City-scale-oriented multi-source heterogeneous data fusion carbon emission spatial distribution simulation method

Abstract

The invention discloses an urban scale-oriented multi-source heterogeneous data fusion carbon emission spatial distribution simulation method, and solves the problems of low spatial resolution and insufficient accuracy of urban carbon emission spatial distribution simulation estimation. Comprising the steps of defining an urban carbon emission accounting range; collecting multi-source heterogeneous data; calculating the consumption of main energy types of seven industry departments under the urban scale; correcting the energy consumption of seven industry departments of the city; matching the seven industry departments with corresponding urban building types, and establishing a corresponding relationship between the energy consumption of the urban industry departments and building function application types; calculating the carbon emission; and a refined energy consumption carbon emission space distribution model is constructed, and the carbon emission space is distributed to various single buildings. According to the method, multi-source data are comprehensively utilized, high-resolution and dynamic estimation of urban scale carbon emission spatial distribution is achieved, and the limitation that an existing method is coarse in spatial resolution and difficult to quantitatively analyze carbon emission of different energy consumption departments is overcome.

Description

Technical Field

[0001] The present invention relates to the field of refined carbon emission accounting for cities, and particularly to a method for simulating the spatial distribution of carbon emissions through the fusion of multi-source heterogeneous data at the urban scale. Background Art

[0002] Global climate change has become a severe challenge faced by humanity. The burning of fossil fuels is the main cause of climate change intensification, accounting for more than 75% of global greenhouse gas emissions and nearly 90% of all carbon dioxide emissions. As an important carrier of human production and life, cities have much higher energy consumption and carbon emission intensity than other regions, and are an important source of global carbon emissions, with their carbon emissions accounting for more than 70% of the global total. According to a report by the International Energy Agency (IEA), by 2050, the global urban population will increase by at least 20%, and the urban energy demand will also increase significantly. Therefore, accurately quantifying and analyzing the carbon emissions generated by urban energy consumption and deeply understanding its spatio-temporal distribution characteristics are of great significance for understanding the evolution law of urban carbon emissions, formulating effective control policies, and enabling countries and governments to achieve emission reduction targets and promote global response to climate change.

[0003] Due to data acquisition limitations, current methods for simulating the spatio-temporal distribution of carbon emissions in Chinese cities mainly estimate based on carbon emission monitoring satellite data, population distribution, and night light data, etc. These methods have limitations in spatial resolution. For example, the spatial resolution of night light data is only 1 km. In addition, existing methods are also difficult to refine the quantification and analysis of carbon emissions from different energy consumption sectors (civil, industrial, commercial buildings, etc.) within the city.

[0004] In recent years, with the progress of remote sensing technology, the simulation method of urban carbon emission spatial distribution mainly relies on the total urban carbon emissions, combined with satellite data for carbon emission monitoring, population distribution, and night light data, etc., to spatially process urban carbon emissions. This method first calculates the total carbon emissions based on urban energy consumption data, and then distributes the total urban carbon emissions in the spatial dimension through weight allocation according to the night light intensity, population quantity, and the proportion of carbon dioxide concentration in the whole city within the urban grid. This technology utilizes the characteristics of high spatio-temporal resolution of remote sensing data and can achieve a preliminary estimation of the spatio-temporal distribution of urban carbon emissions. However, in depicting the differences in carbon emission intensities at fine scales within the city and among different sectors, this technology still has limitations. For example, industrial enterprises such as urban power generation and heating plants are usually strong carbon emission point sources, but when applying this technology to estimate the spatio-temporal distribution of urban carbon emissions, there may be a serious underestimation of the carbon emissions in these areas, and thus an overestimation of the carbon emissions of urban civil buildings. This estimation deviation stems from the lack of fine discrimination and quantification capabilities for different carbon emission sources within the city in the existing methods, resulting in a certain difference between the estimation results and the actual carbon emission spatial distribution.

[0005] In view of the deficiencies of the existing technology, the present invention aims to provide a method for estimating the spatio-temporal distribution of urban carbon emissions with high spatio-temporal resolution based on the fusion of multi-source heterogeneous data. Summary of the Invention

[0006] The object of the present invention is to provide a simulation method for the spatial distribution of carbon emissions by fusing multi-source heterogeneous data at the urban scale to solve the technical problems of low spatial resolution and insufficient accuracy in the simulation and estimation of the spatial distribution of urban carbon emissions.

[0007] To achieve the above object, the present invention provides the following technical solutions: A simulation method for the spatial distribution of carbon emissions by fusing multi-source heterogeneous data at the urban scale provided by the present invention includes the following steps: Step 1: Define the scope of urban carbon emission accounting; Step 2: Collect multi-source heterogeneous data; Step 3: Based on the provincial energy balance sheet, combined with the socio-economic indicators of different industrial sectors, calculate the consumption of the main energy types of the seven major industrial sectors at the urban scale; Step 4: Amend the energy consumption of the seven major industrial sectors in the city based on the building energy consumption splitting method of the energy balance sheet; Step 5: Match the seven major industrial sectors with the corresponding urban building types, and establish the corresponding relationship between the energy consumption of urban industrial sectors and the building function use categories; Step 6: Calculate the carbon emissions based on the energy consumption and carbon emission factors of different building types and energy types; Step 7: Integrate multi-source heterogeneous data, construct a refined spatial distribution model of energy consumption carbon emissions, allocate the carbon emissions spatially to various individual buildings, and achieve refined visualization of urban carbon emissions.

[0008] Further, in Step 1, urban carbon emissions are divided into two major categories: direct carbon emissions and indirect carbon emissions. Direct carbon emissions include physical emissions generated within the urban boundary, mainly from fossil energy fuel combustion activities and industrial production processes. Indirect carbon emissions include the carbon emissions contained in the electricity and heat input into buildings from outside, and the heat part of which includes the heat sent into buildings from cogeneration and district boilers.

[0009] Further, in Step 2, the multi-source heterogeneous data includes a spatial data set and a non-spatial data set. The spatial data set includes individual building distribution data, community-level census data, and POI data; the non-spatial data set includes provincial energy balance sheet statistical data, provincial and municipal social and economic indicator data, the list of industries to which urban industrial enterprises belong, information on key polluting enterprises, and the carbon content, lower calorific value, and oxidation rate corresponding to energy types.

[0010] Further, in Step 3, the seven major industry sectors include industry; transportation, warehousing, and postal services; wholesale and retail, accommodation and catering; others; urban residents' living; rural residents' living; thermal power generation; the calculation formula for the energy consumption of energy types is as follows: (1); In the formula, AD represents energy consumption, i represents different industry types, and A represents the statistical indicators selected for different industries.

[0011] Further, in Step 4, the method for correcting the energy consumption of the seven major industry sectors in the city is as follows: Determine the basic amount of building energy consumption; Remove the non-building energy consumption from the basic amount of building energy consumption; Supplement the building energy consumption included in the transportation sector.

[0012] Further, in Step 6, the carbon emissions accounting for different building types and energy types is as follows: (1) Calculate the carbon emission factor based on the lower calorific value of the selected energy type, the carbon content per unit energy calorific value, and the oxidation rate. The specific calculation formula is as follows: (2); Among them, I is the carbon emission factor, j is the energy type, L is the lower calorific value of the energy, P is the carbon content per unit energy calorific value (kJ / m 3 Or kJ / kg), O is the oxidation rate during the energy combustion process (%), and 44 / 12 is the conversion coefficient for converting carbon to carbon dioxide; (2) Based on the energy consumption of different building types and the carbon emission factors of energy types, calculate the carbon emissions of each building type. The specific calculation formula is as follows: (3); Among them, E is the total carbon emissions generated by anthropogenic energy consumption, m is different building types, j is energy types, C is the physical quantity of energy consumption, and I is the carbon emission factor.

[0013] Furthermore, in step 7, the specific steps include: According to the correspondence between the seven major industry sectors in the city and the affiliated building types, divide the calculated carbon emissions into three categories: carbon emissions from residential buildings, carbon emissions from the tertiary industry buildings, and carbon emissions from industrial enterprises; Comprehensively consider different factors affecting the three major carbon emission areas, select spatial distribution indicators for each type of carbon emission, and construct a refined spatial distribution model of energy consumption carbon emissions; Apply the refined spatial distribution model of energy consumption carbon emissions to accurately calculate and simulate the spatial distribution of the carbon emissions of three types of buildings: residential buildings, tertiary industry buildings, and industrial enterprises.

[0014] Furthermore, the calculation steps of the carbon emissions from residential buildings are specifically as follows: Step 711: Screen the plots in the urban single-building distribution data where the building types belong to urban residential buildings and rural residential houses, and identify the census blocks containing these plots; Step 712: According to the weight of the population quantity of each census block in the total population quantity of the whole city, allocate the corrected annual carbon emissions of urban and rural residents' living to the corresponding census blocks to obtain the community-level carbon emissions of residents' living. The specific calculation formula is as follows: (4); In the formula, E i represents the total carbon emissions of the i-th type of industry sector; E com(i,j) represents the carbon emissions within the j-th community of the i-th type of industry sector, P com(i,j) represents the population quantity within the j-th community of the i-th type of industry sector; P i represents the total population of the i-th type of industry sector; Step 713: Within each census block, through spatial overlay analysis, further identify the individual urban residential buildings and rural residential houses in the block, and calculate the weight of the building volume of each building in the total building volume of the block; Step 714: Based on the calculated weights, further allocate the block-level residential life carbon emissions to each single building within the block to achieve a refined spatial distribution simulation of residential life carbon emissions at the single building level. The specific calculation formula is as follows: (5); In the formula, E build(i,j,k) represents the carbon emissions of the kth residential building in the jth community of the ith industrial sector; V build(i,j,k) represents the building volume of the kth residential building in the jth community of the ith industrial sector; V com(i,j) represents the total building volume of residential buildings in the jth community of the ith industrial sector.

[0015] Furthermore, the calculation steps for the carbon emissions of the tertiary industry buildings are specifically as follows: Step 721: Determine the carbon emission sources of the tertiary industry; Step 722: Select the corresponding carbon emissions; Step 723: Establish the correspondence between the energy consumption sectors and building categories; Step 724: Calculate the carbon emissions of a single building. Within each building category, calculate the weight value of the building volume of a single building accounting for the total building volume of the category, and allocate the carbon emissions of the building category to each single building according to the weight value to obtain the carbon emissions of a single building, and generate the spatial distribution result of the carbon emissions of a single building in the tertiary industry. The specific calculation formula is as follows: (6); In the formula, E build(m,k) represents the carbon emissions of the kth building in the mth industrial sector; V build(m,k) represents the building volume of the kth building in the mth industrial sector; E m represents the total carbon emissions of the mth industrial sector; V m represents the total building volume of the mth industrial sector.

[0016] Furthermore, the calculation steps for the carbon emissions of industrial enterprises are specifically as follows: Step 731: Carbon emission accounting of key emission industrial enterprises; Based on the spatial distribution map of single buildings and the geographical information of thermal power plants, identify the building plots belonging to thermal power plants in the spatial distribution map of single buildings; Based on the calculated carbon emissions of thermal power generation, combined with the installed capacity information of thermal power plants in the city; Calculate the weight of the installed capacity of each thermal power plant accounting for the total installed capacity of the city, and allocate the carbon emissions of thermal power generation to individual thermal power plants according to the weight. The specific calculation formula is as follows: (7); In the formula, E nrepresents the carbon emissions of the nth thermal power plant; E powerplant represents the carbon emissions of the urban thermal power generation sector; C n represents the installed capacity of the nth thermal power plant; C total It represents the total installed capacity of urban thermal power plants; Step 732: Carbon emission space allocation for other industrial enterprises; Use POI data and the industry directory of industrial enterprises to match them according to the enterprise name to obtain the name, geographic information and industry information of the industrial enterprise; Determine the industrial and mining building plot to which it belongs based on the geographical information of the industrial enterprise, and determine the industry to which the industrial and mining building plot belongs based on the industry information; Calculate the ratio of energy intensity of each industry to total industrial energy intensity, and calculate the carbon emissions of each industry in industrial enterprises based on this; Assuming that the building area of ​​the building plot where the industrial enterprise is located can reflect the size of the enterprise, calculate the weight of each industrial enterprise's building volume in the total building volume of its industry; According to the industry carbon emissions and building volume weights, the carbon emissions of industrial enterprises are allocated to individual industrial enterprises to obtain the carbon emissions of individual industrial enterprises. The specific calculation formula is as follows: ; ; In the formula, E ind,a represents the total carbon emissions of the ath industry in industrial enterprises; R ind,a represents the energy consumption intensity of the ath industry in industrial enterprises; E ind represents the total carbon emissions of the urban industrial sector; R ind E represents the total industrial energy consumption intensity of the urban industrial sector; ind(a,b) represents the total carbon emissions of the bth industrial enterprise in the ath industry among industrial enterprises; V ind(a,b) V represents the building volume of the plot occupied by the bth industrial enterprise in the ath industry among industrial enterprises; ind,a It represents the total building volume of the plot occupied by the ath industry in an industrial enterprise.

[0017] Based on the above technical solution, the embodiments of the present invention can at least produce the following technical effects: (1) High degree of refinement. This paper uses multi-source data to conduct a detailed calculation of carbon emissions from different industry sectors in the city, and constructs a refined energy consumption carbon emission spatial distribution model for different industry sectors, achieving a highly refined simulation of the spatial distribution of urban carbon emissions, making up for the problem of insufficient fine scale within the existing methods. It provides data support for the next step of refined urban carbon source and sink accounting and dynamic spatiotemporal simulation of atmospheric CO2.

[0018] (2) Consider industry differences. The present invention fully considers the differences in carbon emission intensities among different industry sectors. For the carbon emission influencing factors of each industry sector, a targeted spatial distribution model is constructed, improving the accuracy and reliability of the simulation of carbon emission spatial distribution and overcoming the deficiency of existing methods that do not consider industry differences.

[0019] (3) Wide applicability. The method provided by the present invention can be applied to cities of different types and scales. By adjusting data sources and model parameters, refined simulation of carbon emission spatial distribution in different cities can be achieved, with wide applicability and popularization value. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on the structures shown in these drawings.

[0021] Figure 1 is the technical roadmap of the embodiment of the present invention; Figure 2 is the simulation result diagram of the spatial distribution of the total refined carbon emissions in the city of the present invention; Figure 3 is the simulation result diagram of the spatial distribution of refined carbon emissions from urban residents' living, industry, and the tertiary industry of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement it. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0023] As Figure 1 shown, a multi-source heterogeneous data fusion carbon emission spatial distribution simulation method for urban scale includes the following steps: Step 1: Define the scope of urban carbon emission accounting; Urban carbon emissions can be divided into two major categories: direct carbon emissions and indirect carbon emissions. Direct carbon emissions refer to the physical emissions generated within the urban boundary, mainly from fossil energy fuel combustion activities and industrial production processes, specifically including greenhouse gas emissions caused by direct heating, cooking, domestic hot water, hospital or hotel steam, etc. Indirect carbon emissions refer to the carbon emissions contained in the electricity and heat input from outside the building to the building. The heat part includes the heat sent to the building from cogeneration and district boilers.

[0024] Considering that the use of clean energy such as urban wind power and hydropower may cause large errors in the carbon emission accounting results, the present invention adopts the principle of the place of consumption and only calculates the direct carbon emissions generated by urban energy consumption to ensure the accuracy and reliability of the accounting results.

[0025] Step 2: Collect multi-source heterogeneous data, including provincial energy consumption, provincial and municipal social and economic indicators, urban individual building attributes, census and key polluting enterprise information, etc. Specifically, the data used in the present invention can be divided into two major categories: spatial data sets and non-spatial data sets. Non-spatial data mainly includes: ① Provincial energy balance sheet statistical data; ② Provincial and municipal social and economic indicator data, including the main energy consumption of industrial enterprises above designated size, thermal power generation, passenger turnover, freight turnover, total retail sales of consumer goods, operating income of service enterprises above designated size, permanent urban residents and permanent rural residents; ③ Industry list of urban industrial enterprises; ④ Information of key polluting enterprises; ⑤ Carbon content, lower calorific value and oxidation rate corresponding to energy types. Spatial data sets mainly include: ① Distribution data of individual buildings, which need to include building volume and building type information; ② Community-level census data; ③ POI (Point of Interest) data.

[0026] Step 3: Based on the provincial energy balance sheet, combined with the social and economic indicators of different industry sectors, calculate the main energy type consumption of seven industry sectors at the urban scale. Step 3 specifically includes the following steps: Step 31: Based on the provincial-scale energy balance sheet data, select the energy consumption statistical information of the following seven industry sectors: (1) Industry; (2) Transportation, warehousing and postal services; (3) Wholesale and retail, accommodation and catering; (4) Others; (5) Urban residents' life; (6) Rural residents' life; (7) Thermal power generation. Step 32: Screen the energy types in the energy consumption statistics information. Non-fuel products such as paraffin wax, lubricating oil, and naphtha are excluded, and finally 21 major energy types are selected for accounting, including raw coal, washed clean coal, other washed coal, coal products, coke, coke oven gas, blast furnace gas, converter gas, other gas, other coking products, crude oil, gasoline, kerosene, diesel, fuel oil, liquefied petroleum gas, refinery dry gas, other petroleum products, natural gas, and liquefied natural gas; Step 33: Calculate the energy consumption of different industry sectors and energy types at the urban scale. Based on the provincial energy consumption statistics data, combined with the characteristics of different industries, appropriate socioeconomic indicators are selected as distribution factors. According to the corresponding weights, the provincial energy consumption of the corresponding industry sectors is allocated to the municipal scale to obtain the energy consumption of different industry sectors and energy types at the urban scale. The distribution factors selected for different industries are shown in Table 1.

[0027] Table 1 Carbon emission distribution factors for different energy consumption sectors in the calculation of urban energy consumption The calculation formula for the energy consumption of different industry sectors at the urban scale is as follows: (1); In the formula, AD represents energy consumption, i represents different industry types, and A represents the statistical indicators selected for different industries.

[0028] Step 4: Based on the building energy consumption splitting method of the energy balance sheet, correct the energy consumption of the seven major industry sectors in the city; Since the energy consumption is statistically based on the affiliated industry and the building energy consumption data is not listed separately, it is necessary to correct the energy consumption data.

[0029] Step 4 specifically includes the following steps: Step 41: Determine the basic amount of building energy consumption.

[0030] Among the urban energy consumption, the four items of "wholesale, retail, accommodation, and catering", "others", "urban resident life", and "rural resident life" are mainly building energy consumption because these four types of energy consumption are mainly building energy consumption; Step 42: Remove the non-building energy consumption from the basic amount of building energy consumption.

[0031] The basic amount of building energy consumption includes the energy consumption of relevant industrial enterprises or private transportation vehicles, and this part of the energy consumption needs to be removed. Specifically, in the energy consumption of "wholesale and retail, accommodation and catering" and "others", 95% of gasoline consumption and 35% of diesel consumption are deducted as transportation energy consumption; in the energy consumption of "urban residents' life" and "rural residents' life", 100% of gasoline consumption and 95% of diesel consumption are deducted as transportation energy consumption; Step 43: Supplement the building energy consumption included in the transportation sector.

[0032] The energy consumption of "transportation, warehousing and postal services" includes some building energy consumption, such as the energy consumption of railway stations, bus stations, terminals, and post offices. According to the research results of relevant literature, 100% of the coal consumption and 40% of the electricity consumption of this industry are used as the energy consumption of the building department of transportation, warehousing and postal services and supplemented to the building energy consumption.

[0033] Step 5: Match the above seven major industry sectors with the corresponding urban building types, (5) Establish the corresponding relationship between the energy consumption of urban industry sectors and the building function use categories; According to different industry characteristics, match the seven major energy consumption sectors with the single building space distribution data to make their energy consumption sectors correspond to specific building function use categories. Table 2 details this corresponding relationship.

[0034] Table 2 Corresponding relationship between urban energy consumption sectors and building function use categories Step 6: Based on the energy consumption and carbon emission factors of different building types and energy types, calculate the carbon emissions; (1) Calculate the carbon emission factor based on the lower calorific value of the selected energy type, the carbon content per unit energy calorific value, and the oxidation rate. The specific calculation formula is as follows: (2); Among them, I is the carbon emission factor, j is the energy type, L is the lower calorific value of the energy, P is the carbon content per unit energy calorific value (kJ / m 3 or kJ / kg), O is the oxidation rate during the energy combustion process (%), and 44 / 12 is the conversion coefficient for carbon to carbon dioxide.

[0035] (2) Based on the energy consumption of different building types and the carbon emission factors of energy types, calculate the carbon emissions of each building type. The specific calculation formula is as follows: (3); Among them, E is the total carbon emissions generated by anthropogenic energy consumption, m is different building types, j is energy types, C is the physical quantity of energy consumption, and I is the carbon emission factor.

[0036] Step 7: Integrate multi-source heterogeneous data such as building volume, POI (Point of Interest) data, industrial enterprise industry catalogs, energy consumption intensities of major industrial sectors, community-level population censuses, and information on key urban polluting enterprises to construct a refined spatial distribution model of energy consumption carbon emissions, spatially allocate carbon emissions to various individual buildings, and achieve refined visualization of urban carbon emissions.

[0037] According to the correspondence between the seven major industry departments in the city and the corresponding building types, the calculated carbon emissions are divided into three categories: carbon emissions from residential buildings, carbon emissions from tertiary industry buildings, and carbon emissions from industrial enterprises. Considering different factors affecting the three major carbon emission areas, appropriate spatial allocation indicators are selected for each type of carbon emission to construct a refined spatial distribution model of energy consumption carbon emissions. Apply the refined spatial distribution model of energy consumption carbon emissions to accurately calculate and simulate the spatial distribution of carbon emissions from residential buildings, tertiary industry buildings, and industrial enterprises.

[0038] First, for the carbon emissions from residential buildings, for the corrected urban and rural residential carbon emissions, combined with community-level population census data and urban residential building volume, complete the spatial distribution simulation of residential carbon emissions at the individual building level. The specific steps are as follows: Step 711: Screen the plots in the urban individual building distribution data where the building types belong to urban residential buildings and rural residential houses, and identify the census blocks containing these plots; Step 712: According to the weight of the population quantity of each census block in the total population of the city, allocate the corrected annual urban and rural residential carbon emissions to the corresponding census blocks to obtain the community-level residential carbon emissions. The specific calculation formula is as follows: (4); In the formula, E i represents the total carbon emissions of the i-th type of industry department (urban residents' life or rural residents' life); E com(i,j) represents the carbon emissions within the j-th community of the i-th type of industry department, P com(i,j) represents the population quantity within the j-th community of the i-th type of industry department; P i represents the total population of the i-th type of industry department; Step 713: Within each census block, through spatial overlay analysis, further identify the individual urban residential buildings and rural residential houses in the block, and calculate the weight of the building volume of each building in the total building volume of the block; Step 714: Based on the calculated weights, further allocate the block-level residential life carbon emissions to each individual building within the block to achieve a refined spatial distribution simulation of residential life carbon emissions at the individual building level. The specific calculation formula is as follows: (5); In the formula, E build(i,j,k) represents the carbon emissions of the kth residential building in the jth community of the ith industrial sector; V build(i,j,k) represents the building volume of the kth residential building in the jth community of the ith industrial sector; V com(i,j) represents the total building volume of residential buildings in the jth community of the ith industrial sector.

[0039] Secondly, for the carbon emissions of the tertiary industry buildings, the specific steps are as follows: Step 721: Determine the carbon emission sources of the tertiary industry. The carbon emissions of the tertiary industry mainly come from the energy consumption emissions of tertiary industry enterprises and life service commercial venues in business operations.

[0040] Step 722: Select the corresponding carbon emissions. According to the characteristics of the carbon emission sources of the tertiary industry, select the carbon emissions of the three industrial sectors of "construction part of transportation, warehousing and postal services", "wholesale and retail, accommodation and catering", and "others" as the carbon emissions of the tertiary industry.

[0041] Step 723: Establish the correspondence between the energy consumption sectors and building categories. Based on the correspondence between the energy consumption sectors and building categories in Table 2, allocate the selected carbon emissions to the corresponding building categories, including transportation buildings, commercial buildings, public management and public service buildings, business and financial buildings, entertainment and fitness buildings, warehousing buildings, public utility buildings, special buildings, rural community service facilities buildings, and urban community service facilities buildings.

[0042] Step 724: Calculate the carbon emissions of individual buildings. Within each building category, calculate the weight value of the building volume of an individual building accounting for the total building volume of the category, and allocate the carbon emissions of the building category to each individual building according to the weight value to obtain the carbon emissions of individual buildings, generating the spatial distribution result of the carbon emissions of individual buildings in the tertiary industry. The specific calculation formula is as follows: (6); In the formula, E build(m,k) represents the carbon emissions of the kth building in the mth industrial sector ("construction part of transportation, warehousing and postal services", "wholesale and retail, accommodation and catering", "others"); V build(m,k) represents the building volume of the kth building in the mth industrial sector; E m represents the total carbon emissions of the mth industrial sector; Vm Represents the total building volume of the m-th type of industrial sector.

[0043] Finally, for the carbon emissions of industrial enterprises, the specific steps are as follows: Step 731: Carbon emission accounting for key-emitting industrial enterprises. First, based on the single-building space distribution map and the geographical information of thermal power plants, identify the building plots in the single-building space distribution map that belong to thermal power plants; secondly, based on the calculated carbon emissions from thermal power generation, combined with the installed capacity information of thermal power plants in the city, calculate the weight of the installed capacity of each thermal power plant in the total installed capacity of the city, and allocate the carbon emissions from thermal power generation to individual thermal power plants according to the weight. The specific calculation formula is as follows: (7); In the formula, E n Represents the carbon emissions of the n-th thermal power plant; E powerplant Represents the carbon emissions of the thermal power generation sector in the city; C n Represents the installed capacity of the n-th thermal power plant; C total Represents the sum of the total installed capacities of thermal power plants in the city.

[0044] Step 732: Spatial allocation of carbon emissions for other industrial enterprises.

[0045] Use POI data and the industrial enterprise industry directory, match according to the enterprise name, and obtain the name, geographical information, and industry information of industrial enterprises; Based on the geographical information of industrial enterprises, determine the industrial and mining housing building plots they belong to, and based on the industry information, determine the industries to which the industrial and mining housing building plots belong; Calculate the ratio of the energy consumption intensity of each industry to the total industrial energy consumption intensity, and calculate the carbon emissions of each industry of industrial enterprises accordingly; Assume that the building area of the building plot where the industrial enterprise is located can reflect the enterprise scale, and calculate the weight of the building volume of each industrial enterprise in the total building volume of the industry to which it belongs; According to the industry carbon emissions and the building volume weight, allocate the carbon emissions of industrial enterprises to individual industrial enterprises to obtain the carbon emissions of individual industrial enterprises. The specific calculation formula is as follows: ; ; In the formula, E ind,a Represents the total carbon emissions of the a-th industry in industrial enterprises; R ind,a Represents the energy consumption intensity of the a-th industry in industrial enterprises; E ind Represents the total carbon emissions of the industrial sector in the city; R ind Represents the total industrial energy consumption intensity of the industrial sector in the city; E ind(a,b)represents the total carbon emissions of the b-th industrial enterprise in the a-th industry in industrial enterprises; V ind(a,b) represents the building volume of the land plot occupied by the b-th industrial enterprise in the a-th industry in industrial enterprises; V ind,a represents the total building volume of the land plot occupied by the a-th industry in industrial enterprises.

[0046] Taking Wuhan in 2022 as an example, the multi-source heterogeneous data fusion carbon emission spatial distribution simulation method for urban scale of the present invention is applied for simulation, and the simulation results of the urban carbon emission spatial distribution are as Figure 2 shown, and the simulation results of the carbon emission spatial distribution of urban residents' living, industry and the tertiary industry are as Figure 3 shown.

[0047] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification only illustrates the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale, characterized in that: The following steps are involved: Step 1: Define the scope of urban carbon emissions accounting; Step 2: Collect multi-source heterogeneous data; Step 3: Based on the provincial energy balance table and combined with the socio-economic indicators of different industrial sectors, calculate the main energy consumption of the seven major industrial sectors at the city scale; Step 4: Based on the building energy consumption splitting method of the energy balance sheet, the energy consumption of the seven major industrial sectors in the city is corrected; Step 5: Match the seven major industry sectors with the corresponding urban building types to establish the corresponding relationship between the energy consumption of urban industry sectors and the functional use categories of buildings; Step 6: Calculate carbon emissions based on energy consumption and carbon emission factors of different building types and energy types; Step 7: Integrate multi-source heterogeneous data to build a refined spatial distribution model of energy consumption carbon emissions, allocate the carbon emissions to various types of individual buildings, and achieve refined visualization of urban carbon emissions.

2. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 1 is characterized in that: In step 1, urban carbon emissions are divided into two categories: direct carbon emissions and indirect carbon emissions. Direct carbon emissions include physical emissions generated within the city boundaries, mainly from fossil energy fuel combustion activities and industrial production processes. Indirect carbon emissions include carbon emissions contained in external electricity and heat input into buildings, of which the thermal part includes heat sent to buildings from cogeneration and regional boilers.

3. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 1 is characterized in that: In step 2, the multi-source heterogeneous data include spatial data sets and non-spatial data sets. The spatial data sets include single building distribution data, community-level census data, and POI data; the non-spatial data sets include provincial energy balance statistics, provincial and municipal socioeconomic indicator data, a list of industries to which urban industrial enterprises belong, information on key polluting enterprises, and carbon content, lower heating value, and oxidation rate corresponding to energy types.

4. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 1 is characterized in that: In step 3, the seven major industry sectors include industry; transportation, warehousing and postal services; wholesale and retail trade, accommodation and catering; others; urban residents' life; rural residents' life; thermal power generation; the calculation formula for energy type consumption is as follows: （1）； In the formula, AD represents energy consumption, i represents different industry types, and A represents the statistical indicators selected by different industries.

5. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 1 is characterized in that: In step 4, the method for correcting the energy consumption of the seven major industrial sectors in the city is as follows: Determine the basic amount of building energy consumption; Remove non-building energy consumption from the building energy consumption base; Complements building energy use included in the transportation sector.

6. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 1 is characterized in that: In step 6, the carbon emissions of different building types and energy types are calculated as follows: (1) The carbon emission factor is calculated based on the lower calorific value, carbon content per unit energy calorific value and oxidation rate of the selected energy type. The specific calculation formula is as follows: （2）； Where I is the carbon emission factor, j is the energy type, L is the lower calorific value of the energy, and P is the carbon content per unit energy calorific value, kJ / m 3 Or kJ / kg, O is the oxidation rate during energy combustion, %, and 44 / 12 is the conversion factor of carbon to carbon dioxide; (2) Based on the energy consumption of different building types and the carbon emission factors of energy types, the carbon emissions of each building type are calculated. The specific calculation formula is as follows: （3）； Among them, E is the total carbon emissions generated by energy consumption in human activities, m is different building types, j is the energy type, C is the physical amount of energy consumption, and I is the carbon emission factor.

7. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 1 is characterized in that: In step 7, the specific steps include: According to the correspondence between the seven major industrial sectors in the city and the types of buildings they belong to, the calculated carbon emissions are divided into three categories: carbon emissions from residential buildings, carbon emissions from tertiary industry buildings, and carbon emissions from industrial enterprises; Taking into account the different factors that affect the three major carbon emission areas, we select spatial allocation indicators for each type of carbon emission and build a refined energy consumption carbon emission spatial distribution model; By applying a refined spatial distribution model of carbon emissions from energy consumption, we can accurately calculate and simulate the spatial distribution of three types of carbon emissions: residential buildings, tertiary industry buildings and industrial enterprises.

8. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 7 is characterized in that: The calculation steps of the residential building carbon emissions are as follows: Step 711: Filter the plots whose building types belong to urban residential buildings and rural residential buildings in the urban single building distribution data, and identify the census blocks containing these plots; Step 712: Based on the weight of the population of each census block to the total population of the city, the revised annual carbon emissions of urban and rural residents are allocated to the corresponding census blocks to obtain the carbon emissions of community-level residents. The specific calculation formula is as follows: （4）； In the formula, E i represents the total carbon emissions of the i-th industry sector; E com(i,j) represents the carbon emissions in the jth community of the i-th industry sector, P com(i,j) P represents the population of the jth community in the i-th industry sector; i represents the total population of the i-th industry sector; Step 713: In each census block, further identify urban residential buildings and rural residential housing units in the block through spatial overlay analysis, and calculate the weight of the building volume of each building in the total building volume of the block; Step 714: Based on the calculated weights, the block-level residential carbon emissions are further allocated to each individual building in the block, so as to achieve a refined spatial distribution simulation of residential carbon emissions at the individual building level. The specific calculation formula is as follows: （5）； In the formula, E build(i,j,k) V represents the carbon emissions of the kth residential building in the jth community of the i-th industry sector; build(i,j,k) V represents the volume of residential buildings in the kth community of the i-th industry sector; com(i,j) It represents the total volume of residential buildings in the jth community of the i-th industry sector.

9. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 7 is characterized in that: The calculation steps of the tertiary industry building carbon emissions are as follows: Step 721: Determine the carbon emission sources of the tertiary industry; Step 722: Select corresponding carbon emissions; Step 723: Establishing the correspondence between energy consumption departments and building categories; Step 724: Calculate the carbon emissions of a single building. In each building category, calculate the weight of the volume of a single building to the total building volume of that category, and distribute the carbon emissions of the building category to each single building according to the weight value to obtain the carbon emissions of a single building, and generate the spatial distribution results of the carbon emissions of a single building in the tertiary industry. The specific calculation formula is as follows: （6）； In the formula, E build(m,k) V represents the carbon emissions of the kth building in the mth industry sector; build(m,k) E represents the volume of the kth building in the mth industry sector; m V represents the total carbon emissions of the mth industry sector; m Represents the total building volume of the mth industry sector.

10. The method for simulating the spatial distribution of carbon emissions by fusion of multi-source heterogeneous data at the city scale according to claim 7 is characterized in that: The calculation steps of the industrial enterprise carbon emissions are as follows: Step 731: Calculate carbon emissions of key emission industrial enterprises; Based on the spatial distribution map of individual buildings and the geographic information of thermal power plants, identify the building plots in the spatial distribution map of individual buildings that belong to thermal power plants; Based on the calculated carbon emissions from thermal power generation, combined with the installed capacity information of thermal power plants in the city; Calculate the weight of each thermal power plant's installed capacity in the total installed capacity of the city, and allocate the thermal power generation carbon emissions to a single thermal power plant according to the weight. The specific calculation formula is as follows: （7）； In the formula, E n represents the carbon emissions of the nth thermal power plant; E powerplant represents the carbon emissions of the urban thermal power generation sector; C n represents the installed capacity of the nth thermal power plant; C total It represents the total installed capacity of urban thermal power plants; Step 732: Carbon emission space allocation for other industrial enterprises; Use POI data and the industry directory of industrial enterprises to match them according to the enterprise name to obtain the name, geographic information and industry information of the industrial enterprise; Determine the industrial and mining building plot to which it belongs based on the geographical information of the industrial enterprise, and determine the industry to which the industrial and mining building plot belongs based on the industry information; Calculate the ratio of energy intensity of each industry to total industrial energy intensity, and calculate the carbon emissions of each industry in industrial enterprises based on this; Assuming that the building area of ​​the building plot where the industrial enterprise is located can reflect the size of the enterprise, calculate the weight of each industrial enterprise's building volume in the total building volume of its industry; According to the industry carbon emissions and building volume weights, the carbon emissions of industrial enterprises are allocated to individual industrial enterprises to obtain the carbon emissions of individual industrial enterprises. The specific calculation formula is as follows: ； ； In the formula, E ind,a represents the total carbon emissions of the ath industry in industrial enterprises; R ind,a represents the energy consumption intensity of the ath industry in industrial enterprises; E ind represents the total carbon emissions of the city’s industrial sector; R ind E represents the total industrial energy consumption intensity of the urban industrial sector; ind(a,b) represents the total carbon emissions of the bth industrial enterprise in the ath industry among industrial enterprises; V ind(a,b) V represents the building volume of the plot occupied by the bth industrial enterprise in the ath industry among industrial enterprises; ind,a It represents the total building volume of the plot occupied by the ath industry in an industrial enterprise.

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