Road construction stage carbon emission quantitative evaluation method and device suitable for multi-source solid waste paving

Abstract

The invention discloses a road construction stage carbon emission quantitative evaluation method suitable for multi-source solid waste paving, and the method comprises the following steps: S10, obtaining the carbon emission coefficient of each material in a production stage according to the carbon emission coefficient of the material and a mixed material proportion parameter; s20, according to the vehicle parameters and the temperature parameters, a COPERT model is combined, and the material carbon emission coefficient in the step S10 is calculated; s30, according to the energy consumption of the construction machinery and the carbon emission factor of the energy in the construction stage, calculating the carbon emission coefficient of the material construction in the step S10; s40, establishing a road construction carbon emission evaluation method, and calculating the standard deviation of parameters in combination with the parameters of the set indexes to obtain the objective weight of each index; s50, establishing a weighted standardization matrix of the highway construction schemes in combination with the objective weights of the indexes in the S40, and calculating the distance from each scheme to the superior and inferior solutions through the Euclidean distance so as to obtain the distance score of the construction schemes; the invention further discloses a corresponding device. And accurate quantification and scheme evaluation of carbon emission are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of highway construction, and more specifically, to a method and device for quantitatively evaluating carbon emissions during the highway construction stage suitable for paving with multi-source solid waste. Background Art

[0002] With the rapid development of China's economy and industrialization, the problem of carbon emissions from transportation is severe, especially in highway transportation, which accounts for more than 85% of the total carbon emissions of the transportation sector. At the same time, carbon emissions during the construction and maintenance of highway infrastructure cannot be ignored, accounting for 10% - 20% of highway traffic carbon emissions. In addition, a large amount of solid waste generated by industrialization pollutes the environment, and green highway construction based on the utilization of multi-source solid waste has become an important measure for energy conservation and emission reduction. However, there is currently a lack of scientific and reasonable methods for carbon emission quantification and evaluation, making it difficult to accurately assess the carbon emissions during the green highway construction process based on the utilization of multi-source solid waste and unable to provide strong data support for energy conservation and emission reduction.

[0003] To solve these problems, some existing technologies focus on comprehensively analyzing the carbon emissions throughout the road construction life cycle by conducting detailed research and analysis on carbon emissions in aspects such as construction activities and traffic impacts, in order to identify major energy-consuming users and main sources of carbon emissions, thereby optimizing the use of materials and the design of pavement structures, and proposing low-carbon improvement approaches for construction technologies. However, these technologies mainly focus on the carbon emissions of traditional road construction materials and do not consider sufficiently the utilization of multi-source solid waste and its carbon emission impacts. Therefore, when evaluating the carbon emission characteristics and emission reduction potential during the paving process of multi-source solid waste, accurate and comprehensive data support may not be provided. Summary of the Invention

[0004] In view of the above-mentioned defects or improvement requirements of the existing technology, the present invention provides a method and device for quantitatively evaluating carbon emissions during the highway construction stage suitable for paving with multi-source solid waste. This method particularly considers the slag asphalt mixture surface layer, cement-stabilized slag crushed stone base layer, and carbide slag composite gel material solidified special soil subgrade during the highway construction stage of paving with multi-source solid waste. The construction process is also divided into a material production stage, a transportation stage, and a construction stage. By combining the carbon emission coefficients of various materials, the mixing ratio parameters, and the COPERT model, etc., the accurate quantification of carbon emissions from solid waste resource utilization technology during the highway construction stage is realized, solving the technical problem of quantitatively evaluating the resource utilization of multi-source solid waste for energy conservation and emission reduction.

[0005] To achieve the above object, according to the first aspect of the present invention, there is provided a method for quantitatively evaluating carbon emissions during the highway construction stage suitable for paving with multi-source solid waste, including the following steps;

[0006] Including the following steps:

[0007] S10. Obtain the carbon emission coefficients of each of the materials in the production stage respectively according to the carbon emission coefficients of the set materials and the mixing ratio parameters.

[0008] S20. Calculate the carbon emission coefficients for transporting each of the materials in S10 in combination with the vehicle parameters and temperature parameters using the COPERT model.

[0009] S30. Calculate the carbon emission coefficients for constructing each of the materials in S10 according to the energy consumption of the construction machinery and the carbon emission factors of the energy in the construction stage.

[0010] S40. Establish a carbon emission evaluation method for highway construction. Combine the parameters of the set indicators, and obtain the objective weights of each of the indicators by calculating the standard deviation of the parameters.

[0011] S50. Establish a weighted standardized matrix for the highway construction plan in combination with the objective weights of the indicators in S40. Calculate the distances from each plan to the ideal solution and the negative ideal solution through the Euclidean distance, and then obtain the distance scores of the construction plans.

[0012] Further, the set materials in S10 include slag asphalt mixture. The method for obtaining the carbon emission coefficient of the slag asphalt mixture in the production stage is as follows:

[0013]

[0014] In the formula, C α1 is the carbon emission coefficient of the slag asphalt mixture in the production stage, P b is the asphalt-aggregate ratio of the slag asphalt mixture in the production stage, C b is the carbon emission coefficient of asphalt, m t、 t, w are respectively the dosage, particle size number and total number of particle size numbers of each particle size aggregate of the slag asphalt mixture in the production stage, where t = 1, 2, 3... w, C at is the carbon emission coefficient of the t-th particle size aggregate, m m is the dosage of mineral powder, C m is the carbon emission coefficient of mineral powder.

[0015] Further, the set materials in S10 include cement-stabilized slag gravel mixture. The method for obtaining the carbon emission coefficient of the cement-stabilized slag gravel mixture in the production stage is as follows:

[0016]

[0017] In the formula, C α2 is the carbon emission coefficient of the cement-stabilized slag gravel mixture in the production stage, m c is the dosage of cement in the cement-stabilized slag gravel mixture in the production stage, Cc is the carbon emission coefficient of cement, m x, x and y are the dosages, particle size numbers, and total numbers of particle size numbers of the aggregate of each particle size corresponding to the cement-stabilized slag gravel mixture in the production stage, respectively, where x = 1, 2, 3…y, C ax is the carbon emission coefficient of the x-th particle size aggregate.

[0018] Furthermore, the set materials in the S10 include the carbide slag composite gel material. The method for obtaining the carbon emission coefficient of the carbide slag composite gel material in the production stage is as follows:

[0019] C α3 = m f ·C f + m SC ·C c ,

[0020] In the formula, C α3 is the carbon emission coefficient of the carbide slag composite gel material in the production stage, m f is the dosage of fly ash, C f is the carbon emission coefficient of fly ash, m sc is the dosage of cement in the carbide slag composite gel material in the production stage, and Cc is the carbon emission coefficient of cement.

[0021] Furthermore, the method for calculating the carbon emission coefficient of transporting each material in the S10 in the S20 is as follows:

[0022] The COPERT model is a road transport emission calculation program. The carbon emission coefficient of material transportation is calculated by inputting vehicle parameters and temperature parameters into the program. In addition, the resting carbon emission coefficient corresponding to each material in the non-operating state of the vehicle during transportation is obtained through experiments. The carbon emission coefficient of the transported material is the sum of the transportation carbon emission coefficient and the resting carbon emission coefficient;

[0023] The vehicle parameters include vehicle type, average driving speed, fuel parameters, average single-trip mileage, and vehicle load; the temperature parameters include the monthly maximum temperature and the minimum temperature; both the vehicle parameters and the temperature parameters are obtained through research.

[0024] Furthermore, the method for calculating the carbon emission coefficient of constructing each material in the S10 in the S30 is as follows:

[0025] The energy consumption Ee of the e-th construction machine in the construction stage is obtained through experiments, where e = 1, 2, 3,…, e m , e is the construction machine category number, and e m is the total number of construction machine categories; the carbon emission coefficient Eq of the q-th type of energy, where q = 1, 2, 3,…, q m , q is the energy category number, and q m is the total number of energy categories. The carbon emissions C in the construction stage are calculated based on the above parameters.β :

[0026]

[0027] Wherein, e and q correspond according to the construction conditions.

[0028] Further, the method for calculating the standard deviation of the parameters by combining the parameters of the set indexes in S40 is as follows:

[0029] According to the carbon emission coefficients of the materials in each production stage in S10, the carbon emission coefficients of transporting the materials in S10 in S20, and the carbon emission coefficients of constructing the materials in S10 in S30, combined with the weights of the materials in practice, calculate the carbon emissions of the corresponding plan; the parameters of the set indexes include the carbon emissions of the corresponding plan;

[0030] Establish a highway construction carbon emission decision matrix A = (a ij ) n×m , where m is the number of evaluation indexes, j represents the serial number of the evaluation index, j = 1, 2... m; n is the number of samples to be evaluated, i represents the serial number of the sample, i = 1, 2... n;

[0031] Perform dimensionless processing on each index to obtain a normalized decision matrix B = (b ij ) n×m , and calculate to obtain the standard deviation S j ,

[0032]

[0033]

[0034] Among them, Sj represents the standard deviation of the j-th index. The larger the standard deviation, the greater the numerical difference of the index, and the higher the weight of the index.

[0035] Further, the method for obtaining the objective weights of the indexes in S40 is as follows:

[0036]

[0037] Wherein, C j , Sj, and Wj are the information amount, standard deviation, and objective weight of the j-th index respectively, m is the number of evaluation indexes, j and k are the serial numbers of two groups of evaluation indexes, j = 1, 2... m, k = 1, 2... m, and r jk is the correlation coefficient obtained through experiments for the j-th and k-th indexes.

[0038] Further, the method for obtaining the distance score of the construction plan in S50 is as follows:

[0039] R ij = (W j b ij ) n×m ,

[0040]

[0041] wherein, R ij is the weighted normalization matrix, i represents the serial number of the sample, D i(lowest) and D i(best) are respectively the worst distance and the best distance of the i-th group under each factor, S pi is the distance score, and the larger the value of S pi is, the better the sample scheme is.

[0042] According to the second aspect of the present invention, there is provided a device for quantitatively evaluating carbon emissions in the highway construction stage applicable to multi-source solid waste paving, including:

[0043] The first module, according to the carbon emission coefficients of the set materials and the mixing ratio parameters, respectively obtains the carbon emission coefficients of each of the materials in the production stage;

[0044] The second module, according to the vehicle parameters and temperature parameters in combination with the COPERT model, calculates the carbon emission coefficients of transporting each of the materials in S10;

[0045] The third module, according to the energy consumption of the construction machinery and the carbon emission factors of the energy in the construction stage, calculates the carbon emission coefficients of constructing each of the materials in S10;

[0046] The fourth module, establishes a method for evaluating highway construction carbon emissions, in combination with the parameters of the set indicators, and obtains the objective weights of each of the indicators by calculating the standard deviation of the parameters;

[0047] The fifth module, combines the objective weights of the indicators in S40 to establish a weighted normalization matrix for the highway construction plan, calculates the distances of each plan to the optimal and worst solutions through the Euclidean distance, and further obtains the distance score of the construction plan.

[0048] Generally speaking, compared with the prior art through the above technical solutions conceived by the present invention, the following beneficial effects can be achieved:

[0049] 1. The quantitative evaluation method of the present invention, by subdividing the carbon emission links into the material production stage, the transportation stage and the construction stage, and combining the carbon emission coefficients of each material, the mixing ratio parameters and the COPERT model, etc., realizes the accurate quantification of the carbon emissions of the solid waste resource utilization technology in the highway construction stage, and solves the technical problem of the quantitative evaluation of energy conservation and emission reduction in the aspect of multi-source solid waste resource utilization.

[0050] 2. The quantitative evaluation method of the present invention realizes the evaluation of carbon emissions in the highway construction stage paved with multi-source solid waste by establishing a highway construction carbon emission evaluation method and obtaining the distance score of the construction plan, and conducts comparative screening among various plans, improving the green highway evaluation system. It also provides an evaluation method and guiding ideas for green highway construction, which helps to promote the sustainable development of green highway construction. Description of the Drawings

[0051] Figure 1 It is a working flowchart provided by a preferred embodiment of the present invention;

[0052] Figure 2 It is a schematic diagram of the device provided by a preferred embodiment of the present invention. Detailed Embodiments

[0053] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0054] Based on the above problems, the present invention proposes a carbon emission quantitative evaluation method and device for the highway construction stage suitable for paving with multi-source solid waste. The method first focuses on the calculation of carbon emission coefficients in each stage, which includes three core links: material production, transportation and construction. In the material production stage, according to the carbon emission characteristics and composition of different materials, combined with the corresponding carbon emission coefficients and mixing ratio parameters, the carbon emission coefficient of each material is calculated. For specific materials, such as slag asphalt mixture, cement stabilized slag crushed stone mixture and carbide slag composite gel material, specific formulas will be used for calculation.

[0055] Next, in the transportation stage, using the COPERT model, combined with detailed vehicle parameters (such as vehicle type, average driving speed, fuel parameters, average single-trip mileage, and vehicle load) and temperature parameters (including monthly maximum and minimum temperatures), the carbon emission coefficients of various materials during transportation are calculated. Among them, the COPERT model originated from the EU's research on vehicle emission factors and is the official European road transport emission factor model. This software was developed by the European Environment Agency (EEA) to accurately calculate vehicle exhaust emissions by considering various factors. The COPERT model can calculate the emission factors of different vehicle types under different driving conditions, including the emissions of CO (carbon monoxide), HC (hydrocarbons), NOx (nitrogen oxides), PM (particulate matter), and carbon dioxide. In addition, the resting carbon emission coefficient of the vehicle in the non-operating state during transportation is also considered to ensure a comprehensive assessment of carbon emissions in the transportation stage.

[0056] In the construction stage, based on the energy consumption of construction machinery and the carbon emission factors of energy, the carbon emissions during construction are calculated. This includes obtaining the energy consumption of construction machinery through experiments and the carbon emission coefficients of various types of energy, and then calculating the carbon emissions in the entire construction stage.

[0057] After obtaining the carbon emission coefficients of each stage, combined with the weights of various materials in practice, the carbon emissions of the corresponding plan are calculated. Then, a highway construction carbon emission decision matrix is established, and dimensionless processing is performed on each index, and the standard deviation is calculated to determine the objective weights of each evaluation index.

[0058] Finally, according to the determined index weights, a weighted standardization matrix of highway construction plans is constructed. Then, methods such as Euclidean distance are used to calculate the distances of each construction plan to the optimal and worst solutions, so as to obtain the distance scores of the construction plans. This score can be used to evaluate the advantages and disadvantages of different construction plans and provide a scientific decision-making basis for highway construction.

[0059] Specifically,

[0060] Please refer to Figure 1 , the present invention relates to a method for quantitatively evaluating carbon emissions in the highway construction stage applicable to the paving of multi-source solid waste, including the following steps:

[0061] S10, according to the carbon emission coefficients of the set materials and the mixing ratio parameters, respectively obtain the carbon emission coefficients of each of the materials in the production stage;

[0062] Specifically, the set materials in S10 include slag asphalt mixture, and the method for obtaining the carbon emission coefficient of the slag asphalt mixture in the production stage is:

[0063]

[0064] Wherein, C α1 is the carbon emission coefficient of slag asphalt mixture in the production stage, P b is the asphalt-aggregate ratio of slag asphalt mixture in the production stage, C b is the carbon emission coefficient of asphalt, m t、 t, w are respectively the dosage, particle size number and total number of particle size numbers of each particle size aggregate of slag asphalt mixture in the production stage, where t = 1, 2, 3... w, C at is the carbon emission coefficient of the t-th particle size aggregate, m m is the dosage of mineral powder, C m is the carbon emission coefficient of mineral powder.

[0065] Specifically, the set materials in S10 include cement stabilized slag gravel mixture, and the method for obtaining the carbon emission coefficient of the cement stabilized slag gravel mixture in the production stage is as follows:

[0066]

[0067] Wherein, C α2 is the carbon emission coefficient of cement stabilized slag gravel mixture in the production stage, m c is the dosage of cement in the cement stabilized slag gravel mixture in the production stage, Cc is the carbon emission coefficient of cement, m x , x, y are respectively the dosage, particle size number and total number of particle size numbers of each particle size aggregate corresponding to the cement stabilized slag gravel mixture in the production stage, where x = 1, 2, 3... y, C ax is the carbon emission coefficient of the x-th particle size aggregate.

[0068] Specifically, the set materials in S10 include carbide slag composite gel material, and the method for obtaining the carbon emission coefficient of the carbide slag composite gel material in the production stage is as follows:

[0069] C α3 = m f ·C f + m SC ·C c ,

[0070] Wherein, C α3 is the carbon emission coefficient of carbide slag composite gel material in the production stage, m f is the dosage of fly ash, C f is the carbon emission coefficient of fly ash, m sc is the dosage of cement in the carbide slag composite gel material in the production stage, Cc is the carbon emission coefficient of cement.

[0071] S20. According to the vehicle parameters and temperature parameters, combined with the COPERT model, calculate the carbon emission coefficients of transporting each material in S10;

[0072] The method for calculating the carbon emission coefficients of transporting various materials in S10 in S20 is as follows:

[0073] The COPERT model is a road transport emission calculation program. The carbon emission coefficients of material transportation are calculated by inputting vehicle parameters and temperature parameters into the program. In addition, the resting carbon emission coefficients corresponding to various materials in the non-operating state of the vehicle during transportation are obtained through experiments. The carbon emission coefficient of the transported material is the sum of the transportation carbon emission coefficient and the resting carbon emission coefficient.

[0074] The vehicle parameters include vehicle type, average driving speed, fuel parameters, average single-trip mileage, and vehicle load. The temperature parameters include the monthly maximum temperature and the minimum temperature. Both the vehicle parameters and the temperature parameters are obtained through research.

[0075] S30. Calculate the carbon emission coefficients for the construction of various materials in S10 based on the energy consumption of construction machinery and the carbon emission factors of the energy during the construction stage.

[0076] The method for calculating the carbon emission coefficients for the construction of various materials in S10 in S30 is as follows:

[0077] The energy consumption Ee of the e-th type of construction machinery during the construction stage is obtained through experiments, where e = 1, 2, 3,..., e m , e is the construction machinery category number, and e m is the total number of construction machinery categories; the carbon emission coefficient Eq of the q-th type of energy, where q = 1, 2, 3,..., q m , q is the energy category number, and q m is the total number of energy categories. The carbon emissions C during the construction stage are calculated based on the above parameters β :

[0078]

[0079] In the formula, e and q correspond according to the construction situation.

[0080] S40 and S50 are namely the establishment of a carbon emission evaluation method for green highway construction based on the CRITIC-TOPSIS algorithm. In some preferred embodiments, indicators are established for the energy consumption, carbon emissions, and cost of green highway construction. The variability, conflict, and information content of each indicator are calculated through the CRITIC algorithm, and then the weight of each indicator is obtained. The indicator weights are brought into the TOPSIS algorithm to establish a weighted standardized evaluation matrix for the green highway construction construction plan. The distances from each plan to the optimal and worst solutions are calculated through the Euclidean distance, and then the distance scores of the construction plans are obtained, and the comprehensive benefits of the plans are compared and evaluated.

[0081] Among them, the CRITIC method is an objective weighting method based on data characteristics. First, it measures the contrast intensity by calculating the standard deviation of each evaluation index. The larger the standard deviation, the greater the difference between this index among different objects, and the more information content it has. Therefore, a larger weight should be assigned. At the same time, the correlation coefficient between indicators is used to reflect the conflict, that is, the stronger the correlation between indicators, the lower its weight should be to avoid information overlap. By comprehensively considering the contrast intensity and conflict, the CRITIC method can determine more reasonable index weights.

[0082] The TOPSIS method is a ranking method that approximates the ideal solution. First, according to the actual situation of the evaluation problem, an ideal solution (i.e., the optimal solution) and a negative ideal solution (i.e., the worst solution) are constructed. The ideal solution usually contains the optimal values of all evaluation indicators, while the negative ideal solution contains the worst values of all evaluation indicators. Then, the Euclidean distance or other forms of distance between each evaluation object and the ideal solution and the negative ideal solution is calculated. The object that is closer to the ideal solution and farther from the negative ideal solution has a better comprehensive evaluation result, and vice versa.

[0083] The CRITIC-TOPSIS algorithm combines the CRITIC method and the TOPSIS method. First, it uses the CRITIC method to determine the weights of each evaluation index, and then uses these weights to perform weighted processing on the original data to obtain a weighted decision matrix. Next, based on the weighted decision matrix, the TOPSIS method is used to calculate the distances between each evaluation object and the ideal solution and the negative ideal solution, and sort according to the distance size to obtain the comprehensive evaluation result. This method combines the advantages of the two methods, taking into account both the objective differences and conflicts between indicators and making full use of the information of the original data, improving the accuracy and reliability of the comprehensive evaluation.

[0084] Specifically,

[0085] S40, establish a highway construction carbon emission evaluation method, combine the parameters of the set indicators, and obtain the objective weights of each of the indicators by calculating the standard deviation of the parameters.

[0086] The method of combining the parameters of the set indicators and calculating the standard deviation of the parameters in S40 is as follows:

[0087] According to the carbon emission coefficients of each material in the production stage in S10, the carbon emission coefficients of transporting each material in S10 in S20, and the carbon emission coefficients of constructing each material in S10 in S30, combined with the weights of each material in practice, calculate the carbon emissions of the corresponding plan; the parameters of the set indicators include the carbon emissions of the corresponding plan.

[0088] Establish a highway construction carbon emission decision matrix A=(a ij )n×m , where m is the number of evaluation indicators, j represents the serial number of the evaluation indicator, and j = 1, 2,..., m; n is the number of samples to be evaluated, i represents the serial number of the sample, and i = 1, 2,..., n;

[0089] Perform dimensionless processing on each indicator to obtain the normalized decision matrix B = (b ij ) n×m , and calculate the standard deviation S j ,

[0090]

[0091]

[0092] Among them, Sj represents the standard deviation of the j-th indicator. The larger the standard deviation, the greater the numerical difference of the indicator, and the higher the weight of the indicator.

[0093] The method for obtaining the objective weights of the indicators in S40 is as follows:

[0094]

[0095] In the formula, C j , Sj, and Wj are the information amount, standard deviation, and objective weight of the j-th indicator respectively. m is the number of evaluation indicators, and j and k are the serial numbers of two groups of evaluation indicators. j = 1, 2,..., m, k = 1, 2,..., m, and r jk is the correlation coefficient obtained through experiments for the j-th and k-th indicators.

[0096] S50. Combine the objective weights of the indicators in S40 to establish a weighted standardized matrix for the highway construction construction plan. Calculate the distances from each plan to the optimal and worst solutions through the Euclidean distance, and then obtain the distance score of the construction plan.

[0097] The method for obtaining the distance score of the construction plan in S50 is as follows:

[0098] R ij = (W j b ij ) n×m ,

[0099]

[0100] In the formula, R ij is the weighted standardized matrix, i represents the serial number of the sample, D i(lowest) and D i(best) are the worst distance and the best distance of the i-th group under each factor respectively, S pi is the distance score, and the larger the value of S pi , the better the sample plan.

[0101] Please refer to Figure 2 , as another aspect of the present invention, it also relates to a device for quantitatively evaluating carbon emissions during the highway construction stage applicable to the paving of multi-source solid waste, including:

[0102] The first module obtains the carbon emission coefficients of each of the above materials during the production stage respectively according to the carbon emission coefficients of the set materials and the mixing ratio parameters of the mixture;

[0103] The second module calculates the carbon emission coefficients of transporting each of the materials in S10 according to the vehicle parameters and temperature parameters in combination with the COPERT model;

[0104] The third module calculates the carbon emission coefficients of constructing each of the materials in S10 according to the energy consumption of construction machinery and the carbon emission factors of the energy during the construction stage;

[0105] The fourth module establishes a method for evaluating highway construction carbon emissions, combines the parameters of the set indicators, and obtains the objective weights of each of the above indicators by calculating the standard deviation of the parameters;

[0106] The fifth module establishes a weighted standardization matrix of the highway construction construction plan in combination with the objective weights of the indicators in S40, calculates the distances of each plan to the optimal and worst solutions through the Euclidean distance, and further obtains the distance score of the construction plan.

[0107] Example 1

[0108] In a certain green highway construction, the solid waste resource utilization technology adopts a slag asphalt mixture surface layer, a cement stabilized slag crushed stone base layer, and a special soil subgrade solidified by an electric slag composite gel material. The carbon emission calculation is as follows.

[0109] Based on actual measurements or by referring to the carbon emission database of relevant raw materials, determine the carbon emission factors of various raw materials. The carbon emission coefficient Cb of SBS modified asphalt is 323.04 kg / t, the carbon emission coefficient Ca of aggregate is 3.45 kg / t, the carbon emission coefficient Cm of mineral powder is 7.36 kg / t, the carbon emission coefficient Cc of cement is 678 kg / t, the carbon emission coefficient C sl of lime is 415 kg / t, the carbon emission coefficient C f of fly ash is 8 kg / t, and the carbon emission coefficient Cu of the mixing equipment for mixing unit volume of mixture is 0.03914 kg / m 3 .

[0110] Determine the optimal asphalt-aggregate ratio of 5.02% for the slag asphalt mixture, a slag content of 10%, a limestone aggregate content of 88%, and a mineral powder content of 2% during the material production process; calculate the carbon emission C α1 of the slag asphalt mixture during the material production process according to the above key parameters:

[0111]

[0112] Determine that the cement content of the cement-stabilized slag gravel mixture is 5%, the slag content is 20%, and the limestone aggregate content is 75%. Calculate the carbon emissions C of the cement-stabilized slag gravel mixture during the material production process based on the above key parameters α2 :

[0113] C α2 = 0.05·678 + 3.45·0.75 = 36.49

[0114] Determine that the carbide slag content of the carbide slag composite gel material for solidifying special soil subgrade is 8%, the fly ash content is 15%, the cement content is 3%, and the saline soil content is 74%. Calculate the carbon emissions C of the carbide slag composite gel material for solidifying special soil subgrade materials during the material production process based on the above key parameters α3 :

[0115] C α3 = 0.15·8 + 0.03·678 = 21.54

[0116] According to the investigation, determine the vehicle types, average driving speeds, fuel parameters, monthly maximum and minimum temperatures, average single-trip mileage, and vehicle loads of various dump trucks and trucks during the transportation stage, input them into the COPERT model, calculate the greenhouse gas emissions of various transportation vehicles, and calculate the unit carbon dioxide emissions of transportation vehicles according to the global warming potential (GWP):

[0117] Table 1 Greenhouse gas emission results per kilometer of driving

[0118]

[0119] Considering that waiting for loading, unloading and other work contents will also generate carbon dioxide, therefore, the carbon emissions of the first 1 km of transportation vehicles refer to the mechanical working hours and energy consumption of the "Highway Engineering Budget Quota". According to the investigation, the average distance for transporting raw materials is 200 km, and the average distance for transporting the mixture is 30 km. Then, based on the transportation carbon emissions of various materials in the table and the quality of various materials in the mix ratio, the transportation carbon emissions C of the slag asphalt mixture can be known γ1 is 10.8027 kg / t, and the transportation carbon emissions C of the cement-stabilized slag gravel mixture γ2 is 13.0827 kg / t, and the transportation carbon emissions C of the carbide slag composite gel material for solidifying special soil subgrade γ3 is 8.1024 kg / t.

[0120] Table 2 Carbon emissions per ton of transported raw materials Determine the carbon emission parameters of construction machinery based on actual measurements, or by referring to account books and relevant quotas, and determine the carbon emission factors of various construction machinery:

[0121] Table 3 Carbon emissions during the construction of 1t slag asphalt mixture surface course

[0122]

[0123]

[0124] Table 4 Carbon emissions during the construction of 1t cement stabilized slag gravel base course

[0125] Table 5 Carbon emissions during the construction of 1t special soil subgrade solidified by carbide slag composite gel material

[0126] Determine the carbon emission C of slag asphalt mixture construction based on the above parameters β1 is 115.811 kg / t, the carbon emission C of cement stabilized slag gravel mixture construction β2 is 1.373 kg / t, and the carbon emission of special soil subgrade solidified by carbide slag composite gel material is C β3 is 0.3686 kg / t.

[0127] Determine that the carbon emission C1 of slag asphalt mixture is 143.5737 kg, the carbon emission C2 of cement stabilized slag gravel mixture is 50.9457 kg / t, and the carbon emission C3 of special soil subgrade solidified by carbide slag composite gel material is 30.0110 kg / t according to the calculation results of the above parameters.

[0128] Example 2

[0129] Summarize the carbon emissions of green highway construction for different pavement structures or different design schemes, and establish an evaluation sample dataset Ds.

[0130] Table 6 Summary of construction plans for green highway construction

[0131] Scheme Energy consumption (MJ) Carbon emission (kg) Cost (yuan) 1 1356266 169345 831956 2 1274570 160543 903700 3 1208101 155411 721224 4 1412575 173181 868982 5 1330879 164379 940726

[0132] Establish a carbon emission evaluation method for green highway construction based on the CRITIC-TOPSIS algorithm. Establish indicators for the three aspects of energy consumption, carbon emission, and cost in green highway construction, calculate the weights of each indicator through the CRITIC algorithm, and substitute the indicator weights into the TOPSIS algorithm to finally obtain the comprehensive evaluation of each green highway design scheme.

[0133] Calculate the indicator weights according to the evaluation sample dataset and the CRITIC weight method. The calculation results are as follows:

[0134] Weights of various indicators in Table 7

[0135] Index Index variability Index conflict Information volume Objective weight Energy consumption 0.6397 0.9588 0.3924 0.2179 Carbon emission 0.6306 1.3421 0.5336 0.2964 Cost 0.6386 2.1434 0.8741 0.4856

[0136] The TOPSIS algorithm is used to construct a carbon emission evaluation model for green highway construction. The decision matrix is standardized to obtain a standardized matrix. According to the index weights obtained by the CRITIC algorithm, a weighted standardized matrix is obtained. Calculate the goodness and badness values of each green highway construction plan, and define the comprehensive score of each plan by the distance from each plan to the optimal solution and the distance to the worst solution. The Euclidean distance is used to calculate the optimal distance and the worst distance of each plan under each factor and calculate the comprehensive score.

[0137] Comprehensive scores of construction plans for green highway construction in Table 8

[0138]

[0139]

[0140] According to the carbon emission evaluation model for green highway construction, the comprehensive scores and rankings of each construction plan are calculated. The specific ranking is Plan 3 > Plan 1 > Plan 2 > Plan 4 > Plan 5.

[0141] It is easy for those skilled in the art to understand that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A carbon emission quantification and evaluation method for the highway construction stage applicable to the paving of multi-source solid waste, characterized in that It includes the following steps: S10. Obtain the carbon emission coefficients of each of the materials in the production stage respectively according to the carbon emission coefficients of the set materials and the mixing ratio parameters; S20. Calculate the carbon emission coefficients of transporting each of the materials in S10 according to the vehicle parameters and temperature parameters in combination with the COPERT model; S30. Calculate the carbon emission coefficients of constructing each of the materials in S10 according to the energy consumption of construction machinery and the carbon emission factors of the energy in the construction stage; S40. Establish a carbon emission evaluation method for highway construction. Combine the parameters of the set indicators, and obtain the objective weights of each of the indicators by calculating the standard deviation of the parameters; S50. Establish a weighted standardization matrix for the highway construction construction plan in combination with the objective weights of the indicators in S40. Calculate the distances from each plan to the optimal and worst solutions through the Euclidean distance, and then obtain the distance scores of the construction plans.

2. The carbon emission quantification and evaluation method applicable to the highway construction stage of multi-source solid waste paving according to claim 1, characterized in that The set materials in S10 include slag asphalt mixture. The method for obtaining the carbon emission coefficient of the slag asphalt mixture in the production stage is: In the formula, C α1 is the carbon emission coefficient of slag asphalt mixture in the production stage, P b is the asphalt-aggregate ratio of slag asphalt mixture in the production stage, C b is the carbon emission coefficient of asphalt, m t、 t, w are the dosage, particle size number and total number of particle size numbers of each particle size aggregate of slag asphalt mixture in the production stage, where t = 1, 2, 3... w, C at is the carbon emission coefficient of the t-th particle size aggregate, m m is the dosage of mineral powder, C m is the carbon emission coefficient of mineral powder.

3. The carbon emission quantification and evaluation method applicable to the highway construction stage of multi-source solid waste paving according to claim 1, characterized in that The set materials in S10 include cement stabilized slag gravel mixture. The method for obtaining the carbon emission coefficient of the cement stabilized slag gravel mixture in the production stage is: Where C α2 is the carbon emission coefficient of the cement-stabilized slag gravel mixture in the production stage, m c is the dosage of cement in the cement-stabilized slag gravel mixture in the production stage, Cc is the carbon emission coefficient of cement, m x , x, and y are respectively the dosage, particle size grade number, and total number of particle size grade numbers of each particle size aggregate corresponding to the cement-stabilized slag gravel mixture in the production stage, where x = 1, 2, 3... y, C ax is the carbon emission coefficient of the x-th particle size aggregate.

4. The carbon emission quantification and evaluation method applicable to the highway construction stage of multi-source solid waste paving according to claim 1, characterized in that, The set materials in S10 include carbide slag composite gel material. The method for obtaining the carbon emission coefficient of the carbide slag composite gel material in the production stage is: C α3 = m f · C f + m sc · C c , Where C α3 is the carbon emission coefficient of carbide slag composite gel material in the production stage, m f is the fly ash content, C f is the carbon emission coefficient of fly ash, m sc is the content of cement in carbide slag composite gel material in the production stage, and Cc is the carbon emission coefficient of cement.

5. The carbon emission quantification and evaluation method applicable to the highway construction stage of multi-source solid waste paving according to claim 1, wherein The method for calculating the carbon emission coefficients of transporting each of the materials in S10 in S20 is: The COPERT model is a road transport emission calculation program. Calculate the carbon emission coefficients of material transportation by inputting vehicle parameters and temperature parameters into the program; in addition, obtain the resting carbon emission coefficients corresponding to each material in the non-operating state of the vehicle during transportation through experiments. The carbon emission coefficient of the transported material is the sum of the transportation carbon emission coefficient and the resting carbon emission coefficient; The vehicle parameters include vehicle type, average driving speed, fuel parameters, average single-trip driving mileage and vehicle load; the temperature parameters include the monthly maximum temperature and the minimum temperature; both the vehicle parameters and the temperature parameters are obtained through research.

6. The carbon emission quantification and evaluation method for the highway construction stage applicable to multi-source solid waste paving according to claim 1, characterized in that, The method for calculating the carbon emission coefficients of constructing each of the materials in S10 in S30 is: During the construction stage, the energy consumption Ee of the e-th type of construction machinery is obtained through experiments, where e = 1, 2, 3, …, e m , where e is the serial number of the construction machinery type, and e m is the total number of construction machinery types; the carbon emission factor Eq of the q-th type of energy, where q = 1, 2, 3, …, q m , where q is the serial number of the energy type, and q m is the total number of energy types. The carbon emissions C during the construction stage are calculated based on the above parameters β : In the formula, e and q correspond to the construction situation.

7. The carbon emission quantification and evaluation method applicable to the highway construction stage of multi-source solid waste paving according to any one of claims 1-6, characterized in that, The method for calculating the standard deviation of the parameters in combination with the parameters of the set indicators in S40 is: According to the carbon emission coefficients of each of the materials in the production stage in S10, the carbon emission coefficients of transporting each of the materials in S10 in S20, and the carbon emission coefficients of constructing each of the materials in S10 in S30, and combining the weights of each material in practice, calculate the carbon emissions of the corresponding plan; the parameters of the set indicators include the carbon emissions of the corresponding plan; Establish a highway construction carbon emission decision matrix \(A=(a ij ) n×m , where \(m\) is the number of evaluation indicators, \(j\) represents the serial number of the evaluation indicator, \(j = 1, 2,\cdots,m\); \(n\) is the number of samples to be evaluated, \(i\) represents the serial number of the sample, \(i = 1, 2,\cdots,n\); The dimensionless treatment is carried out on each index to obtain the normalized decision matrix B=(b ij ). n×m , and the standard deviation S j is calculated and obtained. Among them, Sj represents the standard deviation of the jth indicator. The larger the standard deviation, the greater the numerical difference of the indicator, and the higher the weight of the indicator.

8. The method for quantitatively evaluating carbon emissions during the highway construction stage applicable to multi-source solid waste paving according to claim 7, characterized in that, The method for obtaining the objective weights of each of the indicators in S40 is: where C j , Sj, and Wj are the information content, standard deviation, and objective weight of the j-th index respectively, m is the number of evaluation indices, j and k are the serial numbers of two groups of evaluation indices, j = 1, 2... m, k = 1, 2... m, and r jk is the correlation coefficient obtained through experiments for the j-th and k-th indices.

9. The carbon emission quantification and evaluation method applicable to the highway construction stage of multi-source solid waste paving according to claim 8, characterized in that, The method for obtaining the distance scores of the construction plans in S50 is: R ij = (W j b ij ) n×m , where R ij is the weighted normalization matrix, i represents the serial number of the sample, D i(lowest) and D i(best) are respectively the worst distance and the best distance of the i-th group under each factor, S pi is the distance score, and the larger the value of S pi , the better the sample scheme.

10. A carbon emission quantification and evaluation device for highway construction stages applicable to multi-source solid waste paving, characterized in that, It includes: The first module. Obtain the carbon emission coefficients of each of the materials in the production stage respectively according to the carbon emission coefficients of the set materials and the mixing ratio parameters; The second module calculates the carbon emission coefficients for transporting each material in S10 by combining vehicle parameters and temperature parameters with the COPERT model; The third module calculates the carbon emission coefficients for constructing each material in S10 based on the energy consumption of construction machinery and the carbon emission factors of energy during the construction stage; The fourth module establishes a carbon emission evaluation method for highway construction. By combining the parameters of the set indicators and calculating the standard deviation of the parameters, the objective weights of each indicator are obtained; The fifth module establishes a weighted standardization matrix for the highway construction plan by combining the objective weights of the indicators in S40. By calculating the distances of each plan to the ideal and anti-ideal solutions through the Euclidean distance, the distance scores of the construction plans are obtained.

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