission real-life data inventory, and check and evaluate the data quality of the background data set. If it does not meet the pre-set quality evaluation requirements, proceed to S1.4 and re-collect the background data. Otherwise, proceed to S1.6.

[0013] S1.4. According to the accounting object, determine the spatial resolution requirements for the assessment, determine the background data source, and collect the initial spatial full life cycle pollution carbon emission background data inventory;

[0014] S1.5. Check and evaluate the data quality of the initial spatialized full-life cycle carbon emission background data inventory. If it does not meet the pre-set quality evaluation requirements, proceed to S1.4 and re-determine the background data source. Otherwise, proceed to S1.6.

[0015] S1.6. Integrate the spatialized full life cycle carbon pollution emission real-life data list and background data list that meet the pre-set quality assessment requirements to obtain the spatialized full life cycle carbon pollution emission data list.

[0016] Furthermore, the calculation formula of the spatialized full life cycle carbon emission data inventory is as follows:

[0017]

[0018] Where M i,j,k A is the total carbon emission of the kth carbon emission flow in the ith location or region over its entire life cycle; i,1,k , A i,2,k …A i,n,k For the carbon emissions of the 1st, 2nd, ... nth life cycle stages of the kth carbon emission flow in the ith location or region, when the spatial resolution required for accounting is high, the integrated spatialized full life cycle carbon emission data inventory is calculated at the micro scale through on-site investigation, satellite remote sensing observation data inversion or data collection by online monitoring equipment of pollution sources; when the spatial resolution required for accounting is low, the integrated spatialized full life cycle carbon emission data inventory is calculated at the macro and meso scales through investigation of the National Bureau of Statistics, provincial and municipal air pollutant and carbon emission inventories or environmental impact assessment report data.

[0019] Furthermore, the modeling method of the spatial model based on the universal cross-media impact factor of carbon pollution emissions is as follows:

[0020] S2.1. Modeling based on site scale: When the required spatial resolution is high and the spatialized environmental characteristic data is sufficient, the site scale modeling of the fate factors, exposure factors and exposure response factors of the cross-media impact factors of carbon emissions is carried out to calculate the site scale spatialized cross-media impact factor dataset of carbon emissions;

[0021] The site-scale modeling approach is:

[0022] EP i,j,k =GP i,j,k OP i,j,k ·OR i,j,k

[0023] Among them, EP i,j,k , GP i,j,k OP i,j,k OR i,j,kThey are the cross-media impact factor, fate factor, exposure factor and exposure response factor of the kth carbon emission flow at the jth location in the ith region. Usually, the fate factor is a mathematical function of the carbon emission flow characteristics, source characteristics and sink characteristics, the exposure factor is a mathematical function of the carbon emission flow characteristics, sink characteristics and receptor characteristics, and the exposure response factor is a mathematical function of the carbon emission flow characteristics and receptor characteristics:

[0024] GP i,j,k =f(cbp k ,sfp i,j ,scp i,j )

[0025] OP i,j,k =f(cbp k ,scp i,j ,rcp i,j )

[0026] OR i,j,k =f(cbp k ,rcp i,j )

[0027] Among them, cbp k is the characteristic parameter of the kth carbon emission flow, sfp i,j 、scp i,j and rcp i,j They are the source characteristic parameters, sink characteristic parameters and receptor characteristic parameters of the jth location in the ith region, respectively. Usually, the fate factor data is used to associate the source and sink of carbon emissions, and the residence time of the emission substances is used to represent their instantaneous diffusion state, which is calculated based on the location and height of the gas emission source and the terrain parameters and meteorological parameters of the diffusion process of the gas emission substances; the exposure factor data is used to associate the sink and receptor of carbon emissions, and is calculated based on the spatialized receptor characteristic parameters through the duration and concentration of the emission substances exposed to the receptors; the exposure response factor data is used to identify the sensitivity of the receptor to carbon emissions, and is calculated based on the spatialized receptor characteristic parameters through the environmental impact of the emission substances on the receptors after exposure to the receptors;

[0028] S2.2, Modeling based on regional scale: When the required spatial resolution is low or the spatialized environmental characteristic data is insufficient, modeling based on regional scale is carried out by accurately identifying and spatializing the sensitive factors that significantly affect the cross-media impact factors of carbon emissions, and calculating the regional scale spatialized cross-media impact factor dataset of carbon emissions driven by proxy data;

[0029] The regional scale modeling method is as follows:

[0030] AP i,k =EP kAE i,k

[0031]

[0032] Among them, AP i,k The cross-media impact factor of carbon emissions of the kth carbon emission flow in the ith region driven by proxy data; EP k is the universal cross-media impact factor of carbon emission for the kth carbon emission flow; AE i,k KE is the sensitivity factor of the cross-media impact factor of the carbon emission of the kth carbon emission flow in the ith region; i,k KE is the key parameter of the cross-media influencing factor of the carbon emission of the kth carbon emission flow in the ith region; k It is the universal key parameter of the cross-media influencing factor of carbon emissions of the kth carbon emission flow.

[0033] Furthermore, the method of step S3 is as follows:

[0034] S3.1. When the required spatial resolution is high and the spatialized environmental characteristic data are sufficient, the spatialized carbon emission cross-media impact data set at the site scale is calculated based on the spatialized full life cycle carbon emission data inventory and the site-scale spatialized carbon emission cross-media impact factor data set at the same spatial resolution;

[0035] S3.2. When the required spatial resolution is low or the spatialized environmental characteristic data are insufficient, the regional scale spatialized carbon emission cross-media impact data set driven by proxy data is calculated based on the spatialized full life cycle carbon emission data inventory and the regional scale spatialized carbon emission cross-media impact factor data set at the same spatial resolution.

[0036] The calculation method for the cross-media impact of spatial pollution carbon emissions at the site scale is:

[0037] CM a =∑ k ∑ j ∑ i bp i,j,k,a ·EP i,j,k

[0038] Among them, CM a is the cross-media impact of carbon emissions per unit of final product at the ath site, bp i,j,k,a is the carbon emission flow intensity of the kth location in the i-th region related to the final product of the a-th site,

[0039] The calculation method of the cross-media impact of regional-scale spatial pollution carbon emissions driven by the proxy data is:

[0040] CMb =∑ k ∑ i bp i,k,b ·AP i,k

[0041] Among them, CM b is the cross-media impact of carbon emissions from the final product of the b-th regional unit, bp i,k,b is the carbon emission flow intensity of the kth region in the ith region related to the final product of the bth region.

[0042] Another technical solution provided by the present invention is a system for assessing the cross-media impact of carbon emissions throughout their entire life cycle, comprising:

[0043] Spatialized full life cycle carbon emission module: used to identify the real-life industrial chain and the background industrial chain corresponding to the real-life industrial chain according to the accounting object and spatial resolution requirements, determine the real-life data source and the background data source, and obtain a spatialized full life cycle carbon emission data list that meets the quality assessment requirements;

[0044] Site-scale calculation module: Based on the spatialized environmental characteristic data, the site-scale spatialized carbon emission cross-media impact factor dataset is obtained;

[0045] Regional scale calculation module: Based on the sensitive factor data that significantly affects the cross-media impact factors of carbon emissions, a regional scale spatialized cross-media impact factor dataset of carbon emissions driven by proxy data is obtained;

[0046] Spatialized carbon pollution emission cross-media impact module: Based on the spatialized full life cycle carbon pollution emission data inventory and the spatialized carbon pollution emission cross-media impact factor data set with the same spatial resolution, a spatialized carbon pollution emission cross-media impact data set is obtained.

[0047] Furthermore, the spatialized full life cycle carbon emission module includes:

[0048] Real-life pollution carbon emission data source definition module: used to define the geographical boundaries of the real-life industrial chain according to the accounting object, identify the spatial characteristics of each unit process, match the spatial resolution of the accounting, and then determine the real-life pollution carbon emission data source;

[0049] Real scene pollution carbon emission data collection module: used to collect and form an initial spatial real scene pollution carbon emission data set according to the determined real scene pollution carbon emission data source;

[0050] Real-life pollution carbon emission data processing module: used to check and evaluate the quality of the initial spatialized real-life pollution carbon emission data set, convert the data into a unified format, and obtain a spatialized real-life pollution carbon emission data set that meets the pre-set quality evaluation requirements;

[0051] Background carbon emission data storage and management module: used to structure the spatialized carbon emission data over the entire life cycle and store it in the database;

[0052] Background carbon emission data extraction module: used to extract the carbon emission data set of the background industrial chain corresponding to the real-life industrial chain, and obtain a spatialized background carbon emission data set that meets the pre-set quality assessment requirements;

[0053] Background carbon emission data source definition module: used to define the geographical boundaries of the background industrial chain according to the accounting object, identify the spatial characteristics of each unit process, match the spatial resolution of the accounting, and then redefine the background carbon emission data source when the spatialized background carbon emission data set extracted by the background carbon emission data extraction module does not meet the pre-set quality assessment requirements;

[0054] Background carbon emission data collection module: used to collect and form an initial spatial background carbon emission data set based on the re-determined background carbon emission data source;

[0055] Background pollution carbon emission data processing module: used to check and evaluate the quality of the initial spatial background pollution carbon emission data set, convert the data into a unified format, and obtain a spatial background pollution carbon emission data set that meets the pre-set quality evaluation requirements;

[0056] Spatialized full life cycle carbon emission data calculation and integration module: Integrate the spatialized real-life carbon emission data set and the spatialized background carbon emission data set that meet the pre-set quality assessment requirements to form a spatialized full life cycle carbon emission data list;

[0057] Data verification module: used to verify the spatialized full life cycle carbon emission data inventory and form a data verification report;

[0058] Data publishing module: used to publish the spatialized full life cycle carbon emission data list that has passed data verification, and send it to the background carbon emission data storage and management module for storage;

[0059] Data update module: used to drive the real-scene carbon emission data source definition module and the background carbon emission data source definition module according to data update requirements, and identify the updated spatialized full life cycle carbon emission data.

[0060] Furthermore, the site scale calculation module includes:

[0061] Spatial calculation module of fate factor data: used to associate the sources and sinks of carbon emissions, express the instantaneous diffusion state of the emission substances by their residence time, and calculate the spatial fate factor data based on the location and height of the gas emission source and the geographic information data of the diffusion process of the gas emission substances;

[0062] Spatialized exposure factor data calculation module: used to associate the sinks and receptors of carbon emissions, calculate the spatialized exposure factor data based on the duration and concentration of the emission substances exposed to the receptors and the spatialized receptor characteristic parameters;

[0063] Spatialized exposure response factor data calculation module: used to identify the sensitivity of receptors to emission substances, and calculate the spatialized exposure response factor data based on the spatialized receptor characteristic parameters through the environmental impact of the emission substances on the receptors after exposure to the receptors;

[0064] Spatial calculation and integration module of cross-media impact factor data of carbon emissions: used for the spatial cross-media impact factor model of carbon emissions based on the site scale, integrating spatialized fate factor data, exposure factor data and exposure response factor data, and calculating and integrating the spatial cross-media impact factor data of carbon emissions based on the site scale;

[0065] Data verification module: used to verify the data of cross-media influencing factors of spatial carbon emissions and form a data verification report;

[0066] Data publishing module: used to publish data-verified spatial carbon emission cross-media impact factor data;

[0067] Furthermore, the regional scale calculation module includes:

[0068] Sensitive factor data identification module: used to identify the spatial characteristics of several sensitive factors that significantly affect the cross-media influencing factors of carbon pollution emissions when it is difficult to obtain sufficient spatial receptor characteristic parameters;

[0069] Sensitive factor data spatial calculation module: based on the sensitive factors and their spatial characteristics, the spatial sensitive factor data is calculated;

[0070] Spatial calculation and integration module of cross-media impact factor data of carbon pollution emissions: It is used to integrate spatial sensitive factor data based on regional scale spatial cross-media impact factor model of carbon pollution emissions, calculate and integrate spatial sensitive factors as proxy data-driven regional scale spatial cross-media impact factor data of carbon pollution emissions;

[0071] Data verification module: used to verify the data of cross-media influencing factors of spatial carbon emissions and form a data verification report;

[0072] Data publishing module: used to publish data on cross-media impact factors of spatialized carbon emissions that have been verified.

[0073] Furthermore, the spatialized carbon emission cross-media impact module includes:

[0074] Spatial calculation integration module for cross-media impact data of carbon emissions: It is used to integrate the spatialized full-life cycle carbon emissions data inventory and spatialized cross-media impact factor data set of carbon emissions that meet the pre-set quality assessment requirements based on the universal spatialized model of cross-media impact of carbon emissions, and calculate the spatialized cross-media impact data of carbon emissions;

[0075] Data verification module: used to verify the spatialized cross-media impact data of carbon emissions and form a data verification report;

[0076] Data publishing module: used to publish spatialized cross-media impact data of carbon emissions that have been verified.

[0077] Another technical solution provided by the present invention is: a processing device, including computer program instructions, wherein the computer program instructions, when executed by the processing device, are used to implement any of the above-mentioned methods and systems for cross-media impact assessment of carbon emissions throughout their life cycle.

[0078] The present invention provides another technical solution: a computer-readable storage medium, on which computer program instructions are stored, wherein the computer program instructions, when executed by a processor, are used to implement any of the above-mentioned methods and systems for assessing the cross-media impact of carbon emissions throughout their life cycle.

[0079] Compared with the prior art, this solution has the following beneficial effects:

[0080] 1. This scheme is universal in the spatialization of the cross-media impact assessment method for the entire life cycle of carbon emissions. It can not only quantify the cross-media environmental impact caused by carbon emissions in the industrial chain, but also identify the spatial distribution characteristics of the cross-media impact of carbon emissions.

[0081] 2. When the spatial resolution required by the assessment object is high and the spatialized environmental characteristic data is sufficient, the cross-media impact assessment of carbon emissions can be carried out at a microscopic scale to show the differences in environmental impacts between specific sites caused by carbon emissions. The present invention improves the accuracy, precision and comprehensiveness of the cross-media impact assessment of carbon emissions.

[0082] 3. When the spatial resolution required by the assessment object is low or the spatial environmental characteristic data are insufficient, the cross-media impact assessment of carbon emissions needs to accurately identify the sensitive factors that significantly affect the cross-media impact factors of carbon emissions. This method is simple to operate, requires a small amount of data, has a wide range of applications and low calculation complexity, and can quickly realize the spatial assessment of the cross-media impact of carbon emissions throughout their life cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 It is a flow chart of a method for assessing the cross-media impact of carbon emissions throughout the entire life cycle of the present invention. DETAILED DESCRIPTION

[0084] The following is a further description of the method for assessing the cross-media impact of carbon emissions throughout the entire life cycle of the present invention through specific examples. However, the present invention is not limited to the following examples.

[0085] Example 1

[0086] As attached Figure 1 As shown, a method for assessing the cross-media impact of carbon emissions throughout the entire life cycle includes the following steps:

[0087] S1. According to the accounting object, determine the spatial resolution requirements of the assessment and obtain a spatialized full life cycle carbon emission data list that meets the quality assessment requirements;

[0088] The method of step S1 is as follows:

[0089] S1.1. According to the accounting object, determine the spatial resolution requirements for the assessment, determine the real-life data source, and collect the initial spatial full-life cycle pollution carbon emission real-life data inventory;

[0090] S1.2. Check and evaluate the data quality of the initial spatialized full-life cycle carbon emission real-life data inventory. If it does not meet the pre-set quality evaluation requirements, proceed to S1.1 to re-determine the real-life data source. Otherwise, proceed to S1.3.

[0091] S1.3. Extract the background data set from the international mainstream database corresponding to the spatialized full life cycle pollution carbon emission real-life data inventory, and check and evaluate the data quality of the background data set. If it does not meet the pre-set quality evaluation requirements, proceed to S1.4 and re-collect the background data. Otherwise, proceed to S1.6.

[0092] S1.4. According to the accounting object, determine the spatial resolution requirements for the assessment, determine the background data source, and collect the initial spatial full life cycle pollution carbon emission background data inventory;

[0093] S1.5. Check and evaluate the data quality of the initial spatialized full-life cycle carbon emission background data inventory. If it does not meet the pre-set quality evaluation requirements, proceed to S1.4 and re-determine the background data source. Otherwise, proceed to S1.6.

[0094] S1.6. Integrate the spatialized full life cycle carbon pollution emission real-life data list and background data list that meet the pre-set quality assessment requirements to obtain the spatialized full life cycle carbon pollution emission data list.

[0095] S2. Based on the spatialization model of the universal cross-media impact factor of carbon pollution emissions, the spatialized cross-media impact factor data of carbon pollution emissions is obtained according to the spatialized environmental characteristic data or the sensitive factor data that significantly affects the cross-media impact factor of carbon pollution emissions;

[0096] The modeling method based on the spatial model of universal cross-media impact factors of carbon emissions is as follows:

[0097] S2.1. Modeling based on site scale: When the required spatial resolution is high and the spatialized environmental characteristic data is sufficient, the site scale modeling of the fate factors, exposure factors and exposure response factors of the cross-media impact factors of carbon emissions is carried out to calculate the site scale spatialized cross-media impact factor dataset of carbon emissions;

[0098] The modeling method based on site scale is:

[0099] EP i,j,k =GP i,j,k OP i,j,k ·OR i,j,k

[0100] Among them, EP i,j,k , GP i,j,k OP i,j,k OR i,j,k They are the cross-media impact factor, fate factor, exposure factor and exposure response factor of the kth carbon emission flow at the jth location in the ith region. Usually, the fate factor is a mathematical function of the carbon emission flow characteristics, source characteristics and sink characteristics, the exposure factor is a mathematical function of the carbon emission flow characteristics, sink characteristics and receptor characteristics, and the exposure response factor is a mathematical function of the carbon emission flow characteristics and receptor characteristics:

[0101] GP i,j,k =f(cbp k ,sfp i,j ,scp i,j )

[0102] OP i,j,k =f(cbp k ,scp i,j,rcp i,j )

[0103] OR i,j,k =f(cbp k ,rcp i,j )

[0104] Among them, cbp k is the characteristic parameter of the kth carbon emission flow, sfp i,j 、scp i,j and rcp i,j They are the source characteristic parameters, sink characteristic parameters and receptor characteristic parameters of the jth location in the ith region, respectively. Usually, the fate factor data is used to associate the source and sink of carbon emissions, and the residence time of the emission substances is used to represent their instantaneous diffusion state, which is calculated based on the location and height of the gas emission source and the terrain parameters and meteorological parameters of the diffusion process of the gas emission substances; the exposure factor data is used to associate the sink and receptor of carbon emissions, and is calculated based on the spatialized receptor characteristic parameters through the duration and concentration of the emission substances exposed to the receptors; the exposure response factor data is used to identify the sensitivity of the receptor to carbon emissions, and is calculated based on the spatialized receptor characteristic parameters through the environmental impact of the emission substances on the receptors after exposure to the receptors;

[0105] S2.2, Modeling based on regional scale: When the required spatial resolution is low or the spatialized environmental characteristic data is insufficient, modeling based on regional scale is carried out by accurately identifying and spatializing the sensitive factors that significantly affect the cross-media impact factors of carbon emissions, and calculating the regional scale spatialized cross-media impact factor dataset of carbon emissions driven by proxy data;

[0106] The modeling method based on regional scale is as follows:

[0107] AP i,k =EP k AE i,k

[0108]

[0109] Among them, AP i,k The cross-media impact factor of carbon emissions of the kth carbon emission flow in the ith region driven by proxy data; EP k is the universal cross-media impact factor of carbon emission for the kth carbon emission flow; AE i,k KE is the sensitivity factor of the cross-media impact factor of the carbon emission of the kth carbon emission flow in the ith region; i,k KE is the key parameter of the cross-media influencing factor of the carbon emission of the kth carbon emission flow in the ith region; kIt is the universal key parameter of the cross-media influencing factor of carbon emissions of the kth carbon emission flow (the spatial resolution is generally at the national or continental scale).

[0110] S3. Based on the universal spatialized model of cross-media impact of carbon emissions, the spatialized cross-media impact dataset of carbon emissions is obtained according to the spatialized full life cycle carbon emissions data inventory and the spatialized cross-media impact factor dataset of carbon emissions with the same spatial resolution.

[0111] The method of step S3 is as follows:

[0112] S3.1. When the required spatial resolution is high and the spatialized environmental characteristic data are sufficient, the spatialized carbon emission cross-media impact data set at the site scale is calculated based on the spatialized full life cycle carbon emission data inventory and the site-scale spatialized carbon emission cross-media impact factor data set at the same spatial resolution;

[0113] S3.2. When the required spatial resolution is low or the spatialized environmental characteristic data are insufficient, the regional scale spatialized carbon emission cross-media impact data set driven by proxy data is calculated based on the spatialized full life cycle carbon emission data inventory and the regional scale spatialized carbon emission cross-media impact factor data set at the same spatial resolution.

[0114] The calculation method of the cross-media impact of spatial pollution carbon emissions at the site scale is:

[0115] CM a =∑ k ∑ j ∑ i bp i,j,k,a ·EP i,j,k

[0116] Among them, CM a is the cross-media impact of carbon emissions per unit of final product at the ath site, bp i,j,k,a is the carbon emission flow intensity of the kth location in the i-th region related to the final product of the a-th site,

[0117] The calculation method of the cross-media impact of spatialized pollution carbon emissions at the regional scale driven by proxy data is:

[0118] CM b =∑ k ∑ i bp i,k,b ·AP i,k

[0119] Among them, CM b is the cross-media impact of carbon emissions from the final product of the b-th regional unit, bp i,k,bis the carbon emission flow intensity of the kth region in the ith region related to the final product of the bth region.

[0120] In this embodiment, the calculation formula for the spatialized full life cycle carbon emission data inventory is as follows:

[0121]

[0122] Where M i,j,k A is the total carbon emission of the kth carbon emission flow in the ith location or region over its entire life cycle; i,1,k , A i,2,k …A i,n,k For the carbon emissions of the 1st, 2nd, ... nth life cycle stages of the kth carbon emission flow in the ith location or region, when the spatial resolution required for accounting is high, the integrated spatialized full life cycle carbon emission data inventory is calculated at the micro scale of sites, technologies or products through on-site investigations, inversion of satellite remote sensing observation data or data collection by online monitoring equipment of pollution sources; when the spatial resolution required for accounting is low, the integrated spatialized full life cycle carbon emission data inventory is calculated at the macro and meso scales of provinces, cities or industries through investigations of materials such as the National Bureau of Statistics, provincial and municipal air pollutants and carbon emission inventories or environmental impact assessment reports.

[0123] Example 2

[0124] A cross-media impact assessment system for the entire life cycle of carbon emissions, including:

[0125] Spatialized full life cycle carbon emission module: used to identify the real-life industrial chain and the background industrial chain corresponding to the real-life industrial chain according to the accounting object and spatial resolution requirements, determine the real-life data source and the background data source, and obtain a spatialized full life cycle carbon emission data list that meets the quality assessment requirements;

[0126] The spatialized full life cycle carbon emission module includes:

[0127] Real-life pollution carbon emission data source definition module: used to define the geographical boundaries of the real-life industrial chain according to the accounting object, identify the spatial characteristics of each unit process, match the spatial resolution of the accounting, and then determine the real-life pollution carbon emission data source;

[0128] Real scene pollution carbon emission data collection module: used to collect and form an initial spatial real scene pollution carbon emission data set according to the determined real scene pollution carbon emission data source;

[0129] Real-life pollution carbon emission data processing module: used to check and evaluate the quality of the initial spatialized real-life pollution carbon emission data set, convert the data into a unified format, and obtain a spatialized real-life pollution carbon emission data set that meets the pre-set quality evaluation requirements;

[0130] Background carbon emission data storage and management module: used to structure the spatialized carbon emission data over the entire life cycle and store it in the database;

[0131] Background carbon emission data extraction module: used to extract the carbon emission data set of the background industrial chain corresponding to the real-life industrial chain, and obtain a spatialized background carbon emission data set that meets the pre-set quality assessment requirements;

[0132] Background carbon emission data source definition module: used to define the geographical boundaries of the background industrial chain according to the accounting object, identify the spatial characteristics of each unit process, match the spatial resolution of the accounting, and then redefine the background carbon emission data source when the spatialized background carbon emission data set extracted by the background carbon emission data extraction module does not meet the pre-set quality assessment requirements;

[0133] Background carbon emission data collection module: used to collect and form an initial spatial background carbon emission data set based on the re-determined background carbon emission data source;

[0134] Background pollution carbon emission data processing module: used to check and evaluate the quality of the initial spatial background pollution carbon emission data set, convert the data into a unified format, and obtain a spatial background pollution carbon emission data set that meets the pre-set quality evaluation requirements;

[0135] Spatialized full life cycle carbon emission data calculation and integration module: Integrate the spatialized real-life carbon emission data set and the spatialized background carbon emission data set that meet the pre-set quality assessment requirements to form a spatialized full life cycle carbon emission data list;

[0136] Data verification module: used to verify the spatialized full life cycle carbon emission data inventory and form a data verification report;

[0137] Data publishing module: used to publish the spatialized full life cycle carbon emission data list that has passed data verification, and send it to the background carbon emission data storage and management module for storage;

[0138] Data update module: used to drive the real-life carbon emission data source definition module and the background carbon emission data source definition module according to data update requirements, and identify the updated spatialized full life cycle carbon emission data.

[0139] Site-scale calculation module: Based on the spatialized environmental characteristic data, the site-scale spatialized carbon emission cross-media impact factor dataset is obtained;

[0140] Regional scale calculation module: Based on the sensitive factor data that significantly affects the cross-media impact factors of carbon emissions, a regional scale spatialized cross-media impact factor dataset of carbon emissions driven by proxy data is obtained;

[0141] The site-scale computing module includes:

[0142] Spatial calculation module of fate factor data: used to associate the sources and sinks of carbon emissions, express the instantaneous diffusion state of the emission substances by their residence time, and calculate the spatial fate factor data based on a series of geographic information data such as the location and height of the gas emission source and the terrain parameters and meteorological parameters of the gas emission substance diffusion process;

[0143] Spatialized exposure factor data calculation module: used to associate the sinks and receptors of carbon emissions, calculate the spatialized exposure factor data based on the duration and concentration of the emission substances exposed to the receptors and the spatialized receptor characteristic parameters;

[0144] Spatialized exposure response factor data calculation module: used to identify the sensitivity of receptors to emission substances, and calculate the spatialized exposure response factor data based on the spatialized receptor characteristic parameters through the environmental impact of the emission substances on the receptors after exposure to the receptors;

[0145] Spatial calculation and integration module of cross-media impact factor data of carbon emissions: used for the spatial cross-media impact factor model of carbon emissions based on the site scale, integrating spatialized fate factor data, exposure factor data and exposure response factor data, and calculating and integrating the spatial cross-media impact factor data of carbon emissions based on the site scale;

[0146] Data verification module: used to verify the data of cross-media influencing factors of spatial carbon emissions and form a data verification report;

[0147] Data publishing module: used to publish data-verified spatial carbon emission cross-media impact factor data;

[0148] Regional scale computing modules include:

[0149] Sensitive factor data identification module: used to identify the spatial characteristics of several sensitive factors that significantly affect the cross-media influencing factors of carbon pollution emissions when it is difficult to obtain sufficient spatial receptor characteristic parameters;

[0150] Sensitive factor data spatial calculation module: based on the sensitive factors and their spatial characteristics, the spatial sensitive factor data is calculated;

[0151] Spatial calculation and integration module of cross-media impact factor data of carbon pollution emissions: It is used to integrate spatial sensitive factor data based on regional scale spatial cross-media impact factor model of carbon pollution emissions, calculate and integrate spatial sensitive factors as proxy data-driven regional scale spatial cross-media impact factor data of carbon pollution emissions;

[0152] Data verification module: used to verify the data of cross-media influencing factors of spatial carbon emissions and form a data verification report;

[0153] Data publishing module: used to publish data on cross-media impact factors of spatialized carbon emissions that have been verified.

[0154] Spatialized carbon pollution emission cross-media impact module: Based on the spatialized full life cycle carbon pollution emission data inventory and the spatialized carbon pollution emission cross-media impact factor data set with the same spatial resolution, a spatialized carbon pollution emission cross-media impact data set is obtained.

[0155] The spatial carbon emission cross-media impact module includes:

[0156] Spatial calculation integration module for cross-media impact data of carbon emissions: It is used to integrate the spatialized full-life cycle carbon emissions data inventory and spatialized cross-media impact factor data set of carbon emissions that meet the pre-set quality assessment requirements based on the universal spatialized model of cross-media impact of carbon emissions, and calculate the spatialized cross-media impact data of carbon emissions;

[0157] Data verification module: used to verify the spatialized cross-media impact data of carbon emissions and form a data verification report;

[0158] Data publishing module: used to publish spatialized cross-media impact data of carbon emissions that have been verified.

[0159] Example 3

[0160] A processing device includes computer program instructions, wherein the computer program instructions, when executed by the processing device, are used to implement the method and system for assessing the cross-media impact of carbon emissions throughout the life cycle of any one of embodiments 1 or 2.

[0161] Example 4

[0162] A computer-readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, are used to implement the method and system for assessing the cross-media impact of carbon emissions throughout their life cycle of any one of embodiments 1 or 2.

[0163] Case 1

[0164] The coal mining industry in China is taken as the evaluation object. The real industry chain is coal mining. The background industry chain includes energy supply, raw material supply, auxiliary material supply and waste disposal. The spatial resolution is set to the site scale. The actual enterprise operation data, satellite remote sensing observation data or pollution source online monitoring data are collected to calculate the site-scale spatial full life cycle carbon emission data set. x For example, the calculation formula is as follows:

[0165] M i =A i,DI +A i,EC +A i,TE +A i,EX +A i,TI +A i,ST +A i,CE +A i,CM +A i,WD +A i,SD

[0166] Where M i NO for the i-th location x Total emissions over its entire life cycle; A i,DI The diesel supply phase NO for the i-th location x Emissions; A i,EC For the electricity supply stage NO of the i-th location x Emissions; A i,TE For the heat supply stage NO of the i-th location x Emissions; A i,EX Explosive supply phase NO for the i-th location x Emissions; A i,TI For the i-th location pit wood supply stage NO x Emissions; A i,ST For the steel supply stage NO of the i-th location x Emissions; A i,CE For the cement supply stage of the i-th location NO x Emissions; A i,CM is the coal mining stage NO at the i-th location x Emissions; A i,WD is the NO of the wastewater treatment stage at the i-th site x Emissions; A i,SD is the solid waste disposal stage NO at the i-th location x emissions.

[0167] The carbon emissions at the site scale can be further aggregated to the regional scale, also in terms of NO x For example, the calculation formula is as follows:

[0168]

[0169] Where M a For the ath region NO x Total emissions over the entire life cycle; Cap i is the production scale of the coal mine at the i-th location. Finally, the NO x The emission dataset is shown in Table 1.

[0170] Table 1 NO in China's coal mining industry over its entire life cycle x Emissions dataset

[0171]

[0172] Case 2

[0173] Taking China's coal mining industry as the evaluation object, considering that the spatial resolution is at the provincial scale, a regional scale-based modeling method is chosen to identify and spatialize the sensitive factors that significantly affect the cross-media impact factors of carbon emissions, and calculate a provincial-scale spatialized cross-media impact factor dataset of carbon emissions driven by proxy data. x Taking the cross-media environmental impacts caused by emissions (acidification, eutrophication, photochemical smog, etc.) as an example, the acidification impact factor is calculated by multiplying the fate factor of the acidifying substance by the exposure factor of the forest vegetation. Therefore, the relative forest coverage rate of each province is used as the spatial sensitivity factor of the impact factor. The calculation formula is as follows:

[0174]

[0175] Among them, TA i is the acidification environmental impact of the ith province; bp i,k is the kth carbon emission flow in the ith province; TAEF k TASF is the cross-media impact factor of carbon dioxide emissions that causes acidification of the kth carbon dioxide emission flow; i is the forest coverage rate of the ith province; TASF is the forest coverage rate of the region corresponding to the universal cross-medium impact factor of carbon emissions affected by acidification environment.

[0176] The eutrophication influencing factor is the fate factor of eutrophic substances. Therefore, the relative concentration of total phosphorus in each province is used as the spatial sensitivity factor of the influencing factor. The calculation formula is as follows:

[0177]

[0178] Among them, EU i is the eutrophication environmental impact of the i-th province; EUEF k EUSF is the cross-media impact factor of carbon emissions that causes eutrophication in the kth carbon emission flow;i is the total phosphorus concentration in the ith province; EUSF is the total phosphorus concentration in the corresponding region of the universal cross-media impact factor of carbon pollution emissions affected by eutrophication.

[0179] The photochemical smog impact factor is calculated by multiplying the fate factor of the photochemical smog substance and the human exposure factor and exposure response factor. Therefore, the relative population density of each province is used as the spatial sensitivity factor of the impact factor. The calculation formula is as follows:

[0180]

[0181] Among them, PC i is the environmental impact of photochemical smog in the ith province; PCEF k PCSF is the cross-media impact factor of carbon emissions that causes photochemical smog environmental impact for the kth carbon emission stream; i is the population density of the ith province; PCSF is the population density of the region corresponding to the universal cross-medium impact factor of carbon emissions for photochemical smog environmental impact.

[0182] Finally, a dataset of cross-media impacts of spatialized carbon emissions from China’s coal mining industry at the provincial and regional scale driven by proxy data was calculated, as shown in Tables 2 and 3.

[0183] Table 2 Spatial sensitivity factor dataset

[0184]

[0185]

[0186] Table 3 Spatial cross-media environmental impact dataset of China's coal mining industry

[0187]

[0188]

[0189] Case 3

[0190] Taking the toxic impact model as an example, the fate factor describes the migration-transformation path of the polluted carbon emission flow in the environment, the exposure factor describes the contact-intake-accumulation of the polluted carbon emission flow in the human food chain and ecosystem, and the exposure response factor describes the impact of the polluted carbon emission flow on human health and ecosystem. Among them, the fate factor and exposure factor can be calculated based on the cross-media fate model and cross-media exposure model, and the exposure response factor can be estimated based on human and animal toxicity experimental data:

[0191]

[0192] GP i,j,k =∑g GP i,j,g,k

[0193] Among them, GP i,g,j,k It is expressed as the fate factor of the kth carbon emission flow from the gth location to the jth location in the i-th region, C i,j,k It is expressed as the ambient steady-state concentration of the kth carbon emission flow at the jth location in the i-th region, M i,g,k It is expressed as the emission of the kth carbon emission flow at the gth location in the ith region.

[0194]

[0195] OP i,j,k =∑ r OP r,i,j,k

[0196] Among them, OP r,i,j,k It is expressed as the exposure factor of the kth carbon emission flow in the jth location in the i-th region entering crops or humans through the rth pathway, I r,i,j,k It is expressed as the fraction of carbon emissions from the kth pollutant emission flow at the jth location in the ith region that enters crops or humans through the rth pathway. The calculation process obtains the calculation results by inputting relevant data such as the average temperature, wind speed, wind direction, land area, water area, soil type and food intake of each site.

[0197]

[0198] D i,j =N h ·∑ e D i,j,e ·R i,j,e

[0199] D i,j,e =f(ED 50,k ,W i,j ,L i,j ,X 365 ,CF a ,CF t )

[0200] Among them, OR i,j,k (Human health) is expressed as the exposure response factor of the damage to human health caused by the kth carbon emission flow in the jth location in the ith region. i,j It is expressed as the total human health damage caused by multiple diseases at the jth location in the i-th region. i,j,k,e It is expressed as the incidence of e diseases after the k-th carbon emission flow in the j-th location in the i-th region acts on the exposed population. i,j,k,eIt is expressed as the effective toxicity (toxicity unit) of the kth carbon emission flow at the jth location in the i-th region causing e types of diseases to the exposed population. i,j,k It is expressed as the total intake fraction of the kth carbon emission flow in the jth location of the i-th region into crops or humans. N h It is expressed as the total population of the jth location in the i-th region. i,j,e It is expressed as the human health damage caused by the e-type disease at the j-th location in the i-th region. i,j,e It is expressed as the incidence of disease e at the jth location in the i-th region. 50,k W is expressed as the half effective dose of the kth carbon emission flow (i.e., the dose that causes 50% of the population to become ill when the benchmark dose is higher than the background benchmark dose), i,j It is expressed as the average weight of the population at the jth location in the ith region, L i,j represents the average life expectancy of the population at the jth location in the i-th region, X 365 Expressed as the number of days per year, CF a Expressed as a correction factor for interspecies differences in the exposed population, CF t It is expressed as a correction factor for differences in exposure time. The calculation process obtains the calculation results by inputting relevant data such as the population size, average life expectancy, average weight, ethnic proportion and age distribution of each site.

[0201]

[0202] F i,j (Ecotoxicity) = f(L(E)C 50,i,j,k )

[0203] Among them, OR i,j,k Ecotoxicity is the exposure response factor of the damage caused to the ecosystem by the k-th carbon emission flow at the j-th location in the i-th region, F i,j The comprehensive ecosystem impact at the jth site in the ith region can be calculated using a behavior-specific species loss model, which can be estimated by the distribution of species sensitivity to the median lethal concentration (LC50) and toxic effect concentration (EC50) under the action mode of each carbon emission stream. i,j,k It is expressed as the effective toxicity (toxicity unit) of the kth carbon emission stream in the jth location in the ith region with the same action mode, for example, in calculating the exposure response factor OR of water ecotoxicity i,j,k When using the water ecotoxicity parameter, 0.5 can be set as the typical value of the toxic effect unit. 50,i,j,k It is expressed as the median lethal concentration caused by the kth carbon emission flow at the jth location in the i-th region. EC 50,i,j,kIt is expressed as the toxic effect concentration caused by the kth carbon emission flow at the jth location in the ith region.

[0204] The above are only embodiments of the present invention, and the common knowledge such as the known specific structures and / or characteristics in the scheme are not described in detail here. It should be pointed out that for those skilled in the art, several deformations and improvements can be made without departing from the structure of the present invention, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A method for assessing the cross-media impact of carbon emissions over the entire life cycle, characterized by: The steps include: S1. According to the accounting object, determine the spatial resolution requirements of the assessment and obtain a spatialized full life cycle carbon emission data list that meets the quality assessment requirements; S2. Based on the spatialization model of the universal cross-media impact factor of carbon pollution emissions, the spatialized cross-media impact factor data of carbon pollution emissions is obtained according to the spatialized environmental characteristic data or the sensitive factor data that significantly affects the cross-media impact factor of carbon pollution emissions; S3. Based on the universal spatialized model of cross-media impact of carbon emissions, the spatialized cross-media impact dataset of carbon emissions is obtained according to the spatialized full life cycle carbon emissions data inventory and the spatialized cross-media impact factor dataset of carbon emissions with the same spatial resolution.

2. According to claim 1, a method for assessing the cross-media impact of carbon emissions over the entire life cycle is characterized by: The method of step S1 is as follows: S1.

1. According to the accounting object, determine the spatial resolution requirements for the assessment, determine the real-life data source, and collect the initial spatial full-life cycle pollution carbon emission real-life data inventory; S1.

2. Check and evaluate the data quality of the initial spatialized full-life cycle carbon emission real-life data inventory. If it does not meet the pre-set quality evaluation requirements, proceed to S1.1 to re-determine the real-life data source. Otherwise, proceed to S1.

3. S1.

3. Extract the background data set from the international mainstream database corresponding to the spatialized full life cycle pollution carbon emission real-life data inventory, and check and evaluate the data quality of the background data set. If it does not meet the pre-set quality evaluation requirements, proceed to S1.4 and re-collect the background data. Otherwise, proceed to S1.

6. S1.

4. According to the accounting object, determine the spatial resolution requirements for the assessment, determine the background data source, and collect the initial spatial full life cycle pollution carbon emission background data inventory; S1.

5. Check and evaluate the data quality of the initial spatialized full-life cycle carbon emission background data inventory. If it does not meet the pre-set quality evaluation requirements, proceed to S1.4 and re-determine the background data source. Otherwise, proceed to S1.

6. S1.

6. Integrate the spatialized full life cycle carbon pollution emission real-life data list and background data list that meet the pre-set quality assessment requirements to obtain the spatialized full life cycle carbon pollution emission data list.

3. According to claim 1, a method for assessing the cross-media impact of carbon emissions over the entire life cycle is characterized by: The calculation formula for the spatialized full life cycle carbon emission data inventory is as follows: Where M i,j,k A is the total carbon emission of the kth carbon emission flow in the ith location or region over its entire life cycle; i,1,k , A i,2,k …A i,n,k For the carbon emissions of the 1st, 2nd, ... nth life cycle stages of the kth carbon emission flow in the ith location or region, when the spatial resolution required for accounting is high, the integrated spatialized full life cycle carbon emission data inventory is calculated at the micro scale through on-site investigation, satellite remote sensing observation data inversion or data collection by online monitoring equipment of pollution sources; when the spatial resolution required for accounting is low, the integrated spatialized full life cycle carbon emission data inventory is calculated at the macro and meso scales through investigation of the National Bureau of Statistics, provincial and municipal air pollutant and carbon emission inventories or environmental impact assessment report data.

4. According to claim 1, a method for assessing the cross-media impact of carbon emissions over the entire life cycle is characterized by: The modeling method of the spatial model based on the universal cross-media impact factor of carbon pollution emissions is as follows: S2.

1. Modeling based on site scale: When the required spatial resolution is high and the spatialized environmental characteristic data is sufficient, the site scale modeling of the fate factors, exposure factors and exposure response factors of the cross-media impact factors of carbon emissions is carried out to calculate the site scale spatialized cross-media impact factor dataset of carbon emissions; The site-scale modeling approach is: EP i,j,k =GP i,j,k ·OP i,j,k ·OR i,j,k Among them, EP i,j,k , GP i,j,k OP i,j,k OR i,j,k They are the cross-media impact factor, fate factor, exposure factor and exposure response factor of the kth carbon emission flow at the jth location in the ith region. Usually, the fate factor is a mathematical function of the carbon emission flow characteristics, source characteristics and sink characteristics, the exposure factor is a mathematical function of the carbon emission flow characteristics, sink characteristics and receptor characteristics, and the exposure response factor is a mathematical function of the carbon emission flow characteristics and receptor characteristics: GP i,j,k =f(cbp k ,sfp i,j ,scp i,j ) OP i,j,k =f(cbp k ,scp i,j ,rcp i,j ) OR i,j,k =f(cbp k ,rcp i,j ) Among them, cbp k is the characteristic parameter of the kth carbon emission flow, sfp i,j 、scp i,j and rcp i,j They are the source characteristic parameters, sink characteristic parameters and receptor characteristic parameters of the jth location in the ith region, respectively. Usually, the fate factor data is used to associate the source and sink of carbon emissions, and the residence time of the emission substances is used to represent their instantaneous diffusion state, which is calculated based on the location and height of the gas emission source and the terrain parameters and meteorological parameters of the diffusion process of the gas emission substances; the exposure factor data is used to associate the sink and receptor of carbon emissions, and is calculated based on the spatialized receptor characteristic parameters through the duration and concentration of the emission substances exposed to the receptors; the exposure response factor data is used to identify the sensitivity of the receptor to carbon emissions, and is calculated based on the spatialized receptor characteristic parameters through the environmental impact of the emission substances on the receptors after exposure to the receptors; S2.2, Modeling based on regional scale: When the required spatial resolution is low or the spatialized environmental characteristic data is insufficient, modeling based on regional scale is carried out by accurately identifying and spatializing the sensitive factors that significantly affect the cross-media impact factors of carbon emissions, and calculating the regional scale spatialized cross-media impact factor dataset of carbon emissions driven by proxy data; The regional scale modeling method is as follows: AP i,k =EP k ·AE i,k Among them, AP i,k The cross-media impact factor of carbon emissions of the kth carbon emission flow in the ith region driven by proxy data; EP k is the universal cross-media impact factor of carbon emission for the kth carbon emission flow; AE i,k KE is the sensitivity factor of the cross-media impact factor of the carbon emission of the kth carbon emission flow in the ith region; i,k KE is the key parameter of the cross-media influencing factor of the carbon emission of the kth carbon emission flow in the ith region; k It is the universal key parameter of the cross-media influencing factor of carbon emissions of the kth carbon emission flow.

5. According to claim 1, a method for assessing the cross-media impact of carbon emissions over the entire life cycle is characterized by: The method of step S3 is as follows: S3.

1. When the required spatial resolution is high and the spatialized environmental characteristic data are sufficient, the spatialized carbon emission cross-media impact data set at the site scale is calculated based on the spatialized full life cycle carbon emission data inventory and the site-scale spatialized carbon emission cross-media impact factor data set at the same spatial resolution; S3.

2. When the required spatial resolution is low or the spatialized environmental characteristic data are insufficient, the regional scale spatialized carbon emission cross-media impact data set driven by proxy data is calculated based on the spatialized full life cycle carbon emission data inventory and the regional scale spatialized carbon emission cross-media impact factor data set at the same spatial resolution. The calculation method for the cross-media impact of spatial pollution carbon emissions at the site scale is: CM a =∑ k ∑ j ∑ i bp i,j,k,a ·EP i,j,k Among them, CM a is the cross-media impact of carbon emissions per unit of final product at the ath site, bp i,j,k,a is the carbon emission flow intensity of the kth location in the i-th region related to the final product of the a-th site, The calculation method of the cross-media impact of regional-scale spatialized carbon emissions driven by the proxy data is: CM b =∑ k ∑ i bp i,k,b ·AP i,k Among them, CM b is the cross-media impact of carbon emissions from the final product of the b-th regional unit, bp i,k,b is the carbon emission flow intensity of the kth region in the ith region related to the final product of the bth region.

6. A cross-media impact assessment system for carbon emissions throughout the entire life cycle, characterized by: include: Spatialized full life cycle carbon emission module: used to identify the real-life industrial chain and the background industrial chain corresponding to the real-life industrial chain according to the accounting object and spatial resolution requirements, determine the real-life data source and the background data source, and obtain a spatialized full life cycle carbon emission data list that meets the quality assessment requirements; Site-scale calculation module: Based on the spatialized environmental characteristic data, the site-scale spatialized carbon emission cross-media impact factor dataset is obtained; Regional scale calculation module: Based on the sensitive factor data that significantly affects the cross-media impact factors of carbon emissions, a regional scale spatialized cross-media impact factor dataset of carbon emissions driven by proxy data is obtained; Spatialized carbon pollution emission cross-media impact module: Based on the spatialized full life cycle carbon pollution emission data inventory and the spatialized carbon pollution emission cross-media impact factor data set with the same spatial resolution, a spatialized carbon pollution emission cross-media impact data set is obtained.

7. A system for assessing the cross-media impact of carbon emissions throughout the entire life cycle according to claim 6, characterized in that: The spatialized full life cycle carbon emission module includes: Real-life pollution carbon emission data source definition module: used to define the geographical boundaries of the real-life industrial chain according to the accounting object, identify the spatial characteristics of each unit process, match the spatial resolution of the accounting, and then determine the real-life pollution carbon emission data source; Real scene pollution carbon emission data collection module: used to collect and form an initial spatialized real scene pollution carbon emission data set based on the determined real scene pollution carbon emission data source; Real-life pollution carbon emission data processing module: used to check and evaluate the quality of the initial spatialized real-life pollution carbon emission data set, convert the data into a unified format, and obtain a spatialized real-life pollution carbon emission data set that meets the pre-set quality evaluation requirements; Background carbon emission data storage and management module: used to structure the spatialized carbon emission data over the entire life cycle and store it in the database; Background carbon emission data extraction module: used to extract the carbon emission data set of the background industrial chain corresponding to the real-life industrial chain, and obtain a spatialized background carbon emission data set that meets the pre-set quality assessment requirements; Background carbon emission data source definition module: used to define the geographical boundaries of the background industrial chain according to the accounting object, identify the spatial characteristics of each unit process, match the spatial resolution of the accounting, and then redefine the background carbon emission data source when the spatialized background carbon emission data set extracted by the background carbon emission data extraction module does not meet the pre-set quality assessment requirements; Background pollution carbon emission data collection module: used to collect and form an initial spatial background pollution carbon emission data set based on the re-determined background pollution carbon emission data source; Background pollution carbon emission data processing module: used to check and evaluate the quality of the initial spatial background pollution carbon emission data set, convert the data into a unified format, and obtain a spatial background pollution carbon emission data set that meets the pre-set quality evaluation requirements; Spatialized full life cycle carbon emission data calculation and integration module: Integrate the spatialized real-life carbon emission data set and the spatialized background carbon emission data set that meet the pre-set quality assessment requirements to form a spatialized full life cycle carbon emission data list; Data verification module: used to verify the spatialized full life cycle carbon emission data inventory and form a data verification report; Data publishing module: used to publish the spatialized full life cycle carbon emission data list that has passed data verification, and send it to the background carbon emission data storage and management module for storage; Data update module: used to drive the real-scene carbon emission data source definition module and the background carbon emission data source definition module according to data update requirements, and identify the updated spatialized full life cycle carbon emission data.

8. The system for assessing the cross-media impact of carbon emissions throughout the entire life cycle according to claim 6 is characterized by: The site scale calculation module includes: Spatial calculation module of fate factor data: used to associate the sources and sinks of carbon emissions, express the instantaneous diffusion state of the emission substances by their residence time, and calculate the spatial fate factor data based on the location and height of the gas emission source and the geographic information data of the diffusion process of the gas emission substances; Spatialized exposure factor data calculation module: used to associate the sinks and receptors of carbon emissions, calculate the spatialized exposure factor data based on the duration and concentration of the emission substances exposed to the receptors and the spatialized receptor characteristic parameters; Spatialized exposure response factor data calculation module: used to identify the sensitivity of receptors to emission substances, and calculate the spatialized exposure response factor data based on the spatialized receptor characteristic parameters through the environmental impact of the emission substances on the receptors after exposure to the receptors; Spatial calculation and integration module of cross-media impact factor data of carbon emissions: used for the spatial cross-media impact factor model of carbon emissions based on the site scale, integrating spatialized fate factor data, exposure factor data and exposure response factor data, and calculating and integrating the spatial cross-media impact factor data of carbon emissions based on the site scale; Data verification module: used to verify the data of cross-media influencing factors of spatial carbon emissions and form a data verification report; Data publishing module: used to publish data-verified spatial carbon emission cross-media impact factor data.

9. A system for assessing the impact of carbon emissions on the entire life cycle across media according to claim 6, characterized in that : The regional scale calculation module includes: Sensitive factor data identification module: used to identify the spatial characteristics of several sensitive factors that significantly affect the cross-media influencing factors of carbon pollution emissions when it is difficult to obtain sufficient spatial receptor characteristic parameters; Sensitive factor data spatial calculation module: based on the sensitive factors and their spatial characteristics, the spatial sensitive factor data is calculated; Spatial calculation and integration module of cross-media impact factor data of carbon pollution emissions: It is used to integrate spatial sensitive factor data based on regional scale spatial cross-media impact factor model of carbon pollution emissions, calculate and integrate spatial sensitive factors as proxy data-driven regional scale spatial cross-media impact factor data of carbon pollution emissions; Data verification module: used to verify the data of cross-media influencing factors of spatial carbon emissions and form a data verification report; Data publishing module: used to publish data-verified spatial carbon emission cross-media impact factor data.

10. The system for assessing the cross-media impact of carbon emissions throughout the entire life cycle according to claim 6, characterized in that: The spatial carbon emission cross-media impact module includes: Spatial calculation integration module for cross-media impact data of carbon emissions: It is used to integrate the spatialized full-life cycle carbon emissions data inventory and spatialized cross-media impact factor data set of carbon emissions that meet the pre-set quality assessment requirements based on the universal spatialized model of cross-media impact of carbon emissions, and calculate the spatialized cross-media impact data of carbon emissions; Data verification module: used to verify the spatialized cross-media impact data of carbon emissions and form a data verification report; Data release module: used to release spatialized cross-media impact data of carbon emissions that have been verified.

11. A processing device, characterized in that: It includes computer program instructions, wherein the computer program instructions, when executed by a processing device, are used to implement the method and system for assessing the cross-media impact of carbon emissions throughout the life cycle as described in any one of claims 1-10.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, wherein the computer program instructions, when executed by a processor, are used to implement the method and system for assessing the cross-media impact of carbon emissions throughout their life cycle as described in any one of claims 1-10.

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