Emergency emission reduction measure generation method and device

Abstract

The invention provides an emergency emission reduction measure generation method and device, and the method comprises the steps: obtaining index data sets of a plurality of industries in a target region, and each index data set comprises the environment impact dimension index data of the corresponding industry, the social and economic impact dimension index data, and the atmospheric pollutant emission reduction data under an early warning condition; determining a comprehensive score of each industry according to the environmental influence dimension index data and the social economic influence dimension index data of each industry; and according to the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning condition, determining an early warning response industry in the target area and generating corresponding emergency emission reduction measures. According to the method, the influence of the multi-dimensional index data on the generation of the emergency emission reduction measures can be considered, and the economic benefit of emergency emission reduction can be improved while the environmental benefit is ensured.

Description

Technical Field

[0001] The present application relates to the field of environmental technology, and in particular to a method and device for generating emergency emission reduction measures. Background Art

[0002] With the progress of air pollution prevention and control, enterprises in different industries are currently divided into A, B and C grades based on performance grading indicators such as energy type, pollution control technology level, enterprise production process level, unorganized control situation, emission limit, environmental management level, monitoring and supervision level, and transportation mode. Performance-graded differentiated emergency emission reduction measures are implemented for different warning types.

[0003] However, the gap between the production process level and pollution control measures of existing manufacturers has been significantly reduced. Therefore, the existing performance grading indicators that only consider the environmental impact dimension will be difficult to meet the actual needs of emergency emission reduction, and there is a risk of poor emergency emission reduction effects. Summary of the invention

[0004] In response to at least one problem in the prior art, the present application proposes a method and device for generating emergency emission reduction measures, which can consider the impact of multi-dimensional indicator data on the generation of emergency emission reduction measures, and can improve the economic benefits of emergency emission reduction while ensuring environmental benefits.

[0005] In order to solve the above technical problems, this application provides the following technical solutions:

[0006] In a first aspect, the present application provides a method for generating emergency emission reduction measures, comprising:

[0007] Obtain indicator data groups for multiple industries in the target area, each indicator data group includes: indicator data of environmental impact dimension, indicator data of social and economic impact dimension, and data on reduction of air pollutant emissions under early warning conditions for the corresponding industry;

[0008] Determine the comprehensive score of each industry based on the environmental impact dimension indicator data and the socioeconomic impact dimension indicator data of each industry;

[0009] According to the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation, the early warning response industry in the target area is determined and its corresponding emergency emission reduction measures are generated.

[0010] In one embodiment, determining the comprehensive score of each industry based on the environmental impact dimension indicator data and the socio-economic impact dimension indicator data of each industry includes:

[0011] Based on the environmental impact dimension indicator data of each industry, determine the total score of the environmental impact dimension of each industry;

[0012] Based on the socio-economic impact dimension indicator data of each industry, determine the total socio-economic impact dimension score of each industry;

[0013] The comprehensive score of each industry is determined based on the total score of the environmental impact dimension and the total score of the socioeconomic impact dimension of each industry.

[0014] In one embodiment, the atmospheric pollutant emission reduction data under the early warning situation includes: released emissions, emission reduction potential, emission reduction during the early warning period, and emissions during the early warning period; correspondingly, according to the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation, the early warning response industry in the target area is determined and its corresponding emergency emission reduction measures are generated, including:

[0015] According to the comprehensive score of each industry, determine the typical polluting industries in the target area and their classification results;

[0016] According to the classification results of each typical polluting industry, the emission reduction during the warning period and the emission during the warning period, determine the non-warning response industry and the warning response industry from each typical polluting industry;

[0017] Based on the emission reduction potential of all non-early warning response industries, the emissions released by all early warning response industries and the emission reduction potential of each early warning response industry, emergency emission reduction measures for each early warning response industry are generated. Each emergency emission reduction measure includes: the emission reduction increment of the early warning response industry.

[0018] In one embodiment, the environmental impact dimension indicator data includes: values ​​of a plurality of environmental impact dimension indicators;

[0019] Correspondingly, the total score of the environmental impact dimension of each industry is determined based on the environmental impact dimension indicator data of each industry, including:

[0020] From the values ​​of the same environmental impact dimension indicator of each industry, the maximum value is selected as the maximum value of the environmental impact dimension indicator, and the minimum value is selected as the minimum value of the environmental impact dimension indicator;

[0021] According to the maximum value and minimum value of each environmental impact dimension indicator and the value of the environmental impact dimension indicator in each industry, determine the indicator score of the environmental impact dimension indicator in each industry;

[0022] According to the weight values ​​of the pre-acquired multiple environmental impact dimension indicators, the indicator scores of each environmental impact dimension indicator in each industry are weighted and summed to obtain the total environmental impact dimension score of each industry;

[0023] The weight value of each environmental impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the environmental impact dimension indicator in each industry.

[0024] In one embodiment, the socio-economic impact dimension indicator data includes: values ​​of multiple socio-economic impact dimension indicators; correspondingly, determining the total socio-economic impact dimension score of each industry based on the socio-economic impact dimension indicator data of each industry includes:

[0025] From the values ​​of the same socio-economic impact dimension indicator of each industry, the maximum value is selected as the maximum value of the socio-economic impact dimension indicator, and the minimum value is selected as the minimum value of the socio-economic impact dimension indicator;

[0026] According to the maximum value and minimum value of each socio-economic impact dimension indicator and the value of the socio-economic impact dimension indicator in each industry, determine the indicator score of the socio-economic impact dimension indicator in each industry;

[0027] According to the weight values ​​of multiple socio-economic impact dimension indicators obtained in advance, the indicator scores of each socio-economic impact dimension indicator in each industry are weighted and summed to obtain the total score of the environmental impact dimension of each industry;

[0028] The weight value of each socio-economic impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the socio-economic impact dimension indicator in each industry.

[0029] In a second aspect, the present application provides an emergency emission reduction measure generation device, comprising:

[0030] An acquisition module is used to acquire indicator data groups of multiple industries in the target area, each indicator data group including: indicator data of environmental impact dimension, indicator data of social and economic impact dimension and air pollutant emission reduction data under early warning conditions of the corresponding industry;

[0031] A determination module, used to determine the comprehensive score of each industry based on the environmental impact dimension indicator data and the socio-economic impact dimension indicator data of each industry;

[0032] The generation module is used to determine the early warning response industry in the target area and generate its corresponding emergency emission reduction measures based on the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation.

[0033] In one embodiment, the determining module includes:

[0034] The first determination unit is used to determine the total score of the environmental impact dimension of each industry based on the environmental impact dimension indicator data of each industry;

[0035] The second determination unit is used to determine the total score of the socio-economic impact dimension of each industry based on the socio-economic impact dimension indicator data of each industry;

[0036] The third determination unit is used to determine the comprehensive score of each industry based on the total score of the environmental impact dimension and the total score of the socio-economic impact dimension of each industry.

[0037] In one embodiment, the atmospheric pollutant emission reduction data under the warning situation includes: released emissions, emission reduction potential, emission reduction during the warning period, and emissions during the warning period; correspondingly, the generation module includes:

[0038] A grading unit, used to determine typical polluting industries in the target area and their grading results according to the comprehensive score of each industry;

[0039] The fourth determination unit is used to determine non-warning response industries and warning response industries from each typical polluting industry according to the classification results of each typical polluting industry, the emission reduction during the warning period, and the emission during the warning period;

[0040] The fifth determination unit is used to generate emergency emission reduction measures for each early warning response industry based on the emission reduction potential of all non-early warning response industries, the emissions released by all early warning response industries and the emission reduction potential of each early warning response industry. Each emergency emission reduction measure includes: the emission reduction increment of the early warning response industry.

[0041] In one embodiment, the environmental impact dimension indicator data includes: values ​​of a plurality of environmental impact dimension indicators;

[0042] Correspondingly, the total score of the environmental impact dimension of each industry is determined based on the environmental impact dimension indicator data of each industry, including:

[0043] From the values ​​of the same environmental impact dimension indicator of each industry, the maximum value is selected as the maximum value of the environmental impact dimension indicator, and the minimum value is selected as the minimum value of the environmental impact dimension indicator;

[0044] According to the maximum value and minimum value of each environmental impact dimension indicator and the value of the environmental impact dimension indicator in each industry, determine the indicator score of the environmental impact dimension indicator in each industry;

[0045] According to the weight values ​​of the pre-acquired multiple environmental impact dimension indicators, the indicator scores of each environmental impact dimension indicator in each industry are weighted and summed to obtain the total environmental impact dimension score of each industry;

[0046] The weight value of each environmental impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the environmental impact dimension indicator in each industry.

[0047] In one embodiment, the socio-economic impact dimension indicator data includes: values ​​of a plurality of socio-economic impact dimension indicators; correspondingly, the second determining unit is used to execute:

[0048] From the values ​​of the same socio-economic impact dimension indicator of each industry, the maximum value is selected as the maximum value of the socio-economic impact dimension indicator, and the minimum value is selected as the minimum value of the socio-economic impact dimension indicator;

[0049] According to the maximum value and minimum value of each socio-economic impact dimension indicator and the value of the socio-economic impact dimension indicator in each industry, determine the indicator score of the socio-economic impact dimension indicator in each industry;

[0050] According to the weight values ​​of multiple socio-economic impact dimension indicators obtained in advance, the indicator scores of each socio-economic impact dimension indicator in each industry are weighted and summed to obtain the total score of the environmental impact dimension of each industry;

[0051] The weight value of each socio-economic impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the socio-economic impact dimension indicator in each industry.

[0052] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for generating emergency emission reduction measures when executing the program.

[0053] In a fourth aspect, the present application provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the method for generating emergency emission reduction measures.

[0054] It can be seen from the above technical solution that the present application provides a method and device for generating emergency emission reduction measures. The method includes: obtaining indicator data groups of multiple industries in the target area, each indicator data group includes: environmental impact dimension indicator data, social and economic impact dimension indicator data of the corresponding industry, and atmospheric pollutant emission reduction data under early warning conditions; determining the comprehensive score of each industry based on the environmental impact dimension indicator data and social and economic impact dimension indicator data of each industry; determining the early warning response industry in the target area and generating its corresponding emergency emission reduction measures based on the comprehensive score of each industry and the atmospheric pollutant emission reduction data under early warning conditions, which can consider the impact of multi-dimensional indicator data on the generation of emergency emission reduction measures, and can improve the economic benefits of emergency emission reduction while ensuring environmental benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1 It is a first flow chart of the method for generating emergency emission reduction measures in an embodiment of the present application;

[0057] Figure 2 It is a second flow chart of the method for generating emergency emission reduction measures in an embodiment of the present application;

[0058] Figure 3 It is a second flow chart of the method for generating emergency emission reduction measures in an embodiment of the present application;

[0059] Figure 4 It is a structural schematic diagram of an emergency emission reduction measure generating device in an embodiment of the present application;

[0060] Figure 5 It is a schematic block diagram of the system structure of the electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0061] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0062] The details are described through the following embodiments.

[0063] In order to improve the economic benefits of emergency emission reduction while ensuring environmental benefits, this embodiment provides an emergency emission reduction measure generation method in which the execution subject is an emergency emission reduction measure generation device, and the emergency emission reduction measure generation device includes but is not limited to a server, such as Figure 1 As shown, the method specifically includes the following contents:

[0064] Step 100: Obtain indicator data groups for multiple industries in the target area, each indicator data group including: environmental impact dimension indicator data, socio-economic impact dimension indicator data, and atmospheric pollutant emission reduction data under early warning conditions for the corresponding industry.

[0065] Specifically, the target area may be a city, and the industries may include steel, cement, bricks and tiles, etc. The indicator data of environmental impact dimension may include: industrial enterprise atmospheric pollutant emission information, and the indicator data of social and economic impact dimension may include: industrial enterprise electricity consumption and industrial enterprise output value; the atmospheric pollutant emission reduction data under early warning may include: released emissions, emission reduction potential, emission reduction during the early warning period, and emissions during the early warning period.

[0066] Step 200: Determine the comprehensive score of each industry based on the environmental impact dimension indicator data and the socio-economic impact dimension indicator data of each industry.

[0067] Step 300: According to the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation, the early warning response industry in the target area is determined and its corresponding emergency emission reduction measures are generated.

[0068] In order to improve the reliability of determining the composite score of the industry, such as Figure 2 As shown, in one embodiment, step 200 includes:

[0069] Step 201: Determine the total score of the environmental impact dimension of each industry based on the environmental impact dimension indicator data of each industry.

[0070] Step 202: Determine the total score of the socio-economic impact dimension of each industry based on the socio-economic impact dimension indicator data of each industry.

[0071] Step 203: Determine the comprehensive score of each industry based on the total score of the environmental impact dimension and the total score of the socioeconomic impact dimension of each industry.

[0072] Specifically, the comprehensive score S of industry i can be determined according to the following formula:

[0073] S=(P total +E total ) / 2

[0074] Among them, P total is the total score of the environmental impact dimension of industry i, E total is the total score of the socio-economic impact dimension of industry i.

[0075] In order to improve the reliability of generating emergency emission reduction measures, in one embodiment, the atmospheric pollutant emission reduction data under the early warning situation includes: released emissions, emission reduction potential, emission reduction during the early warning period, and emissions during the early warning period; correspondingly, Figure 3 As shown, step 300 includes:

[0076] Step 301: According to the comprehensive score of each industry, determine the typical polluting industries in the target area and their classification results.

[0077] Specifically, the typical polluting industries in the target area can be determined based on the comprehensive score of each industry; the typical polluting industries can be ranked from high to low based on the comprehensive scores, and the grading results of the typical polluting industries can be determined based on the ranking results and the existing performance grading indicators corresponding to each enterprise in the typical polluting industry. The selected typical polluting industries can be ranked from high to low based on the comprehensive scores, and named industry 1, industry 2, etc. On this basis, the target area can be considered to further subdivide the typical polluting industries according to the graded management and control performance (A, B, C, D) of different existing enterprises in the industry: A-level enterprises in industry 1, B-level enterprises in industry 1, C-level enterprises in industry 1, D-level enterprises in industry 1, etc. A-level enterprises in industry 3, etc.

[0078] Step 302: According to the classification results of each typical polluting industry, the emission reduction during the warning period, and the emission during the warning period, non-warning response industries and warning response industries are determined from each typical polluting industry.

[0079] Step 303: Generate emergency emission reduction measures for each early warning response industry based on the emission reduction potential of all non-early warning response industries, the emissions released by all early warning response industries, and the emission reduction potential of each early warning response industry. Each emergency emission reduction measure includes: the emission reduction increment of the early warning response industry.

[0080] Specifically, the emission reduction increment of early warning response industry i can be determined according to the following formula:

[0081] The incremental emission reduction of early warning response industry i = the emission reduction potential of early warning response industry i / the emission reduction potential of all early warning response industries * emissions released by non-early warning response industries.

[0082] Among them, the emission reduction potential of the early warning response industry can represent the emission reduction space of the early warning response industry, which refers to the difference in pollutant emissions caused by the early warning response industry producing at the original load and directly stopping production during the early warning period; the emissions released by the non-early warning response industry can refer to the difference in pollutant emissions between the non-early warning response industry producing at full load and producing at the original load during the early warning period; the original load can refer to the production load corresponding to the current emergency response measures for heavy pollution of industrial enterprises; and the emergency emission reduction measures of the early warning response industry can also be implemented to increase the emission reduction of the early warning response industry by the emission reduction increment.

[0083] In order to improve the reliability of determining the total score of the environmental impact dimension, in one embodiment, the environmental impact dimension indicator data includes: values ​​of multiple environmental impact dimension indicators; step 201 includes:

[0084] From the values ​​of the same environmental impact dimension indicator of each industry, the maximum value is selected as the maximum value of the environmental impact dimension indicator, and the minimum value is selected as the minimum value of the environmental impact dimension indicator; according to the maximum value, minimum value and value of each environmental impact dimension indicator in each industry, the indicator score of the environmental impact dimension indicator in each industry is determined; according to the weight values ​​of multiple environmental impact dimension indicators pre-acquired, the indicator scores of each environmental impact dimension indicator in each industry are weighted and summed to obtain the total environmental impact dimension score of each industry; the weight value of each environmental impact dimension indicator is determined according to the number of industries in the target area and the probability of occurrence of the environmental impact dimension indicator in each industry.

[0085] Specifically, the maximum value of the pollution index can be the maximum value of the pollution index emission in each industry, and the minimum value of the pollution index can be the minimum value of the pollution index emission in each industry; for example, assuming there are industries 1, 2, and 3, among which the value of the environmental impact dimension indicator SO2 emission in industry 1 is A1, the value of the environmental impact dimension indicator SO2 emission in industry 2 is A2, and the value of the environmental impact dimension indicator SO2 emission in industry 3 is A3, A1>A2>A3, then it can be determined that the maximum value of the environmental impact dimension indicator SO2 emission is A1, and the minimum value is A3. The total score of the environmental impact dimension of industry i can be determined according to the following formula:

[0086] P i，j =(p i，j -p j，min ) / (p j,max -p j，min )

[0087] P total =w1×NO Xi +w2×SO 2i +w3×PM i +w4×VOCs i

[0088] Where P i，j represents the pollution index score of industry j in i (i.e., the index score of environmental impact dimension index j), p i，j is the pollution index emission of industry j in i, p j，max is the maximum value of the j environmental impact dimension index, p j，min is the minimum value of the j environmental impact dimension index, P total is the total score of the environmental impact dimension of industry i, NOx i NO for the i industry X Pollution index score, SO 2i Score for SO2 pollution index of industry i, PM iScore for the particle pollution index of industry i, VOCs i is the VOCs pollution index score of industry i, w1, w2, w3, and w4 are NO X , SO2, PM, VOC s Pollution indicator weights.

[0089] Specifically, the weight value of each indicator in this embodiment can be preset according to actual needs; the weight value of each indicator can also be determined according to the following formula:

[0090]

[0091] If indicator j is an environmental impact dimension indicator, then If indicator j is a socio-economic impact dimension indicator, then

[0092] Where: p(x i，j ) is the probability of occurrence of indicator j in industry i, m is the number of industries in the target area, f i，j is the value of the normalized result of the index after shifting +0.00001 for industry i, E j is the information entropy of the indicator, m is the number of industries in the target area, p(x i，j ) is the probability of occurrence of indicator j in industry i, w j is the information entropy weight of the j index, n is the number of evaluation indicators, E j is the information entropy of index j, f i，j is the score of indicator j in industry i, f i，j is the corresponding value of indicator j in industry i, f i，max is the maximum value of this indicator, f i，min is the minimum value of the index. Considering that the subsequent formula needs to use logarithmic operations, it is generally necessary to perform a shift after the normalized index. To ensure its accuracy, the shift value is preferably +0.00001. For example, k is NOx, then f i，j It can be the normalized result of NOx emissions in industry i.

[0093] In order to improve the reliability of determining the total score of the socio-economic dimension, in one embodiment, the socio-economic impact dimension indicator data includes: values ​​of multiple socio-economic impact dimension indicators; correspondingly, step 202 includes:

[0094] From the values ​​of the same socioeconomic impact dimension indicator of each industry, the maximum value is selected as the maximum value of the socioeconomic impact dimension indicator, and the minimum value is selected as the minimum value of the socioeconomic impact dimension indicator; according to the maximum value and minimum value of each socioeconomic impact dimension indicator and the value of the socioeconomic impact dimension indicator in each industry, the indicator score of the socioeconomic impact dimension indicator in each industry is determined; according to the weight values ​​of multiple socioeconomic impact dimension indicators obtained in advance, the indicator scores of each socioeconomic impact dimension indicator in each industry are weighted and summed to obtain the total environmental impact dimension score of each industry; the weight value of each socioeconomic impact dimension indicator is determined according to the number of industries in the target area and the probability of occurrence of the socioeconomic impact dimension indicator in each industry.

[0095] For example, suppose there are industries 1, 2, and 3, among which the value of the electricity consumption of the socio-economic impact dimension indicator in industry 1 is B1, the value of the electricity consumption of the socio-economic impact dimension indicator in industry 2 is B2, and the value of the electricity consumption of the socio-economic impact dimension indicator in industry 3 is B3, B1>B2>B3, then it can be determined that the maximum value of the electricity consumption of the socio-economic impact dimension indicator is B1, and the minimum value is B3. Specifically, the total score of the socio-economic impact dimension of industry i can be determined according to the following formula:

[0096] E i，j =(e i，j -e j，min ) / (e j，max -e j，min )

[0097] E total =w5×GDP i +w6×Power i

[0098] Among them, E i，j represents the socioeconomic indicator score of industry i, e i，j is the emission of indicator j in industry i, e j，max is the maximum value of this indicator, e j，min is the minimum value of this indicator, E total is the total score of the socio-economic impact dimension of industry i, GDP i The total industrial output value index score for industry i, Power i is the electricity consumption index score of industry i, w5 and w6 are the weights of total industrial output value and electricity consumption index respectively.

[0099] In order to further illustrate this solution, this application provides an application example of a method for generating emergency emission reduction measures. In the application example, ** District, ** City is taken as the target area. The method is specifically described as follows:

[0100] Step 1: Obtaining sample data.

[0101] Obtain the target area's 2019 environmental impact dimension indicator data, socio-economic impact dimension indicator data, historical warning period information of industrial enterprises, and data on reduction of atmospheric pollutants under warning conditions; environmental impact dimension indicator data include: atmospheric pollutant (particulate matter, sulfur dioxide, nitrogen oxides, volatile organic pollutants) emission information of industrial enterprises; socio-economic impact dimension indicator data include: electricity consumption of industrial enterprises, industrial enterprise output value data; for example, historical warning period information of industrial enterprises may include: "From 0:00 on December 19 to 24:00 on December 24, 2019, further strengthening measures will be taken for key industries", Table 1 shows the atmospheric pollutant emission reduction data under warning conditions in 2019 in the target area, and the atmospheric pollutant emission reduction data include: atmospheric pollutant emissions (kg / day), electricity consumption (10,000 kWh / year) and total industrial output value (10,000 yuan).

[0102] Table 1

[0103]

[0104] Step 2: Select typical polluting industries based on multi-criteria decision-making. Multi-criteria decision-making refers to the decision-making process of selecting from a set of conflicting and incommensurable finite (infinite) solutions. It is one of the important contents of analytical decision theory. Step 2 specifically includes:

[0105] Step 21: Conduct environmental impact dimension data (NO X , SO2, PM, VOCs emissions), the formula is as follows:

[0106] P i，j =(p i，j -p j，min ) / (p j，max -p j，min ) (1)

[0107] Where P i，j represents the pollution index score of industry j in i, p i，j is the pollution index emission of industry j in i, p j，max is the maximum value of pollution index j, p j，min is the minimum value of pollution index j. The index normalization results are shown in Table 2.

[0108] Table 2

[0109]

[0110] Step 22: Calculate the total score of the environmental impact dimension using proportional weighting:

[0111] P total =w1×NOXi +w2×SO 2i +w3×PM i +w4×VOCs i (2)

[0112] Where P total is the total score of the environmental impact dimension of industry i, NOx i NO for the i industry X Index score, SO 2i SO2 index score for i industry, PM i The particle index score for industry i, γOCs i is the VOCs index score of industry i, w1, w2, w3, and w4 are NO X , SO2, PM, VOC s The indicator weight can be taken as 0.25 here. The weight of each indicator can be obtained based on the entropy weight method:

[0113] (1) Calculate the probability value of the indicator

[0114]

[0115] Where: p(x i，j ) is the probability of occurrence of indicator j in industry i, m is the number of industries in the target area, f i，j It is the value after the normalized result of indicator j in industry i is shifted by +0.00001.

[0116] (2) Calculate the information entropy value of each indicator

[0117]

[0118] In the formula, E j is the information entropy of index j, m is the number of industries in the target area, p(x i，j ) is the probability of occurrence of indicator j in industry i.

[0119] (3) Determine the weight of each indicator

[0120]

[0121] In the formula, w j is the information entropy weight of the j index, n is the number of evaluation indicators, E j is the information entropy of index j. The weights of each index are shown in Table 3.

[0122] Table 3

[0123]

[0124] Step 23: Normalize the socio-economic impact dimension data (industrial enterprise electricity consumption, industrial enterprise output value):

[0125] E i，j =(e i，j -e j，min ) / (e j，max -e j，min ) (6)

[0126] In the formula, E i，j represents the socioeconomic indicator score of industry i, e i，j is the emission of indicator j in industry i, e j，max is the maximum value of this indicator, e j，min The normalized results are shown in Table 2.

[0127] Step 24: Calculate the total score of the socio-economic impact dimension using proportional weighting:

[0128] E tatal =w5×GDP i +w6×Power i (7)

[0129] In the formula, E total is the total score of the socio-economic impact dimension of industry i, GDP i The total industrial output value index score for industry i, Power i is the electricity consumption index score of industry i, w5 and w6 are the weights of total industrial output value and electricity consumption index respectively, both of which can be taken as 0.5, or the weights of each index can be obtained based on the entropy weight method.

[0130] Step 25: Calculate the total score of the industry and sort it. The total score S of the industry is the average of the environmental impact dimension score and the socio-economic impact dimension score:

[0131] S=(P total +E tatal ) / 2 (8)

[0132] Using Pareto analysis, industries with a cumulative comprehensive score of 80% are considered typical polluting industries. The principle of Pareto analysis is the 20 / 80 law, which states that 80% of the benefits often come from 20% of the inputs, while the other 80% of the inputs only produce 20% of the benefits. The total scores and cumulative percentages of each industry are shown in Table 4.

[0133] Table 4

[0134] Industry Type Industry Total Score Cumulative percentage of comprehensive score Selection results of typical polluting industries f 0.4374 50.89 Typical polluting industries d 0.2052 74.76 Typical polluting industries X 0.0846 84.60 / 0.0487 90.27 / p 0.0442 95.42 / b 0.0155 97.21 / z 0.0056 97.86 / n 0.0044 98.37 / o 0.0020 98.59 / r 0.0019 98.82 / e 0.0018 99.03 / t 0.0015 99.21 / h 0.0013 99.36 / aa 0.0011 99.49 / u 0.0009 99.60 / C 0.0009 99.70 / m 0.0007 99.78 / q 0.0004 99.82 / 1 0.0003 99.86 / a 0.0003 99.90 / W 0.0003 99.94 / s 0.0002 99.96 / g 0.0001 99.98 / v 0.0001 99.99 / y 0.0001 100.00 / k 0.0000 100.00 / i 0.0000 100.00 /

[0135] Step 3: Select industries to respond to pollution warnings in different districts and counties.

[0136] The selected typical polluting industries are ranked and their enterprise performance level information is included. The ranking results are 1A, 1B, 1C and below, 2A, 2B, 2C and below, etc.

[0137] Specifically, the selected typical polluting industries can be ranked from high to low according to the comprehensive scores, and named industry 1, industry 2, etc. On this basis, the target area can be considered according to the graded control performance of different enterprises in the industry (A, B, C, D), and further numbered as: A-level enterprises in industry 1, B-level enterprises in industry 1, C-level enterprises in industry 1, D-level enterprises in industry 1, etc. A-level enterprises in industry 3, etc. The results of the numbering of typical polluting industry enterprises and the corresponding relationship between the corresponding emissions and the orange warning emission reduction (kg / day) are shown in Table 5.

[0138] Table 5

[0139]

[0140] Based on the principle of total pollutant emission balance, the emission reduction space is reallocated. The specific principles are as follows:

[0141] Particulate matter: Emission reduction during the warning period due to the implementation of early warning measures (emissions of industry 1 B level and below + emissions of industry 2 B level and below + … + emissions of industry n B level and below) ≤ emissions during the warning period (emissions of industry (n+1) B level and below + emissions of industry m B level and below). That is: Emission reduction during the warning period due to the implementation of early warning measures (C-level enterprises in industry 1 + B-level enterprises in industry 2 + B-level enterprises in industry 3 + C-level enterprises in industry 4) = 7404 + 0 + 0 + 313.5 + 349 = 8066.5 < Emissions during the warning period (B-level enterprises in industry 5 + C-level enterprises in industry 5 + D-level enterprises in industry 5) = 6843.8 + 1179.03 + 1226.63 = 9249.46 kg / day.

[0142] Sulfur dioxide: the emission reduction during the warning period due to the current early warning measures (emissions of industry 1 B level and below + emissions of industry 2 B level and below + … + emissions of industry n B level and below) ≤ emissions during the warning period (emissions of industry (n+1) B level and below + emissions of industry m B level and below). That is: the emission reduction during the warning period due to the current early warning measures (C-level enterprises in industry 1 + B-level enterprises in industry 2) = 11817 + 0 = 11817 < emissions during the warning period (B-level enterprises in industry 3 + C-level enterprises in industry 4 + B-level enterprises in industry 5 + C-level enterprises in industry 5 + D-level enterprises in industry 5) = 943.1 + 4460.61 + 0 + 6250.6 + 287.18 + 303.63 = 12245.12 kg / day.

[0143] Nitrogen oxides: the emission reduction amount during the warning period due to the implementation of the warning measures now (emissions of industry 1 B level and below + emissions of industry 2 B level and below + … + emissions of industry n B level and below) ≤ emissions during the warning period (emissions of industry (n+1) B level and below + emissions of industry m B level and below). That is: the emission reduction amount during the warning period due to the implementation of the warning measures now (C-level enterprises in industry 1 + B-level enterprises in industry 2) = 11821 + 0 = 11821 < emissions during the warning period (B-level enterprises in industry 3 + C-level enterprises in industry 4 + B-level enterprises in industry 5 + C-level enterprises in industry 5 + D-level enterprises in industry 5) = 885.1 + 3187 + 0 + 5800.2 + 1875.72 + 660.46 = 12408.48 kg / day;

[0144] Industries 1 to n that meet the above critical conditions are non-early warning response industries, and industries n+1 to m are early warning response industries. Since Class A enterprises all implement voluntary emission reduction measures, Class A enterprises are not considered when allocating emission reduction space. That is, industries 1 and 2 are non-early warning response industries, and industries 3, 4, and 5 are early warning response industries.

[0145] For example: for enterprises at level 1B and below in the industry, enterprises at level 2B and below in the industry, enterprises at level 3B and below in the industry, and enterprises at level 4B and below in the industry, the particulate matter emission reductions during the warning period are 10, 20, 30, and 40 respectively, and the particulate matter emissions during the warning period are 20, 25, 20, and 25 respectively; emission reductions (enterprises at level 1B and below in the industry + enterprises at level 2B and below in the industry) = 10 + 20 ≤ emissions (enterprises at level 3B and below in the industry + enterprises at level 4B and below in the industry) = 20 + 25; emission reductions (enterprises at level 1B and below in the industry + enterprises at level 2B and below in the industry + enterprises at level 3B and below in the industry) > emissions (enterprises at level 4B and below in the industry); in this case, industries 1 and 2 are non-warning response industries, and the increased emissions from full-load production of these two industries during the warning period need to be offset proportionally by industries 3 and 4.

[0146] Step 4: Determine the incremental emission reduction for the early warning response industry.

[0147] In order to determine the emission reductions corresponding to the optimized production emergency emission reduction measures of each enterprise in different industries during the heavy pollution warning period, and provide a basis for generating feasible measures in the next step, the emissions released by non-warning response industries can be allocated to the warning response industries according to the emission reduction potential.

[0148] The incremental emission reduction of early warning response industry i = the emission reduction potential of early warning response industry i / the emission reduction potential of all early warning corresponding industries * the emissions released by non-early warning response industries. For example, the incremental particulate matter emission reduction of early warning response industry 3 = the particulate matter emission reduction potential of early warning response industry 3 / the particulate matter emission reduction potential of all early warning corresponding industries * the particulate matter emissions released by non-early warning response industries = 1704.7 / (1704.7 + 1108.9 + 349 + 6843.8 + 1179.03 + 1226.63) * (0 + 7404 + 0) = 1016.89 kg / day; then the emission reduction of each early warning response industry will be allocated to enterprises and specific processes according to the pollutant emission intensity.

[0149] Step 5: Generate optimized emergency emission reduction measures.

[0150] Among the optimization measures, enterprises in non-early warning response industries shall implement voluntary emission reduction measures. Early warning response industries shall increase the emission reduction increment in step 5 on the basis of the original emission reduction.

[0151] In order to ensure the feasibility of the early warning response industry measures, the theoretical production load corresponding to the optimized early warning measures is first calculated, and then the production load is rounded down based on the actual characteristics of the process, and finally the original early warning measures of the process are tightened accordingly.

[0152] Take the steel industry as an example: Steel enterprises are mainly divided into long-process steel and steel rolling enterprises. Steel rolling enterprises are generally enterprises that roll crude steel through cold rolling, hot rolling and other methods. Generally, except for key high-quality manufacturing enterprises that take independent emission reduction measures, other enterprises basically stop production directly. For long-process steel, it is necessary to consider the process separately.

[0153] ①Converter process

[0154] The converter process is generally regulated by limiting the number of steel produced per day for each converter. During the orange warning period, the number of steel produced per day for a Class B enterprise is generally not more than 36 furnaces, for a Class C enterprise it is generally not more than 26 furnaces, and for a Class D enterprise it is not more than 22 furnaces; during the red warning period for Class B and Class C, it is not more than 32 and 22 respectively, and production will be stopped directly for those below Class C. This will lead to a reduction in the overall production load. Therefore, the production load under the original measures and the number of steel produced per day for each converter are determined, as shown in Formula 9:

[0155]

[0156] Where C and C′ are the daily steel production of each converter under the original control measures and the new control measures, respectively; P and P′ are the production loads of the converter under the original control measures and the new control measures, respectively.

[0157] ②Sintering process

[0158] Independent sintering and pelletizing enterprises generally stop all production during yellow and above warning periods, while sintering machines generally stop part of the production line / equipment according to demand. According to the original and existing production load and the original measures, new measures are also generated by rounding.

[0159] ③Coking and pelletizing process

[0160] The pelletizing process is generally produced by three types of methods: vertical furnace, chain grate-rotary kiln, and belt roaster, while coking is generally produced by coke oven. Considering that kiln production must be maintained, it can only be limited by adjusting the daily production output. Specifically, the coke oven coke time can be extended according to formula 10, while the pelletizing process is further limited according to production load and daily output (formula 11).

[0161]

[0162] Wherein, L is the coke oven coking time under the early warning measures, Lmax is the original full-load production coking time (designed coking time), F is the coke oven production load under the production restriction measures during the early warning period, T and T′ are the daily pellet production under the original control measures and the new control measures, respectively, and B and B′ are the pelletizing process production loads under the original control measures and the new control measures.

[0163] ④Other processes

[0164] Under the emergency emission reduction measures, when the corresponding suspension and restriction ratio requirements are met, enterprises generally reasonably arrange and adjust the corresponding smelting equipment according to the steel output of each converter and the number of steel-producing furnaces. Therefore, the measures are generally self-adjusted.

[0165] Step 6: Evaluate the environmental and economic benefits of optimization measures.

[0166] The optimized emergency list was used to drive the air quality model and conduct simulation studies to calculate the improvement in air quality. Given that the total emissions remain unchanged, the improvement in air quality is similar to the original measures.

[0167] Economic benefit evaluation calculates the product output data of the optimized emergency emission reduction measures and the original measures during the heavy pollution warning period. The difference between the two and the product of the economic output per unit product is the improved economic benefit.

[0168] This optimization measure can maintain the original environmental benefits during the warning period while bringing about a steady improvement in the economic level.

[0169] Taking the orange emergency response to heavy pollution weather initiated in ** City from 20:00 on November 19, 2019 to 12:00 on November 24, 2019 as an example, the economic benefits of emergency emission reduction measures before and after the optimization of power big data are calculated and analyzed:

[0170] (1) Calculation method

[0171] The orange emergency response for heavy pollution weather lasts for 6 days, so it is necessary to calculate the increase in product output and economic benefits during the 6-day emergency response period. The calculation is done by collecting product output, production capacity, and total industrial output value data in the emergency emission reduction list, combined with the original production load ratio and the production load ratio under the above-mentioned new control measures.

[0172] The production situation in each factory, especially the steel mill, is complex, the production lines are not unified, and the economic output value is difficult to trace. Therefore, it is necessary to quantify the total industrial output value in order to reasonably estimate the economic benefits of the emergency emission reduction measures before and after optimization. Considering that the main economic product categories of the factory are limited and have high accessibility, the ratio of the total industrial output value and product output data in the emergency emission reduction list is defined as the industrial output value per unit product output, unit (yuan / ton). Based on this ratio, combined with the product increment under the emergency emission reduction measures before and after optimization, a preliminary estimate of the economic benefits can be made.

[0173] ① Calculation of industrial output value per unit of factory product output

[0174] Since the product categories and output of each factory are different, the source of industrial output value is relatively complex, so it is necessary to unify the units of industrial output value. Considering that the research object of this plan is mainly the factory production load, unifying the units of industrial output value based on product output can better combine the load to calculate economic benefits. Considering that the products of factories in different industry categories are different, and the output of products of factories in the same category is also different, the products of various factories are unified. The research on medium and long process steel mainly focuses on crude steel; the steel rolling industry mainly focuses on steel rolling parts (cold forging, hot forging, other forging parts, etc.); the cement industry mainly focuses on cement (clinker is converted at a certain ratio, that is, clinker: cement = 0.64:1) as the research object; bricks and tiles, ceramics, glass, and coking are bricks and tiles, ceramic parts, glass, and coke as the research objects respectively. Factory unit product output industrial output value Z j The calculation formula is as follows:

[0175]

[0176] Where, j is the industry, which are long-process steel, steel rolling, cement, coking, ceramics, bricks and tiles; IO j is the total industrial output value of a factory, in ten thousand yuan; IPO j It is the annual output of a factory’s products (crude steel, steel rolling parts, cement, coking, ceramics, bricks and tiles), in 10,000 tons (10,000 square meters, 10,000 pieces).

[0177] ② Factory product increment calculation

[0178] The study is based on the factory-level data of the emergency emission reduction inventory. Through the power data obtained in the above study, the production load of emergency emission reduction measures before and after optimization can be obtained. The daily product increment during the study period can be obtained through the daily product output. The calculation formula for a factory's product increment (Aj, unit: 10,000 tons) is as follows:

[0179]

[0180] In the formula, S ij and S′ ij is the daily output on the i-th day under the original control measures and the new control measures. R ij and R′ ij D is the production load on the i-th day after rounding off under the original control measures and the new control measures, in %. j It is the daily production output of a factory's products, in ten thousand tons (ten thousand square meters, ten thousand pieces).

[0181] ③ Economic benefit calculation

[0182] The economic benefit can be preliminarily estimated based on the industrial output value of the factory's unit product output and the cumulative product increment under the emergency emission reduction measures before and after optimization. The calculation formula of the economic benefit EP is as follows:

[0183]

[0184] Among them, EP j The economic benefits of each factory, unit, ten thousand yuan.

[0185] From the software level, in order to ensure environmental benefits while improving the economic benefits of emergency emission reduction, the present application provides an embodiment of an emergency emission reduction measure generation device for realizing all or part of the contents of the emergency emission reduction measure generation method, see Figure 4 , the emergency emission reduction measures generating device specifically includes the following contents:

[0186] Acquisition module 01 is used to acquire indicator data groups of multiple industries in the target area, each indicator data group includes: environmental impact dimension indicator data of the corresponding industry, social and economic impact dimension indicator data, and atmospheric pollutant emission reduction data under early warning conditions;

[0187] Determination module 02, used to determine the comprehensive score of each industry based on the environmental impact dimension indicator data and the socio-economic impact dimension indicator data of each industry;

[0188] The generation module 03 is used to determine the early warning response industry in the target area and generate its corresponding emergency emission reduction measures based on the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation.

[0189] In one embodiment, the determining module includes:

[0190] The first determination unit is used to determine the total score of the environmental impact dimension of each industry based on the environmental impact dimension indicator data of each industry;

[0191] The second determination unit is used to determine the total score of the socio-economic impact dimension of each industry based on the socio-economic impact dimension indicator data of each industry;

[0192] The third determination unit is used to determine the comprehensive score of each industry based on the total score of the environmental impact dimension and the total score of the socio-economic impact dimension of each industry.

[0193] In one embodiment, the atmospheric pollutant emission reduction data under the warning situation includes: released emissions, emission reduction potential, emission reduction during the warning period, and emissions during the warning period; correspondingly, the generation module includes:

[0194] A grading unit, used to determine typical polluting industries in the target area and their grading results according to the comprehensive score of each industry;

[0195] The fourth determination unit is used to determine non-warning response industries and warning response industries from each typical polluting industry according to the classification results of each typical polluting industry, the emission reduction during the warning period, and the emission during the warning period;

[0196] The fifth determination unit is used to generate emergency emission reduction measures for each early warning response industry based on the emission reduction potential of all non-early warning response industries, the emissions released by all early warning response industries and the emission reduction potential of each early warning response industry. Each emergency emission reduction measure includes: the emission reduction increment of the early warning response industry.

[0197] In one embodiment, the environmental impact dimension indicator data includes: values ​​of a plurality of environmental impact dimension indicators;

[0198] Correspondingly, the total score of the environmental impact dimension of each industry is determined based on the environmental impact dimension indicator data of each industry, including:

[0199] From the values ​​of the same environmental impact dimension indicator of each industry, the maximum value is selected as the maximum value of the environmental impact dimension indicator, and the minimum value is selected as the minimum value of the environmental impact dimension indicator;

[0200] According to the maximum value and minimum value of each environmental impact dimension indicator and the value of the environmental impact dimension indicator in each industry, determine the indicator score of the environmental impact dimension indicator in each industry;

[0201] According to the weight values ​​of the pre-acquired multiple environmental impact dimension indicators, the indicator scores of each environmental impact dimension indicator in each industry are weighted and summed to obtain the total score of the environmental impact dimension of each industry;

[0202] The weight value of each environmental impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the environmental impact dimension indicator in each industry.

[0203] In one embodiment, the socio-economic impact dimension indicator data includes: values ​​of a plurality of socio-economic impact dimension indicators; correspondingly, the second determining unit is used to execute:

[0204] From the values ​​of the same socio-economic impact dimension indicator of each industry, the maximum value is selected as the maximum value of the socio-economic impact dimension indicator, and the minimum value is selected as the minimum value of the socio-economic impact dimension indicator;

[0205] According to the maximum value and minimum value of each socio-economic impact dimension indicator and the value of the socio-economic impact dimension indicator in each industry, determine the indicator score of the socio-economic impact dimension indicator in each industry;

[0206] According to the weight values ​​of multiple socio-economic impact dimension indicators obtained in advance, the indicator scores of each socio-economic impact dimension indicator in each industry are weighted and summed to obtain the total environmental impact dimension score of each industry;

[0207] The weight value of each socio-economic impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the socio-economic impact dimension indicator in each industry.

[0208] The embodiment of the emergency emission reduction measures generation device provided in this specification can be specifically used to execute the processing flow of the embodiment of the above-mentioned emergency emission reduction measures generation method. Its functions will not be repeated here, and reference can be made to the detailed description of the embodiment of the above-mentioned emergency emission reduction measures generation method.

[0209] From the hardware level, in order to ensure environmental benefits while improving the economic benefits of emergency emission reduction, the present application provides an embodiment of an electronic device for implementing all or part of the contents of the method for generating emergency emission reduction measures. The electronic device specifically includes the following contents:

[0210] Processor, memory, communication interface and bus; wherein the processor, memory and communication interface communicate with each other through the bus; the communication interface is used to realize information transmission between the emergency emission reduction measures generation device and related devices such as user terminals; the electronic device can be a desktop computer, a tablet computer and a mobile terminal, etc., but this embodiment is not limited to this. In this embodiment, the electronic device can be implemented with reference to the embodiment for realizing the emergency emission reduction measures generation method and the embodiment for realizing the emergency emission reduction measures generation device, and their contents are incorporated herein, and the repeated parts are not repeated.

[0211] Figure 5 FIG. 9 is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Figure 5 As shown, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. It is worth noting that Figure 5 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0212] In one or more embodiments of the present application, the emergency emission reduction measures generation function may be integrated into the central processor 9100. The central processor 9100 may be configured to perform the following control:

[0213] Step 100: Obtain indicator data groups for multiple industries in the target area, each indicator data group including: environmental impact dimension indicator data, socio-economic impact dimension indicator data, and atmospheric pollutant emission reduction data under early warning conditions for the corresponding industry.

[0214] Step 200: Determine the comprehensive score of each industry based on the environmental impact dimension indicator data and the socio-economic impact dimension indicator data of each industry.

[0215] Step 300: According to the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation, the early warning response industry in the target area is determined and its corresponding emergency emission reduction measures are generated.

[0216] From the above description, it can be seen that the electronic device provided by the embodiment of the present application can consider the impact of multi-dimensional indicator data on the generation of emergency emission reduction measures, and can improve the economic benefits of emergency emission reduction while ensuring environmental benefits.

[0217] In another embodiment, the emergency emission reduction measures generating device can be configured separately from the central processing unit 9100. For example, the emergency emission reduction measures generating device can be configured as a chip connected to the central processing unit 9100, and the emergency emission reduction measures generating function can be realized through the control of the central processing unit.

[0218] like Figure 5 As shown, the electronic device 9600 may also include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily have to include Figure 5 In addition, the electronic device 9600 may also include Figure 5 For components not shown, reference may be made to the prior art.

[0219] like Figure 5 As shown, the central processing unit 9100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor device and / or logic device, which receives input and controls the operation of various components of the electronic device 9600.

[0220] The memory 9140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 9100 may execute the program stored in the memory 9140 to implement information storage or processing, etc.

[0221] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used to display display objects such as images and texts. The display may be, for example, an LCD display, but is not limited thereto.

[0222] The memory 9140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 9600 through the central processor 9100.

[0223] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0224] The communication module 9110 is a transmitter / receiver 9110 that sends and receives signals via an antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0225] Based on different communication technologies, multiple communication modules 9110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module, etc. The communication module (transmitter / receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide an audio output via the speaker 9131 and receive an audio input from the microphone 9132, thereby realizing a common telecommunication function. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 9130 is also coupled to the central processor 9100, so that recording can be performed on the local machine through the microphone 9132, and the sound stored on the local machine can be played through the speaker 9131.

[0226] From the above description, it can be seen that the electronic device provided in the embodiment of the present application can consider the impact of multi-dimensional indicator data on the generation of emergency emission reduction measures, and can improve the economic benefits of emergency emission reduction while ensuring environmental benefits.

[0227] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps in the method for generating emergency emission reduction measures in the above embodiments. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all the steps in the method for generating emergency emission reduction measures in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0228] Step 100: Obtain indicator data groups for multiple industries in the target area, each indicator data group including: environmental impact dimension indicator data, socio-economic impact dimension indicator data, and atmospheric pollutant emission reduction data under early warning conditions for the corresponding industry.

[0229] Step 200: Determine the comprehensive score of each industry based on the environmental impact dimension indicator data and the socio-economic impact dimension indicator data of each industry.

[0230] Step 300: According to the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation, the early warning response industry in the target area is determined and its corresponding emergency emission reduction measures are generated.

[0231] From the above description, it can be seen that the computer-readable storage medium provided in the embodiment of the present application can consider the impact of multi-dimensional indicator data on the generation of emergency emission reduction measures, and can improve the economic benefits of emergency emission reduction while ensuring environmental benefits.

[0232] In this application, each embodiment of the above method is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. For relevant parts, refer to the partial description of the method embodiment.

[0233] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0234] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0235] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0236] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0237] Specific embodiments are used in this application to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core idea of ​​this application. At the same time, for those skilled in the art, according to the idea of ​​this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on this application.

Claims

1. A method for generating emergency emission reduction measures, characterized in that: include: Obtain indicator data groups for multiple industries in the target area, each indicator data group includes: indicator data of environmental impact dimension, indicator data of social and economic impact dimension, and data on reduction of air pollutant emissions under early warning conditions for the corresponding industry; Determine the comprehensive score of each industry based on the environmental impact dimension indicator data and the socioeconomic impact dimension indicator data of each industry; According to the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation, the early warning response industry in the target area is determined and its corresponding emergency emission reduction measures are generated.

2. The method for generating emergency emission reduction measures according to claim 1, characterized in that: The comprehensive scores of each industry are determined based on the environmental impact dimension indicator data and the socio-economic impact dimension indicator data of each industry, including: Based on the environmental impact dimension indicator data of each industry, determine the total score of the environmental impact dimension of each industry; Based on the socio-economic impact dimension indicator data of each industry, determine the total socio-economic impact dimension score of each industry; The comprehensive score of each industry is determined based on the total score of the environmental impact dimension and the total score of the socioeconomic impact dimension of each industry.

3. The method for generating emergency emission reduction measures according to claim 1, characterized in that: The air pollutant emission reduction data under the early warning situation include: released emissions, emission reduction potential, emission reduction during the early warning period, and emissions during the early warning period; correspondingly, according to the comprehensive score of each industry and the air pollutant emission reduction data under the early warning situation, the early warning response industry in the target area is determined and its corresponding emergency emission reduction measures are generated, including: According to the comprehensive score of each industry, determine the typical polluting industries in the target area and their classification results; According to the classification results of each typical polluting industry, the emission reduction during the warning period and the emission during the warning period, the non-warning response industry and the warning response industry are determined from each typical polluting industry; Based on the emission reduction potential of all non-early warning response industries, the emissions released by all early warning response industries and the emission reduction potential of each early warning response industry, emergency emission reduction measures for each early warning response industry are generated. Each emergency emission reduction measure includes: the emission reduction increment of the early warning response industry.

4. The method for generating emergency emission reduction measures according to claim 2, characterized in that: The environmental impact dimension indicator data includes: values ​​of multiple environmental impact dimension indicators; correspondingly, the total environmental impact dimension score of each industry is determined based on the environmental impact dimension indicator data of each industry, including: From the values ​​of the same environmental impact dimension indicator of each industry, the maximum value is selected as the maximum value of the environmental impact dimension indicator, and the minimum value is selected as the minimum value of the environmental impact dimension indicator; According to the maximum value and minimum value of each environmental impact dimension indicator and the value of the environmental impact dimension indicator in each industry, determine the indicator score of the environmental impact dimension indicator in each industry; According to the weight values ​​of the pre-acquired multiple environmental impact dimension indicators, the indicator scores of each environmental impact dimension indicator in each industry are weighted and summed to obtain the total environmental impact dimension score of each industry; The weight value of each environmental impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the environmental impact dimension indicator in each industry.

5. The method for generating emergency emission reduction measures according to claim 2, characterized in that: The socio-economic impact dimension indicator data includes: values ​​of multiple socio-economic impact dimension indicators; correspondingly, the total socio-economic impact dimension score of each industry is determined based on the socio-economic impact dimension indicator data of each industry, including: From the values ​​of the same socio-economic impact dimension indicator of each industry, the maximum value is selected as the maximum value of the socio-economic impact dimension indicator, and the minimum value is selected as the minimum value of the socio-economic impact dimension indicator; According to the maximum value and minimum value of each socio-economic impact dimension indicator and the value of the socio-economic impact dimension indicator in each industry, determine the indicator score of the socio-economic impact dimension indicator in each industry; According to the weight values ​​of multiple socio-economic impact dimension indicators obtained in advance, the indicator scores of each socio-economic impact dimension indicator in each industry are weighted and summed to obtain the total score of the environmental impact dimension of each industry; The weight value of each socio-economic impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the socio-economic impact dimension indicator in each industry.

6. An emergency emission reduction measure generation device, characterized in that: include: An acquisition module is used to acquire indicator data groups of multiple industries in the target area, each indicator data group including: indicator data of environmental impact dimension, indicator data of social and economic impact dimension and air pollutant emission reduction data under early warning conditions of the corresponding industry; A determination module, used to determine the comprehensive score of each industry based on the environmental impact dimension indicator data and the socio-economic impact dimension indicator data of each industry; The generation module is used to determine the early warning response industry in the target area and generate its corresponding emergency emission reduction measures based on the comprehensive score of each industry and the atmospheric pollutant emission reduction data under the early warning situation.

7. The device for generating emergency emission reduction measures according to claim 6, characterized in that: The determining module comprises: The first determination unit is used to determine the total score of the environmental impact dimension of each industry based on the environmental impact dimension indicator data of each industry; The second determination unit is used to determine the total score of the socio-economic impact dimension of each industry based on the socio-economic impact dimension indicator data of each industry; The third determination unit is used to determine the comprehensive score of each industry based on the total score of the environmental impact dimension and the total score of the socio-economic impact dimension of each industry.

8. The device for generating emergency emission reduction measures according to claim 6, characterized in that: The atmospheric pollutant emission reduction data under the warning situation includes: released emissions, emission reduction potential, emission reduction during the warning period, and emissions during the warning period; correspondingly, the generation module includes: A grading unit, used to determine typical polluting industries in the target area and their grading results according to the comprehensive score of each industry; The fourth determination unit is used to determine non-warning response industries and warning response industries from each typical polluting industry according to the classification results of each typical polluting industry, the emission reduction during the warning period, and the emission during the warning period; The fifth determination unit is used to generate emergency emission reduction measures for each early warning response industry based on the emission reduction potential of all non-early warning response industries, the emissions released by all early warning response industries and the emission reduction potential of each early warning response industry. Each emergency emission reduction measure includes: the emission reduction increment of the early warning response industry.

9. The device for generating emergency emission reduction measures according to claim 7, characterized in that: The environmental impact dimension indicator data includes: values ​​of multiple environmental impact dimension indicators; Correspondingly, the first determining unit is used to execute: From the values ​​of the same environmental impact dimension indicator of each industry, the maximum value is selected as the maximum value of the environmental impact dimension indicator, and the minimum value is selected as the minimum value of the environmental impact dimension indicator; According to the maximum value and minimum value of each environmental impact dimension indicator and the value of the environmental impact dimension indicator in each industry, determine the indicator score of the environmental impact dimension indicator in each industry; According to the weight values ​​of the pre-acquired multiple environmental impact dimension indicators, the indicator scores of each environmental impact dimension indicator in each industry are weighted and summed to obtain the total environmental impact dimension score of each industry; The weight value of each environmental impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the environmental impact dimension indicator in each industry.

10. The device for generating emergency emission reduction measures according to claim 7, characterized in that: The second determining unit is configured to execute: According to the weight values ​​of multiple socio-economic impact dimension indicators obtained in advance, weighted sum calculation is performed on multiple socio-economic impact dimension indicator data of each industry to obtain the total score of the economic impact dimension of each industry; The weight value of each socio-economic impact dimension indicator is determined based on the number of industries in the target area and the probability of occurrence of the socio-economic impact dimension indicator in each industry.

11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method for generating emergency emission reduction measures according to any one of claims 1 to 5 is implemented.

12. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instructions are executed by the processor, the method for generating emergency emission reduction measures according to any one of claims 1 to 5 is implemented.

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