A highway construction emission reduction optimization method and system based on principal component analysis

Abstract

The present invention discloses a highway construction emission reduction optimization method and system based on principal component analysis, which uses the principal component analysis method to analyze each carbon emission element in each segmented project to determine the comprehensive principal component factor of carbon emissions; based on the comprehensive principal component factor of carbon emissions, determine the comprehensive emission reduction performance index of each emission reduction plan; determine the optimal plan based on the comprehensive emission reduction performance index of each emission reduction plan. The present invention determines the comprehensive principal component factor of carbon emissions by analyzing the correlation of each carbon emission element based on the principal component analysis method, and calculates the comprehensive emission reduction performance index of each emission reduction plan on this basis, improving the accuracy of the calculation of the emission reduction performance index, and further improving the emission reduction effect of the emission reduction plan selected or optimized based on this comprehensive emission reduction performance index.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental protection, and particularly to a method and system for optimizing carbon emission reduction in highway construction based on principal component analysis. Background Art

[0002] Determining the main objects of emissions during the highway construction stage is very important for improving carbon reduction. However, due to the wide variety of materials, complex energy types, and complex generation scenarios required during the construction stage, it is necessary to evaluate the sources and magnitudes of their combined emission contributions and the significant differences in carbon emission levels to determine the key points of carbon reduction work from material and machinery use. Therefore, it is very difficult to identify emission hotspots during the highway construction stage and propose scientific carbon emission reduction measures. Researchers have proposed many methods for formulating emission hotspots, such as calculating the emissions of materials and machinery through the life cycle approach, determining emission hotspots through the Pareto law, and formulating corresponding carbon emission reduction measures. Although this method greatly reduces the carbon emissions of construction projects, it ignores the combined relationship between material emissions and machinery emissions, and the carbon emission reduction effect is affected. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for optimizing carbon emission reduction in highway construction based on principal component analysis to improve the carbon emission reduction effect.

[0004] To achieve the above object, the present invention provides the following solution:

[0005] The present invention provides a method for optimizing carbon emission reduction in highway construction based on principal component analysis, and the method includes the following steps:

[0006] Analyze each carbon emission factor in each section project by using the principal component analysis method to determine the comprehensive principal component factor of carbon emissions; the carbon emission factors include: consumption of crushed stones, consumption of steel bars, consumption of cement, consumption of asphalt, consumption of steel, consumption of iron parts, usage of air compressors, usage of rollers, and usage of bulldozers;

[0007] Based on the comprehensive principal component factor of carbon emissions, determine the comprehensive carbon emission reduction performance index of each carbon emission reduction plan;

[0008] Determine the optimal plan based on the comprehensive carbon emission reduction performance index of each carbon emission reduction plan.

[0009] Optionally, the step of analyzing each carbon emission factor in each section project by using the principal component analysis method to determine the comprehensive principal component factor of carbon emissions specifically includes:

[0010] Obtain the e section projects divided in highway construction and the values of f carbon emission factors in each section project to form a sample matrix;

[0011] Normalize each element in the sample matrix to obtain the normalized sample matrix;

[0012] Construct a correlation coefficient matrix based on the normalized sample matrix;

[0013] Sort the eigenvalues of the correlation coefficient matrix in descending order to obtain an eigenvalue sequence;

[0014] Calculate the comprehensive carbon emission factor corresponding to each eigenvalue according to the eigenvector corresponding to each eigenvalue in the eigenvalue sequence and the normalized sample matrix;

[0015] Let the value of p be 1;

[0016] Calculate the cumulative contribution rate of the first p eigenvalues in the eigenvalue sequence;

[0017] Judge whether the cumulative contribution rate of the first p eigenvalues is greater than the contribution rate threshold to obtain a judgment result;

[0018] If the judgment result is no, then increase the value of p by 1 and return to the step "Calculate the cumulative contribution rate of the first p eigenvalues in the eigenvalue sequence";

[0019] If the judgment result is yes, then select the comprehensive carbon emission factors corresponding to the first p eigenvalues as the comprehensive main component factors of carbon emissions.

[0020] Optionally, constructing a correlation coefficient matrix based on the normalized sample matrix specifically includes:

[0021] Based on the normalized sample matrix, use the formula Calculate the correlation coefficient between any two carbon emission factors;

[0022] where r ij is the correlation coefficient between the i-th carbon emission factor and the j-th carbon emission factor, is the normalized value of the i-th carbon emission factor of the k-th sectional project; is the average value of the normalized values of the i-th carbon emission factor of each sectional project, is the normalized value of the j-th carbon emission factor of the k-th sectional project; is the average value of the normalized values of the j-th carbon emission factor of each sectional project;

[0023] Based on the correlation coefficient between any two carbon emission factors, construct a correlation coefficient matrix as: R=(r ij ) f×f , where R is the correlation coefficient matrix.

[0024] Optionally, the formula for calculating the comprehensive carbon emission factor corresponding to each eigenvalue is:

[0025] y l = v 1l X1 + v 2l X2 + … + v fl X f , l = 1, 2…, f

[0026] Where y l is the comprehensive carbon emission factor corresponding to the l-th eigenvalue, v 1l , v 2l and v fl are the l-th elements in the first, second, and f-th eigenvectors of the correlation coefficient matrix respectively; X1, X2, and X f are the first, second, and f-th column vectors in the sample matrix after normalization processing.

[0027] Optionally, the formula for calculating the cumulative contribution rate of the first p eigenvalues in the eigenvalue sequence is:

[0028]

[0029]

[0030] Where b p is the cumulative contribution rate of the first p eigenvalues, a l is the information contribution rate of the l-th eigenvalue, λ l and λ m are the l-th and m-th eigenvalues respectively.

[0031] Optionally, the formula for determining the comprehensive emission reduction performance index of each emission reduction plan based on the comprehensive principal component factor of carbon emissions is:

[0032] K = b1y1 + b2y2 + … + b p y p

[0033] Where K is the comprehensive emission reduction performance index of the emission reduction plan, b1, b2, and b p are the cumulative contribution rates of the first 1, first 2, and first p eigenvalues respectively, y1, y2, and y p are the comprehensive carbon emission factors corresponding to the first, second, and p-th eigenvalues respectively, and their values are calculated based on the values of each carbon emission element in the emission reduction plan.

[0034] A highway construction emission reduction optimization system based on principal component analysis, the system is applied to the above method, and the system includes:

[0035] The principal component analysis module is used to analyze each carbon emission factor in each segmented project by using the principal component analysis method to determine the comprehensive principal component factor of carbon emissions; the carbon emission factors include: the consumption of crushed stones, the consumption of steel bars, the consumption of cement, the consumption of asphalt, the consumption of steel, the consumption of iron parts, the usage amount of air compressors, the usage amount of rollers, and the usage amount of bulldozers;

[0036] The comprehensive emission reduction performance index determination module is used to determine the comprehensive emission reduction performance index of each emission reduction plan based on the comprehensive principal component factor of carbon emissions;

[0037] The optimal plan determination module is used to determine the optimal plan based on the comprehensive emission reduction performance index of each emission reduction plan.

[0038] An electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above method is implemented.

[0039] A computer-readable storage medium stores a computer program, and when the computer program is executed, the above method is implemented.

[0040] According to the specific embodiments provided by the present invention, the following technical effects are disclosed by the present invention:

[0041] The present invention discloses a highway construction emission reduction optimization method and system based on principal component analysis. The principal component analysis method is used to analyze each carbon emission factor in each segmented project to determine the comprehensive principal component factor of carbon emissions; the carbon emission factors include: the consumption of crushed stones, the consumption of steel bars, the consumption of cement, the consumption of asphalt, the consumption of steel, the consumption of iron parts, the usage amount of air compressors, the usage amount of rollers, and the usage amount of bulldozers; based on the comprehensive principal component factor of carbon emissions, the comprehensive emission reduction performance index of each emission reduction plan is determined; the optimal plan is determined based on the comprehensive emission reduction performance index of each emission reduction plan. The present invention determines the comprehensive principal component factor of carbon emissions by analyzing the correlation of each carbon emission factor based on the principal component analysis method. On this basis, the comprehensive emission reduction performance index of each emission reduction plan is calculated, which improves the accuracy of the calculation of the emission reduction performance index, and further improves the emission reduction effect of the emission reduction plan selected or optimized based on the comprehensive emission reduction performance index. Description of the Drawings

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0043] Figure 1 Flow chart of a highway construction emission reduction optimization method based on principal component analysis provided by an embodiment of the present invention;

[0044] Figure 2 Schematic diagram of the highway construction emission reduction optimization method based on principal component analysis provided by an embodiment of the present invention. Detailed implementation manners

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] The purpose of the present invention is to provide a highway construction emission reduction optimization method and system based on principal component analysis to improve the emission reduction effect.

[0047] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.

[0048] As Figure 1 and Figure 2 shown, an embodiment of the present invention provides a highway construction emission reduction optimization method based on principal component analysis. The method includes the following steps:

[0049] Step 101: Analyze each carbon emission factor in each segmented project using the principal component analysis method to determine the comprehensive carbon emission principal component factor; the carbon emission factors include: consumption of crushed stones, consumption of steel bars, consumption of cement, consumption of asphalt, consumption of steel, consumption of iron parts, usage of air compressors, usage of rollers, and usage of bulldozers.

[0050] Step 102: Determine the comprehensive emission reduction performance index of each emission reduction plan based on the comprehensive carbon emission principal component factor.

[0051] Step 103: Determine the optimal plan based on the comprehensive emission reduction performance index of each emission reduction plan. An exemplary selection method for the carbon emission factors in step 101 is:

[0052] Determine each level of the highway construction project, and determine the carbon emission result of the target layer based on the carbon emission result of the base layer. Specifically:

[0053] S11: Divide each level of the highway construction project, and determine the target layer, the base layer, and the carbon emission factors of the base layer unit types;

[0054] S12 Determine the input of carbon emission factors for the basic layer unit types and the corresponding emission factors according to the carbon emission factors of the basic layer unit types.

[0055] S13 Determine the carbon emissions of the basic layer unit types according to the input of carbon emission factors for the basic layer unit types and the emission factors.

[0056] S14 Determine the carbon emissions of the unit types in the layer above the known layer according to the carbon emissions of the known layer unit types.

[0057] S15 Repeat step S14 until the carbon emissions of the target layer unit types are iterated.

[0058] S16 Determine the carbon emissions of the relevant factors at the target level according to the carbon emissions of the target layer unit types.

[0059] Taking a certain highway construction project as an example, in step S11, the highway construction project is divided into five levels: section works, unit works, sub - works, sub - items, and processes. It is determined that the first - level section works is the target layer, and the fifth - level process layer is the basic layer m.

[0060] In step S12, taking the manual excavation of rock - filled trenches unit and mechanical excavation of rock - filled trenches unit in the basic layer as examples, according to the "Highway Engineering Budget Quota" (JTG / T 3822 - 2018), it is confirmed that the unit - type emission factors include {hollow steel drill rods, ammonium nitrate explosives...}, and the corresponding input of emission factors is determined based on the highway engineering budget quota and construction account books. Determine the corresponding emission factors through the carbon emission factor library.

[0061] In step S13, the calculation formulas for each material in the manual excavation of rock - filled trenches unit and mechanical excavation of rock - filled trenches unit at the basic level are as follows:

[0062]

[0063]

[0064]

[0065]

[0066] In the formula: E is the carbon emissions, p is the input of carbon emission factors, g is the emission factor, t is the type (t1 is hollow steel drill rods, t2 is ammonium nitrate explosives), x is the unit at the basic level (x1 is manual excavation of rock - filled trenches, x2 is mechanical excavation of rock - filled trenches), y is the unit at the fourth level (y1 is excavation of trenches); m of the unit (x1 is manual excavation of rock - filled trenches, x2 is mechanical excavation of rock - filled trenches), y is the unit at the fourth level (y1 is excavation of trenches);

[0067] In the step S14, the carbon emissions at the fourth level are summed up in a bottom-up recursive manner, and can be obtained by recursively going up to the required level from the bottom. The carbon emissions calculation formula for the hollow steel drill rod in the trench excavation unit at the fourth level is as follows:

[0068]

[0069] In the formula: E is the carbon emissions, p is the input of carbon emission factors, g is the carbon emission factor, t is the type (t1 is the hollow steel drill rod, t2 is the ammonium nitrate explosive), x is the unit belonging to the basic level l m (x1 is the manual excavation of rock trenches, x2 is the mechanical excavation of rock trenches), y is the unit belonging to the fourth level (y1 is the trench excavation), z is the unit belonging to the third level (z3 is the drainage project);

[0070] In the step S15, repeat the step S14 to determine the carbon emissions of the unit types at the target level;

[0071] In the step S16, select {crushed stone, steel bars, cement, asphalt, steel, iron parts, air compressor, roller, excavator, bulldozer} as the relevant factors for analysis by combining a large number of experiments and research. Therefore, the consumption of crushed stone, the consumption of steel bars, the consumption of cement, the consumption of asphalt, the consumption of steel, the consumption of iron parts, the usage of air compressor, the usage of roller and the usage of bulldozer are used as the carbon emission factors.

[0072] In step 101, the principal component analysis method is used to analyze each carbon emission factor in each segmented project to determine the comprehensive principal component factors of carbon emissions, specifically including:

[0073] S21 constitutes a sample matrix X through e segmented projects and f carbon emission-related factors in the target layer:

[0074]

[0075] S22 performs the following mean value processing (i.e., normalization processing) on the samples:

[0076]

[0077] In S23, the normalized sample matrix obtained through step S22

[0078]

[0079] S24 calculates of the correlation coefficient matrix R:

[0080] R=(r ij ) f×f

[0081]

[0082] S25 Calculate the eigenvalues of the correlation coefficient matrix R and sort them from largest to smallest as λ1, λ2... λ f , and the corresponding eigenvectors v1, v2... v f :

[0083] v1 = [v 11 , v 12 ... v 1f T , v2 = [v 21 , v 22 ... v 2f T ... v f = [v f1 , v f2 ... v ff T

[0084] S26 Calculate the comprehensive carbon emission factor y:

[0085]

[0086] S27 Calculate the information contribution rate formula of the eigenvalue λ i is:

[0087]

[0088] S28 Calculate the cumulative contribution rate formula of the eigenvalue λ i is:

[0089]

[0090] S29 When b p > 95%, select the first p comprehensive carbon emission factors y1, y2... y p to replace the original f comprehensive carbon emission factors as the comprehensive main component factors of carbon emissions;

[0091] Step 102 is specifically:

[0092] Calculate the comprehensive emission reduction performance index for each emission reduction plan and conduct comprehensive evaluation respectively:

[0093] k = b1y1 + b2y2 +... b p y p

[0094] The determination of the optimal solution of the present invention can also be based on the following steps to specifically optimize the existing emission reduction plans, specifically:

[0095] ​​​S31 Determine the emission reduction plan that optimally matches the comprehensive materials and machinery based on the contribution rate of the comprehensive carbon emission factors;

[0096] S32 Mine the key engineering projects with great emission reduction potential in the highway construction project based on the comprehensive emission reduction performance index.

[0097] Taking this highway construction project as an example, divide the data obtained in steps S11 - S16 into 14 segments through project documents, etc.;

[0098] In step S21, a sample matrix X is formed by the 14 segment projects and 10 related factors of the obtained target level;

[0099] In steps S22 and S23, by performing mean value processing on the samples, a new sample matrix X is obtained, and the processing results are shown in Table 1;

[0100] Table 1 Data table after standardization processing

[0101] -0.555 -0.839 -0.289 -0.571 -0.598 -0.491 -0.461 -0.863 -0.528 -0.557 -0.324 0.086 -0.261 -0.569 -0.585 -0.489 -0.284 -0.341 -0.424 -1.351 -0.540 -0.814 -0.283 -0.573 -0.586 -0.491 -0.143 -0.824 -0.482 -0.272 -0.446 0.118 -0.291 -0.568 -0.672 -0.490 -1.168 -0.561 -0.610 -0.605 -0.689 -0.165 -0.321 -0.523 -0.665 -0.490 -1.051 -0.368 -0.607 -0.368 -0.655 -0.887 -0.284 0.256 -0.667 -0.489 0.938 -0.447 -0.632 -0.283 3.109 2.842 3.473 2.976 2.777 -0.469 1.633 2.880 3.007 -1.795 0.409 -0.167 -0.256 0.796 0.344 -0.479 -0.685 0.799 0.868 0.969 0.413 0.002 -0.246 0.383 0.418 -0.476 -0.097 0.239 0.344 1.313 0.598 0.168 -0.251 0.662 0.746 -0.473 -0.899 0.798 0.695 0.732 -0.340 -0.534 -0.256 -0.567 -0.501 0.569 0.799 -0.625 -0.374 1.053 0.110 1.316 -0.199 -0.563 1.091 3.105 1.152 0.420 -0.166 0.305 -0.317 -0.485 -0.244 -0.571 -0.475 0.668 1.434 -0.547 -0.482 -0.624 -0.775 -0.643 -0.291 -0.568 -0.627 0.496 -1.168 -0.561 -0.610 1.484

[0102] In step S24, calculate the correlation coefficient matrix R of the data, and the processing results are shown in Table 2;

[0103] Table 2 Correlation coefficient matrix table

[0104]

[0105]

[0106] In step S25, calculate the eigenvectors λ1, λ2... λ of the correlation coefficient matrix R f Sort them from largest to smallest, and the corresponding eigenvectors v1, v2... v f , and the processing results are shown in Table 3;

[0107] Table 3 Eigenvalues and corresponding contribution rates, cumulative contribution rates table

[0108] Eigenvalue Contribution rate % Cumulative contribution rate % 6.6803 66.8030 66.8030 1.5000 14.9997 81.8026 1.1260 11.2599 93.0626 0.4870 4.8701 97.9326 0.1080 1.0799 99.0125 0.0441 0.4410 99.4535 0.0339 0.3392 99.7927 0.0168 0.1685 99.9612 0.0027 0.0272 99.9884

[0109] In step S26, calculate the comprehensive carbon emission factor y;

[0110] In steps S27 and S28, calculate the eigenvalues λ1, λ2... λ f The corresponding information contribution rates a1, a2... a f And the cumulative contribution rate b p , and the processing results are shown in Table 3;

[0111] In step S29, when b pWhen >95%, the first three carbon emission principal component factors y1, y2, and y3 are selected to replace the original carbon emission comprehensive variable;

[0112] y1=0.3823X1-0.0490X2+0.0746X3+0.0361X4-0.0442X5+-0.5050X6-0.0981X7+0.1028X8+0.5115X9-0.5529X 10

[0113] y2=0.3507X1+0.1692X2-0.0195X3-0.4898X4+0.0366X5-0.1730X6+0.6954X7+0.0632X8+0.0605X9+0.2923X 10

[0114] y3=0.3607X1-0.0617X2-0.1948X3+0.0221X4+0.8656X5+0.1057X6-0.1055X7-0.0698X8-0.1967X9-0.1119X 10

[0115] In step S10, a comprehensive evaluation k=6.6803y1+1.500y2+1.1260y3 is performed on each segmented project, and the comprehensive evaluation ranking is shown in Table 4.

[0116] Table 4 Comprehensive evaluation value table

[0117]

[0118] In the present example, step S3 includes the following sub-steps:

[0119] S31 Determine the optimal comprehensive emission reduction plan based on the main component factors of carbon emissions;

[0120] S32 explores engineering projects with greater emission reduction potential among highway construction projects based on the comprehensive emission reduction performance index.

[0121] Taking the highway construction project as an example, in step S31, based on the main component factors of carbon emissions in step S29, three effective comprehensive emission reduction schemes can be obtained: Scheme 1 reduces the emissions of crushed stone, iron parts, excavators, and bulldozers, accounting for 66.80% of the total emission contribution rate; Scheme 2 reduces the emissions of asphalt, air compressors, road rollers, and bulldozers, accounting for 15.00% of the total emission contribution rate, and the two aspects contribute 81.80% to carbon emissions in total; Scheme 3 reduces the emissions of crushed stone, cement, excavators, and bulldozers, accounting for 11.26% of the total emissions, and the three items cumulatively account for 93.06% of the total emissions; among them, Scheme 1 has the best comprehensive emission reduction effect;

[0122] In step S32, based on the comprehensive evaluation ranking in step S210, the emission reduction potential of the 7th segment is the largest, followed by the 12th segment. Therefore, these two segments are the key objects for emission reduction during the construction stage of this highway.

[0123] The present invention uses the principal component analysis method to standardize the data, avoiding the influence of different dimensions on the data. An integrated emission reduction plan is proposed through the main component factors of carbon emissions, breaking the boundaries between various factors, considering the connections between various factors, and narrowing the scope of carbon emission factors. And through principal component analysis, the complex original data is concentrated into each principal component, and the main links are determined by comprehensive evaluation, which helps to find the key path for emission reduction from the source in highway construction activities.

[0124] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts among the various embodiments can be referred to each other. For the system disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description in the method section.

[0125] Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those of ordinary skill in the art, there will be changes in the specific implementation manner and application scope according to the idea of the present invention. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. An emission reduction optimization method for highway construction based on principal component analysis, characterized in that, The method includes the following steps: Use the principal component analysis method to analyze each carbon emission factor in each segmented project to determine the comprehensive principal component factor of carbon emissions; the carbon emission factors include: the consumption of crushed stones, the consumption of steel bars, the consumption of cement, the consumption of asphalt, the consumption of steel, the consumption of iron parts, the usage of air compressors, the usage of rollers, and the usage of bulldozers; Based on the comprehensive principal component factor of carbon emissions, determine the comprehensive emission reduction performance index of each emission reduction plan; Determine the optimal plan based on the comprehensive emission reduction performance index of each emission reduction plan; The selection method of carbon emission factors is as follows: Determine each level of the highway construction project, and determine the carbon emission results of the target level according to the carbon emission results of the basic level. Specifically: S11 Divide each level of the highway construction project, and determine the target level, the basic level, and the carbon emission factors of the basic level unit types; S12 According to the carbon emission factors of the basic level unit types, determine the input of the carbon emission factors of the basic level unit types and the corresponding emission factors; S13 According to the input of the carbon emission factors of the basic level unit types and the emission factors, determine the carbon emissions of the basic level unit types; S14 According to the known carbon emissions of the unit types of the known layer, determine the carbon emissions of the unit types of the upper layer of the known layer; S15 Repeat step S14 until the carbon emissions of the unit types of the target level are iterated; S16 According to the carbon emissions of the unit types of the target level, determine the carbon emissions of the relevant factors of the target level; In step S11, the highway construction project is divided into 5 levels: segmented project, unit project, sub - project, sub - item project, and process. Determine the first - level segmented project as the target level and the fifth - level process layer as the basic level m; In the step S12, for the manually excavated rock trench unit and the mechanically excavated rock trench unit in the base layer, confirm that the unit type emission factors include hollow steel drills and ammonium nitrate explosives, and determine the corresponding input of emission factors based on the highway engineering budget quota and the construction account Determine the corresponding emission factors through the carbon emission factor library In step S13, the calculation formulas for each material in the manual excavation of rock - filled trenches unit and the mechanical excavation of rock - filled trenches unit of the basic level are: Wherein, E is the carbon emission; p is the input of carbon emission factors; g is the carbon emission factor; t is the type, where t1 is a hollow steel drill rod and t2 is ammonium nitrate explosive; x is the unit belonging to the basic level l m where x1 is the manual excavation of rock trench and x2 is the mechanical excavation of rock trench; y is the unit belonging to the 4th level, where y1 is the excavation of trench; In step S14, the carbon emissions of the 4th level are summed up in a bottom - up recursive manner. The carbon emissions of the hollow steel drill in the excavation trench unit of the 4th level can be obtained by recursively summing up to the required layer. The calculation formula is: In the formula, z is the unit of the 3rd level, where z3 is the drainage project; In step S15, repeat step S14 until the carbon emissions of the unit types of the target level are determined; In step S16, select crushed stones, steel bars, cement, asphalt, steel, iron parts, air compressors, rollers, excavators, and bulldozers as relevant factors for analysis; take the consumption of crushed stones, the consumption of steel bars, the consumption of cement, the consumption of asphalt, the consumption of steel, the consumption of iron parts, the usage of air compressors, the usage of rollers, and the usage of bulldozers as carbon emission factors; Use the principal component analysis method to analyze each carbon emission factor in each segmented project to determine the comprehensive principal component factor of carbon emissions. Specifically include: S21 Through e segmented projects and f carbon emission factors in the target level, construct a sample matrix X: S22 Perform the following mean - value processing on the sample, that is, normalization processing: In S23, the normalized sample matrix obtained through step S22 S24 calculation for the correlation coefficient matrix R: R＝(r ij ) f×f where r ij is the correlation coefficient between the i-th carbon emission factor and the j-th carbon emission factor, is the normalized value of the i-th carbon emission factor of the k-th sectional project; is the average value of the normalized values of the i-th carbon emission factor of each sectional project, is the normalized value of the j-th carbon emission factor of the k-th sectional project; is the average value of the normalized values of the j-th carbon emission factor of each sectional project; S25 Calculate the eigenvalues of the correlation coefficient matrix R and sort them from largest to smallest as λ1, λ2... λ f , and the corresponding eigenvectors v1, v2... v f : v1 = [v 11 , v 12 ... v 1f T , v2 = [v 21 , v 22 ... v 2f T ... v f = [v f1 , v f2 ... v ff T ​​​ S26 Calculate the comprehensive carbon emission factor y: The formula for calculating the comprehensive carbon emission factor corresponding to each eigenvalue is: y l = v 1l X1 + v 2l X2 + … + v fl X f , l = 1, 2…, f Among them, y l is the comprehensive carbon emission factor corresponding to the l-th eigenvalue, and v 1l , v 2l and v fl are the l-th elements in the 1st, 2nd, and f-th eigenvectors of the correlation coefficient matrix respectively; X1, X2, and X f are the 1st, 2nd, and f-th column vectors in the sample matrix after normalization respectively; S27 Calculate the eigenvalue λ i The information contribution rate formula is as follows: S28 Calculate the eigenvalue λ i The cumulative contribution rate formula is as follows: Among them, b p is the cumulative contribution rate of the first p eigenvalues, and a l is the information contribution rate of the l-th eigenvalue, λ l and λ m are the l-th and m-th eigenvalues respectively; S29 When b p > 95%, select the first p carbon emission comprehensive factors y1, y2... y p to replace the original f carbon emission comprehensive factors as the main carbon emission comprehensive component factors; Calculate the comprehensive emission reduction performance index for each emission reduction plan and conduct comprehensive evaluations respectively: k = b1y1 + b2y2 +...b p y p Among them, k is the comprehensive emission reduction performance index of the emission reduction plan, and b1, b2, and b p are the cumulative contribution rates of the first 1, the first 2, and the first p eigenvalues respectively, and y1, y2, and y p are the comprehensive carbon emission factors corresponding to the first 1, the first 2, and the first p eigenvalues respectively, and their values are calculated based on the values of each carbon emission element in the emission reduction plan.

2. An emission reduction optimization system for highway construction based on principal component analysis, characterized in that, The system is applied to the method described in claim 1, and the system includes: A principal component analysis module, which is used to analyze each carbon emission factor in each segmented project by using the principal component analysis method to determine the comprehensive principal component factor of carbon emissions; the carbon emission factors include: the consumption of gravel, the consumption of steel bars, the consumption of cement, the consumption of asphalt, the consumption of steel, the consumption of iron parts, the usage amount of air compressors, the usage amount of rollers, and the usage amount of bulldozers; A comprehensive emission reduction performance index determination module, which is used to determine the comprehensive emission reduction performance index of each emission reduction plan based on the comprehensive principal component factor of carbon emissions; An optimal plan determination module, which is used to determine the optimal plan based on the comprehensive emission reduction performance index of each emission reduction plan.

3. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and operable on the processor. When the processor executes the computer program, the method described in claim 1 is implemented.

4. A computer-readable storage medium, characterized in that, A computer program is stored thereon, and when the computer program is executed, the method described in claim 1 is implemented.

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