Element emission detection method and device for multi-scale coupling network of coal industry chain

Abstract

The application provides a coal industry chain multi-scale coupling network element emission detection method and device, the method comprises the following steps: according to different consumption scenarios, generating the element migration characteristics in the coal products in different regions according to the full sample micro data set and the localized element content data set; through the mass balance and material flow balance method, the multi-medium emission of the elements in the point sources is generated according to the element migration characteristics in the coal products in different regions and the point source information, the environmental extended multi-region input-output model is constructed and the consumption path optimization is carried out, and the optimal consumption path is generated; based on the optimal consumption path and the multi-medium emission of the elements in the point sources, the multi-source data gridding is carried out, the element emission distribution map of the multi-scale coupling network is generated, a full-chain energy-material-carbon-pollution coupling network is constructed, the systematic tracking of the carbon and pollutant migration path of the coal full industry chain can be realized, and quantitative decision support for multi-target collaborative management is provided.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method and apparatus for detecting element emissions in a multi-scale coupled network of a coal industry chain. Background Technology

[0002] Coal-fired systems, as a critical energy supply link, are a significant source of greenhouse gases and various pollutants. Currently, by increasing the proportion of front-end washing and beneficiation and popularizing end-of-pipe ultra-low emission technologies, the emission of conventional air pollutants from coal-fired flue gas has been effectively controlled. However, this has led to a sharp increase in solid waste such as coal gangue, fly ash, and desulfurization gypsum. During the cross-industry integrated utilization process, these wastes cause secondary emissions and cross-media transfer of pollutants. At the same time, the washing and beneficiation and pollution control processes themselves are accompanied by water consumption and wastewater discharge, creating new environmental burdens.

[0003] Currently, existing technical solutions for environmental impact assessment and management of the coal industry chain mostly focus on independent studies of single links or single environmental media. For example, existing studies have either systematically or specifically calculated greenhouse gas emissions from coal combustion, assessed the end-of-pipe treatment effects of a single type of air pollutant, or only statistically analyzed the amount of solid waste generated. These methods lack systematicity, have blind spots in assessment, and ignore the transfer of a large number of pollutants from the atmosphere to water, solid waste, and other media, as well as the secondary emissions caused by the cross-industry resource utilization of solid waste, leading to an overestimation of current environmental governance effectiveness. Due to fragmented models and data silos, it is difficult to support the decision-making transformation from single-objective governance to multi-objective synergistic optimization such as pollution reduction, carbon reduction, water conservation, and solid waste resource utilization, and it cannot meet the comprehensive management needs under multiple objectives.

[0004] In summary, existing technological solutions exhibit inherent shortcomings when addressing the complex multi-media environmental problems of the coal industry chain, including insufficient systemicity, limited assessment dimensions, and limited decision support capabilities. Given the urgent need to achieve synergistic efficiency in pollution and carbon reduction, developing a comprehensive simulation method and system that can connect the entire industry chain, couple multiple factors, and simulate cross-media migration processes has become an inevitable direction for technological development in this field. Summary of the Invention

[0005] One objective of this invention is to provide a method for detecting elemental emissions in a multi-scale coupled network of the coal industry chain, constructing a full-chain energy-material-carbon-pollution coupled network. This enables systematic tracking of carbon and pollutant migration paths throughout the entire coal industry chain, precisely quantifying cross-media transfer and secondary emissions of pollutants, and providing quantitative decision support for multi-objective collaborative management. Another objective of this invention is to provide a device for detecting elemental emissions in a multi-scale coupled network of the coal industry chain. A further objective of this invention is to provide a computer-readable medium. A final objective of this invention is to provide a computer device.

[0006] To achieve the above objectives, this invention discloses, in one aspect, a method for detecting elemental emissions in a multi-scale coupled network of the coal industry chain, comprising: Construct a full-sample micro-dataset and a localized element content dataset for the coal industry chain; Based on different consumption scenarios, and using the full-sample micro-dataset and local element content dataset, element migration characteristics of coal products in different regions are generated. Using mass balance and material flow balance methods, multi-media emission calculations are performed based on the element migration characteristics in coal products from different regions and information from various point sources, generating the multi-media emission amounts of elements at point sources. Based on the element migration characteristics in coal products from different regions and the multi-media emissions of elements at point sources, an environmentally extended multi-regional input-output model is constructed and the absorption path is optimized to generate the optimal absorption path. Multi-source data is rasterized based on the optimal absorption path and the multi-media emission of elements at point sources to generate an element emission distribution map of a multi-scale coupled network.

[0007] Preferably, a full-sample micro-dataset and a localized elemental content dataset for the coal industry chain are constructed, including: The multi-source datasets of the coal industry chain were cleaned, aligned, and fused to construct a full-sample micro dataset. The coal samples from mining areas in the coal industry chain are sampled and their elemental content is analyzed to generate a localized elemental content dataset.

[0008] Preferably, the full-sample micro-dataset includes coal input, regional coal consumption, regional coal transport matrix, and coal products, while the localized element content dataset includes the percentage of elements in coal, the percentage of elements in coal products, and the regional coal element content matrix. Based on different consumption scenarios, and using full-sample micro-datasets and localized element content datasets, element migration characteristics of coal products from different regions are generated, including: Based on different consumption scenarios, the element input is generated according to the coal input, the element percentage in the coal, and the element percentage in the coal product. Based on different consumption scenarios, element migration features are generated according to element input, regional coal consumption, regional coal transport matrix, and regional coal element content matrix.

[0009] Preferably, the consumption scenario is washed coal that has been processed by a coal washing plant or raw coal that has not been processed by a coal washing plant; Based on different consumption scenarios, elemental input quantities are generated according to the coal input volume, the elemental content in the coal, and the elemental content in coal products, including: If the consumption scenario is washed coal that has been processed by a coal washing plant, the total element input of the coal washing plant is generated based on the element percentage content in the washed coal and the input amount of the washed coal. The element input amount of coal products is generated based on the total amount of element input to the coal washing plant, the percentage content of elements in coal products, and the total mass of elements in the products after coal washing. If the consumption scenario involves raw coal that has not been processed by a coal washing plant, the element input amount of the raw coal is generated based on the element percentage content in the raw coal and the amount of raw coal input.

[0010] Preferably, according to different consumption scenarios, element migration features are generated based on element input, regional coal consumption, regional coal transport matrix, and regional coal element content matrix, including: If the consumption scenario is washed coal processed by a coal washing plant, the element quality of the regional coal product is generated based on the quality of the coal product, the element input of the coal product, the regional coal washing consumption, the regional coal washing transfer matrix, and the element content matrix of the regional coal product. The element quality of the regional coal product is then determined as the first element migration feature. If the consumption scenario involves raw coal that has not been processed by a coal washing plant, the element input quality of the region is generated based on the region's raw coal consumption, the region's raw coal transport matrix, and the element content matrix of the region's raw coal. The element input quality of the region is then determined as the second element migration feature.

[0011] Preferably, the point source information includes by-product type, process efficiency parameters, and secondary utilization path parameters; Using mass balance and material flow balance methods, multi-media emission calculations are performed based on the element migration characteristics of coal products from different regions and information from various point sources. This generates the multi-media emission quantities of elements at point sources, including: Based on process efficiency parameters and element migration characteristics, the initial emission amounts of elements corresponding to different by-product types are generated. Based on the secondary utilization path parameters and the initial emission amount of the element, the multi-media emission amount of the element at the point source is generated.

[0012] Preferably, based on the element migration characteristics in coal products from different regions and the multi-media emissions of elements at point sources, an environmentally extended multi-regional input-output model is constructed and the absorption path is optimized to generate the optimal absorption path, including: Based on the multi-regional input-output model architecture, an environmentally extended multi-regional input-output model is constructed according to the element migration characteristics in coal products from different regions and the multi-media emission of elements at point sources. An environmental load is generated based on the multi-regional input-output model with environmental extension, according to the multi-media emissions of elements at point sources. Using a linear programming framework, based on environmental load and pre-set constraints, and with the objectives of minimizing total cost and maximizing environmental benefits, an optimization function for the absorption path is constructed and solved to generate the optimal absorption path.

[0013] Preferably, multi-source data is rasterized based on the optimal absorption path and the multi-media emission of elements at point sources to generate an element emission distribution map of a multi-scale coupled network, including: Using a geographic information system, the multi-media emissions of elements at point sources are rasterized to generate an element emission intensity distribution map. Based on the element emission intensity distribution map, the optimal absorption path and the acquired area source data are rasterized to generate an element emission distribution map of a multi-scale coupled network.

[0014] This invention also discloses an element emission detection device for a multi-scale coupled network in the coal industry chain, comprising: Multi-source database construction unit, used to construct full-sample micro-datasets and localized element content datasets for the coal industry chain; The element migration feature generation unit is used to generate element migration features in coal products from different regions based on the full sample micro dataset and the localized element content dataset, according to different consumption scenarios. The multi-media emission calculation unit is used to perform multi-media emission calculations based on the element migration characteristics in coal products from different regions and information from various point sources using mass balance and material flow balance methods, and to generate the multi-media emission amount of elements at point sources. The absorption path optimization unit is used to construct an environmentally extended multi-regional input-output model and optimize the absorption path based on the element migration characteristics of coal products in different regions and the multi-media emission of elements at point sources, and generate the optimal absorption path. The element emission distribution detection unit is used to perform multi-source data rasterization based on the optimal absorption path and the multi-media emission amount of elements at point sources, and generate an element emission distribution map of a multi-scale coupled network.

[0015] The present invention also discloses a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the method described above.

[0016] The present invention also discloses a computer device, including a memory and a processor, wherein the memory is used to store information including program instructions, and the processor is used to control the execution of the program instructions, wherein the processor executes the program to implement the method described above.

[0017] The present invention also discloses a computer program product, including a computer program / instruction, which, when executed by a processor, implements the method described above.

[0018] This invention constructs a full-sample micro-dataset and a localized element content dataset for the coal industry chain. Based on the full-sample micro-dataset and the localized element content dataset, it generates element migration characteristics in coal products from different regions according to different consumption scenarios. Using mass balance and material flow balance methods, it calculates multi-media emissions based on the element migration characteristics in coal products from different regions and information from various point sources, generating multi-media emissions of elements at point sources. Based on the element migration characteristics in coal products from different regions and the multi-media emissions of elements at point sources, it constructs an environmentally extended multi-regional input-output model and optimizes the absorption path to generate the optimal absorption path. Based on the optimal absorption path and the multi-media emissions of elements at point sources, it performs multi-source data rasterization to generate a multi-scale coupled network element emission distribution map, constructing a full-chain energy-material-carbon-pollution coupled network. This enables systematic tracking of carbon and pollutant migration paths throughout the entire coal industry chain, precisely quantifies cross-media transfer and secondary emissions of pollutants, and provides quantitative decision support for multi-objective collaborative management. Attached Figure Description

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

[0020] Figure 1 A flowchart illustrating an element emission detection method for a multi-scale coupled network in a coal industry chain, provided as an embodiment of the present invention; Figure 2 A schematic diagram of coal flow direction provided for an embodiment of the present invention; Figure 3 A flowchart of another element emission detection method for a multi-scale coupled network in the coal industry chain provided in this embodiment of the invention; Figure 4 A schematic diagram of a multi-scale energy-material-carbon-pollution coupling network simulation system for the coal industry chain provided in this embodiment of the invention; Figure 5 A multi-media emission flow diagram of Hg element flow direction is provided in this embodiment of the invention; Figure 6 This is a schematic diagram illustrating the spatial gridded emission of Hg under a coal washing scenario and a coal washing-unwashed coal scenario, provided by an embodiment of the present invention. Figure 7 A schematic diagram of the structure of an element emission detection device for a multi-scale coupled network in the coal industry chain provided in an embodiment of the present invention; Figure 8This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] It should be noted that the element emission detection method and device for a multi-scale coupled network in the coal industry chain disclosed in this application can be used in the field of artificial intelligence technology, or in any field other than artificial intelligence technology. The application field of the element emission detection method and device for a multi-scale coupled network in the coal industry chain disclosed in this application is not limited.

[0023] To facilitate understanding of the technical solution provided in this application, the relevant content of the technical solution will be described below. This invention relates to the full-process tracking and simulation of the cross-media migration, transformation, and final fate of carbon and various polluting elements in coal during the coal production and consumption process. Based on the energy and material flows of processes such as raw coal mining and washing, coal transportation and use, and comprehensive utilization of solid waste and by-products, it tracks the flow of elements such as carbon (C), sulfur (S), nitrogen (N), mercury (Hg), lead (Pb), arsenic (As), cadmium (Cd), and chromium (Cr) throughout the coal supply and demand process, revealing their migration, transformation, and multi-media emission patterns, thereby constructing a multi-scale energy-material-carbon-pollution coupled network simulation system for the coal industry chain. The greenhouse gases involved in this invention include carbon dioxide (C₂). ), methane (C ), nitrous oxide ( O), air pollutants include nitrogen oxides (NOx) and sulfur dioxide (S). The pollutants include fine particulate matter (PM2.5), and the main cross-media pollutants are harmful trace elements such as Hg, Pb, As, Cd, and Cr. Solid waste and by-products include fly ash, bottom ash, desulfurization gypsum, coal gangue, coal slime, and middlings. This invention can provide technical support for promoting the coordinated control of carbon pollution in coal systems.

[0024] The following uses an element emission detection device for a multi-scale coupled network in the coal industry chain as an example to illustrate the implementation process of the element emission detection method for a multi-scale coupled network in the coal industry chain provided in this embodiment of the invention. It is understood that the execution entities of the element emission detection method for a multi-scale coupled network in the coal industry chain provided in this embodiment of the invention include, but are not limited to, element emission detection devices for a multi-scale coupled network in the coal industry chain.

[0025] Figure 1 A flowchart of an element emission detection method for a multi-scale coupled network in a coal industry chain, provided as an embodiment of the present invention, is shown below. Figure 1 As shown, the method includes: Step 101: Construct a full-sample micro-dataset and a localized element content dataset for the coal industry chain.

[0026] In this embodiment of the invention, official statistical documents, inter-provincial coal transportation data, pollutant discharge permit point source lists (including information such as geographical location, coal type, process, and pollution control facilities), and relevant scientific research literature are obtained. These multi-scale, multi-source documents are cleaned, aligned, and fused to construct a unified dataset containing four-dimensional attributes of province, product, element, and year. Coal production, consumption, and inter-regional transportation volume are extracted from the data in the dataset to form a skeleton network of coal energy and material flow. Further data aggregation is performed to construct a full-sample micro-database. The full-sample micro-database includes, but is not limited to, coal input, regional coal consumption, regional coal transmission matrix, and coal products.

[0027] Taking the statistics of coal flow in a certain year, in metric tons (Mt) as an example, Figure 2 This is a schematic diagram of coal flow direction provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the total coal sources in a certain year were 5227 Mt from mining and 259 Mt from imports. Coal from mining was used for thermal coal washing (2560 Mt), coking coal washing (969 Mt), and direct use. Imported coal and a portion of the coal from mining were used directly, totaling 1957 Mt. Thermal coal washing produced 2303 Mt of thermal coal, coal slime, and gangue. Coking coal washing produced 256 Mt of coal slime, middlings, gangue, and 582 Mt of refined coal. Coal slime from thermal coal washing and coking coal washing... A total of 20 Mt were produced, including 388 Mt of gangue from thermal coal washing and coking coal washing; 3476 Mt of coal used directly in combination with gangue, middlings, coal slime, and thermal coal for heating / power supply; 238 Mt of coal used directly in combination with gangue for cement production; 235 Mt of coal used directly in industrial filtration, 184 Mt in steel, 90 Mt in aluminum, 53 Mt in residential use, and 343 Mt in other applications; 294 Mt of gangue was used for comprehensive gangue utilization; and 582 Mt of refined coal was used for coking.

[0028] In this embodiment of the invention, to address the issue of factor localization, the input and output allocation factors for each sub-process, including mining, washing, coal slime recovery, and gangue discharge, are localized. Combined with literature review data, a localized elemental content dataset covering four types of products—clean coal, middlings coal, coal slime, and coal gangue—is formed. This localized elemental content dataset includes, but is not limited to, the percentage content of elements in coal, the percentage content of elements in coal products, and a regional coal elemental content matrix.

[0029] This application utilizes detailed information on key industrial point sources from the pollutant emission permit database, including geographical location, coal type, production process, and associated pollution control facilities (APCDs), to achieve refined emission accounting based on differences in technological levels. Furthermore, the system incorporates literature review results to establish background data on the content of target elements in raw coal for various regions, enhancing the accuracy of source pollution identification.

[0030] It is worth noting that the target element can be set according to actual needs, and this embodiment of the invention does not limit this. As an optional solution, the target element is Hg.

[0031] Step 102: Based on different consumption scenarios, generate element migration characteristics of coal products in different regions using the full sample micro dataset and the localized element content dataset.

[0032] In this embodiment of the invention, in order to track the flow of elements in coal products, the invention analyzed coal product output, average element concentration by province, and typical trace element content database to determine the element content and its distribution factors in coal products.

[0033] In this embodiment of the invention, the consumption scenario is either washed coal processed by a coal washing plant or raw coal that has not been processed by a coal washing plant. This step includes an input layer and a transport layer. The input layer is used to calculate the amount of element input and its distribution; the transport layer is used to calculate element migration characteristics. The transport layer focuses on the inter-provincial transport of raw coal and washed coal products produced by the coal washing plant to study the spatial distribution of elements.

[0034] Step 103: Using mass balance and material flow balance methods, multi-media emission calculations are performed based on the element migration characteristics in coal products from different regions and information from each point source to generate the multi-media emission amount of elements at the point source.

[0035] In this embodiment of the invention, the point source information includes by-product type, process efficiency parameters, and secondary utilization path parameters.

[0036] In this embodiment of the invention, after coal is transported to various point sources, the elements are redistributed according to the coal type, dust removal process, and boiler type. Based on the point source information, the multi-media distribution of elements at the point source can be calculated. For the calculation of multi-media emissions of elements at point sources, the mass balance and material flow balance methods are used to classify by-products into flue gas, desulfurization gypsum, and solid waste. For ash and gypsum, although they are by-products, more than 70% of them are comprehensively utilized, and the unutilized portion is treated as stockpiled. The comprehensively utilized portion is mostly reused in various industries, entering different media and causing pollution. The multi-media emissions of elements at point sources are further calculated.

[0037] Step 104: Based on the element migration characteristics in coal products from different regions and the multi-media emissions of elements at point sources, construct an environmentally extended multi-regional input-output model and optimize the consumption path to generate the optimal consumption path.

[0038] In this embodiment of the invention, to study the mutual influence of various point sources and the element transport paths, a network-based approach is employed. A multi-regional input-output (MRIO) model is used, and the energy and material transport matrices of multiple sources are integrated to form point-to-point networked transport optimization paths, constructing an environmentally extended multi-regional input-output model. By analyzing the influence of point sources, the focus is on addressing provincial-level material transport and optimizing the intra-provincial disposal paths for solid waste, generating the optimal disposal path.

[0039] Step 105: Based on the optimal absorption path and the multi-media emission of elements at point sources, perform multi-source data rasterization to generate an element emission distribution map of a multi-scale coupled network.

[0040] In this embodiment of the invention, by parameterizing and tracing the transformation flow of elements in coal in multiple media, the multi-source parameters can be gridded; by fusing point source and area source data and processing them into a grid, an element emission distribution map of a multi-scale coupled network is generated, thereby gaining a comprehensive understanding of the emission characteristics of elements in coal and enabling the monitoring of element emissions.

[0041] The technical solution provided in this invention involves constructing a full-sample micro-dataset and a localized element content dataset for the coal industry chain; generating element migration characteristics in coal products from different regions based on the full-sample micro-dataset and the localized element content dataset, according to different consumption scenarios; performing multi-media emission calculations based on the element migration characteristics in coal products from different regions and point source information using mass balance and material flow balance methods, generating multi-media emissions of elements at point sources; constructing an environmentally extended multi-regional input-output model and optimizing the absorption path based on the element migration characteristics in coal products from different regions and the multi-media emissions of elements at point sources, generating the optimal absorption path; and performing multi-source data rasterization based on the optimal absorption path and the multi-media emissions of elements at point sources to generate an element emission distribution map of a multi-scale coupled network, constructing a full-chain energy-material-carbon-pollution coupled network. This enables systematic tracking of carbon and pollutant migration paths throughout the entire coal industry chain, precise quantification of cross-media transfer and secondary emissions of pollutants, and provides quantitative decision support for multi-objective collaborative management.

[0042] Figure 3 A flowchart of another element emission detection method for a multi-scale coupled network in the coal industry chain provided by an embodiment of the present invention is shown below. Figure 3 As shown, the method includes: Step 201: Clean, align and merge the multi-source datasets of the coal industry chain to construct a full-sample micro dataset.

[0043] In this embodiment of the invention, each step is performed by an element emission detection device of a multi-scale coupled network in the coal industry chain.

[0044] In this embodiment of the invention, the full-sample micro-dataset includes, but is not limited to, coal input, regional coal consumption, regional coal transport matrix, and coal products.

[0045] Specifically, the multi-source dataset encompasses macro-statistical data, micro-point source data, geospatial data, and experimental measurement data. For example: macro-statistical data such as coal production, consumption, and inter-provincial transportation volume in various regions from official statistical documents; key industrial point source information obtained from the pollutant emission permit platform as micro-point source data, including its geographical location, coal type, boiler and kiln model, pollution control technology used, and its efficiency; elemental content in coal and its by-products (such as coking coal, middlings, coal slime, coal gangue, fly ash, and desulfurization gypsum) obtained through literature review and on-site sampling and testing, as well as key elemental distribution factors, as material attribute data; and spatial basis data such as provincial and regional divisions, population distribution, and GDP spatialization data.

[0046] Cleaning and processing of multi-source datasets includes, but is not limited to, outlier handling, missing value imputation, and unit standardization. Outlier handling specifically includes identifying and removing values ​​that are clearly outside the reasonable range; missing value imputation specifically includes using statistical methods (such as mean or median imputation) or mechanism-based interpolation methods to appropriately fill in missing data; unit standardization specifically includes converting data from different data sources with different units of measurement into standardized units of measurement required by the model.

[0047] Alignment processing for multi-source datasets includes, but is not limited to, temporal alignment, spatial alignment, and attribute alignment. Temporal alignment specifically involves aligning all dynamic data to a base year to ensure data consistency over time. Spatial alignment involves using provincial regions as the basic spatial unit, merging and associating all statistical data, logistics data, and point source data to establish a clear correspondence between data and geographic space. Attribute alignment involves establishing a unified coding system to standardize the classification and coding of coal types, process types, product types, and pollutant types, ensuring that the same entity in different datasets can be correctly identified and associated.

[0048] In this embodiment of the invention, after cleaning and alignment, the aforementioned multi-source data are fused within a unified four-dimensional framework of "province-product-element-year". Through data association and matching, for example, combining point source process information with macroscopic coal consumption, and associating experimentally measured element allocation factors with specific coal washing plant types, a full-sample micro-dataset is finally constructed. This dataset not only includes macroscopic coal input, regional coal consumption, regional coal transport matrix, and coal product information, but also more precisely integrates all the attributes required for each calculation unit (such as a certain type of process in a province), forming a structured and complete database capable of supporting accurate accounting from macroscopic flow to microscopic emissions. This provides reliable data support for subsequent steps to achieve accurate tracking of element flows, quantitative accounting of multi-media emissions, and cross-regional environmental impact assessments.

[0049] Step 202: Sample coal from mining areas in the coal industry chain and perform elemental content analysis to generate a localized elemental content dataset.

[0050] In this embodiment of the invention, the localized element content dataset includes the percentage content of elements in coal, the percentage content of elements in coal products, and a regional coal element content matrix.

[0051] Specifically, based on the distribution and production patterns of coal resources, on-site sampling was conducted in representative mining areas and coal washing plants in major coal-producing regions. The sampling covered the entire coal production and processing chain, and quantitative analysis was performed on the collected coal samples to generate localized elemental content datasets.

[0052] The localized element content dataset established by this invention significantly improves the spatiotemporal accuracy of the model input data, provides a reliable basis for the material properties of elements for accurate tracking, and fundamentally enhances the accuracy and reliability of the entire simulation system.

[0053] Step 203: Based on different consumption scenarios, generate element input quantities according to the coal input quantity, the element percentage content in the coal, and the element percentage content in the coal products.

[0054] In this embodiment of the invention, the consumption scenario is either washed coal that has been processed by a coal washing plant or raw coal that has not been processed by a coal washing plant.

[0055] In this embodiment of the invention, if the consumption scenario is washed coal processed by a coal washing plant, the coal input is the washed coal input, and the elemental percentage content in the coal is the elemental percentage content in the washed coal, step 203 specifically includes: Step 2031: Generate the total element input of the coal washing plant based on the percentage content of elements in the washed coal and the amount of washed coal input.

[0056] In this embodiment of the invention, by The percentage content of elements in washed coal and the input amount of washed coal are calculated to generate the total element input of the coal washing plant. Among them, PCI i,t,n For coal washing plant n Type t Elements in coal washing i Total input, For coal washing plant n Type t The percentage content of element i in the washed coal. For coal washing plant n Type t The input volume of coal washing and preparation, w For coal washing and preparation.

[0057] Step 2032: Generate the element input amount of the coal product based on the total element input of the coal washing plant, the percentage content of elements in the coal product, and the total mass of elements in the product after coal washing.

[0058] In this embodiment of the invention, the element input amount of the coal product is generated by calculating the total element input of the coal washing plant, the percentage content of elements in the coal product, and the total mass of elements in the product after coal washing using the following formula:

[0059] Among them, F p,i coal products p Middle elements i The output distribution coefficient, M p,i coal products p Middle elements i The percentage content, For elements i In the total mass of the products after coal washing, PCI i,t,n For coal washing plant n Type t Elements in coal washing i Total input, OT p,i coal products p elements i The amount of input.

[0060] In this embodiment of the invention, if the consumption scenario is raw coal that has not been processed by a coal washing plant, the coal input amount is the raw coal input amount, and the element percentage content in the coal is the element percentage content in the raw coal, step 203 specifically includes: generating the element input amount of raw coal based on the element percentage content in the raw coal and the raw coal input amount.

[0061] Specifically, through The elemental percentages in raw coal and the amount of raw coal input are calculated to generate the elemental input values ​​for raw coal. Among these, RCI... i The elements of raw coal iInput volume, Elements in raw coal i percentage content, m r Let r be the amount of raw coal input.

[0062] Step 204: Based on different consumption scenarios, generate element migration features according to element input quantity, regional coal consumption, regional coal transport matrix, and regional coal element content matrix.

[0063] In this embodiment of the invention, if the consumption scenario is washed coal processed by a coal washing plant, the element input amount is the element input amount of the coal product, the regional coal consumption amount is the regional washed coal consumption amount, the regional coal transmission matrix is ​​the regional washed coal transmission matrix, and the regional coal element content matrix is ​​the element content matrix in the regional coal product.

[0064] Specifically, the element quality of regional coal products is generated using the following formula, based on the quality of coal products, the element input of coal products, regional coal washing consumption, regional coal washing transport matrix, and element content matrix of regional coal products. This element quality is then defined as the first element migration feature:

[0065] Where, m a,i,p For the region a coal products p elements in i The quality, i.e., the first element's migration feature; c a,p For products p In the region a Consumption; {t m,n} m,n For products p The transmission matrix; {p a,n,i,p} 1×n For the region a Coal washing plant n Products p elements i Content matrix; OT p,i coal products p elements i The input quantity; {c n,t} 1×n For products p The transmission matrix for each region is constructed based on the region's coal washing consumption; m p For products p . production.

[0066] In this embodiment of the invention, if the consumption scenario is raw coal that has not been processed by a coal washing plant, the regional coal consumption is the regional raw coal consumption, the regional coal transport matrix is ​​the regional raw coal transport matrix, and the regional coal element content matrix is ​​the element content matrix in the regional raw coal.

[0067] Specifically, the elemental input quality of a region is generated based on the region's raw coal consumption, raw coal transport matrix, and elemental content matrix in raw coal using the following formula, and this elemental input quality is determined as the second elemental migration feature:

[0068] Where, m a,i For elements i To the region a The total quality of the input, i.e., the region. a elements i Input quality, also known as: second-element transfer features; c a For the region a Consumption of raw coal; {b m,n} m,n For the raw coal transport matrix of each region; {p a,n,i} 1×n For each region in region a i The elemental content matrix, based on the elements of raw coal i Input RCI i Build; {c n} 1× n The transmission matrix for raw coal in each region is constructed based on the region's raw coal consumption.

[0069] This invention, by constructing a coal input layer and a transport layer, can accurately characterize the distribution of various elements in coal washing products, laying the foundation for tracking the multi-media emission of substances; at the same time, it improves upon previous data and obtains more refined information on the element content in coal consumed in various regions.

[0070] Step 205: Based on the process efficiency parameters and element migration characteristics, generate the preliminary emission amounts of elements corresponding to different by-product types.

[0071] In this embodiment of the invention, the by-product types include flue gas, desulfurization gypsum, and solid waste; the process efficiency parameters include the desulfurization process efficiency, denitrification process efficiency, dust removal process efficiency, and element release rate adopted by the point source.

[0072] This invention provides a method for calculating the allocation of regional total quantities to point sources, thereby achieving a precise mapping from regional input quantities to point-level emission sources. This method establishes the correspondence between regions and point sources by introducing an allocation factor, as detailed below: First, set up regions a The corresponding total number of elements input is This input amount needs to be based on all relevant emission sources within the region. n The activity level data is allocated, and the allocation result for each point source is denoted as... .

[0073] By introducing the allocation factor α The following allocation relationship can be established:

[0074] in: Point source n In elements i Total allocation across dimensions; Indicates region a elements i Total input; α Point source n The allocation factor represents the proportion of the activity level of this point source to the total activity level of all similar point sources in the region.

[0075] The allocation factor is determined as follows: If the area a Contains n For individual coal-fired power plants, the allocation factor for each point source can be determined based on the annual coal consumption of each plant. Allocation factor The calculation formula is:

[0076] Based on the above calculations, the sum of the allocation factors for all point sources satisfies the following condition:

[0077] This method achieves quantitative linkage between regional statistical data and point source monitoring data through a weighted allocation mechanism based on activity levels (such as fuel consumption, power generation, etc.), ensuring the completeness and traceability of the allocation of emissions from each point source.

[0078] In this embodiment of the invention, the calculation formulas for the initial emission amounts of elements corresponding to different by-product types are as follows:

[0079] in, Point source n Elements emitted into the atmosphere i The total amount, that is: the initial emission amount of the elements corresponding to the flue gas; Point source n elements i Total allocation across dimensions; In order to be in x Under the process, elements iRelease rate; Point source n The efficiency of the desulfurization process used; Point source n The efficiency of the denitrification process used; Point source n The efficiency of the dust removal process used; The element input from point source n to desulfurized gypsum i The total amount, i.e., the initial emission amount of elements corresponding to desulfurized gypsum; The remaining elements obtained from mass balance i Ash matter, i.e., the initial emission amount of elements corresponding to solid waste.

[0080] This invention, through the above formula, can clearly define the element migration status of each coal-fired source, not only statistically analyzing the total amount of elements in the atmosphere, but also detailing the comprehensive utilization of solid waste, forming a full-process element monitoring system.

[0081] Step 206: Based on the secondary utilization path parameters and the initial emission amount of the element, generate the multi-media emission amount of the element at the point source.

[0082] In this embodiment of the invention, the secondary utilization path parameters include the allocation factor of the element output to the by-product type and the allocation factor of the element output in the by-product type during the application. Multi-media emissions refer to the emissions through different by-product types.

[0083] In this embodiment of the invention, although over 70% of the ash and desulfurized gypsum are used as byproducts, the unused portion is disposed of through stockpiling. The utilized portion is mostly reused in various industries, entering different media and causing pollution. The formula for calculating this pollution is as follows:

[0084] in, For elements i To by-product type t The total amount of input, i.e., the amount of element emitted in multiple media at a point source; For elements i To by-product type t The allocation factor for the output was obtained through literature review; For elements i The total mass, this data comes from material flow analysis, obtained through the balance method; For use c By-product types g The allocation factor output by element i is also obtained from literature review.

[0085] Based on the above formula, this invention can track the characteristics of cross-industry transformation of elements, allocate them step by step according to the allocation factors of different industries, and clarify the fate of elements.

[0086] Step 207: Based on the MRIO model architecture, construct an environmentally extended multi-regional input-output (EE-MRIO) model according to the element migration characteristics in coal products from different regions and the multi-media emissions of elements at point sources.

[0087] In this embodiment of the invention, the EE-MRIO model constructed for network processing of elements is as follows:

[0088] First, a balance relationship is constructed. The method is based on input-output theory, establishing a balance relationship between total output and demand within the economic system. Here, X is the column vector of total output of the economic system; Y is the column vector of final demand of the economic system; and T is a multi-regional direct input coefficient matrix representing the technological and economic linkages between regions and sectors. (Total output column vector) Output from various regions Vertically stacked, each Each is one A column vector whose elements Representative region Internal Department The total output value. The matrix It is a dimension The block matrix, each sub-block yes Matrix, describing regions To be used in the region Inter-departmental direct input coefficient, sub-block elements In order to be in the region Department An increase of 1 unit of output directly requires a region Department Intermediate inputs (by value). Sub-blocks elements In order to be in the region Department An increase of 1 unit of output directly requires a region Department Intermediate inputs (in terms of value), of which The value of products or services derived from sector k in region r that are consumed as intermediate inputs in the production process of sector l in region s. Total output of sector l in region s. Final demand column vector. Composed of the final use of the product in each region, recorded as the "regional" The final demand for the product is Then the region Total final demand vector For cross-regional aggregation: Final demand column vector Composed of the final use of the product in each region, recorded as the regional use of the product in each region. The final demand for the product is Then the region Total final demand vector For cross-regional aggregation, the equilibrium equation yields a linear relationship between total output and final demand: .in This is the inverse Leontief matrix, whose elements reflect the total direct and indirect output resulting from satisfying a unit of final demand. Finally, environmental intensity is combined with total consumption: final demand. The total environmental impact caused is .in This is a row vector of environmental intensity arranged by sector. Using the above EE-MRIO model, this invention can trace emission pathways and study point source emissions across provinces and involving multiple media.

[0089] Step 208: Using the EE-MRIO model, generate the environmental load based on the multi-media emission of elements at point sources.

[0090] In this embodiment of the invention, the EE-MRIO model is used to trace and redistribute the multi-media emissions of elements at point sources within a macroscopic system, revealing the environmental responsibility driven by regional final consumption, i.e., generating environmental loads from the production side to the consumption side.

[0091] Specifically, the multi-media emissions of elements at point sources are input into the EE-MRIO model, and the environmental load is output.

[0092] This invention couples micro-level point source emission data with macro-level consumption activities to generate a clear environmental load. This not only quantifies the pollution transfer implied by inter-regional trade, providing a precise data foundation for implementing consumption-based carbon responsibility assessment and ecological compensation, but also provides crucial decision-making basis for optimizing absorption pathways in subsequent steps.

[0093] Step 209: Using a linear programming framework, based on the environmental load and pre-set constraints, construct and solve the absorption path optimization function with the objectives of minimizing total cost and maximizing environmental benefits, and generate the optimal absorption path.

[0094] In this embodiment of the invention, in order to optimize the absorption path, the following linear programming framework needs to be constructed to minimize the comprehensive objective function Z:

[0095] Among them, c To start from point source n To the disposal point j The economic cost of transporting each ton of solid waste reflects the unit transportation cost under different transportation routes. Let be the decision variable, representing the variable originating from the point source. n Transport to disposal point j The solid waste mass, used to describe the flow direction and distribution of waste, is the core optimization object of the model. k This refers to the additional costs or fixed expenses incurred during inter-regional transportation, used to avoid long-distance transportation and make the model more consistent with real-world economic conditions. As a binary auxiliary variable, when the transportation route n→j The value is 1 for cross-regional transportation and 0 otherwise, used to distinguish between intra-regional and inter-regional transportation and trigger corresponding cost constraints. To start from point source n The environmental impact factor caused by transporting a unit mass of solid waste to disposal point j is used to characterize the environmental cost of the transportation process. α is the environmental benefit weighting coefficient, used to balance the trade-off between economic costs and environmental impact. When the value of α is large, the model will place greater emphasis on environmental emission reduction benefits. W Point source n The total amount of solid waste generated is used to limit the maximum transportable waste quantity at that point source, ensuring that its output does not exceed its generation capacity. For disposal points j The maximum processing or absorption capacity is used to constrain its receiving limit and prevent overload operation. L Point source n To the disposal point j The transport distance (in kilometers) is used to measure the spatial constraints of a transport route. The maximum permissible transport distance (in kilometers) is used to limit the model solution to within the feasible range of actual transport. ≥0 indicates that the transport volume is a non-negative real number, y ∈{0,1} represents a binary logic constraint. This invention, through this model, can optimize the inter-provincial transportation and intra-provincial disposal routes of solid waste, minimizing transportation and treatment costs while maximizing environmental benefits, while meeting the needs of all sources and disposal sites.

[0096] Furthermore, the objective function Minimize ultimately aims to minimize the total cost of solid waste transportation and disposal while maximizing environmental benefits, such as reducing greenhouse gas emissions or avoiding other negative environmental impacts. The objective function can be expressed as:

[0097] Where: c To start from point source n To the disposal point j The unit transportation cost per ton of solid waste is used to characterize the economic expenditure in the transportation process. Let be the decision variable, representing the variable originating from the point source. n To the disposal point j The actual quantity of solid waste transported is used to determine the allocation plan for waste logistics. k This refers to the unit surcharges or fixed costs incurred during inter-regional transportation, reflecting the additional economic burden caused by long transportation distances between regions. As a binary auxiliary variable, when the transportation route n→j A value of 1 is assigned when the transport involves inter-regional transportation; otherwise, a value of 0 is assigned. This is used to determine whether the inter-regional cost item is triggered. α is the environmental benefit weighting coefficient, used to establish a balance between economic costs and environmental impacts. The larger the α value, the more the model tends to pursue environmental emission reduction benefits. To start from point source n To the disposal point j The environmental impact factor generated per unit mass of solid waste during transportation reflects the level of carbon emissions or other environmental loads during transportation and treatment. In the above formula, the first term... The total economic cost of solid waste transportation and inter-regional transportation; Item 2 The environmental benefit term is used to quantify the contribution to emission reduction and reflect environmental value in the overall objectives. The model achieves the optimal balance between economic costs and environmental benefits by minimizing the comprehensive objective function Z.

[0098] Step 210: Using a Geographic Information System (GIS), the multi-media emissions of elements at point sources are rasterized to generate an emission intensity distribution map. In this embodiment of the invention, a unified geographic coordinate system (such as WGS1984) is used to divide the geographic area into regular spatial raster units. As an optional solution, the resolution of the spatial raster unit is set to 12km × 12km, which can ensure a macroscopic representation of the geographic area while taking into account the detail resolution at the regional level. The dataset containing the precise latitude and longitude information of point sources and the multi-media emissions of their corresponding elements is imported into the GIS platform. The emission amount of each point source is regarded as the attribute value of its location. Based on the latitude and longitude coordinates of the point sources, spatial interpolation or direct allocation methods are used to distribute the discrete point source emission data into the divided spatial raster units. In this invention, for each grid cell, the system identifies and counts all point sources falling within its boundary range; the emissions of specific elements from all point sources within the grid are summed to obtain the total emissions for that grid; alternatively, for sparse point source areas, spatial interpolation algorithms (such as inverse distance weighting or Kriging interpolation) can be used to estimate the grid value based on the emissions of neighboring point sources; finally, each grid cell is assigned a value representing the total element emissions in that area. In this embodiment, the processed grid data layer is color-rendered based on its emission values ​​to generate an element emission intensity distribution map. As an optional approach, a gradient color band from cool to warm tones can be used to visually represent emission intensities from low to high. This generates one or more element emission intensity distribution maps (by element or by medium). This map clearly displays the macroscopic pattern and core hotspot areas of emissions using spatial language.

[0099] Step 211: Based on the element emission intensity distribution map, the optimal disposal path and the acquired area source data are rasterized to generate an element emission distribution map of a multi-scale coupled network. In this embodiment of the invention, for dispersed emission sources that are difficult to characterize with specific locations (such as residential open burning, fugitive emissions, etc.), their provincial or municipal total statistical data are obtained. Using area source data such as population distribution, GDP density, and land use type, the area source data is allocated to a raster network with the same resolution as the element emission intensity distribution map in the GIS platform through a spatial allocation model, generating an area source emission intensity raster map; the optimal disposal path is spatially visualized. Each path includes the source location (solid waste generation point), disposal location (solid waste utilization or disposal point), and transmission volume. In GIS, this is represented as a vector line layer connecting the source and the disposal location; the multiple spatial layers obtained above are overlaid and merged to generate an element emission distribution map of a multi-scale coupled network. The elemental emission distribution map of the multi-scale coupled network not only demonstrates the spatial heterogeneity of emission intensity but also clearly indicates the cross-regional flow direction and flux of solid waste and its contained elements through superimposed absorption paths, achieving an integrated spatial expression of static emission distribution and dynamic material flow. This invention, through the fusion and rasterization of point source and area source data, can comprehensively understand the emission characteristics of elements in coal and realize the monitoring of elemental emissions within a geographical area. This invention integrates multiple types of databases, GIS, and material flow analysis models to perform network tracking and source tracing of carbon pollution flow and multi-media emissions from all coal-fired sources within a geographical area, with particular emphasis on the monitoring system for spatial transfer of carbon pollution emissions from production to consumption and cross-industry and cross-media transfer. The following specific embodiment verifies the effectiveness of the elemental emission detection method of the multi-scale coupled network in the coal industry chain of this invention. This embodiment selects mercury (Hg) as the target element: Figure 4 This is a schematic diagram of a multi-scale energy-material-carbon-pollution coupled network simulation system for the coal industry chain provided in an embodiment of the present invention, as shown below. Figure 4 As shown, the coal flow distribution in combined heat and power (CHP) includes heating, wastewater treatment, coking, steelmaking, landfilling, construction, industrial filtration, cement, and rivers. The flow directions include water flow, material flow, energy flow, and potential other flows. Firstly, regarding the distribution characteristics of Hg in the washing and beneficiation process, this invention selected several representative coal washing plants in multiple typical coal-producing areas to conduct on-site sampling and testing. Samples collected included clean coal, middlings, coal slime, and coal gangue, and the mass fraction of Hg in these samples was determined. Simultaneously, the raw coal feed rate, product output, and relevant process parameters of the corresponding plants were obtained. Based on the principles of mass conservation and material flow balance, the Hg input factor and output distribution factor for various coal products were quantitatively calculated, as shown in Table 1.

[0100] Table 1

[0101] A localized Hg content dataset was established by weighting the actual output of each coal washing plant. Taking 2020 as an example, the total Hg input corresponding to the raw coal input in the washing and beneficiation stage was approximately 437 tons, of which about 62% was ultimately enriched in coal gangue. The system incorporates literature review results to establish background Hg content data in raw coal for each province, enhancing the accuracy of source pollution identification. After completing the construction of the dataset and factor library, the system dynamically analyzed the migration path of Hg in the coal system in 2020 based on the Material Flow Analysis (MFA) model, tracking its multi-scale flow across stages, industries, and regions. The results show that approximately 825 tons of Hg were introduced into the coal system in 2020. Of these, 437 tons entered the washing and beneficiation stage, and 388 tons were directly supplied to end-user industries in the form of raw coal. During the washing process, Hg undergoes significant redistribution. Among them, about 83 tons of Hg are enriched in middlings, about 36 tons in coking coal, and as much as 128 tons of Hg are enriched in coal gangue, which significantly indicates that the washing plant is a key node for pollutants.

[0102] Figure 5 A multi-media emission flow diagram for Hg element flow direction is provided in an embodiment of the present invention, such as... Figure 5 As shown in the figure, the numbers represent the amount of coal in this environment, in tons (t). Coal sources include mining and imports, flowing to thermal coal washing, coking coal washing, and direct use; further flowing to thermal coal, gangue, middlings, refined coal, and coal slime; further leaving behind electricity and heat, cement, industrial filtration, steel, domestic boilers, and others; further flowing to fly ash, blast furnace slag, sintering dust, bottom ash, gypsum, and wastewater; further flowing to cement, soil, products, atmosphere, landfill, mineral extraction, and water bodies. This invention uses a full-sample microscopic dataset as input and a localized elemental content dataset as the computational rules to dynamically simulate the complete life cycle of mercury in the coal system in 2020. This simulation process not only tracks the flow of coal as an energy and material carrier, but more importantly, it embeds the migration and transformation of mercury into these flows. Based on the analysis results, this system constructs a multi-media carbon pollution emission database with industry, process, and medium dimensions, systematically characterizing the final fate of Hg in the coal system (e.g., Figure 3(As shown in the image). Analysis shows that of the 825 tons of Hg, only 155 tons (18.8%) were emitted into the atmosphere as flue gas, while approximately 409 tons (49.6%) entered industrial systems such as building materials through the resource utilization of by-products such as fly ash and desulfurization gypsum, solidifying in products or being released again. Another approximately 219 tons (26.5%) entered landfills with unused solid waste. These results reveal the trend of mercury pollution migrating from the atmosphere to solid media, indicating that traditional end-of-pipe treatment is insufficient to comprehensively control environmental risks. The system also revealed the "transfer effect" of pollution between industries through scenario analysis. Taking the coal washing process as an example, although primary emission reduction (22.9 tons) was achieved at the main product end, secondary emissions of 25.9 tons were generated due to the subsequent combustion and utilization of by-products, particularly evident in the cement industry (an increase of 17.2 tons), highlighting the pollution risks of cross-industry utilization of coal by-products. To improve the spatial identification accuracy of hazardous element emissions from coal mining systems, this invention constructs a multi-media carbon pollution emission database with a resolution of 12km×12km and performs spatial rasterization processing to achieve high-precision spatial representation of emissions. The system integrates point source and area source emission data within a geographical area and combines them with geographical coordinates to perform emission intensity rasterization, constructing a high-resolution spatial emission map covering the geographical area.

[0103] Figure 6 This is a schematic diagram illustrating the spatial gridded emission of Hg under a coal washing scenario and a coal washing-unwashed coal scenario, as provided in an embodiment of the present invention. Figure 6 As shown, the left figure illustrates the spatial distribution of Hg emission intensity within a geographical area under actual coal washing and beneficiation scenarios. The emission range includes 0 to 0.1, 0.1 to 1, 1 to 3, 3 to 5, and greater than 5, with units of kilograms per grid cell (kg / grid). The emission values ​​are mapped to 12km × 12km grid cells, reflecting the actual emission load from the coal washing process and its byproduct utilization in each region, thus identifying key areas for pollution control. The right figure shows the emission difference ΔHg between washed and unwashed coal scenarios, further revealing the impact of the coal washing process on the emission pattern. The right figure uses the difference between washed and unwashed emissions as the calculation method to identify the actual increase or decrease in regional pollution levels caused by coal washing. The emission difference range includes less than -1, -1 to 0, 0 to 1, 1 to 2, and greater than 2, with units of kilograms per grid cell (kg / grid). The difference results show that some regions achieve local emission reductions due to the washing and processing stage, while other regions bear part of the external emission load due to receiving washing and processing by-products from other provinces. This invention not only achieves a refined spatial representation of emission sources and pollution trends, but also reveals the pollution redistribution effect caused by industrial chain relocation between regions, providing important support for cross-regional collaborative governance, management of washing and processing by-product transportation, and the formulation of differentiated emission control strategies.

[0104] It is worth noting that the acquisition, storage, use, and processing of data in the technical solution of this application all comply with relevant laws and regulations. The user information in the embodiments of this application was obtained through legal and compliant means, and the acquisition, storage, use, and processing of user information have been authorized and agreed upon by the client.

[0105] It is worth noting that the information collected in this application is information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of this data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, and necessary confidentiality measures have been taken. This process does not violate public order and good morals, and a corresponding access point is provided for the user to choose to authorize or refuse. It is also worth noting that the technical solution provided in this application offers users a corresponding access point to choose whether to agree to or refuse the automated decision-making results; if the user chooses to refuse, the process proceeds to the expert decision-making stage.

[0106] The technical solution of the element emission detection method for a multi-scale coupled network in the coal industry chain provided in this invention involves constructing a full-sample micro-dataset and a localized element content dataset for the coal industry chain; generating element migration characteristics in coal products from different regions based on the full-sample micro-dataset and the localized element content dataset according to different consumption scenarios; calculating multi-media emissions of elements at point sources based on the element migration characteristics in coal products from different regions and the information of each point source using mass balance and material flow balance methods; constructing an environmentally extended multi-regional input-output model and optimizing the absorption path based on the element migration characteristics in coal products from different regions and the multi-media emissions of elements at point sources; and rasterizing multi-source data based on the optimal absorption path and the multi-media emissions of elements at point sources to generate an element emission distribution map of a multi-scale coupled network, thus constructing a full-chain energy-material-carbon-pollution coupled network. This enables systematic tracking of carbon and pollutant migration paths throughout the entire coal industry chain, precise quantification of cross-media transfer and secondary emissions of pollutants, and provides quantitative decision support for multi-objective collaborative management.

[0107] Figure 7 This is a schematic diagram of an element emission detection device for a multi-scale coupled network in a coal industry chain, provided by an embodiment of the present invention. This device is used to execute the aforementioned element emission detection method for a multi-scale coupled network in a coal industry chain. Figure 7 As shown, the device includes: a multi-source database construction unit 11, an element migration feature generation unit 12, a multi-media emission calculation unit 13, a disposal path optimization unit 14, and an element emission distribution detection unit 15.

[0108] The multi-source database construction unit 11 is used to construct a full-sample micro-dataset and a localized element content dataset for the coal industry chain.

[0109] The element migration feature generation unit 12 is used to generate element migration features in coal products from different regions based on the full sample micro dataset and the localized element content dataset, according to different consumption scenarios.

[0110] The multi-media emission calculation unit 13 is used to perform multi-media emission calculations based on the element migration characteristics in coal products from different regions and information from each point source, using mass balance and material flow balance methods, and to generate the multi-media emission amount of elements at point sources.

[0111] The absorption path optimization unit 14 is used to construct an environmentally extended multi-regional input-output model and optimize the absorption path based on the element migration characteristics in coal products in different regions and the multi-media emission of elements at point sources, thereby generating the optimal absorption path.

[0112] The element emission distribution detection unit 15 is used to perform multi-source data rasterization based on the optimal absorption path and the multi-media emission amount of elements at point sources, and generate an element emission distribution map of a multi-scale coupled network.

[0113] In this embodiment of the invention, the multi-source database construction unit 11 is specifically used to clean, align and fuse the multi-source datasets of the coal industry chain to construct a full-sample micro dataset; to sample coal from mining areas of the coal industry chain and perform elemental content analysis to generate a localized elemental content dataset.

[0114] In this embodiment of the invention, the full-sample micro-dataset includes coal input, regional coal consumption, regional coal transport matrix, and coal products; the localized element content dataset includes the percentage content of elements in coal, the percentage content of elements in coal products, and the regional coal element content matrix; the element migration feature generation unit 12 is specifically used to generate element input based on coal input, the percentage content of elements in coal, and the percentage content of elements in coal products according to different consumption scenarios; and to generate element migration features based on element input, regional coal consumption, regional coal transport matrix, and regional coal element content matrix according to different consumption scenarios.

[0115] In this embodiment of the invention, the consumption scenario is either washed coal processed by a coal washing plant or raw coal that has not been processed by a coal washing plant. The element migration feature generation unit 12 is specifically used to generate the total element input of the coal washing plant based on the element percentage content in the washed coal and the amount of washed coal input if the consumption scenario is washed coal processed by a coal washing plant; and to generate the element input of the coal product based on the total element input of the coal washing plant, the element percentage content in the coal product, and the total mass of the elements in the product after coal washing if the consumption scenario is raw coal that has not been processed by a coal washing plant.

[0116] In this embodiment of the invention, the element migration feature generation unit 12 is specifically used to generate the element quality of the regional coal product based on the quality of the coal product, the element input amount of the coal product, the regional coal washing consumption, the regional coal washing transfer matrix, and the element content matrix of the regional coal product if the consumption scenario is washed coal processed by a coal washing plant, and to determine the element quality of the regional coal product as the first element migration feature; if the consumption scenario is raw coal not processed by a coal washing plant, it generates the regional element input quality based on the regional raw coal consumption, the regional raw coal transfer matrix, and the regional raw coal element content matrix, and to determine the regional element input quality as the second element migration feature.

[0117] In this embodiment of the invention, the point source information includes by-product type, process efficiency parameters, and secondary utilization path parameters; the multi-media emission calculation unit 13 is specifically used to generate the initial emission amount of elements corresponding to different by-product types based on the process efficiency parameters and element migration characteristics; and to generate the multi-media emission amount of elements at the point source based on the secondary utilization path parameters and the initial emission amount of elements.

[0118] In this embodiment of the invention, the absorption path optimization unit 14 is used to construct an environmentally extended multi-regional input-output model based on a multi-regional input-output model architecture, according to the element migration characteristics in coal products of different regions and the multi-media emissions of elements at point sources; through the environmentally extended multi-regional input-output model, an environmental load is generated based on the multi-media emissions of elements at point sources; through a linear programming framework, based on the environmental load and pre-set constraints, with the objectives of minimizing total cost and maximizing environmental benefits, the absorption path optimization function is constructed and solved to generate the optimal absorption path.

[0119] In this embodiment of the invention, the element emission distribution detection unit 15 is specifically used to rasterize the multi-media emission of elements at point sources through a geographic information system to generate an element emission intensity distribution map; based on the element emission intensity distribution map, it rasterizes the optimal absorption path and the acquired area source data to generate an element emission distribution map of a multi-scale coupled network.

[0120] In this embodiment of the invention, a full-sample micro-dataset and a localized element content dataset of the coal industry chain are constructed. Based on the full-sample micro-dataset and the localized element content dataset, element migration characteristics in coal products from different regions are generated according to different consumption scenarios. Using mass balance and material flow balance methods, multi-media emission calculations are performed based on the element migration characteristics in coal products from different regions and information from each point source, generating multi-media emissions of elements at point sources. Based on the element migration characteristics in coal products from different regions and the multi-media emissions of elements at point sources, an environmentally extended multi-regional input-output model is constructed and the absorption path is optimized to generate the optimal absorption path. Based on the optimal absorption path and the multi-media emissions of elements at point sources, multi-source data is rasterized to generate an element emission distribution map of a multi-scale coupled network, constructing a full-chain energy-material-carbon-pollution coupled network. This enables systematic tracking of carbon and pollutant migration paths throughout the entire coal industry chain, precise quantification of cross-media transfer and secondary emissions of pollutants, and provides quantitative decision support for multi-objective collaborative management.

[0121] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer device, specifically, a computer device can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices. This invention provides a computer device including a memory and a processor. The memory stores information including program instructions, and the processor controls the execution of the program instructions. When the program instructions are loaded and executed by the processor, they implement the steps of the embodiments of the above-described method for detecting elemental emissions in a multi-scale coupled network of the coal industry chain. For a detailed description, please refer to the embodiments of the above-described method for detecting elemental emissions in a multi-scale coupled network of the coal industry chain.

[0122] The following is for reference. Figure 8 It shows a schematic diagram of the structure of a computer device 600 suitable for implementing embodiments of this application. For example... Figure 8As shown, the computer device 600 includes a central processing unit (CPU) 601, which can perform various appropriate tasks and processes according to programs stored in read-only memory (ROM) 602 or programs loaded from storage section 608 into random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the computer device 600. The CPU 601, ROM 602, and RAM 603 are interconnected via bus 604. An input / output (I / O) interface 605 is also connected to bus 604. The following components are connected to the I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including cathode ray tube (CRT), liquid crystal feedback (LCD), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A driver 610 is also connected to the I / O interface 605 as needed. Removable media 611, such as disks, optical discs, magneto-optical discs, semiconductor memories, etc., are installed on drive 610 as needed so that computer programs read from them can be installed as needed, such as storage units 608.

[0123] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program including program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and / or installed from removable medium 611. Computer-readable media include permanent and non-permanent, removable and non-removable media; information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient media, such as modulated data signals and carrier waves. For ease of description, the above devices are described by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware components.

[0124] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0126] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The acquisition, storage, use, and processing of data in the technical solution of this application all comply with the relevant provisions of national laws and regulations.

[0127] It should be noted that in the embodiments of this application, certain existing solutions in the industry, such as software, components, and models, may be mentioned. These should be considered exemplary and intended only to illustrate the feasibility of implementing the technical solutions of this application, but do not imply that the applicant has already used or necessarily used such solutions. Those skilled in the art should understand that the embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0128] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices. The various embodiments in this specification are described in a progressive manner, with reference to each other for similar or identical parts. Each embodiment focuses on describing the differences from other embodiments. In particular, system embodiments are described simply because they are substantially similar to method embodiments; relevant details can be found in the descriptions of the method embodiments.

[0129] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for detecting elemental emissions in a multi-scale coupled network of a coal industry chain, characterized in that, The method includes: Construct a full-sample micro-dataset and a localized element content dataset for the coal industry chain; Based on different consumption scenarios, and using the full-sample micro-dataset and local element content dataset, element migration characteristics of coal products in different regions are generated. Using mass balance and material flow balance methods, multi-media emission calculations are performed based on the element migration characteristics in coal products from different regions and information from various point sources, generating the multi-media emission amounts of elements at point sources. Based on the element migration characteristics and multi-media emissions of elements in coal products from different regions, an environmentally extended multi-regional input-output model is constructed and the absorption path is optimized to generate the optimal absorption path. Based on the optimal absorption path and the multi-media emission of elements at point sources, multi-source data rasterization is performed to generate an element emission distribution map of a multi-scale coupled network.

2. The element emission detection method for a multi-scale coupled network in the coal industry chain according to claim 1, characterized in that, The construction of the full-sample micro-dataset and localized elemental content dataset for the coal industry chain includes: The acquired multi-source datasets of the coal industry chain are cleaned, aligned, and fused to construct the full-sample micro dataset. Coal samples from mining areas in the coal industry chain are sampled and their elemental content is analyzed to generate the localized elemental content dataset.

3. The element emission detection method for a multi-scale coupled network in the coal industry chain according to claim 1, characterized in that, The full-sample micro-dataset includes coal input, regional coal consumption, regional coal transport matrix, and coal products. The localized element content dataset includes the percentage of elements in coal, the percentage of elements in coal products, and the regional coal element content matrix. The step of generating element migration characteristics in coal products from different regions based on the full-sample micro-dataset and the localized element content dataset, according to different consumption scenarios, includes: Based on different consumption scenarios, the element input amount is generated according to the coal input amount, the element percentage content in the coal, and the element percentage content in the coal product. Based on different consumption scenarios, element migration features are generated according to the element input amount, regional coal consumption, regional coal transport matrix, and regional coal element content matrix.

4. The element emission detection method for a multi-scale coupled network in the coal industry chain according to claim 3, characterized in that, The consumption scenario refers to washed coal that has been processed by a coal washing plant or raw coal that has not been processed by a coal washing plant. The generation of element input quantities based on the coal input quantity, the element percentage content in the coal, and the element percentage content in the coal product, according to different consumption scenarios, includes: If the consumption scenario is washed coal processed by a coal washing plant, the total element input of the coal washing plant is generated based on the element percentage content in the washed coal and the input amount of the washed coal. The element input amount of the coal product is generated based on the total element input amount of the coal washing plant, the percentage content of elements in the coal product, and the total mass of elements in the product after coal washing. If the consumption scenario involves raw coal that has not been processed by a coal washing plant, the element input amount of the raw coal is generated based on the element percentage content in the raw coal and the raw coal input amount.

5. The element emission detection method for a multi-scale coupled network in the coal industry chain according to claim 4, characterized in that, The process of generating element migration features based on different consumption scenarios, including the element input quantity, regional coal consumption, regional coal transport matrix, and regional coal element content matrix, includes: If the consumption scenario is washed coal processed by a coal washing plant, the element quality of the regional coal product is generated based on the quality of the coal product, the element input of the coal product, the regional coal washing consumption, the regional coal washing transfer matrix, and the element content matrix of the regional coal product, and the element quality of the regional coal product is determined as the first element migration feature. If the consumption scenario is raw coal that has not been processed by a coal washing plant, the element input quality of the region is generated based on the region's raw coal consumption, the region's raw coal transport matrix, and the element content matrix of the region's raw coal, and the element input quality of the region is determined as the second element migration feature.

6. The element emission detection method for a multi-scale coupled network in the coal industry chain according to claim 1, characterized in that, Point source information includes by-product type, process efficiency parameters, and secondary utilization path parameters; The method employs mass balance and material flow balance to calculate multi-media emissions of elements at point sources based on element migration characteristics in coal products from different regions and information from various point sources. This calculation generates the multi-media emissions of elements at point sources, including: Based on the process efficiency parameters and element migration characteristics, the initial emission amounts of elements corresponding to different by-product types are generated. Based on the secondary utilization path parameters and the initial emission amount of the element, the multi-media emission amount of the element at the point source is generated.

7. The element emission detection method for a multi-scale coupled network in the coal industry chain according to claim 1, characterized in that, Based on the element migration characteristics of coal products in different regions and the multi-media emissions of elements at point sources, an environmentally extended multi-regional input-output model is constructed and the absorption path is optimized to generate the optimal absorption path, including: Based on the multi-regional input-output model architecture, the environmental extended multi-regional input-output model is constructed according to the element migration characteristics in coal products from different regions and the multi-media emission of elements at point sources. The environmental load is generated based on the multi-regional input-output model of the environment extension and the multi-media emission of the elements at point sources. Using a linear programming framework, based on the environmental load and pre-set constraints, and with the objectives of minimizing total cost and maximizing environmental benefits, an optimization function for the absorption path is constructed and solved to generate the optimal absorption path.

8. The method for detecting elemental emissions in a multi-scale coupled network of the coal industry chain according to claim 1, characterized in that, The process of rasterizing multi-source data based on the optimal absorption path and the multi-media emission of elements at point sources to generate an element emission distribution map of a multi-scale coupled network includes: Using a geographic information system, the multi-media emissions of the elements at point sources are rasterized to generate an element emission intensity distribution map. Based on the element emission intensity distribution map, the optimal absorption path and the acquired area source data are rasterized to generate an element emission distribution map of a multi-scale coupled network.

9. An element emission detection device for a multi-scale coupled network in the coal industry chain, characterized in that, The device includes: Multi-source database construction unit, used to construct full-sample micro-datasets and localized element content datasets for the coal industry chain; The element migration feature generation unit is used to generate element migration features in coal products from different regions based on the full sample micro dataset and the localized element content dataset, according to different consumption scenarios. The multi-media emission calculation unit is used to perform multi-media emission calculations based on the element migration characteristics in coal products from different regions and information from various point sources using mass balance and material flow balance methods, and to generate the multi-media emission amount of elements at point sources. The disposal path optimization unit is used to construct an environmentally extended multi-regional input-output model and optimize the disposal path based on the element migration characteristics of coal products in different regions and the multi-media emission of elements at point sources, and generate the optimal disposal path. The element emission distribution detection unit is used to perform multi-source data rasterization based on the optimal absorption path and the multi-media emission amount of elements at point sources, and generate an element emission distribution map of a multi-scale coupled network.

10. A computer-readable medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the element emission detection method of the multi-scale coupled network of the coal industry chain as described in any one of claims 1 to 8.

11. A computer device comprising a memory and a processor, the memory for storing information including program instructions, and the processor for controlling the execution of the program instructions, characterized in that, When the program instructions are loaded and executed by the processor, they implement the element emission detection method of the multi-scale coupled network of the coal industry chain as described in any one of claims 1 to 8.

12. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the element emission detection method of the multi-scale coupled network of the coal industry chain as described in any one of claims 1 to 8.

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