Method and device for determining optimization target of air quality improvement based on carbon coordination, medium and product
By obtaining the carbon-coordinated air quality comprehensive index from lower-level administrative units, and combining it with carbon emission indicators and PM2.5 concentration reduction rates, air quality improvement and optimization targets are determined, thus solving the coordination problem between air quality improvement and carbon emission control and achieving synchronous management of air quality and carbon emissions.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- CHINESE ACAD OF ENVIRONMENTAL PLANNING
- Filing Date
- 2026-02-09
- Publication Date
- 2026-06-05
AI Technical Summary
In existing technologies, there is a lack of effective coordinated management between air quality improvement and carbon emission control targets, making it difficult to achieve air quality improvement and carbon emission control simultaneously.
By obtaining the carbon-coordinated air quality comprehensive index of each subordinate administrative unit, and combining it with the total carbon emission control target, the baseline year population-weighted PM2.5 concentration, and the PM2.5 concentration reduction rate brought about by end-of-pipe treatment of air pollution, the air quality improvement and optimization targets are determined, so as to achieve synergy between air quality improvement and carbon emission control.
This achieved a synergy between air quality improvement and carbon emission control targets, ensuring that administrative units at all levels reduced PM2.5 concentrations while controlling total carbon emissions, thus improving the efficiency and effectiveness of environmental governance.
Smart Images
Figure CN122155490A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of carbon emission reduction technology, and in particular to a method, apparatus, medium, and product for determining air quality improvement and optimization targets based on carbon synergy. Background Technology
[0002] Conventional air pollutants and greenhouse gas emissions share a high degree of common origin and process characteristics. Promoting coordinated control of atmospheric environmental governance and carbon emissions is a key area for achieving synergistic effects in pollution reduction and carbon reduction.
[0003] Currently, the management of conventional air pollutant and greenhouse gas emission reduction adopts different approaches and management models in terms of target setting and allocation. Air pollution control, with the goal of protecting public health, has established a management system centered on improving air quality. At the national level, air quality improvement and optimization targets are set, while at the provincial and municipal levels, a differentiated target allocation strategy is adopted based on the current air quality status and historical improvement trends. The Ministry of Ecology and Environment plays a leading role in the formulation and allocation of air quality improvement and optimization targets. Regarding carbon emission control, based on national climate commitments and the medium- and long-term low-carbon development strategy, the national level has proposed total carbon dioxide emission and carbon intensity targets. The National Development and Reform Commission (NDRC) leads the implementation of classified carbon emission intensity control, determining provincial carbon emission intensity targets by category. However, there are no mandatory requirements at the city level, and total carbon emission control targets have not yet been clearly allocated at the regional and provincial / municipal levels.
[0004] Therefore, it is urgent to effectively combine air quality improvement and optimization with carbon emission control targets to achieve synergy between the two. Summary of the Invention
[0005] The purpose of this invention is at least to provide a method for determining air quality improvement optimization targets based on carbon synergy, which can achieve synergy between air quality improvement and carbon emission control targets.
[0006] In a first aspect, the present invention provides a method for determining air quality improvement optimization targets based on carbon synergy, comprising: obtaining a carbon-synergistic comprehensive air quality index corresponding to each lower-level administrative unit; wherein the carbon-synergistic comprehensive air quality index is associated with the following parameters: total carbon emission control target, and population-weighted PM2.5 in the baseline year. 2.5 PM2.5 concentration, resulting from end-of-pipe treatment of air pollution 2.5 Concentration reduction rate; based on the comprehensive air quality index of carbon synergy corresponding to each subordinate administrative unit, determine the air quality improvement and optimization target corresponding to each subordinate administrative unit.
[0007] The system obtains the carbon-coordinated comprehensive air quality index for each lower-level administrative unit, and then determines the air quality improvement and optimization targets for each unit based on this index. By combining the carbon-coordinated comprehensive air quality index with the determination of these targets, the system can achieve synergy between air quality improvement and carbon emission control objectives.
[0008] Optionally, determining the air quality improvement and optimization target for each lower-level administrative unit based on the carbon-coordinated comprehensive air quality index corresponding to each lower-level administrative unit includes: obtaining the air quality improvement and optimization target corresponding to a reference unit; the reference unit is any lower-level administrative unit; determining the air quality improvement and optimization targets for the remaining lower-level administrative units based on the air quality improvement and optimization targets corresponding to the reference unit; wherein, the first quotient corresponding to any lower-level administrative unit is equal, and the first quotient is: the quotient of the carbon-coordinated comprehensive air quality index and the air quality improvement and optimization target.
[0009] Optionally, the air quality improvement optimization target corresponding to the reference unit is: ; in, The air quality improvement optimization target corresponding to the reference unit is... Let PM be the corresponding unit of the i-th lower-level administrative unit in the base year. 2.5 The three-year moving average of concentration Let be the total number of subordinate administrative units under the i-th subordinate administrative unit. The total number of subordinate administrative units under a higher-level administrative unit. For the higher-level administrative unit in the target year PM 2.5 Target concentration value, The carbon-coordinated comprehensive air quality index is used as the reference unit. Let be the carbon-coordinated comprehensive air quality index corresponding to the i-th lower-level administrative unit.
[0010] Optionally, obtaining the carbon-coordinated comprehensive air quality index corresponding to each lower-level administrative unit includes: determining the carbon-coordinated comprehensive air quality index corresponding to the i-th lower-level administrative unit using the following formula: ; Among them, SI i SI1 is the carbon-coordinated comprehensive air quality index corresponding to the i-th lower-level administrative unit. i The weighted PM of the baseline year population corresponding to the i-th lower-level administrative unit 2.5 Concentration, SI2i SI3 represents the total carbon emission control target corresponding to the i-th lower-level administrative unit. i The PM2.5 concentration resulting from end-of-pipe air pollution control measures corresponding to the i-th lower-level administrative unit. 2.5 Concentration decrease rate.
[0011] Optionally, the population-weighted PM2.5 of the base year corresponding to the i-th lower-level administrative unit. 2.5 The concentration is calculated using the following formula: ; in, The weighted PM2.5 of the baseline year population corresponding to the i-th lower-level administrative unit 2.5 concentration, Let be the population of the i-th lower-level administrative unit in the base year. Let be the population of the i-th lower-level administrative unit in the year preceding the base year. Let be the population of the i-th lower-level administrative unit in the two years preceding the base year; For the uth subordinate administrative unit in the base year PM 2.5 concentration, For the uth subordinate administrative unit, the PM in the year preceding the base year 2.5 concentration, For the uth subordinate administrative unit, the PM in the two years preceding the base year 2.5 concentration; Let u be the population of the uth subordinate administrative unit in the base year. Let be the population of the u-th sub-subordinate administrative unit in the year preceding the base year. Let be the population of the uth subordinate administrative unit in the two years preceding the base year.
[0012] Optionally, the PM2.5 generated by the end-of-pipe treatment of air pollution corresponding to the i-th lower-level administrative unit 2.5 The concentration reduction rate is obtained through the following steps: obtaining the air pollutant emissions corresponding to the i-th lower-level administrative unit when the best feasible control technology is adopted; and simulating the PM2.5 concentration corresponding to the air pollutant emissions based on the WRF-CMAQ air quality model. 2.5 Concentration; obtain the simulated PM2.5 concentration. 2.5 The concentration relative to the PM2.5 concentration of the i-th lower-level administrative unit in the base year 2.5 The rate of decrease in concentration, as a measure of PM2.5 concentration resulting from end-of-pipe treatment of air pollution. 2.5 Concentration decrease rate.
[0013] Optionally, the total carbon emission control target corresponding to the i-th lower-level administrative unit is associated with the historical responsibility index, economic capacity index, and emission reduction potential index corresponding to the i-th lower-level administrative unit; wherein, the historical responsibility index is associated with the emission intensity in the base year and the cumulative per capita carbon emissions in the past N years, where N is a positive integer; the economic capacity index is associated with the per capita GDP in the base year and the fiscal revenue in the base year; and the emission reduction potential index is associated with the proportion of fossil energy in primary energy consumption in the base year and the energy consumption per 10,000 yuan of industrial added value in the base year.
[0014] Optionally, the total carbon emission control target corresponding to the i-th lower-level administrative unit is obtained using the following formula: SI2 i = ;in, Let i be the carbon emission intensity of the i-th lower-level administrative unit in the base year. Let be the carbon emission intensity reduction indicator for the i-th lower-level administrative unit. Let be the GDP of the i-th lower-level administrative unit in the target year.
[0015] Optionally, the carbon emission intensity reduction index corresponding to any lower-level administrative unit is obtained by the following steps: obtaining the carbon emission intensity reduction index corresponding to the reference unit; the reference unit is any lower-level administrative unit; based on the carbon emission intensity reduction index corresponding to the reference unit, determining the carbon emission intensity reduction index corresponding to the remaining lower-level administrative units; wherein, the second quotient corresponding to any lower-level administrative unit is equal, and the second quotient is: the quotient of the carbon emission fairness comprehensive index and the carbon emission intensity reduction index.
[0016] Optionally, the carbon emission intensity reduction index corresponding to the reference unit is determined using the following formula: ; in, Let i be the carbon emission intensity of the i-th lower-level administrative unit in the base year. Let be the GDP of the i-th lower-level administrative unit in the target year. The carbon emission intensity of the higher-level administrative unit in the base year. The GDP of the higher-level administrative unit in the target year is represented by , and the TCI is the carbon emission intensity reduction indicator of the higher-level administrative unit in the target year. The carbon emission intensity reduction index corresponding to the reference unit, The carbon emission equity composite index corresponding to the reference unit. Let be the carbon emission equity comprehensive index corresponding to the i-th lower-level administrative unit.
[0017] Optionally, the carbon emission equity composite index corresponding to the i-th lower-level administrative unit is determined by the following formula: ;in, This represents the historical responsibility index corresponding to the i-th lower-level administrative unit. Let i be the economic capacity index corresponding to the i-th lower-level administrative unit. Let be the emission reduction potential index corresponding to the i-th lower-level administrative unit; where, , , ; Let be the base year carbon emission intensity corresponding to the i-th lower-level administrative unit. Let N be the cumulative per capita carbon emissions for the i-th administrative unit over the past N years. Let C2 be the base year per capita GDP corresponding to the i-th lower-level administrative unit. i Let P1 be the base year fiscal revenue corresponding to the i-th lower-level administrative unit. i Let P2 be the proportion of fossil fuels in primary energy consumption in the baseline year corresponding to the i-th lower-level administrative unit. i Let be the energy consumption per 10,000 yuan of industrial added value corresponding to the i-th lower-level administrative unit in the benchmark year.
[0018] Secondly, the present invention also provides a carbon-coordinated air quality improvement optimization target determination device, comprising: a carbon-coordinated air quality comprehensive index acquisition unit, used to acquire the carbon-coordinated air quality comprehensive index corresponding to each lower-level administrative management unit; the carbon-coordinated air quality comprehensive index is associated with the following parameters: total carbon emission control target, and population-weighted PM2.5 in the baseline year. 2.5 PM2.5 concentration, resulting from end-of-pipe treatment of air pollution 2.5 Concentration reduction rate; Air quality improvement and optimization target unit, used to determine the air quality improvement and optimization target for each subordinate administrative unit based on the carbon-coordinated air quality comprehensive index corresponding to each subordinate administrative unit.
[0019] Thirdly, the present invention also provides a computer-readable storage medium, which is a non-volatile storage medium or a non-transient storage medium, on which a computer program is stored, wherein the computer program, when run by a processor, executes the steps of any of the above-described methods for determining air quality improvement optimization targets based on carbon synergy.
[0020] Fourthly, the present invention provides a computer program product, including a computer program / instruction, wherein when the computer program / instruction is executed by a computer, any of the above-described methods for determining air quality improvement optimization targets based on carbon synergy are executed.
[0021] Fifthly, the present invention also provides another apparatus for determining air quality improvement optimization targets based on carbon synergy, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the steps of any of the above-described methods for determining air quality improvement optimization targets based on carbon synergy when running the computer program. Attached Figure Description
[0022] Figure 1 This is a flowchart of a method for determining air quality improvement optimization targets based on carbon synergy, as described in an embodiment of the present invention. Figure 2 This is a schematic diagram of a method for determining air quality improvement optimization targets based on carbon synergy, as described in an embodiment of the present invention. Detailed Implementation
[0023] To make the above-mentioned objectives, features and beneficial effects of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
[0024] This invention provides a method for determining air quality improvement optimization targets based on carbon synergy, referring to... Figure 1 The following will provide a detailed explanation through specific steps.
[0025] Step 101: Obtain the carbon-coordinated comprehensive air quality index for each lower-level administrative unit.
[0026] In its implementation, the carbon-coordinated comprehensive air quality index is linked to the following parameters: total carbon emission control targets, and population-weighted PM2.5 in the baseline year. 2.5 PM2.5 concentration, resulting from end-of-pipe treatment of air pollution 2.5 Concentration decrease rate.
[0027] Or, to put it another way, based on the total carbon emission control targets for each lower-level administrative unit and the population-weighted PM2.5 of the baseline year... 2.5 PM2.5 concentration and the effects of end-of-pipe treatment on air pollution 2.5 The rate of decrease in concentration can determine the comprehensive air quality index for carbon synergy corresponding to the lower-level administrative unit.
[0028] In practice, the aforementioned baseline year population-weighted PM2.5 2.5 PM2.5 concentration and the effects of end-of-pipe treatment on air pollution 2.5 The concentration reduction rate, etc., can be obtained through public channels or calculated from publicly available data.
[0029] For example, the aforementioned baseline year population-weighted PM2.5 2.5 Concentration can be based on population and PM2.5 data released by relevant administrative departments. 2.5The concentration data was calculated.
[0030] In this embodiment of the invention, the aforementioned lower-level administrative management unit is a concept relative to the higher-level administrative management unit. When the higher-level administrative management unit is the state, the corresponding lower-level administrative management unit is the provincial-level administrative management unit. When the higher-level administrative management unit is the provincial-level administrative management unit, the lower-level administrative management unit is the municipal-level administrative management unit.
[0031] Step 102: Based on the carbon-coordinated air quality comprehensive index corresponding to each lower-level administrative unit, determine the air quality improvement and optimization target corresponding to each lower-level administrative unit.
[0032] In this embodiment of the invention, the air quality improvement and optimization target can be associated with the PM2.5 concentration of the target year. 2.5 The concentration value and the PM2.5 concentration of the baseline year 2.5 The concentration value. Furthermore, air quality improvement and optimization targets can be set from the target annual PM2.5 concentration. 2.5 The concentration value and the PM2.5 concentration of the baseline year 2.5 The concentration value was calculated.
[0033] In some embodiments, the air quality improvement optimization target can be the PM2.5 concentration for the target year. 2.5 The concentration value relative to the PM2.5 concentration in the baseline year 2.5 The rate of decrease in concentration value.
[0034] In other embodiments, the air quality improvement optimization target can be the PM2.5 concentration for the target year. 2.5 The concentration value.
[0035] In this embodiment of the invention, after obtaining the carbon-coordinated air quality comprehensive index corresponding to each lower-level administrative unit, the air quality improvement and optimization target corresponding to the reference unit can be obtained. The reference unit can be any lower-level administrative unit.
[0036] For example, if a higher-level administrative unit has 13 subordinate administrative units, then one of the 13 subordinate administrative units can be selected as the reference unit.
[0037] After obtaining the air quality improvement and optimization targets corresponding to the reference unit, the air quality improvement and optimization targets corresponding to the other lower-level administrative units can be determined based on the air quality improvement and optimization targets corresponding to the reference unit.
[0038] In practice, the air quality improvement and optimization targets for other lower-level administrative units can be determined based on the following constraints: the first quotient value corresponding to any lower-level administrative unit is equal, and the first quotient value is the quotient of the carbon-coordinated comprehensive air quality index and the air quality improvement and optimization target.
[0039] The specific execution of steps 101 to 102 above will be explained in detail below.
[0040] First, let me explain the specific process of obtaining total carbon emission control targets.
[0041] In this embodiment of the invention, the total carbon emission control target corresponding to the i-th lower-level administrative unit can be associated with the historical responsibility index, economic capacity index, and emission reduction potential index corresponding to the i-th lower-level administrative unit.
[0042] Specifically, the historical responsibility index corresponding to the i-th lower-level administrative unit is related to the emission intensity in the base year and the per capita cumulative carbon emissions in the past N years, where N is a positive integer; the economic capacity index corresponding to the i-th lower-level administrative unit is related to the per capita GDP in the base year and the fiscal revenue in the base year; the emission reduction potential index corresponding to the i-th lower-level administrative unit is related to the proportion of fossil energy (such as coal) in primary energy consumption in the base year and the energy consumption per 10,000 yuan of industrial added value in the base year.
[0043] In this embodiment of the invention, a three-level indicator framework can be pre-constructed, which includes primary indicators, secondary indicators, and tertiary indicators.
[0044] In practice, the primary indicator is the carbon emission equity comprehensive index E, the secondary indicators include the historical responsibility index (R), the economic capacity index (C), and the emission reduction potential index (P), and the tertiary indicators include: the baseline year carbon emission intensity (R1) under the historical responsibility dimension, the per capita cumulative carbon emissions over the past N years (R2), the baseline year per capita GDP (C1) and baseline year fiscal revenue (C2) under the economic capacity dimension, the baseline year proportion of fossil energy (such as coal) in primary energy consumption (P1) and the baseline year energy consumption per 10,000 yuan of industrial added value (P2) under the emission reduction potential dimension.
[0045] The aforementioned base year can also be called a reference year. The base year can be linked to the relevant plans of the administrative department. For example, if the period is from 2021 to 2025, 2020 would be used as the base year.
[0046] The baseline year carbon emission intensity of a particular administrative unit can be obtained from official annual carbon emission reports.
[0047] In practice, carbon emission intensity, also known as carbon intensity, refers to the amount of carbon dioxide emissions generated per unit of GDP growth. It is mainly used to measure the relationship between economic growth and carbon emission growth.
[0048] If a given administrative unit experiences economic growth while its carbon emission intensity decreases, it indicates that the unit has achieved a low-carbon development model.
[0049] The N mentioned above can be 5, 10, or other values. For example, when N is 5, the per capita cumulative carbon emissions over the past N years are the same as the per capita cumulative carbon emissions over the past 5 years.
[0050] In specific implementation, see Table 1 below, which illustrates a three-level indicator framework for optimizing total carbon emission targets in an embodiment of the present invention.
[0051]
[0052] Table 1
[0053] As shown in Table 1, the historical responsibility index (R) in the secondary indicators is related to the baseline year carbon emission intensity (R1) and the per capita cumulative carbon emissions over the past N years in the tertiary indicators. In other words, the historical responsibility index (R) is determined based on the baseline year carbon emission intensity (R1) and the per capita cumulative carbon emissions over the past N years in the tertiary indicators.
[0054] The economic capability index (C) in the secondary indicators is linked to the baseline year's per capita GDP and baseline year's fiscal revenue in the tertiary indicators. In other words, the economic capability index (C) is determined based on the baseline year's per capita GDP and baseline year's fiscal revenue.
[0055] The emission reduction potential index (P) in the secondary indicators is related to the proportion of fossil energy in primary energy consumption in the baseline year (P1) and the energy consumption per 10,000 yuan of industrial added value in the baseline year (P2) in the tertiary indicators. In other words, the emission reduction potential index (P) is determined based on the proportion of fossil energy in primary energy consumption in the baseline year (P1) and the energy consumption per 10,000 yuan of industrial added value in the baseline year (P2).
[0056] After determining the historical responsibility index (R), economic capacity index (C), and emission reduction potential index (P), a primary indicator corresponding to an administrative unit can be determined: the carbon emission equity comprehensive index E.
[0057] In practice, the units corresponding to the six tertiary indicators mentioned above are not entirely the same. Therefore, after obtaining the tertiary indicators, these six tertiary indicators can be standardized to obtain unitless scalar data.
[0058] In practical implementation, the following formula can be used to standardize the six tertiary indicators mentioned above: (1) Among them, X i Let X be a third-level indicator corresponding to the i-th lower-level administrative unit (province / city). For X i After standardization, the three-level indicators are defined as follows: max(X) is the maximum value of the three-level indicator X across all lower-level administrative units, and min(X) is the minimum value of the three-level indicator X across all lower-level administrative units.
[0059] For example, if X is GDP per capita, then X i Let X be the per capita GDP corresponding to the i-th lower-level administrative unit, max(X) be the maximum per capita GDP corresponding to all lower-level administrative units, and min(X) be the minimum per capita GDP corresponding to all lower-level administrative units.
[0060] In the following embodiments of the present invention, unless otherwise stated, the six tertiary indicators involved refer to the tertiary indicators after standardization.
[0061] In this embodiment of the invention, after obtaining the standardized tertiary indicators, three secondary indicators, namely the historical responsibility index (R), the economic capacity index (C), and the emission reduction potential index (P), can be calculated respectively.
[0062] In practical implementation, the historical responsibility index (R) can be calculated using the following formula: (2) Among them, R1 i R2 represents the base year carbon emission intensity corresponding to the i-th lower-level administrative unit. i Let R be the cumulative per capita carbon emissions over the past N years for the i-th administrative unit, where n is the total number of subordinate administrative units. i This represents the historical responsibility index corresponding to the i-th lower-level administrative unit.
[0063] For example, if the superior administrative unit is a provincial-level administrative unit, which includes 13 municipal-level administrative units, then the value of n is 13.
[0064] In practical implementation, the economic capability index (C) can be calculated using the following formula: (3) Among them, C1 i Let C2 be the base year per capita GDP corresponding to the i-th lower-level administrative unit. i Let C be the base year fiscal revenue corresponding to the i-th lower-level administrative unit, n be the total number of lower-level administrative units, and C be the total fiscal revenue of the i-th lower-level administrative unit. i Let be the economic capacity index corresponding to the i-th lower-level administrative unit.
[0065] In practical implementation, the emission reduction potential index (P) can be calculated using the following formula: (4) Among them, P1 i Let P2 be the proportion of fossil fuels in primary energy consumption in the baseline year corresponding to the i-th lower-level administrative unit. i Let P be the energy consumption per 10,000 yuan of industrial added value corresponding to the i-th lower-level administrative unit in the baseline year, where n is the total number of lower-level administrative units. i Let be the emission reduction potential index corresponding to the i-th lower-level administrative unit.
[0066] In this embodiment of the invention, after obtaining the secondary indicators corresponding to the lower-level administrative units, the primary indicator (i.e., the carbon emission fairness comprehensive index) corresponding to each lower-level administrative unit can be calculated. For the i-th lower-level administrative unit, its corresponding carbon emission fairness comprehensive index E i It is related to its corresponding historical responsibility index R i Economic Capacity Index C i and the emission reduction potential index P i get.
[0067] In practical implementation, the carbon emission equity comprehensive index E corresponding to the i-th lower-level administrative unit i It can be calculated using the following formula: (5) In other words, the carbon emission equity comprehensive index E corresponding to the i-th lower-level administrative unit i It can be given its three corresponding secondary indicators (historical responsibility index R). i Economic Capacity Index C i and the emission reduction potential index P i The arithmetic mean of .
[0068] It is understandable that the carbon emission equity comprehensive index E corresponding to the i-th lower-level administrative unit is... i Alternatively, it can be obtained by performing other calculations on its three corresponding secondary indicators.
[0069] For example, the historical responsibility index R i Economic Capacity Index C i and the emission reduction potential index P i Assign different weighting coefficients to each of the three secondary indicators, calculate the weighted average of the values, and use this average as the carbon emission equity composite index E. i .
[0070] In this embodiment of the invention, after calculating the carbon emission fairness comprehensive index E corresponding to each lower-level administrative unit, the carbon emission intensity reduction index corresponding to each lower-level administrative unit can be obtained.
[0071] In practice, a specific lower-level administrative unit can be selected as a reference unit to obtain the corresponding carbon emission intensity reduction index.
[0072] In practical implementation, the carbon emission intensity reduction index corresponding to the reference unit can be calculated using the following formula: (6) Among them, TCI is the carbon emission intensity reduction indicator for the higher-level administrative unit in the target year. l CI is the carbon emission intensity reduction index corresponding to the reference unit. base,i Let be the carbon emission intensity of the i-th lower-level administrative unit in the base year, and be denoted by GDP. target_year,i Let E be the GDP of the i-th lower-level administrative unit in the target year. l The carbon emission equity index is the reference unit.
[0073] After obtaining the carbon emission intensity reduction index corresponding to the reference unit, and based on the fact that the second quotient is equal for different lower-level administrative units, the carbon emission intensity reduction index corresponding to different lower-level administrative units can be calculated sequentially. The aforementioned second quotient is the quotient of the carbon emission equity composite index and the carbon emission intensity reduction index.
[0074] Specifically, the carbon emission intensity reduction target for each lower-level administrative unit can be calculated using the following formula: (7) In equation (7), E1 is the carbon emission equity composite index corresponding to the first lower-level administrative unit, and TCI is... l This is the carbon emission intensity reduction target corresponding to the first lower-level administrative unit; and so on, E n TCI is the carbon emission equity composite index corresponding to the nth lower-level administrative unit. n This represents the carbon emission intensity reduction indicator corresponding to the nth lower-level administrative unit.
[0075] In this embodiment of the invention, after obtaining the carbon emission intensity reduction index corresponding to each lower-level administrative unit, the total carbon emission control index corresponding to each lower-level administrative unit can be determined.
[0076] In practical implementation, the total carbon emission control target corresponding to the i-th lower-level administrative unit can be calculated using the following formula: (8) In equation (8), CE target_year,i Let be the total carbon emission control target for the target year corresponding to the i-th lower-level administrative unit. Let be the carbon emission intensity of the i-th lower-level administrative unit in the base year, and be denoted by GDP. target_year,i Let TCI be the GDP of the i-th lower-level administrative unit in the target year. i Let be the carbon emission intensity reduction index corresponding to the i-th lower-level administrative unit.
[0077] In this embodiment of the invention, after obtaining the total carbon emission control targets for each lower-level administrative unit, a secondary indicator framework based on carbon-coordinated air quality improvement and optimization objectives can be constructed. In this secondary indicator framework, the primary indicator is the carbon-coordinated comprehensive air quality index (SI), and the secondary indicators include: population-weighted PM2.5 in the baseline year. 2.5 Concentration (SI1), total carbon emission control target for the target year (SI2), PM2.5 concentration resulting from end-of-pipe treatment of air pollution 2.5 Concentration decrease rate (SI3).
[0078] In this embodiment of the invention, PM2.5 can be based on the population-weighted average of the baseline year. 2.5 Concentration (SI1), target year carbon emission control target (SI2), PM2.5 concentration resulting from end-of-pipe treatment of air pollution 2.5 The concentration reduction rate (SI3) was used to construct the carbon-coordinated comprehensive air quality index SI.
[0079] Referring to Table 2, a schematic diagram of a secondary index framework for an air quality improvement optimization target based on carbon synergy is given in an embodiment of the present invention.
[0080]
[0081] Table 2
[0082] In this embodiment of the invention, the three secondary indicators (i.e., SI1, SI2, and SI3) can be standardized first. Specifically, the following formula can be used to standardize the three secondary indicators: (9) Among them, Y i For the i-th lower-level administrative unit, there is a certain secondary indicator (such as SI1, SI2 or SI3). For the standardized secondary indicators, max(Y) is the maximum value of the secondary indicator Y corresponding to all lower-level administrative units, and min(Y) is the minimum value of the secondary indicator Y corresponding to all lower-level administrative units.
[0083] For example, Y i Let SI1 be the secondary indicator corresponding to the i-th lower-level administrative unit. That is, for Y iThe standardized results obtained after standardization are as follows: max(Y) is the maximum value of SI1 corresponding to all lower-level administrative units, and min(Y) is the minimum value of SI1 corresponding to all lower-level administrative units.
[0084] In the following embodiments, unless otherwise stated, the three secondary indicators (i.e., SI1, SI2, and SI3) involved refer to the secondary indicators after standardization.
[0085] In practical implementation, the carbon-co-optimized air quality index SI can be calculated using the following formula: (10) Among them, SI i SI1 is the carbon-coordinated comprehensive air quality index corresponding to the i-th lower-level administrative unit. i That is, the base year population weighted PM corresponding to the i-th lower-level administrative unit. 2.5 Concentration, SI2 i That is, the total carbon emission control target corresponding to the i-th lower-level administrative unit, SI3 i That is, the PM2.5 concentration resulting from end-of-pipe treatment of air pollution corresponding to the i-th lower-level administrative unit. 2.5 Concentration decrease rate.
[0086] In specific implementation, SI1 i It can be calculated using the following formula: (11) in, For the uth subordinate administrative unit in the base year PM 2.5 concentration, For the uth subordinate administrative unit, the PM in the year preceding the base year 2.5 concentration, For the uth subordinate administrative unit, the PM in the two years preceding the base year 2.5 concentration; Let u be the population of the uth subordinate administrative unit in the base year. Let be the population of the u-th sub-subordinate administrative unit in the year preceding the base year. The population of the u-th subordinate administrative unit in the two years preceding the base year; Let be the population of the i-th lower-level administrative unit in the base year. Let be the population of the i-th lower-level administrative unit in the year preceding the base year. Let be the population of the i-th lower-level administrative unit in the two years preceding the base year; This represents the total number of subordinate administrative units under the i-th subordinate administrative unit.
[0087] In practice, a lower-level administrative unit is the next level down in administrative hierarchy. For example, if the lower-level administrative unit is a provincial-level administrative unit, then the lower-level administrative units are the municipal-level administrative units under that provincial-level administrative unit. If a provincial-level administrative unit has 13 municipal-level administrative units under its jurisdiction, then... The value of is 13.
[0088] In the above formula (11), the PM2.5 concentration of each city under the jurisdiction of the i-th provincial-level administrative unit in the base year and the two years prior to the base year is used. 2.5 The concentration, the population of each city under its jurisdiction in the base year and the two years prior to the base year, and the population of the i-th provincial administrative unit in the base year and the two years prior to the base year are used to determine SI1. i .
[0089] The two years preceding the base year are defined as the year before the base year. For example, if the base year is 2025, then the two years preceding the base year are 2023. The PM2.5 concentrations for each city in the base year and the two years preceding the base year are... 2.5 Concentration, including PM2.5 levels for each city in 2025. 2.5 Concentration, PM2.5 levels in each city in 2024 2.5 PM2.5 concentration in each city in 2023 2.5 Concentration. And so on.
[0090] In practice, the PM2.5 concentration of a city in a given year... 2.5 Concentration can be used to measure the PM2.5 concentration of a city in a given year. 2.5 The annual average. The population of a city in a given year can be represented as the average population of that city in that year.
[0091] In specific implementation, S2 i The total carbon emission control target for the i-th lower-level administrative unit is the CE calculated using formula (8) above. target_year,i Therefore, S2 i The specific calculation process can be referred to in equation (8), which will not be elaborated here.
[0092] The following is about S3 i The process of obtaining it will be explained.
[0093] In practical implementation, the emissions of various air pollutants can be calculated using the following formulas when the level of socioeconomic activity remains unchanged and the best feasible control technology (BAT) is adopted: (12) Among them, E ik Let j be the emission amount of the k-th type of air pollutant in the i-th lower-level administrative unit, m be the total number of emission source types, A be the level of socio-economic activity, and EF be the emission amount of the k-th type of air pollutant in the i-th lower-level administrative unit. ijk η is the emission factor of the k-th type of air pollutant emitted by the j-th type of emission source in the i-th lower-level administrative unit. ijk The removal rate of Class k air pollutants emitted by Class j emission sources in the i-th lower-level administrative unit.
[0094] In obtaining E ik Subsequently, E was obtained based on the WRF-CMAQ air quality model. ik Corresponding PM 2.5 Concentration. Calculate E. ik Corresponding PM 2.5 Concentration relative to the baseline year PM 2.5 The rate of decrease in concentration, which is the PM2.5 concentration reduction rate resulting from end-of-pipe treatment of air pollution at the i-th lower-level administrative unit. 2.5 Concentration decrease rate SI3 i .
[0095] In practice, the best feasible control technologies mentioned above may include particulate matter emission control, sulfur dioxide emission control, nitrogen oxide emission control, and integrated control technologies (such as ultra-low emission retrofitting, through synergistic desulfurization, denitrification and dust removal technologies).
[0096] In this embodiment of the invention, after obtaining the carbon-coordinated air quality comprehensive index SI corresponding to each lower-level administrative unit, any lower-level administrative unit can be selected as a reference unit to determine the air quality improvement and optimization target based on carbon emission reduction coordination corresponding to that reference unit. Furthermore, based on the air quality improvement and optimization target based on carbon emission reduction coordination corresponding to the reference unit, the air quality improvement and optimization target based on carbon emission reduction coordination for each lower-level administrative unit is determined.
[0097] In practical implementation, the air quality improvement optimization target based on carbon emission reduction synergy corresponding to the reference unit can be calculated using the following formula: (13) Among them, TAQ l This refers to the air quality improvement and optimization target based on synergistic carbon emission reduction corresponding to the reference unit. For the reference unit, the carbon-coordinated comprehensive air quality index, C base,i For lower-level administrative units, the corresponding PM in the base year 2.5 Three-year moving average of concentration, C target_yearPM for the target year set by the higher-level administrative unit 2.5 Concentration target value, N i N represents the number of all subordinate administrative units under the jurisdiction of a lower-level administrative unit. total This refers to the number of all subordinate administrative units under the jurisdiction of a higher-level administrative unit.
[0098] The above C base,i , which is the PM corresponding to the base year 2.5 Concentration, PM2.5 concentration in the year preceding the baseline year 2.5 Concentration, PM2.5 concentrations for the two years prior to the baseline date 2.5 The average concentration. For example, if the base year is 2020, then C base,i The arithmetic mean of the following three factors: the PM of the i-th lower-level administrative unit in 2020. 2.5 Concentration, corresponding to PM2.5 concentration in 2019 2.5 Concentration, corresponding to PM2.5 in 2018 2.5 concentration.
[0099] After obtaining the air quality improvement and optimization targets based on carbon emission reduction coordination for the reference unit, the air quality improvement and optimization targets based on carbon emission reduction coordination for each lower-level administrative unit can be determined. Specifically, the first quotient is equal for any lower-level administrative unit, and the first quotient is the quotient of the carbon-coordinated comprehensive air quality index and the air quality improvement and optimization target.
[0100] In practical implementation, the following formula can be used to determine the air quality improvement and optimization targets based on carbon emission reduction coordination for each lower-level administrative unit: (14) Here, SI1 is the carbon-coordinated comprehensive air quality index corresponding to the first lower-level administrative unit, and TAQ1 is the air quality improvement and optimization target based on carbon emission reduction coordination corresponding to the first lower-level administrative unit. And so on, SI... n This refers to the carbon-coordinated air quality index (TAQ) corresponding to the nth lower-level administrative unit. n This refers to the air quality improvement and optimization target based on carbon emission reduction coordination corresponding to the nth lower-level administrative unit.
[0101] In summary, the technical solution provided in the above embodiments of the present invention obtains the carbon-coordinated comprehensive air quality index corresponding to each lower-level administrative unit, and then determines the air quality improvement and optimization target for each lower-level administrative unit based on the carbon-coordinated comprehensive air quality index. By combining the carbon-coordinated comprehensive air quality index when obtaining the air quality improvement and optimization target for each lower-level administrative unit, the synergy between air quality improvement and carbon emission control targets can be achieved.
[0102] Reference Figure 2 This invention provides an air quality improvement and optimization target determination device 20 based on carbon synergy, comprising: an air quality comprehensive index acquisition unit 201 and an air quality improvement and optimization target unit 202, wherein: The carbon-coordinated air quality comprehensive index acquisition unit 201 is used to acquire the carbon-coordinated air quality comprehensive index corresponding to each lower-level administrative unit; the carbon-coordinated air quality comprehensive index is associated with the following parameters: total carbon emission control target, and population-weighted PM2.5 in the baseline year. 2.5 PM2.5 concentration, resulting from end-of-pipe treatment of air pollution 2.5 Concentration decrease rate; Air quality improvement and optimization target unit 202 is used to determine the air quality improvement and optimization target for each lower-level administrative unit based on the carbon-coordinated air quality comprehensive index corresponding to each lower-level administrative unit.
[0103] In specific implementation, the specific execution process of the carbon-coordinated air quality comprehensive index acquisition unit 201 and the air quality improvement and optimization target unit 202 can be referred to steps 101 to 102, which will not be elaborated here.
[0104] In specific implementation, the modules / units included in the various devices and products described in the above embodiments can be software modules / units, hardware modules / units, or a combination of both.
[0105] For example, for various devices and products applied to or integrated into a chip, each module / unit can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs that run on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits; for various devices and products applied to or integrated into a chip module, each module / unit can be implemented using hardware methods such as circuits, and different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The components can be implemented using software programs that run on the processor integrated within the chip module. The remaining (if any) modules / units can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into the terminal, each of its components / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or in different components within the terminal. Alternatively, at least some modules / units can be implemented using software programs that run on the processor integrated within the terminal, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits.
[0106] This invention also provides a computer-readable storage medium, which is a non-volatile or non-transient storage medium, storing a computer program thereon. When the computer program is run by a processor, it executes the steps of the carbon-coordinated air quality improvement optimization target determination method provided in any of the above embodiments.
[0107] This invention also provides another apparatus for determining air quality improvement optimization targets based on carbon synergy, including a memory and a processor. The memory stores a computer program that can run on the processor. When the processor runs the computer program, it executes the steps of the method for determining air quality improvement optimization targets based on carbon synergy provided in any of the above embodiments.
[0108] This invention also provides a computer program product, including a computer program / instruction, which, when executed by a computer, executes the carbon-synergistic air quality improvement optimization target determination method provided in any of the above embodiments.
[0109] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include ROM, RAM, disk, or optical disk, etc.
[0110] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.
Claims
1. A method for determining air quality improvement optimization targets based on carbon synergy, characterized in that, include: Obtain the carbon-coordinated comprehensive air quality index corresponding to each lower-level administrative unit; the carbon-coordinated comprehensive air quality index is associated with the following parameters: total carbon emission control target, and population-weighted PM2.5 in the baseline year. 2.5 PM2.5 concentration, resulting from end-of-pipe treatment of air pollution 2.5 Concentration decrease rate; Based on the carbon-coordinated comprehensive air quality index corresponding to each subordinate administrative unit, the air quality improvement and optimization targets for each subordinate administrative unit are determined.
2. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 1, characterized in that, The determination of air quality improvement and optimization targets for each lower-level administrative unit, based on the carbon-coordinated comprehensive air quality index corresponding to each lower-level administrative unit, includes: Obtain the air quality improvement and optimization targets corresponding to the reference unit; the reference unit is any lower-level administrative unit. Based on the air quality improvement and optimization target corresponding to the reference unit, the air quality improvement and optimization targets corresponding to the other lower-level administrative units are determined; wherein, the first quotient corresponding to any lower-level administrative unit is equal, and the first quotient is: the quotient of the carbon-coordinated comprehensive air quality index and the air quality improvement and optimization target.
3. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 2, characterized in that, The air quality improvement and optimization target corresponding to the reference unit is: ； in, The air quality improvement optimization target corresponding to the reference unit is... Let PM be the corresponding administrative unit of the i-th lower level in the base year. 2.5 The three-year moving average of concentration Let be the total number of subordinate administrative units under the i-th subordinate administrative unit. The total number of subordinate administrative units under a higher-level administrative unit. For the higher-level administrative unit in the target year PM 2.5 Target concentration value, The carbon-coordinated comprehensive air quality index is used as the reference unit. Let i be the carbon-coordinated comprehensive air quality index corresponding to the i-th subordinate administrative unit; i and n are both positive integers, and 1≤i≤n, where n is the total number of subordinate administrative units under the superior administrative unit.
4. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 3, characterized in that, The process of obtaining the carbon-coordinated comprehensive air quality index for each lower-level administrative unit includes: The carbon-coordinated air quality index corresponding to the i-th lower-level administrative unit is determined using the following formula: ; Among them, SI i SI1 is the carbon-coordinated comprehensive air quality index corresponding to the i-th lower-level administrative unit. i The weighted PM of the baseline year population corresponding to the i-th lower-level administrative unit 2.5 Concentration, SI2 i SI3 represents the total carbon emission control target corresponding to the i-th lower-level administrative unit. i The PM2.5 concentration resulting from end-of-pipe air pollution control measures corresponding to the i-th lower-level administrative unit. 2.5 Concentration decrease rate.
5. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 4, characterized in that, The baseline year population-weighted PM corresponding to the i-th lower-level administrative unit 2.5 The concentration is calculated using the following formula: ； in, The weighted PM2.5 of the baseline year population corresponding to the i-th lower-level administrative unit 2.5 concentration, Let be the population of the i-th lower-level administrative unit in the base year. Let be the population of the i-th lower-level administrative unit in the year preceding the base year. Let be the population of the i-th lower-level administrative unit in the two years preceding the base year; For the uth subordinate administrative unit in the base year PM 2.5 concentration, For the uth subordinate administrative unit, the PM in the year preceding the base year 2.5 concentration, For the uth subordinate administrative unit, the PM in the two years preceding the base year 2.5 concentration; Let u be the population of the uth subordinate administrative unit in the base year. Let be the population of the u-th sub-subordinate administrative unit in the year preceding the base year. Let be the population of the uth subordinate administrative unit in the two years preceding the base year.
6. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 4, characterized in that, The PM2.5 generated by the end-of-pipe treatment of air pollution corresponding to the i-th lower-level administrative unit 2.5 The concentration decrease rate was obtained using the following steps: Obtain the atmospheric pollutant emissions corresponding to the i-th lower-level administrative unit when the best feasible control technology is adopted; Based on the WRF-CMAQ air quality model, the PM2.5 emissions corresponding to the aforementioned air pollutants were simulated. 2.5 concentration; Obtain the simulated PM 2.5 The concentration relative to the PM2.5 concentration of the i-th lower-level administrative unit in the base year 2.5 The rate of decrease in concentration, as a measure of PM2.5 concentration resulting from end-of-pipe treatment of air pollution. 2.5 Concentration decrease rate.
7. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 4, characterized in that, The total carbon emission control target corresponding to the i-th lower-level administrative unit is associated with the historical responsibility index, economic capacity index, and emission reduction potential index of the i-th lower-level administrative unit; wherein, the historical responsibility index is associated with the emission intensity in the base year and the cumulative per capita carbon emissions in the past N years, where N is a positive integer; the economic capacity index is associated with the per capita GDP in the base year and the fiscal revenue in the base year; and the emission reduction potential index is associated with the proportion of fossil energy in primary energy consumption in the base year and the energy consumption per 10,000 yuan of industrial added value in the base year.
8. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 7, characterized in that, The total carbon emission control target corresponding to the i-th lower-level administrative unit is obtained using the following formula: SI2 i = ; in, Let i be the carbon emission intensity of the i-th lower-level administrative unit in the base year. Let be the carbon emission intensity reduction indicator for the i-th lower-level administrative unit. Let be the GDP of the i-th lower-level administrative unit in the target year.
9. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 7, characterized in that, The carbon emission intensity reduction target for any lower-level administrative unit is obtained using the following steps: Obtain the carbon emission intensity reduction index corresponding to the reference unit; the reference unit is any lower-level administrative unit. Based on the carbon emission intensity reduction index corresponding to the reference unit, the carbon emission intensity reduction index corresponding to the other lower-level administrative units is determined; wherein, the second quotient corresponding to any lower-level administrative unit is equal, and the second quotient is: the quotient of the carbon emission fairness comprehensive index and the carbon emission intensity reduction index.
10. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 9, characterized in that, The carbon emission intensity reduction index corresponding to the reference unit is determined using the following formula: ； in, The carbon emission intensity reduction index corresponding to the reference unit. Let i be the carbon emission intensity of the i-th lower-level administrative unit in the base year. Let be the GDP of the i-th lower-level administrative unit in the target year. The carbon emission intensity of the higher-level administrative unit in the base year. The GDP of the higher-level administrative unit in the target year is represented by , and the TCI is the carbon emission intensity reduction indicator of the higher-level administrative unit in the target year. The carbon emission equity composite index corresponding to the reference unit. Let be the carbon emission equity comprehensive index corresponding to the i-th lower-level administrative unit.
11. The method for determining air quality improvement optimization targets based on carbon synergy as described in claim 9, characterized in that, The carbon emission equity index corresponding to the i-th lower-level administrative unit is determined by the following formula: ； in, This represents the historical responsibility index corresponding to the i-th lower-level administrative unit. Let i be the economic capacity index corresponding to the i-th lower-level administrative unit. Let be the emission reduction potential index corresponding to the i-th lower-level administrative unit; in, , , ; Let be the base year carbon emission intensity corresponding to the i-th lower-level administrative unit. Let N be the cumulative per capita carbon emissions for the i-th administrative unit over the past N years. Let C2 be the base year per capita GDP corresponding to the i-th lower-level administrative unit. i Let P1 be the base year fiscal revenue corresponding to the i-th lower-level administrative unit. i Let P2 be the proportion of fossil fuels in primary energy consumption in the baseline year corresponding to the i-th lower-level administrative unit. i Let be the energy consumption per 10,000 yuan of industrial added value corresponding to the i-th lower-level administrative unit in the benchmark year.
12. A device for determining air quality improvement optimization targets based on carbon synergy, characterized in that, include: The carbon-coordinated air quality comprehensive index acquisition unit is used to acquire the carbon-coordinated air quality comprehensive index corresponding to each lower-level administrative unit; the carbon-coordinated air quality comprehensive index is associated with the following parameters: total carbon emission control target, and population-weighted PM2.5 in the baseline year. 2.5 PM2.5 concentration, resulting from end-of-pipe treatment of air pollution 2.5 Concentration decrease rate; The air quality improvement and optimization target unit is used to determine the air quality improvement and optimization target for each subordinate administrative unit based on the carbon-coordinated air quality comprehensive index corresponding to each subordinate administrative unit.
13. A computer-readable storage medium, said computer-readable storage medium being a non-volatile storage medium or a non-transient storage medium, having stored thereon a computer program, characterized in that, When the computer program is run by the processor, it executes the steps of the method for determining the optimization target of air quality improvement based on carbon synergy as described in any one of claims 1 to 11.
14. A computer program product, characterized in that, It includes a computer program / instruction, which, when executed by a computer, executes the method for determining the carbon-based air quality improvement optimization target as described in any one of claims 1 to 11.
15. A device for determining air quality improvement optimization targets based on carbon synergy, comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, characterized in that, When the processor runs the computer program, it performs the steps of the method for determining the optimization target of air quality improvement based on carbon synergy as described in any one of claims 1 to 11.