A method for evaluating ecological impact of shield muck based on hakanson-lca

Abstract

The application discloses a kind of based on Hakanson-LCA's shield slag ecological influence assessment method, it is related to shield slag ecological influence assessment field, the Hakanson ecological risk assessment method is combined with LCA method in the present application, the potential ecological risk of heavy metal element in shield slag is evaluated simultaneously, and carbon emission influence generated in the process of resource utilization and landfill disposal, by the double evaluation method, it can be comprehensive analyzed from two dimensions of environmental pollution and climate change to slag, provide more comprehensive ecological influence assessment, provide scientific basis for environmental protection and waste management.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ecological impact assessment of shield muck, and particularly to a method for ecological impact assessment of shield muck based on Hakanson-LCA. BACKGROUND

[0002] Shield muck is a kind of soil waste generated during the construction of urban underground projects using the shield method. It mainly includes mud, sand and other geotechnical materials. These mucks usually have high humidity and may contain various harmful components such as heavy metals, chemicals, oil stains, etc. due to their origin from underground environments. The source of shield muck is complex, and its physical and chemical properties vary greatly, influenced by factors such as construction site, soil depth, and geological environment. Therefore, the management and treatment of shield muck is an issue that cannot be ignored in urban infrastructure construction, especially considering its potential impact on the environment and ecological system during the treatment process.

[0003] Currently, the ecological impact assessment methods for shield muck have not been fully researched and applied. Although some technical means have been used to analyze the pollution level of muck, most methods only focus on the detection of pollutants and do not comprehensively assess their long-term impact on soil, groundwater, air and other ecological systems. In addition, the existing assessment system lacks quantitative analysis of the ecological risk of muck and lacks effective comprehensive assessment tools for ecological impact, resulting in the management and treatment measures of shield muck often being limited to simple pollution removal or landfill, which cannot fully consider the potential harm to the environment. Therefore, there is an urgent need for a more systematic and comprehensive ecological impact assessment method for shield muck to better manage the environment and make decisions. SUMMARY

[0004] To solve the problems in the prior art, the present application aims to provide a method for ecological impact assessment of shield muck, aiming to solve the lack of effective means for comprehensive assessment of ecological risk of shield muck in the prior art, especially the lack of comprehensive risk analysis methods for potential pollution elements in muck and resource utilization process. By considering the pollution risk and carbon emission risk of muck, the present application can provide more scientific and systematic guidance for the management and treatment of shield muck, reducing the potential harm of muck treatment to the ecological environment.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present application is as follows:

[0006] A method for ecological impact assessment of shield muck based on Hakanson-LCA, comprising the following steps:

[0007] S1. Collect soil samples through soil monitoring points arranged at the shield muck site; respectively determine the pollution of the soil samples to obtain the concentration of pollution elements in the soil samples;

[0008] S2. Based on the Hakanson method, the average content value and the toxicity coefficient of the pollution element are set for each pollution element, the single pollution coefficient of the corresponding pollution element is calculated by combining the pollution element concentration with the pollution element average content value, the potential ecological risk coefficient of the corresponding pollution element is calculated by combining the single pollution coefficient with the toxicity coefficient, and the potential ecological risk index of the region is calculated according to the potential ecological risk coefficients of all pollution elements; the calculated potential ecological risk index is graded and scored, and the ecological pollution score is calculated by grading and scoring;

[0009] S3. Based on the LCA method, the carbon emissions of resource utilization and the carbon emissions of landfill disposal are calculated respectively, and the carbon emission risk score is obtained by calculating the relative difference between the landfill disposal carbon emission and the resource carbon emission;

[0010] S4. According to the ecological pollution score index and the carbon emission risk score, the ecological comprehensive influence index of shield slag soil is obtained by weighted calculation, and the ecological influence of shield slag soil is evaluated according to the ecological comprehensive influence index of shield slag soil.

[0011] Specifically, the shield slag soil ecological impact evaluation method based on Hakanson-LCA combines the ecological risk assessment of Hakanson method and the carbon emission analysis of LCA method, and comprehensively considers the environmental impact of soil pollution and carbon emission through systematic quantitative evaluation. The implementation process of the method includes collecting slag soil samples by laying soil monitoring points, determining the pollution elements, calculating the single pollution coefficient and the potential ecological risk coefficient of the pollution elements combined with the Hakanson model, and finally evaluating the ecological pollution level. At the same time, the carbon emissions of shield slag soil in the process of resource utilization and landfill disposal are evaluated by LCA method, and the comprehensive ecological impact index of shield slag soil is obtained by weighted calculation combined with the carbon emission risk score and the ecological pollution score. The method combines heavy metal pollution risk and carbon emission risk to form a multi-dimensional environmental impact evaluation system, which can not only comprehensively reflect the ecological impact of shield slag soil, but also provide quantitative support for different treatment methods (such as resource utilization and landfill). Through the evaluation method, the ecological impact of shield slag soil can be scientifically and accurately evaluated, which helps to optimize waste management strategies, improve resource recycling efficiency, and provide quantitative data support for environmental protection policies.

[0012] The beneficial effects of the present application are:

[0013] The Hakanson ecological risk assessment method and the LCA method are combined in the application, potential ecological risks of heavy metal elements in shield slurry and carbon emission influences in resource utilization and landfill disposal processes can be evaluated simultaneously.

[0014] The application can determine carbon emission differences of different processing methods by detailed calculation of carbon emissions of resource utilization and landfill disposal, and further calculate carbon emission risk scores, thereby providing quantitative basis for disposal decisions of shield slurry; and ecological pollution scores and carbon emission risk scores are calculated by weighting, and an ecological comprehensive influence index of shield slurry is generated, which can quantitatively compare environmental influences of different slurry processing schemes. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 A method flowchart of a shield slurry ecological influence evaluation method based on Hakanson-LCA is provided for the embodiment of the application.

[0016] Figure 2 A data schematic diagram of average contents of heavy metal elements in typical geology is provided for the embodiment of the application.

[0017] Figure 3 A data schematic diagram of toxicity corresponding coefficients is provided for the embodiment of the application.

[0018] Figure 4 A pollution grading schematic diagram is provided for the embodiment of the application. DETAILED DESCRIPTION

[0019] The embodiments of the application will be described in detail below with reference to the accompanying drawings.

[0020] Embodiment one

[0021] A shield slurry ecological influence evaluation method based on Hakanson-LCA, like Figure 1 , comprises the following steps:

[0022] S1. Collect soil samples through soil monitoring points arranged in a shield slurry site; respectively determine the pollution of the soil samples to obtain the concentration of pollution elements in the soil samples;

[0023] S2. Based on the Hakanson method, the average content value and the toxicity coefficient of the pollution elements are set respectively, the single pollution coefficient of the corresponding pollution element is calculated by combining the pollution element concentration with the pollution element average content value, the potential ecological risk coefficient of the corresponding pollution element is calculated by combining the single pollution coefficient with the toxicity coefficient, the potential ecological risk index of the region is calculated according to the potential ecological risk coefficients of all pollution elements; the calculated potential ecological risk index is graded and scored, and the ecological pollution score is calculated by grading and scoring;

[0024] S3. Based on the LCA method, the carbon emissions of resource utilization and landfill disposal are calculated respectively, and the carbon emission risk score is obtained by calculating the relative difference between the landfill disposal carbon emission and the resource carbon emission;

[0025] S4. According to the ecological pollution score index and the carbon emission risk score, the ecological comprehensive influence index of shield spoil is obtained by weighted calculation, and the ecological influence of shield spoil is evaluated according to the ecological comprehensive influence index of shield spoil.

[0026] Specifically, the above embodiment realizes the comprehensive quantitative evaluation effect of the ecological influence of shield spoil by laying out soil monitoring points, measuring the concentration of pollution elements, calculating the single pollution coefficient and the potential ecological risk coefficient based on the Hakanson method, and evaluating the carbon emission based on the LCA method, and finally calculating the ecological comprehensive influence index by weighting. The core principle of this evaluation method is to couple the Hakanson ecological risk index method and the life cycle assessment (LCA) model to establish a multi-dimensional environmental performance evaluation system. The Hakanson method is based on the biological toxicity response mechanism of pollution elements, and realizes the quantitative characterization of heavy metal pollution risk by constructing a ternary calculation model of "concentration-background value-toxicity coefficient"; the LCA method adopts the principle of "from cradle to grave" system boundary, and carries out inventory analysis on the whole process carbon emission of resource utilization and landfill disposal. The cooperative application of the two methods not only considers the ecological toxicity effect of heavy metal pollution, but also takes into account the climate change influence of carbon emission, forming a comprehensive environmental decision support tool.

[0027] In terms of technical parameter selection, the selection of pollution elements is based on the following standards: 1) Typical associated pollutants in shield construction process (such as Pb from lubricant, Zn from plated material); 2) Having clear toxicological data and environmental standard limit value (such as carcinogenicity of Cd, neurotoxicity of Hg); 3) Having stable migration and transformation characteristics in regional environmental medium. The selection of carbon emission factors follows the "Provincial Greenhouse Gas Inventory Compilation Guide", and is dynamically adjusted combined with the proportion of clean energy in local power grid, to ensure the spatial and temporal representativeness of the data.

[0028] Further, in the step S1, the soil monitoring point arrangement method is: arranging the sampling points in a radial manner with the shielded landfill as the center, and the sampling point density decreases along the gradient from the area close to the landfill to the area far from the landfill. Specifically, the above embodiment arranges the sampling points in a radial gradient manner with the landfill as the center, and the density is close in the near and sparse in the far, so as to ensure the spatial representativeness of the sampling data and the accurate capture effect of the pollution distribution characteristics. The embodiment adopts the radial gradient point arrangement method, and the scientific basis lies in that the pollutant diffusion usually presents a distance attenuation law. In specific implementation: an polar coordinate system is established with the landfill as the center; the sampling density is set according to the logarithmic law (for example, one point every 10 m within 50 m, and one point every 20 m within 50-100 m); and the point arrangement direction is adjusted considering the dominant wind direction and hydrogeological conditions. Exemplarily, the grid method can be used for point arrangement, or the Kriging method of geostatistics can be used for point arrangement. The advantage of the design lies in that the pollution gradient characteristics are captured with the minimum sampling amount.

[0029] Further, the pollution elements in the soil sample at least include arsenic element, cadmium element, chromium element, copper element, mercury element, nickel element, lead element and zinc element. Specifically, the eight heavy metals selected in the above embodiment are typical representatives: covering the priority control pollutants (such as Cd and Hg listed in the USEPA list); containing elements with different valence states (such as Cr³⁺ / Cr 6 ⁺); and taking into account the biological essential elements (Cu, Zn) and the highly toxic elements (As, Hg). Preferably, characteristic elements such as Se and Sb can be added, or the characteristic elements can be adjusted according to the local industrial characteristics (such as increasing the measurement of Sn in the electronic waste area), and the selection is mainly based on the Soil Environmental Quality Standard for Construction Land Risk Control (GB36600-2018).

[0030] Further, in the step S2, the potential ecological risk coefficient calculated is classified and scored, and the calculation of the ecological pollution score through the classification and scoring includes the following sub-steps:

[0031] S201. The potential ecological risk index is divided into four continuous pollution threshold intervals, which correspond to low risk, medium risk, higher risk and high risk levels in turn;

[0032] S202. An independent segmented calculation function is configured for each pollution threshold interval, and the function form is a linear proportional relationship;

[0033] S203. The calculated potential ecological risk coefficient is corresponded to the belonging pollution threshold interval, and the ecological pollution score of the potential ecological risk coefficient is calculated according to the function corresponding to the belonging pollution threshold interval, and the maximum value of the ecological pollution score is 100.

[0034] Further, in the step S202, the linear proportional relationship is specifically:

[0035] The function corresponding to the first pollution threshold interval: based on the proportion of the ecological risk index to the upper limit of the interval;

[0036] The function corresponding to the second and fourth pollution threshold interval: based on the proportion of the part of the ecological risk index exceeding the threshold of the previous interval to the span of the current interval, and the maximum score of the previous interval is accumulated.

[0037] Wherein, the above embodiment can be replaced by using logarithmic conversion or Sigmoid function, but since the linear model is easier to explain, this embodiment is the preferred embodiment. In addition, the threshold interval can be adjusted by ± 20% according to the regional background value, and set according to the actual situation of the technician.

[0038] Further, in the step S3, the carbon emissions of resource utilization include the carbon emissions of energy consumption of shield slag soil treatment and the carbon emissions in the production process of added materials, and the value of carbon emissions of resource utilization is obtained by adding the carbon emissions of energy consumption of shield slag soil treatment and the carbon emissions in the production process of added materials.

[0039] Further, the carbon emissions of energy consumption of shield slag soil treatment are calculated by the product relationship of energy consumption intensity factor and energy carbon emission coefficient, and linear amplification of treatment scale parameter; the carbon emissions in the production process of added materials are calculated by tensor product of material mass balance equation and material life cycle emission factor. Wherein, the energy consumption intensity factor is monitored and collected by monitoring the energy consumption per unit volume (m³) of the treatment equipment through the installation of electric energy meter, fuel flow meter, etc.; the energy carbon emission coefficient is determined by the provincial power grid emission factor for electricity, and the diesel / gasoline refers to IPCC. The treatment scale parameter is obtained by calculating the number of slag soil transport vehicles and volume in the construction log or by inverse calculation of slag soil volume through laser scanning or photogrammetry technology. The material mass is obtained by calculating the mass of curing agent, aggregate and other materials added in the resource utilization process or by calculating according to the mixed design ratio. The material emission factor is obtained from the China life cycle database.

[0040] Further, in the step S3, the carbon emissions of landfill disposal include the carbon emissions in the process of slag soil transportation and the carbon emissions of landfill construction machinery operation, and the value of carbon emissions of resource utilization is obtained by adding the carbon emissions in the process of slag soil transportation and the carbon emissions of landfill construction machinery operation.

[0041] Furthermore, the carbon emissions during the transportation of construction waste are calculated by convolving the mass-distance function with the transportation modal emission factor and adjusting the actual transportation efficiency using an empty-load adjustment coefficient. The carbon emissions from the operation of landfill construction machinery are calculated by mapping the machinery shift matrix with the Hadamard product of energy consumption density and combining it with an energy conversion factor. Specifically, the mass-distance function is represented as M×Dᵢ, where M represents the mass of the construction waste, obtained by weighing and recording the total mass of the transport vehicles, and Dᵢ represents the transport distance, obtained through GPS trajectory analysis. The transportation modal emission factor is calibrated according to vehicle type; specifically, for heavy-duty diesel vehicles, the measured values ​​in the "Limits for Fuel Consumption of Road Transport Vehicles" are used, and for new energy vehicles, the "Guidelines for Carbon Emission Accounting of New Energy Vehicles in China" are referenced. The empty-load adjustment coefficient is obtained by recording the empty-load rate through the transportation dispatch system. The machinery shift matrix is ​​established by recording the actual number of operating shifts of equipment such as excavators and compactors or by automatically collecting operating time through onboard sensors. The energy density is determined by reading the real-time fuel consumption rate (L / h) or electricity consumption (kWh / h) of the mechanical control system, or other rated standards. The energy conversion factor is determined by adjusting the proportion of clean energy in the power grid on a monthly basis, based on the measured carbon oxidation rate or electricity factor for non-standard fuels (such as biodiesel).

[0042] Furthermore, in step S4, the comprehensive ecological impact index of tunnel boring machine slag is obtained by weighted calculation based on the ecological pollution scoring index and the carbon emission risk score. Specifically, the greenhouse effect coefficient is used as the weighting term of the ecological pollution scoring index, and the heavy metal pollution coefficient is used as the weighting term of the carbon emission risk score for weighted summation.

[0043] Example 2

[0044] As a preferred embodiment of the above embodiments, an application scenario is proposed, in which the method described in Embodiment 1 is used to assess the ecological impact of construction waste. The specific implementation process is as follows:

[0045] Based on the site conditions, soil monitoring points were arranged radially outwards from the landfill, with denser sampling points closer to the landfill and sparser sampling points further away, for a total of N sampling points. Soil samples with a radius of r (cm) and a depth of h (cm) were excavated from each sampling point, placed in a sealed container, and sent to the laboratory for testing. Sample pretreatment and analysis were performed in accordance with the "Technical Regulations for Sample Analysis and Testing in the National Soil Pollution Status Survey".

[0046] Measured separately k Heavy metal elements Hm 1. Hm 2... Hm k Measured concentration C i (mg / kg), 1≤i ≤ k . According to Figure 2 the background value provided in the background , the single pollution coefficient of the metal element i is calculated , that is:

[0047] ;

[0048] According to Figure 3 the toxicity coefficient provided in the background , the potential ecological risk coefficient of the heavy metal element i is calculated , that is:

[0049] ;

[0050] After the potential ecological risk coefficient of the heavy metal element k is calculated, the potential ecological risk index of the region can be calculated RI, Then, according to the data in Figure 4 (the risk level defined in the embodiment is 4, and the preferred risk level in Figure 4 is 5, and the skilled person can define it according to the actual situation), the pollution degree is determined, that is:

[0051] ;

[0052] According to the value of RI , the ecological pollution score P 1 is calculated, and the specific calculation method is as follows:

[0053] ;

[0054] After the ecological pollution score P 1 is obtained, the carbon emission amount of shield sludge landfill disposal and resource utilization disposal is calculated to obtain the carbon emission risk score P 2.

[0055] Resource utilization carbon emission calculation:

[0056] ;

[0057] Among them, is the resource utilization carbon emission amount, kgCO 2e ; is the energy consumption of processing 1m 3 of shield sludge in the resource utilization process, kW·h; is the carbon emission factor of energy, kgCO2 / kW·h, kgCO2 / kg; V is the volume of shield sludge, m 3; M r For the first r The mass of the additive material, in tons; For the first r The carbon emission factor of the additive material is kgCO2 / t (considering only the process of strengthening, improving and modifying slag into usable raw materials). For example, when the energy type is diesel (L), the corresponding carbon emission factor is 3.096 kgCO2 / kg; when the energy type is gasoline (L), the corresponding carbon emission factor is 2.925 kgCO2 / kg; and when the energy type is electricity (kWh), the corresponding carbon emission factor is 0.896-0.804 kgCO2 / kWh.

[0058] Carbon emissions calculation for landfill disposal:

[0059] ;

[0060] in, For carbon emissions from landfill disposal, kgCO 2e ; The mass of the tunnel boring machine excavation soil, in tons; The first method for using tunnel boring machine excavation soil r The average transport distance for this mode of transportation, in km; For the first r Carbon emission factor per unit weight of transport distance under this mode of transportation, kgCO 2e / (t·km), for example, when heavy-duty diesel truck transportation (18t) is selected, the corresponding carbon emission factor is 0.129kgCO. 2e / (t·km); f This is the empty vehicle turnaround coefficient; For the first i Consumption of various construction machinery shifts; For the first i Energy consumption per unit shift of construction machinery (kWh / shift, kg / shift).

[0061] This yields a carbon emission risk score. P 2:

[0062] ;

[0063] Comprehensive Ecological Impact Index of Tunnel Boring Waste P for:

[0064] ;

[0065] in, w 1 represents the heavy metal pollution coefficient. w 1. Greenhouse effect coefficient.

[0066] Example 3

[0067] As a preferred embodiment of the above examples, the traditional Hakanson method calculates the potential ecological risk for each heavy metal individually. However, heavy metals in tunnel boring machine (TBM) slag often coexist, exhibit synergistic, and significant cumulative effects, which may lead to linear superposition of single elements failing to accurately reflect the true ecological risk level. Therefore, a multi-metal synergistic cumulative effect index is introduced to construct a nonlinear composite potential ecological risk model. Specifically, this includes the following steps:

[0068] Calculate the potential risk coefficient for each metal. :

[0069] Define the Synergistic Cumulative Index (MSAI):

[0070] ;

[0071] Among them, the The MSAI represents the synergistic accumulation index. A higher MSAI indicates a more severe degree of multi-metal contamination and synergistic pollution in the tunnel boring machine excavation. n represents the total number of polluting elements. This represents the element risk sensitivity coefficient, used to describe the response sensitivity of a metal element in the context of multi-metal synergistic pollution.

[0072] Assign a co-weighting factor to each metal element:

[0073] ;

[0074] Among them, the This represents the adjustment factor, ranging from 1.0 to 2.0, used to control the sensitivity of the weight distribution.

[0075] The final nonlinear potential ecological risk index is calculated using the potential risk coefficient and the synergistic weighting factor.

[0076] ;

[0077] Among them, the This represents a nonlinear potential ecological risk index, the... This represents the nonlinear cumulative index, set between 1.2 and 2.0, determined according to the degree of synergistic effect. For example, if the synergistic effect of polluting elements is significantly aggravated, a higher value (such as 1.5–2.0) is taken; if the effect of polluting elements is weak, a lower value is taken.

[0078] based on The calculated potential ecological risk coefficients are graded and scored in conjunction with the scheme in Example 1, and the ecological pollution score is calculated through the graded scoring.

[0079] The MSAI synergistic cumulative index introduced by the above-mentioned embodiment can comprehensively consider the synergistic effect of multiple metal elements, that is, the risk brought by the joint action of different metal elements is much higher than that of a single metal, and more accurately reflects the ecological harm of a complex pollution system.

[0080] Embodiment four

[0081] As a preferred specific embodiment of the above-mentioned embodiment, a system applying a shield slurry ecological impact assessment method based on Hakanson-LCA is proposed, which comprehensively assesses the ecological impact of shield slurry and specifically includes:

[0082] Soil monitoring module: used for collecting soil samples through soil monitoring points arranged on the spot of shield slurry and determining the concentration of pollution elements in the samples;

[0083] Pollution analysis module: used for calculating the single pollution coefficient of pollution elements according to the Hakanson method through the obtained concentration of pollution elements, and further calculating the potential ecological risk coefficient;

[0084] Carbon emission risk assessment module: used for assessing the carbon emission risk generated in the resource utilization and landfill disposal process of shield slurry through the LCA method. The carbon emission risk score is obtained by calculating the difference between the resource carbon emission and the landfill carbon emission, and the carbon footprint of shield slurry is assessed;

[0085] Comprehensive impact calculation module: used for weighted calculation of the ecological pollution score and the carbon emission risk score to obtain the ecological comprehensive impact index of shield slurry. The ecological impact of shield slurry is quantitatively assessed according to the comprehensive impact index.

[0086] The system proposed in the above-mentioned embodiment can comprehensively assess the ecological risk and carbon emission of shield slurry through the functions of soil monitoring, pollution analysis, carbon emission risk assessment and ecological comprehensive impact calculation, and provide a scientific basis for decision-making. Through the combined analysis of the concentration of pollution elements, the ecological risk coefficient and the carbon emission data, the system can accurately calculate the ecological pollution score and the carbon emission risk score, and obtain the ecological comprehensive impact index based on weighted calculation, so as to help decision-makers comprehensively consider the balance between ecological protection and resource utilization, and optimize the treatment and management scheme of shield slurry.

[0087] The above-mentioned embodiments only express the specific embodiments of the present application, and the description is more specific and detailed, but it cannot be understood as a limitation on the scope of the patent of the present application. It should be noted that for ordinary skilled persons in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application.

Claims

1. A method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA, characterized in that, Includes the following steps: S1. Collect soil samples by setting up soil monitoring points at the tunnel boring machine excavation site; conduct pollution determination on the soil samples to obtain the concentration of polluting elements in the soil samples; S2. Based on the Hakanson method, average content values ​​and toxicity coefficients of polluting elements are set respectively. The individual pollution coefficients of the corresponding polluting elements are calculated by combining the average content values ​​of the polluting elements with the concentrations of the polluting elements. The potential ecological risk coefficients of the corresponding polluting elements are calculated by combining the individual pollution coefficients with the toxicity coefficients. The potential ecological risk index of the area is calculated based on the potential ecological risk coefficients of all polluting elements. The calculated potential ecological risk index is graded and scored, and the ecological pollution score is calculated through the graded scoring. S3. Based on the LCA method, calculate carbon emissions from resource utilization and carbon emissions from landfill disposal respectively, and obtain a carbon emission risk score by calculating the relative difference between carbon emissions from landfill disposal and carbon emissions from resource utilization. S4. Based on the ecological pollution scoring index and carbon emission risk score, the comprehensive ecological impact index of shield tunneling waste is obtained through weighted calculation, and the ecological impact of shield tunneling waste is assessed based on the comprehensive ecological impact index of shield tunneling waste.

2. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 1, characterized in that, In step S1, the method for setting up soil monitoring points is as follows: with the shield tunneling waste landfill as the center, sampling points are set up in a radial pattern, and the density of soil monitoring points decreases gradually from the density of sampling points in the area near the landfill to the density of sampling points in the area far from the landfill.

3. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 1, characterized in that, The soil samples contained at least the following pollutants: arsenic, cadmium, chromium, copper, mercury, nickel, lead, and zinc.

4. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 1, characterized in that, In step S2, the calculated potential ecological risk coefficients are graded and scored. The calculation of the ecological pollution score through graded scoring specifically includes the following sub-steps: S201. The potential ecological risk index is divided into four consecutive pollution threshold intervals, corresponding to low risk, medium risk, relatively high risk and high risk levels respectively; S202. Configure an independent piecewise calculation function for each pollution threshold interval, with the function form being a linear proportional relationship; S203. The calculated potential ecological risk coefficient is matched with the corresponding pollution threshold interval. Based on the function corresponding to the corresponding pollution threshold interval, the ecological pollution score of the potential ecological risk coefficient is calculated. The maximum value of the ecological pollution score is 100.

5. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 4, characterized in that, In step S202, the linear proportional relationship is specifically as follows: The function corresponding to the first pollution threshold interval is calculated based on the proportion of the ecological risk index to the upper limit of the interval. The functions corresponding to the third and fourth pollution threshold intervals are based on the proportion of the portion of the ecological risk index that exceeds the threshold of the previous interval to the current interval span, and are accumulated with the maximum score of the previous interval.

6. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 1, characterized in that, In step S3, carbon emissions from resource utilization include carbon emissions from energy consumption during the treatment of tunnel boring machine excavation and carbon emissions from the production process of additive materials. The value of carbon emissions from resource utilization is obtained by adding up the carbon emissions from energy consumption during the treatment of tunnel boring machine excavation and the carbon emissions from the production process of additive materials.

7. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 6, characterized in that, The energy consumption and carbon emissions from the treatment of tunnel boring machine excavation are calculated by linearly amplifying the treatment scale parameters through the product relationship between the energy intensity factor and the energy carbon emission coefficient. The carbon emissions from the production process of the added materials are calculated by the tensor product of the material mass balance equation and the material's life-cycle emission factor.

8. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 1, characterized in that, In step S3, the carbon emissions from landfill disposal include carbon emissions from the transportation of construction waste and carbon emissions from landfill construction machinery operations. The value of carbon emissions from resource utilization is obtained by adding the carbon emissions from the transportation of construction waste and carbon emissions from landfill construction machinery operations together.

9. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 8, characterized in that, The carbon emissions during the transportation of construction waste are calculated by convolving the mass-distance function with the transportation mode emission factor and correcting the actual transportation efficiency with an empty load adjustment coefficient; the carbon emissions from the operation of landfill construction machinery are calculated by mapping the machinery shift matrix with the Hadamard product of energy consumption density and combining it with an energy conversion factor.

10. The method for assessing the ecological impact of tunnel boring machine (TBM) spoil based on Hakanson-LCA as described in claim 1, characterized in that, In step S4, the comprehensive ecological impact index of tunnel boring machine slag is obtained by weighted calculation based on the ecological pollution scoring index and the carbon emission risk score. Specifically, the greenhouse effect coefficient is used as the weight item of the ecological pollution scoring index, and the heavy metal pollution coefficient is used as the weight item of the carbon emission risk score for weighted summation.

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