CN116522094B

CN116522094B - Analysis and measurement method, device, equipment and storage medium for regional carbon neutralization

Info

Publication number: CN116522094B
Application number: CN202310787038.7A
Authority: CN
Inventors: 肖俊; 张明霞; 唐宇
Original assignee: Shenzhen Zhuoyi Environmental Technology Co ltd
Current assignee: Shenzhen Zhuoyi Environmental Technology Co ltd
Priority date: 2023-06-30
Filing date: 2023-06-30
Publication date: 2023-09-22
Anticipated expiration: 2043-06-30
Also published as: CN116522094A

Abstract

The invention relates to the field of carbon emission measurement and calculation, and discloses an analysis and calculation method, device and equipment for regional carbon neutralization and a storage medium, which are used for realizing intelligent carbon emission transaction measurement and calculation and improving the accuracy of carbon emission transaction measurement and calculation. The method comprises the following steps: calculating a first total amount of carbon emissions from the first base data and the first set of carbon emissions coefficients, and calculating a second total amount of carbon emissions for the second target region from the second base data and the second set of carbon emissions coefficients; creating a first carbon neutral data model from the first total amount of carbon emissions and a second carbon neutral data model from the second total amount of carbon emissions; generating a first carbon neutralization evaluation index according to the first carbon neutralization data model, and generating a second carbon neutralization evaluation index according to the second carbon neutralization data model; inputting the first carbon neutralization evaluation index and the second carbon neutralization evaluation index into a carbon emission trading measurement model to perform carbon emission trading measurement, and generating a carbon emission trading scheme.

Description

Analysis and measurement method, device, equipment and storage medium for regional carbon neutralization

Technical Field

The invention relates to the field of carbon emission measurement and calculation, in particular to an analysis and calculation method, an analysis and calculation device, analysis and calculation equipment and a storage medium for regional carbon neutralization.

Background

As human activities increase, such as energy consumption, transportation, and industrialization, a large amount of carbon dioxide is discharged into the atmosphere, resulting in global temperature rise and climate change. However, control and reduction of carbon emissions has become a significant challenge commonly faced worldwide.

In the existing scheme, regional carbon neutralization measurement is usually carried out manually, and the measurement method has less data samples, so that the measurement result is low in accuracy, namely the accuracy of the existing scheme is low.

Disclosure of Invention

The invention provides an analysis and calculation method, device and equipment for regional carbon neutralization and a storage medium, which are used for realizing intelligent carbon emission transaction calculation and improving the accuracy of carbon emission transaction calculation.

The first aspect of the present invention provides an analysis and measurement method for regional carbon neutralization, which comprises:

acquiring first basic data of a first target area and second basic data of a second target area;

determining a first carbon emission coefficient set according to the first basic data, and determining a second carbon emission coefficient set according to the second basic data;

calculating a first total amount of carbon emissions from the first base data and the first set of carbon emission coefficients, and calculating a second total amount of carbon emissions from the second target region from the second base data and the second set of carbon emission coefficients;

Creating a first carbon neutral data model from the first total carbon emissions and a second carbon neutral data model from the second total carbon emissions;

generating a first carbon neutralization evaluation index of the first target area according to the first carbon neutralization data model, and generating a second carbon neutralization evaluation index of the second target area according to the second carbon neutralization data model;

inputting the first carbon neutralization evaluation index and the second carbon neutralization evaluation index into a preset carbon emission transaction measuring and calculating model to measure and calculate carbon emission, and generating a carbon emission transaction scheme between the first target area and the second target area.

With reference to the first aspect, in a first implementation manner of the first aspect of the present invention, the acquiring first basic data of the first target area includes:

carrying out energy consumption statistics on a first target area to obtain energy consumption data, carrying out traffic analysis on the first target area to obtain traffic data, and carrying out industrial production statistics on the first target area to obtain industrial production data;

generating a first data identifier according to the energy consumption data, generating a second data identifier according to the transportation data, and generating a third data identifier according to the industrial production data;

And carrying out data combination on the energy consumption data, the transportation data and the industrial production data according to the first data identifier, the second data identifier and the third data identifier to generate first basic data.

With reference to the first aspect, in a second implementation manner of the first aspect of the present invention, the determining a first carbon emission coefficient set according to the first basic data, and determining a second carbon emission coefficient set according to the second basic data includes:

inquiring the data sources of the first basic data to obtain a plurality of corresponding first target data sources, and obtaining a first influence factor of the first target area;

respectively acquiring first initial carbon emission coefficients of each first target data source, and carrying out coefficient correction on the first initial carbon emission coefficients according to the first influence factors to obtain a first carbon emission coefficient set;

inquiring the data sources of the second basic data to obtain a plurality of corresponding second target data sources, and obtaining a second influence factor of the second target area;

and respectively acquiring a second initial carbon emission coefficient of each second target data source, and carrying out coefficient correction on the second initial carbon emission coefficient according to the second influence factor to obtain a second carbon emission coefficient set.

With reference to the first aspect, in a third implementation manner of the first aspect of the present invention, the calculating a first total carbon emission amount according to the first base data and the first carbon emission coefficient set includes:

determining the amount of carbon emitted by each energy source when generating a standard unit energy according to the first carbon emission coefficient set;

acquiring all energy consumption contained in the first basic data, and calculating the product of the energy consumption and a corresponding carbon emission coefficient to obtain the carbon emission generated by each energy in the first target area;

and adding the carbon emission generated by each energy source in the first target area to obtain a first total carbon emission.

With reference to the first aspect, in a fourth implementation manner of the first aspect of the present invention, the creating a first carbon neutral data model according to the first total carbon emission includes:

obtaining carbon neutralization target information of the first target area, and determining a plurality of carbon neutralization indexes according to the carbon neutralization target information, wherein the plurality of carbon neutralization indexes comprise: carbon neutralization amount, carbon neutralization cost, and carbon neutralization benefit;

creating a carbon neutralization mode, an implementation time and an implementation cost according to the carbon neutralization indexes;

And constructing a data model of the first target area according to the carbon neutralization mode, the implementation time and the implementation cost to obtain a first carbon neutralization data model.

With reference to the first aspect, in a fifth implementation manner of the first aspect of the present invention, the generating, according to the first carbon neutral data model, a first carbon neutral evaluation index of the first target area, and generating, according to the second carbon neutral data model, a second carbon neutral evaluation index of the second target area includes:

calculating a plurality of first quantized benefit data of the first target region through the first carbon neutral data model;

respectively carrying out evaluation index mapping on the plurality of first quantized benefit data to obtain first carbon neutralization evaluation indexes;

calculating a plurality of second quantized benefit data for the second target region through the second carbon neutral data model;

and respectively carrying out evaluation index mapping on the plurality of second quantized benefit data to obtain second carbon neutralization evaluation indexes.

With reference to the first aspect, in a sixth implementation manner of the first aspect of the present invention, inputting the first carbon neutral evaluation index and the second carbon neutral evaluation index into a preset carbon emission trading measurement model to perform carbon emission trading measurement, and generating a carbon emission trading scheme between the first target area and the second target area includes:

Inputting the first carbon neutralization evaluation index into a preset carbon emission transaction measurement model, and calculating a plurality of first transaction measurement data of the first target area through the carbon emission transaction measurement model;

inputting the second carbon neutralization evaluation index into a preset carbon emission transaction measurement model, and calculating a plurality of second transaction measurement data of the second target area through the carbon emission transaction measurement model;

calculating a carbon emission trading target value between the first target area and the second target area according to the plurality of first trading measurement data and the plurality of second trading measurement data;

and generating a carbon emission trading scheme between the first target area and the second target area according to the carbon emission trading target value.

The second aspect of the present invention provides an analysis and measurement device for regional carbon neutralization, the analysis and measurement device for regional carbon neutralization comprising:

the acquisition module is used for acquiring first basic data of the first target area and acquiring second basic data of the second target area;

the processing module is used for determining a first carbon emission coefficient set according to the first basic data and determining a second carbon emission coefficient set according to the second basic data;

A calculation module for calculating a first total amount of carbon emissions from the first base data and the first set of carbon emission coefficients, and a second total amount of carbon emissions from the second target region from the second base data and the second set of carbon emission coefficients;

a creation module for creating a first carbon neutral data model from the first total amount of carbon emissions and a second carbon neutral data model from the second total amount of carbon emissions;

the generation module is used for generating a first carbon neutralization evaluation index of the first target area according to the first carbon neutralization data model and generating a second carbon neutralization evaluation index of the second target area according to the second carbon neutralization data model;

the measuring and calculating module is used for inputting the first carbon neutralization evaluation index and the second carbon neutralization evaluation index into a preset carbon emission trading measuring and calculating model to measure and calculate carbon emission, and generating a carbon emission trading scheme between the first target area and the second target area.

A third aspect of the present invention provides an analysis and calculation apparatus for regional carbon neutralization, comprising: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the regional carbon neutralization analysis and calculation device to perform the regional carbon neutralization analysis and calculation method described above.

A fourth aspect of the present invention provides a computer readable storage medium having instructions stored therein which, when run on a computer, cause the computer to perform the above-described method of analysis and calculation of regional carbon neutralization.

According to the technical scheme provided by the invention, the first carbon emission total amount is calculated according to the first basic data and the first carbon emission coefficient set, and the second carbon emission total amount of the second target area is calculated according to the second basic data and the second carbon emission coefficient set; creating a first carbon neutral data model from the first total amount of carbon emissions and a second carbon neutral data model from the second total amount of carbon emissions; generating a first carbon neutralization evaluation index according to the first carbon neutralization data model, and generating a second carbon neutralization evaluation index according to the second carbon neutralization data model; the method and the device can quantify and analyze carbon emission conditions, can mutually trade carbon emission rights through measuring and calculating different areas of regional carbon neutralization, optimize the configuration of carbon resources, realize intelligent carbon emission trading and calculating by utilizing the carbon neutralization evaluation index and the carbon trading and calculating model, and improve the accuracy of the carbon emission trading and calculating.

Drawings

FIG. 1 is a schematic diagram of an embodiment of an analytical measurement method for regional carbon neutralization in an embodiment of the present invention;

FIG. 2 is a flow chart of determining a first carbon emission coefficient set and a second carbon emission coefficient set according to an embodiment of the present invention;

FIG. 3 is a flow chart of calculating a first total carbon emissions in an embodiment of the present invention;

FIG. 4 is a flow chart of creating a first carbon neutral data model in an embodiment of the invention;

FIG. 5 is a schematic diagram of an embodiment of an analysis and measurement apparatus for regional carbon neutralization in accordance with an embodiment of the present invention;

FIG. 6 is a schematic diagram of an embodiment of an analytical measurement device for regional carbon neutralization in an embodiment of the present invention.

Detailed Description

The embodiment of the invention provides an analysis and calculation method, device and equipment for regional carbon neutralization and a storage medium, which are used for realizing intelligent carbon emission transaction calculation and improving the accuracy of carbon emission transaction calculation. The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.

For ease of understanding, a specific flow of an embodiment of the present invention is described below with reference to fig. 1, and one embodiment of a method for analysis and measurement of regional carbon neutralization in an embodiment of the present invention includes:

s101, acquiring first basic data of a first target area and second basic data of a second target area;

it is to be understood that the execution subject of the present invention may be an analysis and measurement device for regional carbon neutralization, and may also be a terminal or a server, which is not limited herein. The embodiment of the invention is described by taking a server as an execution main body as an example.

In particular, the server determines the extent and boundaries of the first target area, including the energy sources, traffic and industrial production related sites and facilities within the area. And carrying out energy consumption statistics, traffic analysis and industrial production statistics on the sites and facilities, and obtaining corresponding energy consumption data, traffic data and industrial production data. And generating a first data identifier, a second data identifier and a third data identifier according to the data, combining the energy consumption data, the transportation data and the industrial production data by using the data identifiers to generate first basic data, and further determining the range and the boundary of a second target area by the server in the same way, wherein the range and the boundary comprise the places and facilities related to energy, transportation and industrial production in the area, and finally obtaining the second basic data of the second target area.

S102, determining a first carbon emission coefficient set according to first basic data, and determining a second carbon emission coefficient set according to second basic data;

specifically, the server determines the names or locations of the data sources of the first base data and the first target data sources, for example, the data sources of the first base data may be a database containing the total annual carbon emissions for each industry, and queries are performed in the first base data sources to find data of the total annual carbon emissions associated with the industry. The query result should be one or more data sets, each of which has some data related to the first underlying data. According to the query result, determining a first influence factor related to each target area, wherein the influence factor may be carbon emission pressure generated when the area produces or uses a product, such as carbon emission intensity of each industry or carbon emission intensity of each area, so that the server determines a corresponding first initial carbon emission coefficient according to the first basic data, and carries out coefficient correction on the first initial carbon emission coefficient according to the first influence factor to obtain a first carbon emission coefficient set, and finally, the server determines a second carbon emission coefficient set according to the second basic data.

For example, suppose that the carbon emissions for each area of a particular industry are being queried, wherein the first base data is a database of annual carbon emissions for each company in the industry, and the second base data is a data file of sales of products for each company in the industry. The following are some possible steps: first, a data source for the first underlying data, such as a database containing the total emissions from each company, is determined. This data source is queried by SQL query statements or a Python library such as Pandas. Then, based on the query results, all areas associated with the industry, and their share in the industry, are determined. The total amount of carbon emissions per zone was calculated by the groupby function in pandas. This result may be stored as a query result as input for a subsequent calculation of the first influencing factor. Further, the influence factor of the first region is determined by determining the influence factor of the first region for the carbon emission intensity of each region, and the first influence factor is calculated by dividing the emission amount of each region by the GDP of the region.

S103, calculating a first carbon emission total according to the first basic data and the first carbon emission coefficient set, and calculating a second carbon emission total of the second target area according to the second basic data and the second carbon emission coefficient set;

It should be noted that, the server first determines the basic data and the carbon emission coefficient set, calculates the respective emission total using the basic data and the carbon emission coefficient set, and finally calculates and outputs the emission total, for example:

the first base data is derived from a database of energy consumption and emissions for an area containing data on annual coal, oil and gas consumption for the area. The first carbon emission coefficient set is derived from a reference table of carbon emission coefficients for fuels such as coal, oil, and gas, and can be used to calculate the carbon emissions per unit energy. The second base data is also from a database of sales and usage of products for an area containing annual sales of products for that area. The second carbon emission coefficient set is derived from a carbon emission intensity reference table for each product to calculate carbon emission for each product, and further, the carbon emission amount of the first target region is calculated from the first base data and the first carbon emission coefficient set. Specifically, the discharge amount of the first region is calculated by the following formula:

wherein ,for energy consumption data->Is the carbon emission coefficient of energy source, < > >For traffic data->Is the carbon emission coefficient of traffic, < >>For industrial production data,/->For workersAnd the industrial carbon emission coefficient, F is the first carbon emission total. Further, after the server calculates the first total carbon emission amount of the first target area, the second total carbon emission amount of the second target area is calculated according to the same method.

S104, creating a first carbon neutral data model according to the first carbon emission total amount, and creating a second carbon neutral data model according to the second carbon emission total amount;

specifically, the carbon neutralization target information of the target area is confirmed. And (3) defining carbon neutralization target information of a target area, wherein the carbon neutralization target information comprises the total carbon emission amount required to be neutralized, the neutralization time period, the neutralization mode and the like. The method for calculating the carbon neutralization index is confirmed, and furthermore, the method for calculating the carbon neutralization index is clarified, and the method comprises indexes such as the carbon neutralization amount, the carbon neutralization cost, the carbon neutralization benefit and the like. It should be noted that the calculation method of different indexes may be different, and the calculation method is adjusted according to the specific form of carbon neutralization. And calculating the carbon neutralization amount according to the carbon neutralization target information of the target area, further calculating the carbon neutralization amount according to the carbon neutralization target information of the target area, acquiring the annual average carbon emission amount of the target area according to the neutralization time period and the total carbon emission amount required to be neutralized, and then calculating the carbon neutralization amount. And calculating the carbon neutralization cost according to the carbon neutralization target information of the target area and the selected carbon neutralization mode. And calculating the carbon neutralization cost according to the carbon neutralization target information of the target area and the selected carbon neutralization mode. If carbon quota transaction and other modes are adopted for carbon neutralization, the cost for purchasing the carbon quota needs to be calculated; if carbon neutralization is performed by using clean energy or the like, it is necessary to calculate the cost of installing and maintaining clean energy facilities or the like. The carbon neutralization benefit is calculated from the calculated carbon neutralization amount and the carbon neutralization cost. In this step, the carbon neutralization benefit is calculated from the calculated carbon neutralization amount and the carbon neutralization cost, and is calculated by a formula. And outputting a final calculation result. In this step, the calculated carbon neutralization amount, cost, benefit, and the like are outputted for subsequent use, for example, when a carbon neutralization target of a certain area is calculated and a carbon neutralization index is calculated. The 'certain area' is planned to reduce the total carbon emission by 100 ten thousand tons in the next 5 years, and adopts a carbon neutralization scheme taking afforestation as a main mode. The following calculation can be performed: calculation of carbon neutralization amount: the annual average carbon emission of the target area is 20 ten thousand tons, and the carbon neutralization amount is 20 ten thousand tons/year. Calculation of carbon neutralization costs: if the afforestation is the main way, the cost of afforestation and the like need to be calculated.

S105, generating a first carbon neutralization evaluation index of a first target area according to the first carbon neutralization data model, and generating a second carbon neutralization evaluation index of a second target area according to the second carbon neutralization data model;

specifically, the server confirms the type and index of the carbon neutralization data model, confirms the total carbon emission amount and the neutralization target of the target area, and finally calculates the carbon neutralization evaluation index based on the data model and the neutralization target. For example: the server first determines the carbon neutral data model type and index to generate an evaluation index. The carbon neutralization data model covers a variety of calculation methods and metrics, such as: carbon quota trade, forest carbon sink, clean energy, etc. Further, an evaluation index is further defined, for example: carbon neutralization amount, carbon neutralization cost, carbon neutralization benefit, and the like. For example, if a forest carbon sink is selected as the carbon neutralization model, an evaluation index needs to be defined, such as: forest area, hair volume, carbon reserves, forest management costs, etc. The total amount of carbon emissions and the neutralization target of the target area are determined. This information will be used to calculate a neutralization evaluation index. For example, if a first carbon neutral evaluation index is required to be calculated, the total amount of carbon emissions and the neutral target of the first target region are determined. If the total amount of carbon emissions of the first target area is assumed to be 1000 tons and the neutralization target is to reduce the total amount of carbon emissions by 50%, it is necessary to calculate that the target area needs to be neutralized by 500 tons every year.

S106, inputting the first carbon neutralization evaluation index and the second carbon neutralization evaluation index into a preset carbon emission transaction measuring and calculating model to perform carbon emission transaction measurement and calculation, and generating a carbon emission transaction scheme between the first target area and the second target area.

Specifically, a first carbon neutralization evaluation index and a second carbon neutralization evaluation index are obtained. Inputting the carbon neutralization evaluation index into a carbon emission trading calculation model, and calculating the carbon emission and trading cost. A carbon emissions trading scheme is generated between the first target area and the second target area. For example, a first carbon neutral evaluation index and a second carbon neutral evaluation index are obtained. The first carbon neutral evaluation index and the second carbon neutral evaluation index are stored in a data file, for example, in this example, the first carbon neutral evaluation index has been calculated as: the carbon neutralization amount is 20 tons, the carbon neutralization cost is 10 yuan/ton, and the carbon neutralization benefit is 0.01; and (5) the second carbon neutralization evaluation index is to be calculated. And inputting the first carbon neutralization evaluation index and the second carbon neutralization evaluation index into a carbon emission trading measurement model for calculation. In the calculation process, the indexes are related to the carbon emission and the transaction cost, and a transaction scheme is calculated. For example, in this example, it is assumed that the second carbon neutralization evaluation index is: the carbon neutralization amount is 15 tons, the carbon neutralization cost is 12 yuan/ton, and the carbon neutralization benefit is 0.008. Based on these metrics, they can be correlated with carbon emissions and transaction costs to calculate a transaction scheme. And finally, generating a carbon emission trading scheme according to the carbon emission trading model between the first target area and the second target area. The transaction scheme should contain information such as transaction time, transaction price, transaction amount, etc.

In the embodiment of the invention, the first carbon emission total amount is calculated according to the first basic data and the first carbon emission coefficient set, and the second carbon emission total amount of the second target area is calculated according to the second basic data and the second carbon emission coefficient set; creating a first carbon neutral data model from the first total amount of carbon emissions and a second carbon neutral data model from the second total amount of carbon emissions; generating a first carbon neutralization evaluation index according to the first carbon neutralization data model, and generating a second carbon neutralization evaluation index according to the second carbon neutralization data model; the method and the device can quantify and analyze carbon emission conditions, can mutually trade carbon emission rights through measuring and calculating different areas of regional carbon neutralization, optimize the configuration of carbon resources, realize intelligent carbon emission trading and calculating by utilizing the carbon neutralization evaluation index and the carbon trading and calculating model, and improve the accuracy of the carbon emission trading and calculating.

In a specific embodiment, the process of executing step S101 may specifically include the following steps:

(1) Carrying out energy consumption statistics on the first target area to obtain energy consumption data, carrying out traffic analysis on the first target area to obtain traffic data, and carrying out industrial production statistics on the first target area to obtain industrial production data;

(2) Generating a first data identifier according to the energy consumption data, generating a second data identifier according to the transportation data, and generating a third data identifier according to the industrial production data;

(3) And carrying out data combination on the energy consumption data, the transportation data and the industrial production data according to the first data identifier, the second data identifier and the third data identifier to generate first basic data.

Specifically, the server designs a data structure for each data statistics process to facilitate storing the data. For example, the data for each process is stored by a dictionary data structure. Suppose that the first process requires statistics on date, energy consumption type and energy consumption. A scroll may be used as a key and stored in the dictionary. Each repetition contains three elements, namely date, energy consumption type and energy consumption. For the second process, the transportation related data is stored by the same method. The source of the data is determined because the data sources of different data statistics processes may be different. For example, energy consumption data may need to be collected from sensors in the first target area. Whereas for traffic data, it may be desirable to collect and integrate data from traffic authorities in the first target area. Likewise, it may be desirable to collect data from the industry sector in order to facilitate statistics of the industrial production data. For each process, a corresponding code block needs to be written for data storage and data processing. For example, a function is written to read energy consumption data from the sensor and store it in a dictionary. A function may also be written to calculate traffic related data and store it in a dictionary. The data is cleaned and processed. There is typically some error and inconsistency in the data. Thus, code is written to clean and process these data to ensure accuracy and consistency of the data. For example, it may be necessary to remove outliers in the data, perform average and standard deviation processing of the data, and the like. Visualizing the data, the visualization process can help to better understand the data, discover the regularity and relationship of the data. And carrying out data visualization through libraries such as matplotlib and seaband of Python, and finally obtaining energy consumption data, traffic data and industrial production data.

And respectively generating a first data identifier, a second data identifier and a third data identifier according to the energy consumption, the transportation and the industrial production data. For each data identification, it may be converted to a corresponding unique hash value using a hash function. The hash value is a fixed-length value generated based on a set of inputs and can be used as a unique identification of the data. For example, for the energy consumption data, the ratio of the energy yield to the consumption amount is used to calculate the integrated index value of the energy consumption. For the traffic data, the comprehensive index value of traffic may be calculated using factors such as the frequency of use of public vehicles and private vehicles, the degree of congestion of roads, and the like. For industrial production data, the comprehensive index value of industrial production is calculated by using factors such as production efficiency, power consumption and the like of industrial enterprises. And then, the index values are brought into a hash function, corresponding data identifications are calculated, and finally, the server performs data combination on the energy consumption data, the traffic transportation data and the industrial production data according to the first data identifications, the second data identifications and the third data identifications to generate first basic data.

In a specific embodiment, as shown in fig. 2, the process of executing step S102 may specifically include the following steps:

S201, inquiring a data source of first basic data to obtain a plurality of corresponding first target data sources, and obtaining a first influence factor of a first target area;

s202, respectively acquiring a first initial carbon emission coefficient of each first target data source, and carrying out coefficient correction on the first initial carbon emission coefficient according to a first influence factor to obtain a first carbon emission coefficient set;

s203, inquiring the data sources of the second basic data to obtain a plurality of corresponding second target data sources, and obtaining a second influence factor of a second target area;

s204, respectively acquiring a second initial carbon emission coefficient of each second target data source, and carrying out coefficient correction on the second initial carbon emission coefficient according to a second influence factor to obtain a second carbon emission coefficient set.

Specifically, the server determines the names or locations of the data sources of the first base data and the first target data sources, for example, the data sources of the first base data may be a database containing the total annual carbon emissions for each industry, and queries are made in the first base data sources to find data of the total annual carbon emissions associated with the industry. The query result should be one or more data sets, each of which has some data related to the first underlying data. According to the query result, determining a first influence factor related to each target area, wherein the influence factor may be carbon emission pressure generated when the area produces or uses a product, such as carbon emission intensity of each industry or carbon emission intensity of each area, so that the server determines a corresponding first initial carbon emission coefficient according to the first basic data, and carries out coefficient correction on the first initial carbon emission coefficient according to the first influence factor to obtain a first carbon emission coefficient set, and finally, the server determines a second carbon emission coefficient set according to the second basic data.

In a specific embodiment, as shown in fig. 3, the process of executing step S103 may specifically include the following steps:

s301, determining the carbon quantity discharged by each energy source when generating standard unit energy according to a first carbon discharge coefficient set;

s302, acquiring all energy consumption contained in the first basic data, and calculating the product of the energy consumption and a corresponding carbon emission coefficient to obtain the carbon emission generated by each energy in a first target area;

s303, adding the carbon emission generated by each energy source in the first target area to obtain a first total carbon emission.

wherein ,for energy consumption data->Is the carbon emission coefficient of energy source, < >>For traffic data->Is the carbon emission coefficient of traffic, < >>In order to be able to produce data for an industrial process,/>for the industrial carbon emission coefficient, F is the first total carbon emission. Further, after the server calculates the first total carbon emission amount of the first target area, the second total carbon emission amount of the second target area is calculated according to the same method.

In a specific embodiment, as shown in fig. 4, the process of executing step S104 may specifically include the following steps:

s401, acquiring carbon neutralization target information of a first target area, and determining a plurality of carbon neutralization indexes according to the carbon neutralization target information, wherein the plurality of carbon neutralization indexes comprise: carbon neutralization amount, carbon neutralization cost, and carbon neutralization benefit;

s402, creating a carbon neutralization mode, implementation time and implementation cost according to a plurality of carbon neutralization indexes;

and S403, constructing a data model of the first target area according to the carbon neutralization mode, the implementation time and the implementation cost to obtain a first carbon neutralization data model.

In the data model construction of the first target region according to the carbon neutralization method, the implementation time and the implementation cost, when the first carbon neutralization data model is obtained, a carbon neutralization target participating in the model construction is set, for example: carbon neutralization amount, carbon emission reduction objectives, cost objectives, and the like. The basic step of building a data model is to draw up variables and factors involved in the model for different carbon neutralization targets. In modeling, regression model, deep learning and other technologies can be adopted to model the planned variables and factors, so as to obtain a predictable carbon neutralization result. After the model is built, the model needs to be evaluated and the evaluation result is visualized. Error analysis, cross-validation and other methods can be used to evaluate the accuracy of the model and to demonstrate parameters and calculation results through visual charts and visual images. This step may be accomplished by means of a Python or the like tool. For example: data is then collected and collated according to the reduction of carbon emissions, etc. When the model is built, the data change of the carbon emission amount can be used as one of variables, and a specific carbon neutralization mode, implementation time, implementation cost and the like can be determined according to the scheme. These variables are then analyzed and modeled to yield specific predicted values of carbon neutralization and emission reduction. Finally, the model can be applied to data prediction, as well as effect assessment.

In a specific embodiment, the process of executing step S105 may specifically include the following steps:

(1) Calculating a plurality of first quantized benefit data of the first target region through a first carbon neutral data model;

(2) Respectively carrying out evaluation index mapping on the plurality of first quantized benefit data to obtain first carbon neutralization evaluation indexes;

(3) Calculating a plurality of second quantized benefit data of the second target region through a second carbon neutral data model;

(4) And respectively carrying out evaluation index mapping on the plurality of second quantized benefit data to obtain second carbon neutralization evaluation indexes.

Specifically, the total amount of carbon emissions and the neutralization target of the target area, and the calculated benefit index are defined. After the target is well defined, the type and index of the carbon neutralization data model are further defined, required data are extracted, and data processing is carried out according to the selected model. Based on the selected model and the neutralization objective, a plurality of quantized benefit data for the first and second objective regions are calculated and mapped into corresponding evaluation metrics. For example, in a forest carbon sink model, data such as forest area, hair volume, carbon reserves, forest management cost, etc. are calculated, and then evaluation index mapping is performed based on different model indexes. Specifically, when performing the evaluation index mapping, required data is collected, for example: forest area, hair volume, carbon reserves, forest management costs, etc. And sending the acquired and processed data into a forest carbon sink model for data analysis and processing to obtain benefit data such as forest area, hair volume, carbon reserves, forest management cost and the like. For example, by monitoring forests in a certain area, forest area, hair amount and other data can be obtained, then the storable carbon amount of the forests is calculated according to the type and growth condition of the forests, and the data is modeled according to the forest management cost. After the benefit data is obtained, the benefit data is mapped into corresponding evaluation indexes. This can be done by setting different weight indicators. For example: the indexes such as forest area and carbon reserves can be given a larger weight, and the indexes such as forest management cost can be given a smaller weight. According to the different weights selected, the benefit data may be mapped to corresponding evaluation indicators, such as: and indexes such as carbon neutralization amount, carbon neutralization cost, carbon neutralization benefit and the like. For example, for an evaluation index map of forest carbon sinks in a certain region, indexes such as forest area, carbon reserves, hair volume, forest management cost and the like can be selected, and different weights can be set, for example: the index weight of carbon reserves, forest areas, etc. is set to 60% or more, and the index weight of forest management costs, etc. is set to 40% or less. And then, according to the set weight, mapping the collected data such as forest area, carbon reserves, hair quantity, forest management cost and the like into corresponding carbon neutralization evaluation indexes, and after the calculation of benefit data and the mapping of the evaluation indexes are completed, carrying out data modeling based on the obtained data model. And constructing a learning model by combining data modeling technologies such as multivariate analysis, regression analysis and the like, and predicting indexes such as carbon neutralization amount, carbon neutralization cost, carbon neutralization benefit and the like. The first and second carbon neutral evaluation indexes are calculated and analyzed in this way. Finally, verification and adjustment of the constructed carbon neutralization evaluation index model are required.

In a specific embodiment, the process of executing step S106 may specifically include the following steps:

(1) Inputting a first carbon neutralization evaluation index into a preset carbon emission trading calculation model, and calculating a plurality of first trading calculation data of a first target area through the carbon emission trading calculation model;

(2) Inputting a second carbon neutralization evaluation index into a preset carbon emission trading calculation model, and calculating a plurality of second trading calculation data of a second target area through the carbon emission trading calculation model;

(3) Calculating a carbon emission trading target value between the first target area and the second target area according to the plurality of first trading measurement data and the plurality of second trading measurement data;

(4) And generating a carbon emission trading scheme between the first target area and the second target area according to the carbon emission trading target value.

Specifically, the first carbon neutralization evaluation index is input into a preset carbon emission transaction measurement model, and a plurality of first transaction measurement data of a first target area are calculated. For example, when calculating the transaction measuring and calculating amount, the method can be used for calculating by combining technologies such as a multiple regression model, a decision tree model and the like, and reasonable parameters, weights and the like can be set in the calculating process. Inputting the second carbon neutralization evaluation index into a preset carbon emission trading measurement model, and calculating a plurality of second trading measurement data of a second target area. For example, a transaction amount for the second target area is calculated using the same calculation as in the transaction calculation for the first target area. Inputting the transaction measuring and calculating data of the first target area and the transaction measuring and calculating data of the second target area, and calculating a carbon emission transaction target value between the first target area and the second target area through a preset carbon emission transaction measuring and calculating model. For example, the target value may be calculated by linking an index such as the transaction measurement amount and cost with an index such as the carbon emission amount and the transaction cost. After the target value of the carbon emission trade is calculated, a trade scheme is determined according to the target value, wherein the trade scheme needs to contain information such as trade time, trade price, trade amount and the like. For example, assuming that the target value of the carbon emission trade between the first target area and the second target area is 25 tons and 5 times of trade between the first target area and the second target area is required to be completed, the trade time may be determined first, then the trade amount and the trade price may be determined according to the trade time, and finally the trade scheme may be generated.

The above description of the method for analyzing and measuring regional carbon neutralization in the embodiment of the present invention, the following description of the apparatus for analyzing and measuring regional carbon neutralization in the embodiment of the present invention, refer to fig. 5, and one embodiment of the apparatus for analyzing and measuring regional carbon neutralization in the embodiment of the present invention includes:

an obtaining module 501, configured to obtain first basic data of a first target area, and obtain second basic data of a second target area;

a processing module 502 configured to determine a first set of carbon emission coefficients from the first base data and a second set of carbon emission coefficients from the second base data;

a calculation module 503 for calculating a first total amount of carbon emissions from the first base data and the first set of carbon emission coefficients, and calculating a second total amount of carbon emissions from the second target region from the second base data and the second set of carbon emission coefficients;

a creation module 504 for creating a first carbon neutral data model from the first total amount of carbon emissions and a second carbon neutral data model from the second total amount of carbon emissions;

a generating module 505, configured to generate a first carbon neutralization evaluation index of the first target area according to the first carbon neutralization data model, and generate a second carbon neutralization evaluation index of the second target area according to the second carbon neutralization data model;

The measurement module 506 is configured to input the first carbon neutral evaluation index and the second carbon neutral evaluation index into a preset carbon emission measurement model to perform carbon emission measurement, so as to generate a carbon emission measurement scheme between the first target area and the second target area.

Calculating a first total carbon emission amount according to the first basic data and the first carbon emission coefficient set and calculating a second total carbon emission amount of the second target area according to the second basic data and the second carbon emission coefficient set through the cooperative cooperation of the components; creating a first carbon neutral data model from the first total amount of carbon emissions and a second carbon neutral data model from the second total amount of carbon emissions; generating a first carbon neutralization evaluation index according to the first carbon neutralization data model, and generating a second carbon neutralization evaluation index according to the second carbon neutralization data model; the method and the device can quantify and analyze carbon emission conditions, can mutually trade carbon emission rights through measuring and calculating different areas of regional carbon neutralization, optimize the configuration of carbon resources, realize intelligent carbon emission trading and calculating by utilizing the carbon neutralization evaluation index and the carbon trading and calculating model, and improve the accuracy of the carbon emission trading and calculating.

The above fig. 5 describes the analysis and measurement apparatus for regional carbon neutralization in the embodiment of the present invention in detail from the viewpoint of the modularized functional entity, and the following describes the analysis and measurement apparatus for regional carbon neutralization in the embodiment of the present invention in detail from the viewpoint of hardware processing.

Fig. 6 is a schematic structural diagram of an analysis and measurement device for regional carbon neutralization, where the analysis and measurement device 600 for regional carbon neutralization may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) 610 (e.g., one or more processors) and a memory 620, and one or more storage media 630 (e.g., one or more mass storage devices) storing application programs 633 or data 632 according to an embodiment of the present invention. Wherein the memory 620 and the storage medium 630 may be transitory or persistent storage. The program stored on the storage medium 630 may include one or more modules (not shown), each of which may include a series of instruction operations in the analysis measuring device 600 for regional carbon neutralization. Still further, the processor 610 may be configured to communicate with the storage medium 630 to execute a series of instruction operations in the storage medium 630 on the regional carbon-neutral analysis measuring device 600.

The analysis and measurement device 600 for regional carbon neutralization may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input/output interfaces 660, and/or one or more operating systems 631, such as Windows Serve, mac OS X, unix, linux, freeBSD, and the like. It will be appreciated by those skilled in the art that the regional carbon neutral analysis measuring apparatus configuration shown in fig. 6 does not constitute a limitation of the regional carbon neutral analysis measuring apparatus and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.

The invention also provides an analysis and calculation device for regional carbon neutralization, which comprises a memory and a processor, wherein the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the analysis and calculation method for regional carbon neutralization in the above embodiments.

The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, and may also be a volatile computer readable storage medium, where instructions are stored in the computer readable storage medium, when the instructions are executed on a computer, cause the computer to perform the steps of the analysis and measurement method for regional carbon neutralization.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random acceS memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.

The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An analysis and measurement device for regional carbon neutralization, characterized in that the analysis and measurement device for regional carbon neutralization comprises:

the acquisition module is used for acquiring first basic data of a first target area and acquiring second basic data of a second target area, and specifically comprises the following steps: carrying out energy consumption statistics on a first target area to obtain energy consumption data, carrying out traffic analysis on the first target area to obtain traffic data, and carrying out industrial production statistics on the first target area to obtain industrial production data; generating a first data identifier according to the energy consumption data, generating a second data identifier according to the transportation data, and generating a third data identifier according to the industrial production data; according to the first data identifier, the second data identifier and the third data identifier, carrying out data combination on the energy consumption data, the transportation data and the industrial production data to generate first basic data; the method comprises the steps of respectively generating a first data identifier, a second data identifier and a third data identifier according to energy consumption, traffic transportation and industrial production data, and converting each data identifier into a corresponding unique hash value by using a hash function, wherein the hash value is a fixed-length numerical value generated based on a group of input and is used as a unique identifier of the data; for the energy consumption data, calculating a comprehensive index value of energy consumption by using the ratio of the energy yield to the consumption; for traffic data, calculating comprehensive index values of traffic by using frequency of use of public vehicles and private vehicles and factors of highway congestion degree; for industrial production data, calculating comprehensive index values of industrial production by using production efficiency and power consumption factors of industrial enterprises, introducing the comprehensive index values into a hash function, calculating corresponding data identifications, and carrying out data combination on energy consumption data, traffic transportation data and industrial production data according to the first data identifications, the second data identifications and the third data identifications by a server to generate first basic data;

The processing module is used for determining a first carbon emission coefficient set according to the first basic data and determining a second carbon emission coefficient set according to the second basic data, and specifically comprises the following steps: inquiring the data sources of the first basic data to obtain a plurality of corresponding first target data sources, and obtaining a first influence factor of the first target area; respectively acquiring first initial carbon emission coefficients of each first target data source, and carrying out coefficient correction on the first initial carbon emission coefficients according to the first influence factors to obtain a first carbon emission coefficient set; inquiring the data sources of the second basic data to obtain a plurality of corresponding second target data sources, and obtaining a second influence factor of the second target area; respectively acquiring a second initial carbon emission coefficient of each second target data source, and carrying out coefficient correction on the second initial carbon emission coefficient according to the second influence factor to obtain a second carbon emission coefficient set; the method comprises the steps that a server determines a data source of first basic data and names or positions of first target data sources, wherein the data source of the first basic data is a database containing annual carbon emission total amount of each industry, the first basic data source is queried to find data of the annual carbon emission total amount related to the industry, query results are one or more data sets, each target data source has some data related to the first basic data, a first influencing factor related to each target area is determined according to the query results, the influencing factors are carbon emission pressures generated when products are produced or used in the target areas, namely carbon emission intensity of each industry or carbon emission intensity of each area, the server determines corresponding first initial carbon emission coefficients according to the first basic data, carries out coefficient correction on the first initial carbon emission coefficients according to the first influencing factors to obtain first carbon emission coefficient sets, and similarly, the server determines second carbon emission coefficient sets according to the second basic data;

The calculation module is configured to calculate a first total carbon emission amount according to the first basic data and the first carbon emission coefficient set, and calculate a second total carbon emission amount of the second target area according to the second basic data and the second carbon emission coefficient set, and specifically includes: determining the amount of carbon emitted by each energy source when generating a standard unit energy according to the first carbon emission coefficient set; acquiring all energy consumption contained in the first basic data, and calculating the product of the energy consumption and a corresponding carbon emission coefficient to obtain the carbon emission generated by each energy in the first target area; adding the carbon emission generated by each energy source in the first target area to obtain a first total carbon emission; wherein the carbon emission amount of the first target region is calculated by the first base data and the first carbon emission coefficient set, and the carbon emission amount of the first region is calculated by the following formula:

wherein ,for energy consumption data->Is the carbon emission coefficient of energy source, < >>For traffic data->Is the carbon emission coefficient of traffic, < >>For industrial production data,/->F is the first total carbon emission and is the industrial carbon emission coefficient After the first carbon emission total amount of the first target area is calculated, the second carbon emission total amount of the second target area is calculated according to the same method;

the creation module is used for creating a first carbon neutral data model according to the first carbon emission total amount and creating a second carbon neutral data model according to the second carbon emission total amount, and specifically comprises the following steps: obtaining carbon neutralization target information of the first target area, and determining a plurality of carbon neutralization indexes according to the carbon neutralization target information, wherein the plurality of carbon neutralization indexes comprise: carbon neutralization amount, carbon neutralization cost, and carbon neutralization benefit; creating a carbon neutralization mode, an implementation time and an implementation cost according to the carbon neutralization indexes; according to the carbon neutralization mode, the implementation time and the implementation cost, constructing a data model of the first target area to obtain a first carbon neutralization data model; the method comprises the steps of confirming carbon neutralization target information of a target area, including total carbon emission amount to be neutralized, a neutralization time period and a neutralization mode, confirming a calculation method of carbon neutralization indexes, including carbon neutralization amount, carbon neutralization cost and carbon neutralization benefit indexes, wherein the calculation methods of different indexes are different, adjusting according to specific carbon neutralization forms, calculating the carbon neutralization amount according to the carbon neutralization target information of the target area, obtaining annual average carbon emission amount of the target area according to the neutralization time period and the total carbon emission amount to be neutralized, and then calculating the carbon neutralization amount; calculating the carbon neutralization cost according to the carbon neutralization target information of the target area and the selected carbon neutralization mode, and if the carbon neutralization is carried out by adopting a carbon quota transaction mode, calculating the cost for purchasing the carbon quota; if the carbon neutralization is carried out by adopting a clean energy mode, the cost for installing and maintaining the clean energy facility is calculated; calculating carbon neutralization benefits according to the calculated carbon neutralization amount and the carbon neutralization cost, calculating through a formula, outputting a final calculation result, and outputting the calculated carbon neutralization amount, cost and benefit result; when a first target area is subjected to data model construction according to a carbon neutralization mode, implementation time and implementation cost to obtain a first carbon neutralization data model, setting a carbon neutralization target participating in model construction, wherein the carbon neutralization target comprises a carbon neutralization amount, a carbon emission reduction target and a cost target, the basic steps of building the data model are to set variables and factors participating in the model aiming at different carbon neutralization targets, modeling the set variables and factors by adopting a regression model and a deep learning technology during modeling to obtain a predictable carbon neutralization result, after the model is built, evaluating the model and visualizing an evaluation result, evaluating the accuracy of the model by adopting an error analysis and cross verification method, and displaying parameters and calculation results by a visual chart and a visual image;

The generating module is configured to generate a first carbon neutralization evaluation index of the first target area according to the first carbon neutralization data model, and generate a second carbon neutralization evaluation index of the second target area according to the second carbon neutralization data model, and specifically includes: calculating a plurality of first quantized benefit data of the first target region through the first carbon neutral data model; respectively carrying out evaluation index mapping on the plurality of first quantized benefit data to obtain first carbon neutralization evaluation indexes; calculating a plurality of second quantized benefit data for the second target region through the second carbon neutral data model; respectively carrying out evaluation index mapping on the plurality of second quantized benefit data to obtain second carbon neutralization evaluation indexes; defining the total carbon emission and neutralization targets of a target area and calculated benefit indexes, defining the types and indexes of carbon neutralization data models after the targets are well defined, extracting required data, carrying out data processing according to a selected model, calculating a plurality of quantized benefit data of a first target area and a second target area based on the selected model and the neutralization targets, mapping the data into corresponding evaluation indexes, carrying out evaluation index mapping according to different model indexes after calculating forest area, hair volume, carbon reserve and forest management cost data in a forest carbon sink model, collecting the required data when carrying out evaluation index mapping, and sending the acquired and processed data into a forest carbon sink model for carrying out data analysis and processing to obtain forest area, hair volume, carbon reserve and forest management cost benefit data; after the benefit data is obtained, mapping the benefit data into corresponding evaluation indexes, completing the corresponding evaluation indexes by setting different weight indexes, giving larger weight to forest area and carbon reserve indexes, giving smaller weight to forest management cost indexes, mapping the benefit data into corresponding evaluation indexes according to the selected different weights, after the calculation of the benefit data and the mapping of the evaluation indexes are completed, carrying out data modeling based on the obtained data model, constructing a learning model by combining multivariate analysis and regression analysis data modeling technology, predicting carbon neutralization amount, carbon neutralization cost and carbon neutralization benefit indexes, calculating and analyzing the first carbon neutralization evaluation index and the second carbon neutralization evaluation index, and verifying and adjusting the constructed carbon neutralization evaluation index model;

The measuring and calculating module is used for inputting the first carbon neutralization evaluation index and the second carbon neutralization evaluation index into a preset carbon emission trading measuring and calculating model to carry out carbon emission trading measurement, and generating a carbon emission trading scheme between the first target area and the second target area, and specifically comprises the following steps: inputting the first carbon neutralization evaluation index into a preset carbon emission transaction measurement model, and calculating a plurality of first transaction measurement data of the first target area through the carbon emission transaction measurement model; inputting the second carbon neutralization evaluation index into a preset carbon emission transaction measurement model, and calculating a plurality of second transaction measurement data of the second target area through the carbon emission transaction measurement model; calculating a carbon emission trading target value between the first target area and the second target area according to the plurality of first trading measurement data and the plurality of second trading measurement data; generating a carbon emission trading scheme between the first target area and the second target area according to the carbon emission trading target value; inputting a first carbon neutralization evaluation index into a preset carbon emission transaction measuring and calculating model, calculating a plurality of first transaction measuring and calculating data of a first target area, calculating by combining a multiple regression model and a decision tree model technology when calculating transaction measuring and calculating amount, and setting reasonable parameter weight factors in the calculating process; inputting a second carbon neutral evaluation index into a preset carbon emission transaction measuring and calculating model, calculating a plurality of second transaction measuring and calculating data of a second target area, and calculating a certain transaction measuring and calculating amount of the second target area by using the same calculation mode in the transaction measuring and calculating of the first target area; inputting transaction measurement data of a first target area and transaction measurement data of a second target area, calculating a carbon emission transaction target value between the first target area and the second target area through a preset carbon emission transaction measurement model, associating a transaction measurement amount and a cost index with a carbon emission amount and a transaction cost index, calculating the target value, determining a transaction scheme according to the target value after calculating the carbon emission transaction target value, wherein transaction time, transaction price and transaction amount information are needed to be contained, determining the transaction amount and the transaction price according to the transaction time, and finally generating the carbon emission transaction scheme.