CN111210154A - Method and system for type identification and classification treatment of regional carbon emission characteristics - Google Patents

Method and system for type identification and classification treatment of regional carbon emission characteristics Download PDF

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CN111210154A
CN111210154A CN202010029553.5A CN202010029553A CN111210154A CN 111210154 A CN111210154 A CN 111210154A CN 202010029553 A CN202010029553 A CN 202010029553A CN 111210154 A CN111210154 A CN 111210154A
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闫凤英
杨一苇
杨宇灏
陈阳
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Tianjin University
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Abstract

The invention discloses a method and a system for type identification and classification treatment of regional carbon emission characteristics. The method comprises three steps: establishing an index set of regional carbon emission characteristics and metering; performing type identification on the type of the regional carbon emission characteristic according to the index set; and formulating a low-carbon planning strategy according to the type identification result. The invention is characterized by comprising the following technical points: firstly, establishing a carbon emission characteristic index set; secondly, type identification; third, a graphical method of a carbon emission signature type radar map; and fourthly, formulating a low-carbon planning strategy matched with different carbon emission characteristic types, scientifically, comprehensively and conveniently identifying the carbon emission characteristic types of any county level and above administrative areas, providing the low-carbon planning strategy matched with the county level and the administrative areas, and establishing a good foundation for a regional carbon emission characteristic evaluation and control system.

Description

Method and system for type identification and classification treatment of regional carbon emission characteristics
Technical Field
The invention belongs to the field of low-carbon development treatment and planning, and particularly relates to a method and a system for type identification and classification treatment of regional carbon emission characteristics.
Background
At present, China, as the world with the largest carbon emission, plays an important role in promoting global carbon emission reduction. Administrative regions such as provinces, cities and counties are responsible for achieving the emission reduction target of China, but due to the fact that the regions have characteristics such as unbalanced economic development and natural resource difference, carbon emission in different regions also has significant difference. Therefore, for the development of different regions, the carbon emission characteristics formed under the influence of socio-economic factors closely related to carbon emission in each region need to be comprehensively grasped, and the regions with different carbon emission characteristics are distinguished in types, so that an effective and practical regional development strategy is formulated for different carbon emission characteristic types, the coordinated development of each region is promoted, and an effective management approach for controlling carbon in each administrative region is realized. Therefore, a method and a system for identifying the types of the carbon emission characteristics of the administrative regions at or above the county level are established, and the targets are urgent and have great significance.
The existing regional carbon emission characteristic type identification technical method mainly comprises three types: (1) direct scoring method. For example, the existing division modes of east, middle and west, eight economic areas and main functional areas are adopted to simply distinguish the characteristic types of regional carbon emission; (2) double index marking method. If the per-capita GDP and the carbon emission intensity are used as evaluation indexes, the regional carbon emission characteristics are divided into four types through the construction of an evaluation matrix; (3) and (4) a multi-index clustering analysis method. For example, clustering analysis is performed on direct carbon emission indexes (such as total carbon emission, carbon emission intensity, average carbon emission and the like) and relevant influence factor indexes (such as population, industrial structure, economic level, energy structure and the like) to identify the types of regional carbon emission characteristics under different clustering results.
Existing studies reveal differences in regional carbon emission signature types to varying degrees, but the following limitations still exist in specific applications: (1) the existing zone division mode is easily limited by the original zone division conditions (such as economy, zone functions and the like), the requirement of low-carbon treatment type of each zone cannot be reflected, and the carbon emission characteristics in the same zone have larger difference, so that certain limitation still exists in the establishment of the emission reduction path of each zone; (2) indexes in the existing research are usually from a specific social perspective of the research direction, and comprehensive characteristics of the area related to carbon emission are not researched from the multi-dimensional perspective of the area; (3) in the existing research, the type division of the regional carbon emission characteristics is only carried out on the same level regional scale (province, city) by different methods, and the classification or identification of the carbon emission characteristic types of a plurality of levels of regional levels (province, city, county and the like) under a unified method standard system is difficult to realize.
In summary, for the division, identification and treatment of the multi-dimensional factor carbon emission characteristic types which take regional development as a main target, no strong targeted research and unified method standard exists at present, and a good comprehensive index evaluation system and a method system with strong operability and high applicability are not formed.
Disclosure of Invention
It is therefore one of the primary objectives of the claimed invention to provide a method and system for type identification and classification management of regional carbon emission characteristics, so as to at least partially solve at least one of the above technical problems.
In order to achieve the above object, as one aspect of the present invention, there is provided a method for type identification and classification management of regional carbon emission characteristics, comprising the steps of:
first, an index set of regional carbon emission characteristics is established and metered.
In some embodiments, the region is a region divided based on a single administrative district including province, city, or county; the set of indicators includes: an economic development index, a spatial balance index, an industrial structure index, a family life index, a heavy energy index, a clean energy index and/or a technical level index; the metric of the set of metrics includes:
calculating each index in the index set;
the set of indices is normalized based on the value of each index in combination with the national average level.
Further, wherein:
the calculation of each index in the index set comprises the following steps:
economic development indexes are as follows:
Figure BDA0002362571080000021
wherein, GDPRIndicating the total value of production, GDP, in the regionNIndicates the total value of national production, CAPRIndicates the regional end population, CAPNRepresenting the total number of population at the end of the country;
the space balance index is as follows:
Figure BDA0002362571080000031
wherein, FARIndicating the area of forestry land, FANShowing the land area for national forestry, CARArea of land for setting in the display area, CANRepresenting the area of the country's construction land, AARRepresenting the agricultural acreage, AA, in the areaNRepresenting the agricultural cultivated land area of the country;
industrial structural index:
Figure BDA0002362571080000032
wherein, IERIndicating total industrial energy consumption in the area, IENIndicating the national industry Total energy consumption, IARIndicating an industry increase value in the area, IANRepresents a national industry added value;
the family life index is as follows:
Figure BDA0002362571080000033
wherein RERRepresenting energy consumption of home terminals in the area, RENRepresenting the energy consumption of national family life terminals;
heavy energy index:
Figure BDA0002362571080000034
wherein HERIndicating heavy energy consumption in the area, HENIndicating national heavy energy consumption, TERIndicating the total energy consumption in the area, TENRepresenting the total energy consumption of the country;
clean energy indexes are as follows:
Figure BDA0002362571080000035
wherein, CG isRRepresenting the amount of generated clean energy in the area, CGNIndicates the generated energy of national clean energy, TGRIndicates the total power generation amount, TG, in the areaNRepresenting the total power generation of the country;
technical level indexes are as follows:
Figure BDA0002362571080000036
wherein, SRFRIndicating regional internal medicine development expense investment, SRFNRepresenting the national scientific research fund investment.
Normalizing the set of metrics includes:
the value of a certain index in the index set is less than 1, which indicates that the index is less than the national average level;
the value of a certain index in the index set is more than or equal to 1, which indicates that the index is more than or equal to the national average level.
And/or, when the value of an index in the index set is > 2, defining the value of the index as 2, and indicating that the index is on the national average level.
Then, in some embodiments, identifying the type of regional carbon emission characteristic based on the set of indicators includes:
performing Euclidean distance calculation on the index set of the carbon emission characteristics of the region and index sets of different standard types respectively, wherein the standard type corresponding to the minimum Euclidean distance is taken as the type of the region;
the result of the type recognition is displayed as a characteristic radar chart.
In some embodiments, the euclidean distance calculation includes:
Figure BDA0002362571080000041
wherein x represents the index set of the region, y represents the index set of the standard type, i represents various standard types, j represents the numerical value of 1-n indexes, and xjThe value of the j-th index, y, of the regionijValues representing the j index under the i standard type, DiRepresenting Euclidean distances between each index in the region and each index value corresponding to different standard types;
K＝MinDi，
where K denotes a minimum distance value among the euclidean distances, and i denotes a type of the region.
And finally, formulating a low-carbon planning strategy according to the type identification result.
The invention also provides a system for type identification and classification treatment of regional carbon emission characteristics, which is realized based on the method for type identification and classification treatment.
Based on the technical scheme, the method and the system for identifying the type and classifying and treating the regional carbon emission characteristics, provided by the invention, have the following advantages compared with the prior art:
(1) the method establishes an index set which reflects the intrinsic characteristics of regional carbon emission by using regional socioeconomic attributes, forms the definition of the carbon emission characteristic types of administrative regions at or above the county level based on 7 dimensions of 'economic development', 'space balance', 'industrial structure', 'family life', 'energy consumption structure', 'clean energy' and 'technical level', and has positive practical significance and promotion effect on the high-quality development of the regions;
(2) the method combines the regional carbon emission characteristic index set, the type identification method, the graphic representation method of the type characteristic radar chart and the matching method of the type and the low-carbon planning strategy, scientifically, comprehensively and conveniently identifies the type of the carbon emission characteristic of the region, provides the low-carbon planning strategy matched with the regional carbon emission characteristic, fills the blank of the method for identifying and classifying the carbon emission characteristic in administrative regions at or above the county level, and provides scientific and reliable basis for making effective regional development strategies according with the reality aiming at different types of regions.
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FIG. 1 is a flow chart of a method for type identification and classification abatement of carbon emission characteristics in accordance with an embodiment of the present invention;
FIG. 2 is a regional carbon emission control evaluation index system according to an embodiment of the present invention;
FIG. 3 is a radar chart of class I index features in an embodiment of the present invention;
FIG. 4 is a radar chart of the type II index features in the embodiment of the present invention;
FIG. 5 is a radar chart of class III index features in an embodiment of the present invention;
FIG. 6 is a radar chart of the type IV index features in the embodiment of the present invention;
FIG. 7 is a radar chart of the type V index features in the embodiment of the present invention;
FIG. 8 is a radar chart of the VI index features in an embodiment of the present invention;
FIG. 9 is a radar chart of the type VII index features in the embodiment of the present invention.
Detailed Description
The carbon emission characteristics generally refer to the total amount of carbon emission, the intensity of carbon emission, or the per-capita carbon emission amount, etc. However, these apparent characteristics of carbon emissions make it difficult to interpret the structure of regional carbon emissions and affect the intrinsic cause of high or low carbon emissions. Thus, the apparent amount of carbon emissions is insufficient to provide effective guidance to policy makers and planners to mitigate climate change activity.
The apparent characteristics of carbon emissions are often directly related to certain socio-economic factors which represent the intrinsic cause of regional carbon balance and carbon emission performance related to energy consumption, and represent the intrinsic attributes of regional carbon emissions. These intrinsic characteristics of carbon emissions, reflected by socioeconomic factors, are important aspects of the present invention.
The selected socioeconomic indexes related to regional carbon emission are collectively called regional carbon emission characteristic indexes. And comprehensively describing the multidimensional attribute of the region by a plurality of carbon emission characteristic indexes, and calling the comprehensive description as the carbon emission characteristic of the region.
In order that the objects, technical solutions and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the accompanying drawings in conjunction with the following specific embodiments.
In one embodiment, the present invention adopts, for example, the following technical solutions:
the embodiment of the invention discloses a method and a system for type identification and classification treatment of regional carbon emission characteristics, wherein the region is a county-level administrative region or an administrative region above, and the method comprises the following three steps: establishing and metering a regional carbon emission characteristic index set; type identification of regional carbon emission characteristic types; and formulating a low-carbon planning strategy matched with the regional carbon emission characteristics. The method combines the carbon emission characteristic indexes, the type identification method and the type-matched low-carbon planning strategy, scientifically, comprehensively and conveniently identifies the type of the carbon emission characteristic in any administrative region of county level or above in a graphic expression mode of an index radar chart, provides the matched low-carbon planning strategy, and establishes a good foundation for a regional carbon emission characteristic evaluation and control system.
In this embodiment, the flow of the method is shown in fig. 1, and specifically includes:
establishing and metering regional carbon emission characteristic index set in first step
Step 1, defining regional carbon emission characteristic indexes.
In some embodiments, the region is a region divided based on a single administrative district including province, city, or county.
In this embodiment, the selection of the index is considered from the dual angles of the carbon source and the carbon sink: from the perspective of a carbon source, the most main factor influencing carbon emission is energy consumption extracted according to a KAYA formula, and specifically, the influencing factors are divided into heavy energy, energy carbon emission intensity, energy efficiency and economic development; from the carbon sink perspective, the most important factor affecting carbon absorption is the forestry carbon sink, and the three-generation space (production, living and ecological space) pattern is an important factor determining the carbon sink function. Based on the analysis, five most representative factors influencing the carbon source and the carbon sink are further deconstructed and analyzed, and six major aspects influencing and distinguishing the carbon emission characteristics are 'land use', 'economy', 'industry', 'life', 'energy source' and 'technology', respectively. And the important factor of 'carbon reduction potential' influencing the difference of the carbon emission characteristics is taken into consideration, and 7 indexes for evaluating the carbon emission characteristics, namely a clean energy index, a technical level index, a heavy energy index, an industrial structure index, a family life index, an economic development index and a space balance index, are finally constructed. The economic development index and the space balance index reflect the characteristics of the overall level of the region; the industrial structure index, the family life index and the heavy energy index reflect the specific characteristics of carbon emission in different subsections; and the clean energy index and the technical level index can comprehensively reflect the characteristics of energy-saving potential of a region (figure 2).
And 2, calculating and standardizing indexes. Specifically, the method comprises the following steps: calculating each index in the index set; the set of indices is normalized based on the value of each index in combination with the national average level.
In this embodiment, based on the provincial carbon feature evaluation index system, the definition and measurement formula of each index in the regional carbon emission feature is as follows:
economic development indexes are as follows:
Figure BDA0002362571080000071
wherein, GDPRIndicating the total value of production, GDP, in the regionNIndicates the total value of national production, CAPRIndicates the regional end population, CAPNRepresenting the total number of population at the end of the country;
the space balance index is as follows:
Figure BDA0002362571080000072
wherein, FARIndicating the area of forestry land, FANShowing the land area for national forestry, CARArea of land for setting in the display area, CANRepresenting the area of the country's construction land, AARRepresenting the agricultural acreage, AA, in the areaNRepresenting the agricultural cultivated land area of the country;
industrial structural index:
Figure BDA0002362571080000073
wherein, IERIndicating total industrial energy consumption in the area, IENIndicating the national industry Total energy consumption, IARIndicating an industry increase value in the area, IANRepresents a national industry added value;
the family life index is as follows:
Figure BDA0002362571080000074
wherein RERRepresenting energy consumption of home terminals in the area, RENRepresenting the energy consumption of national family life terminals;
heavy energy index:
Figure BDA0002362571080000075
wherein HERIndicating heavy energy consumption in the area, HENIndicating national heavy energy consumption, TERIndicating the total energy consumption in the area, TENRepresenting the total energy consumption of the country;
clean energy indexes are as follows:
Figure BDA0002362571080000081
wherein, CG isRRepresenting the amount of generated clean energy in the area, CGNIndicates the generated energy of national clean energy, TGRIndicates the total power generation amount, TG, in the areaNRepresenting a countryTotal power generation;
technical level indexes are as follows:
Figure BDA0002362571080000082
wherein, SRFRIndicating regional internal medicine development expense investment, SRFNRepresenting the national scientific research fund investment.
In step 2, normalizing the index set further includes: the indexes are all selected relative indexes in the calculation and are compared with the national average level, the index is less than 1, and a certain characteristic representing the type is lower than the national average level; the index is greater than 1, which represents that a certain characteristic is higher than the national average level; the index is equal to 1, representing that a feature is equal to the national average. In some embodiments, the processing manner for calculating and normalizing the index further includes: a value with an index value greater than 2 is defined directly as 2, representing a feature that is much higher than the national average.
Type identification of second-step regional carbon emission characteristic types
And 3, calculating Euclidean distances between the index set of the carbon emission characteristics of a certain region and the index sets of different standard types respectively, wherein the standard type corresponding to the minimum Euclidean distance value is selected to be the type of the region.
In this embodiment, the euclidean distances between the index set of the carbon emission characteristics of a certain region and the index sets of the 7 standard types are calculated, and the standard type corresponding to the value with the smallest euclidean distance is selected as the type of the region. The calculation formula is as follows:
Figure BDA0002362571080000083
when K is MinDiAt this time, the type of a certain region is i-type corresponding to the minimum value K.
Wherein x represents the index set of a certain area, y represents the index set of standard type (in this embodiment, y can be the index set of type I-type VII described in Table 1), I represents various standard types, and j represents 1 ∞n index values (in this example, j represents a value of 1 to 7 indices, I represents standard types I to VII), and xjI.e. the value of the j-th index, y, representing a regionijI.e. a value representing the j index in the i standard type, DiThe euclidean distance between each index in a certain area and each index value corresponding to different standard types (in this embodiment, 7 standard types) is represented, K represents the minimum distance value in the 7 euclidean distances, and the i class corresponding to the minimum euclidean distance is the type i of the area.
TABLE 1 set of standard type carbon emission characteristic indices
Figure BDA0002362571080000091
The steps further include:
and 4, corresponding the type I to Roman numeral I-VII standard types in the table 1, and displaying the classification result as a characteristic radar chart of the type.
Thirdly, establishing a low-carbon planning strategy matched with regional carbon emission characteristics
And 5, formulating a low-carbon planning strategy matched with the regional carbon emission characteristics according to the characteristic radar chart.
The low-carbon planning strategy is formulated by the following steps: 1) defining the names of types, including the developed degree and the direction of low-carbon treatment (consumption guide type, total amount control type, technology enhancement type, structure adjustment type, economic development type, industrial optimization type, resource utilization type and the like); 2) the regional characteristics are characterized, including the conditions of economy, population, land, energy consumption of each department, industry, industrial structure, energy structure, clean energy and the like and the comparison with the national average level; 3) and forming a low-carbon planning strategy aiming at the regional low-carbon development control direction and the characteristic index control.
In this embodiment, with reference to fig. 3 to 9, the low-carbon planning strategy (table 2) of the corresponding carbon emission characteristic type is selected according to the classification of the carbon emission characteristic types of the regions in step 4.
TABLE 2 characteristics of each type and Low carbon planning strategy
Figure BDA0002362571080000101
The technical solution of the present invention is further illustrated by the following specific embodiments in conjunction with the accompanying drawings. It should be noted that the following specific examples are given by way of illustration only and the scope of the present invention is not limited thereto.
Example 1
The invention aims to establish a set of regional carbon emission characteristic type identification and classification treatment method flows available for planners, form regional carbon emission type division and identification standards with high comprehensiveness, operability and applicability, and further establish a multi-path and differentiated low-carbon planning strategy system research method according to the self carbon emission characteristics of different regions.
In order to solve the defects of the existing method, the invention is based on the following three steps: firstly, establishing an index set of regional carbon emission characteristics and metering; secondly, identifying the type of the regional carbon emission characteristics according to the index set; and thirdly, a low-carbon planning strategy is formulated according to the type recognition result. The method for recognizing the types of the carbon emission characteristics of the administrative regions at or above the county level is provided, the carbon emission characteristic types of any administrative region at or above the county level are scientifically, comprehensively and conveniently recognized, a low-carbon planning strategy matched with the carbon emission characteristic types is provided, and a good foundation is established for a regional carbon emission characteristic evaluation and control system.
Taking a certain province in China as an example, the carbon emission characteristics of 2015 are subjected to type identification and a classification treatment method is proposed. The method comprises the following specific steps:
first step, establishing index set of regional carbon emission characteristics and metering
Step 1, defining regional carbon emission characteristic indexes;
and 2, calculating and standardizing indexes.
According to the metering formula of the carbon emission characteristic index set in the step 2, the economic development index, the space balance index, the industrial structure index, the family life index, the heavy energy index, the clean energy index and the technical level index of a certain province are numerically calculated, and the data are subjected to standardized processing, wherein the results are shown in a table 3.
TABLE 3 carbon emission characteristic index of certain provinces
Figure BDA0002362571080000111
Type identification of second-step regional carbon emission characteristic types
Step 3, respectively carrying out Euclidean distance calculation on the index set of a certain province in the table 3 and the index sets of 7 standard types in the table 1, wherein D1＝1.26，D2＝0.6，D3＝2.14，D4＝2.62，D5＝1.82，D6＝2.4，D73.16, so K ═ D2＝0.6。
Step 4, thus obtaining the province type II.
Thirdly, establishing a low-carbon planning strategy matched with regional carbon emission characteristics
And 5, making a low-carbon planning strategy matched with the regional carbon emission characteristics.
From table 2, type II, named less developed-gross control, has a characteristic radar chart that tends to fig. 4, and its type characteristics are: the highest high-tech industry development level, industrial structure and heavy energy lightening, low clean energy utilization level and household energy consumption level equal to the national average level. This type of low carbon strategy is: 1) attention is paid to the supervision of the total energy consumption of industrial and commercial departments; 2) the index of clean energy is improved, and the index of space balance is controlled.
The result shows that the method is specifically implemented by using data of a certain province in 2015, the numerical values of the 7 carbon emission characteristic indexes of the certain province are obtained through calculation and are subjected to standardization treatment, after type identification, the certain province is identified as type II, and a corresponding low-carbon planning strategy is found according to the type II carbon emission characteristic types in the table 2. The low-carbon planning strategy in the result has obvious optimization result, and has positive practical significance and promotion effect on realizing low-carbon development in county-level and above administrative regions.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A method for type identification and classification treatment of regional carbon emission characteristics is characterized by comprising the following steps:
establishing an index set of regional carbon emission characteristics and metering;
performing type identification on the type of the regional carbon emission characteristic according to the index set;
and formulating a low-carbon planning strategy according to the type identification result.
2. The type recognition and classification abatement method according to claim 1, wherein the region is a region divided based on a single administrative district including province, city or county.
3. The method of type recognition and classification governance according to claim 1 or 2, wherein the set of metrics comprises: economic development index, spatial balance index, industrial structure index, family life index, heavy energy index, clean energy index, and/or technical level index.
4. The method of type recognition and classification governance according to claim 3, wherein the metric of the set of metrics comprises:
calculating each index in the index set;
the set of indicators is normalized based on the values of the indicators in combination with a national average level.
5. The method of claim 4, wherein calculating the set of indicators comprises:
economic development indexes are as follows:
Figure FDA0002362571070000011
wherein, GDPRIndicating the total value of production, GDP, in the regionNIndicates the total value of national production, CAPRIndicates the regional end population, CAPNRepresenting the total number of population at the end of the country;
the space balance index is as follows:
Figure FDA0002362571070000012
wherein, FARIndicating the area of forestry land, FANShowing the land area for national forestry, CARArea of land for setting in the display area, CANRepresenting the area of the country's construction land, AARRepresenting the agricultural acreage, AA, in the areaNRepresenting the agricultural cultivated land area of the country;
industrial structural index:
Figure FDA0002362571070000021
wherein, IERIndicating total industrial energy consumption in the area, IENIndicating the national industry Total energy consumption, IARIndicating an industry increase value in the area, IANRepresents a national industry added value;
the family life index is as follows:
Figure FDA0002362571070000022
wherein RERRepresenting energy consumption of home terminals in the area, RENRepresenting the energy consumption of national family life terminals;
heavy energy index:
Figure FDA0002362571070000023
wherein HERIndicating heavy energy consumption in the area, HENIndicating national heavy energy consumption, TERIndicating the total energy consumption in the area, TENRepresenting the total energy consumption of the country;
clean energy indexes are as follows:
Figure FDA0002362571070000024
wherein, CG isRRepresenting the amount of generated clean energy in the area, CGNIndicates the generated energy of national clean energy, TGRIndicates the total power generation amount, TG, in the areaNRepresenting the total power generation of the country;
technical level indexes are as follows:
Figure FDA0002362571070000025
wherein, SRFRIndicating regional internal medicine development expense investment, SRFNRepresenting the national scientific research fund investment.
6. The method of type identification and classification governance of claim 4, wherein normalizing the set of metrics comprises:
the value of a certain index in the index set is less than 1, which indicates that the index is less than the national average level;
the value of a certain index in the index set is more than or equal to 1, which indicates that the index is more than or equal to the national average level.
7. The method of type identification and classification governance of claim 6, wherein normalizing the set of metrics further comprises:
when the value of an index in the index set is greater than 2, the value of the index is defined as 2, which means that the index is on the national average level.
8. The method of type recognition and classification governance according to claim 7, wherein said type recognizing the type of regional carbon emission characteristics comprises:
respectively carrying out Euclidean distance calculation on the index set of the carbon emission characteristics of the region and index sets of different standard types, wherein the standard type corresponding to the minimum Euclidean distance is taken as the type of the region;
the result of the type recognition is displayed as a characteristic radar chart.
9. The method of type identification and classification governance of claim 8, wherein the euclidean distance calculation comprises:
Figure FDA0002362571070000031
wherein x represents the index set of the region, y represents the index set of the standard type, i represents various standard types, j represents the numerical value of 1-n indexes, and xjThe value of the j-th index, y, of the regionijValues representing the j index under the i standard type, DiRepresenting Euclidean distances between each index in the region and each index value corresponding to different standard types;
K＝MinDi，
where K denotes a minimum distance value among the euclidean distances, and i denotes a type of the region.
10. A system for type identification and classification abatement of regional carbon emission characteristics, characterized in that the system is implemented based on the method of type identification and classification abatement according to any one of claims 1 to 9.
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