Building pollution and carbon reduction collaborative evaluation method based on LCA and dynamic weight analysis

Abstract

The invention discloses a building pollution reduction and carbon reduction collaborative evaluation method based on LCA and dynamic weight analysis, and relates to the field of building pollution reduction and carbon reduction collaborative evaluation. According to the method, the influence parameters of the design, construction and operation stages of the whole life cycle of the building are systematically identified and quantified, and the cooperative and unified evaluation of pollution reduction and carbon reduction is realized through dynamic weight reconstruction analysis and a function coupling LCA model, so that the environmental performance of the building in the whole life cycle can be integrally and accurately reflected, and meanwhile, the environmental performance of the building in the whole life cycle can be accurately evaluated. According to the method, the interaction between indexes and the time sensitivity of inter-stage energy consumption and pollutant transfer and emission can be considered at the same time, the complex multi-index and multi-stage environmental influence is converted into a comprehensive synergistic effect value, and an operable environmental performance grade is formed through grading judgment.

Description

TECHNICAL FIELD

[0001] The application relates to the field of building pollution reduction and carbon reduction collaborative evaluation, and in particular to a building pollution reduction and carbon reduction collaborative evaluation method based on LCA and dynamic weight analysis. BACKGROUND

[0002] During the construction process, environmental pollution problems such as construction dust, noise and solid waste are also accompanied. Therefore, it is of great significance to establish a scientific and systematic building whole-process pollution reduction and carbon reduction evaluation system to promote the sustainable development of the construction industry and achieve the "double carbon" goal. At present, there are certain research foundations in building carbon emission calculation and green building evaluation at home and abroad. However, the existing researches mainly focus on a single stage (such as construction or operation) or a single target (such as only calculating carbon emissions or only controlling pollution), and a collaborative pollution reduction and carbon reduction evaluation system covering the whole chain of "building design-construction operation-maintenance" has not yet been formed, which makes it difficult to scientifically evaluate the environmental benefits of the whole building in actual engineering.

[0003] Under the above background, the following key problems exist: 1. How to determine the grades and weights of the comprehensive index system selected for building design, construction and operation; 2. How to establish a unified quantitative model covering the whole life cycle of building design, construction and operation to solve the collaborative calculation problem of carbon emissions and pollutant emissions; Therefore, it is urgent to build a building pollution reduction and carbon reduction collaborative comprehensive evaluation system based on the combination of life cycle assessment (LCA) and weight analysis method. The system should systematically identify the key influencing factors of the three stages of "design-construction-operation" in the whole life cycle of building, establish a quantifiable and traceable collaborative evaluation system, and realize the scientific evaluation of the collaborative effect of building whole-process pollution reduction and carbon reduction. SUMMARY

[0004] The application provides a building pollution reduction and carbon reduction collaborative evaluation method based on LCA and dynamic weight analysis, which establishes a standardized building pollution reduction and carbon reduction collaborative effect evaluation framework by systematically identifying the key influencing factors of technical performance indexes, pollutant emission indexes, carbon emission indexes and economic indexes of different building types in each life cycle stage.

[0005] The building pollution reduction and carbon reduction collaborative evaluation method based on LCA and dynamic weight analysis comprises the following steps: S1. Obtain the influencing parameters in the design, construction and operation stages of the whole life cycle of the building respectively, and convert the influencing parameters into index values through normalization and standardization processing; and value the influence intensity of each index value in different life cycle stages to obtain the action degree value of each index; Specifically, the step S1 obtains the influence parameters in the design, construction and operation stages of the whole life cycle of the building respectively, and converts the influence parameters into index values through normalization and standardization processing; and the influence intensity of each index value in different life cycle stages is valued, and the action degree value of each index is obtained. In implementation, first, the original influence parameters are systematically collected according to the inventory stage (design, construction and operation) of ISO-LCA; the unit area implicit carbon, renewable energy allocation rate, green building material usage rate, light transmittance, energy consumption / carbon emission simulation value and sponge facility coverage rate are taken in the design stage; the construction dust concentration, construction noise limit value, low-carbon machine tool usage rate and waste water recycling rate are taken in the construction stage; and the unit area annual carbon intensity, photovoltaic self-sufficiency rate, non-traditional water source utilization rate, heating and ventilation energy efficiency ratio, indoor PM2.5 annual concentration and reclaimed water reuse rate are taken in the operation stage. For each original parameter, data cleaning and consistency conversion (such as unified time scale and function unit of “per m²•year”) should be performed first, and a deterministic standardization method (such as range normalization or z-score standardization, which one is recorded and the upper and lower limits are retained) is adopted to obtain the standardized index value of the stage.

[0006] The valuation of the action degree value adopts a deterministic process of multi-evidence fusion based on the raw material data: the absolute contribution degree of the index (for example, the proportion of the index in the stage load) is obtained from the historical monitoring data or LCI calculation, and then the environmental sensitivity of the index (reflecting the elasticity of the index change to pollutants / carbon emissions) is given by referring to authoritative literature or regulations, and finally the synthesized score is obtained by combining the expert qualitative judgment (using a scaling score instead of fuzzy language) according to the determined weight, and the action degree value is obtained by normalizing the synthesized score, which is the input of the subsequent dynamic weight and LCA calculation.

[0007] S2. The index values are calculated by the analytic hierarchy process to obtain the initial weight, and according to the initial weight and the action degree value, a dynamic weight reconstruction function with dynamic weight as output is constructed; Specifically, the hierarchical analysis method is used to calculate the index values to obtain the initial weight, and according to the initial weight and the action degree value, a dynamic weight reconstruction function with dynamic weight as output is constructed. In the implementation, first, the judgment matrix of the index system is constructed by the AHP hierarchical analysis method, and the target layer (full life cycle collaborative pollution reduction and carbon reduction), the criterion layer (technical performance, pollutants, carbon, and economy) and the index layer (the specific indexes mentioned above) are defined. The judgment matrix is given by the industry experts according to the pair comparison, and the characteristic vector is calculated as the initial static weight. At the same time, the consistency ratio test (CR<0.10) is performed, and the comparison matrix is adjusted as necessary to ensure consistency. The principle of dynamic weight reconstruction is to generate stage-by-stage dynamic weight by combining the initial weight with the stage-by-stage action degree value (and the coupling effect between indexes). Specifically, the relative correction factor in the stage is calculated, which takes the action degree value as the base and introduces the coupling term between indexes in the stage (reflecting how the change of a certain index affects other indexes through materials, processes or operation logic), wherein the coupling coefficient is given by historical project regression or Delphi scoring method and is subjected to sensitivity test; then the dynamic weight is obtained by normalization.

[0008] S3. According to the output dynamic weight and the action degree value, an initial LCA model is constructed, and a stage association matrix for representing the energy transfer and pollutant superposition relationship between different life cycle stages and a timing correction coefficient for reflecting the difference in environmental impact of emission time are introduced to construct a function-coupled LCA model; Specifically, according to the output dynamic weight and the action degree value, an initial LCA model is constructed, and a stage association matrix for representing the energy transfer and pollutant superposition relationship between different life cycle stages and a timing correction coefficient for reflecting the difference in environmental impact of emission time are introduced to construct a function-coupled LCA model; The traditional LCA model often assumes that each life cycle stage is independent of each other, ignoring the interaction between stages in energy consumption and pollutant emission. In fact, energy-saving schemes in the design stage will affect the energy demand in the construction stage, and emission control measures in the construction stage will affect the emission reduction potential in the operation stage. By introducing the stage association matrix, the interaction and transmission effect between different stages can be quantified, and the influence of a single stage is extended to the comprehensive effect across stages, thereby improving the systematization and authenticity of the model. At the same time, the environmental effects of pollutant emissions and carbon emissions are not only determined by the amount of emissions, but also closely related to the time point of emission. For example, the same pollutants emitted at different times may cause different degrees of harm to the atmospheric environment or the ecological system. The introduction of the timing correction coefficient solves the problem, which differentiates the weighting of emission time, so that the LCA model can reflect the time sensitivity of emissions. This function-coupled LCA model not only reflects the interaction between stages, but also dynamically adjusts in combination with the time dimension, so as to more comprehensively and accurately depict the collaborative effect of pollution reduction and carbon reduction at the system level.

[0009] S4. According to the function coupling LCA model, the total synergistic pollution reduction and carbon reduction effect value is calculated, and the total synergistic pollution reduction and carbon reduction effect value is graded according to the preset threshold.

[0010] Specifically, according to the function coupling LCA model, the total synergistic pollution reduction and carbon reduction effect value is calculated, and the total synergistic pollution reduction and carbon reduction effect value is graded according to the preset threshold. The function coupling LCA model has integrated dynamic weights, inter-stage energy consumption and pollutant transfer relationships, and time correction coefficients, so that the output total synergistic effect value can reflect the true pollution reduction and carbon reduction level of the building throughout its life cycle. By calculating the total effect value, the environmental performance of the building is comprehensively quantified. Further, by setting the preset threshold and grading, the continuous synergistic effect value is converted into discrete grade results, improving the interpretability and operability of the results. This grading can help relevant parties quickly identify the level of the building in terms of pollution reduction and carbon reduction, such as dividing it into low synergy, medium synergy and high synergy levels. Not only can it provide improvement direction for building design optimization, construction management and operation and maintenance, but also can provide quantitative support for industry standard formulation and policy incentives.

[0011] The beneficial effects of the application are: (1) The application systematically identifies and quantifies the influence parameters of the design, construction and operation stages of the building throughout its life cycle, and realizes the unified evaluation of pollution reduction and carbon reduction through dynamic weight reconstruction analysis and function coupling LCA model, so as to accurately reflect the environmental performance of the building throughout its life cycle. At the same time, the application can consider the interaction between indicators, the energy consumption and pollutant transfer between stages, and the time sensitivity of emissions, and convert the complex multi-indicator and multi-stage environmental impact into a comprehensive synergistic effect value, and form an operable environmental performance grade through grading. (2) The application quantifies the key indicators of pollution and carbon emissions in the design, construction and operation stages of the building, realizes precise control of the environmental impact throughout the life cycle, and significantly reduces the building's energy consumption, carbon emission intensity and total pollution emissions. At the same time, the system is verifiable, efficient and scalable, and can provide scientific decision-making basis for low-carbon operation and maintenance management throughout the life cycle of the building. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 The method schematic diagram of the building pollution reduction and carbon reduction synergistic evaluation method based on LCA and dynamic weight analysis according to the embodiment one of the application is shown. Figure 2 The environmental load grade and synergistic joint determination schematic diagram of the method of the building pollution reduction and carbon reduction synergistic evaluation method based on LCA and dynamic weight analysis according to the embodiment two of the application is shown. DETAILED DESCRIPTION

[0013] The technical solutions of the present application are described in further detail below in conjunction with the accompanying drawings, but the scope of protection of the present application is not limited to the following description.

[0014] For the purpose of the present application, the technical solutions and advantages are more clearly and explicitly understood, the present application is further described in conjunction with the accompanying drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application, and are not used to limit the present application, that is, the described examples are only a part of the examples of the present application, but not all the examples. The components of the embodiments of the present application generally described and shown in the accompanying drawings can be arranged and designed in various different configurations.

[0015] Therefore, the detailed description of the embodiments of the present application provided in the accompanying drawings below is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of the present application. It should be noted that the relational terms such as "first" and "second" and the like are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations.

[0016] Moreover, the term "comprising", "containing" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or mechanical equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or mechanical equipment. Without more limitations, the element defined by the sentence "including a" does not exclude the presence of other identical elements in the process, method, article or mechanical equipment including the element.

[0017] The features and properties of the present application are further described in detail below in conjunction with the examples.

[0018] Example One Among them, such as Figure 1 The building pollution reduction and carbon reduction collaborative evaluation method based on LCA and dynamic weight analysis includes the following steps: S1. Obtain the influence parameters in the design, construction and operation stages of the building life cycle respectively, and convert the influence parameters into index values by normalization and standardization processing; and value the influence intensity of each index value in different life cycle stages to obtain the action degree value of each index; S2. Calculate the initial weight by analytic hierarchy process on each index value, and construct a dynamic weight reconstruction function with dynamic weight as output according to the initial weight and the degree of action value; S3. According to the output dynamic weight and the degree of action value, construct the initial LCA model, and introduce the stage association matrix for representing the energy transfer and pollutant superposition relationship between different life cycle stages and the time sequence correction coefficient for reflecting the difference of environmental impact caused by emission time, to construct the function coupling LCA model; S4. According to the function coupling LCA model, calculate the overall synergistic pollution reduction and carbon reduction effect value, and grade the overall synergistic pollution reduction and carbon reduction effect value according to the preset threshold.

[0019] Specifically, the implementation process of the above steps is as follows: first, the real-time or historical operation parameters of each stage of the building life cycle are obtained through the data acquisition system, and the original data is cleaned, normalized and standardized to make different types of environmental, energy consumption and emission data comparable under the same dimension; further, according to the literature and expert experience, the actual contribution of each parameter to the overall pollution reduction and carbon reduction effect of the building in different stages is analyzed, a parameter action intensity model is established, and the degree of action value of each parameter is calculated by weighted calculation, which is used to form the stage association matrix to quantify the mutual influence between different stages. After obtaining the degree of action value, the system calls the analytic hierarchy process to preliminarily calculate the index weight, and constructs a dynamic weight reconstruction model combined with the degree of action value and the interaction effect between parameters. The model automatically adjusts the weight output according to the actual influence relationship between stages, so that the weight of each index can be dynamically updated with the change of stages, and the importance and change trend of each index in the life cycle are truly reflected. Further, the dynamic weight, the degree of action value and the index value are input into the function-coupled life cycle assessment model, and the model internally calculates the energy transfer and emission superposition effect between stages through the stage association matrix, and adjusts the emission impact at different time points by combining the time sequence correction coefficient, to realize the coupling and correction of the environmental load of each stage. During the model execution process, the system will gradually calculate the function-coupled environmental load of each stage, and obtain the overall synergistic pollution reduction and carbon reduction effect value by summation, and further weight the load of each stage by combining the dynamic weight and the degree of action value, to generate the integrated overall synergistic effect data. Further, the system compares the overall synergistic effect value with the preset threshold, grades the synergistic pollution reduction and carbon reduction level of the building in the design, construction and operation stages, and generates an analysis report on the contribution of each index to the overall synergistic effect, to provide specific and operable decision basis for building scheme optimization, construction management improvement and operation and maintenance.

[0020] Further, in the step S1: The impact parameters in the design stage include at least unit area implicit carbon estimation, renewable energy configuration rate, green building material usage rate, energy-saving glass light transmittance, energy consumption simulation value, carbon emission simulation value, and sponge facility coverage rate. Specifically, the decision in the design stage directly determines the basic level of building materials, energy consumption strategy, and pollution control scheme. The unit area implicit carbon estimation reflects the potential influence of material selection and design scheme on carbon emission. The renewable energy configuration rate reflects the degree of renewable energy utilization. The green building material usage rate and the energy-saving glass light transmittance affect the life cycle energy consumption and environmental load of the building. The energy consumption simulation value and the carbon emission simulation value can quantify the influence of the design stage scheme on the subsequent construction and operation stage. The sponge facility coverage rate reflects the potential of rainwater management and ecological emission reduction. The impact parameters in the construction stage include at least construction dust emission concentration, construction waste recycling rate, construction noise diurnal limit value, low-carbon machine usage rate, wastewater recycling rate, and construction waste recycling rate. Specifically, the construction stage is the actual release period of pollutants and carbon emissions in the whole life cycle of the building. Each index directly reflects the environmental pressure of the construction process. The construction dust emission concentration and the construction noise limit value reflect the influence of construction on the air environment and the surrounding ecology. The construction waste recycling rate and the construction waste recycling rate reflect the resource recycling and emission reduction potential. The low-carbon machine usage rate affects the energy efficiency of construction, and the wastewater recycling rate represents the water resource saving and emission control.

[0021] The impact parameters in the operation stage include at least unit area annual carbon emission intensity, photovoltaic power generation self-sufficiency rate, non-traditional water source utilization rate, heating and ventilation system energy efficiency ratio, indoor PM2.5 annual concentration, and reclaimed water recycling rate. Specifically, the operation stage is the dominant stage of building life cycle energy consumption and emission. Each index reflects the building operation efficiency and environmental impact. The unit area annual carbon emission intensity quantifies the carbon emission level in the operation stage. The photovoltaic power generation self-sufficiency rate and the non-traditional water source utilization rate reflect the utilization efficiency of renewable energy and water resources. The heating and ventilation system energy efficiency ratio measures the energy consumption efficiency. The indoor PM2.5 annual concentration reflects the air quality index. The reclaimed water recycling rate reflects the water recycling level.

[0022] Further, in the step S1, the influence intensity of each index value in different life cycle stages is valued to obtain the action degree value of each index, which includes the following sub-steps: S101. According to historical data, reference literature and expert experience, identify the main influencing factors of each index in each stage; S102. Take the main influencing factors as the index weighting factor, and calculate the action degree value combined with the index value; S103. Output the action degree value of all indexes in each stage, wherein the output value is in matrix form, that is: ; wherein the is a matrix representing the degree of action value of all indicators at each stage, the is a degree of action value of the 1st indicator under the life cycle design stage, the is a degree of action value of the 1st indicator under the life cycle construction stage, the is a degree of action value of the 1st indicator under the life cycle operation stage.

[0023] Specifically, the contribution of indicators at different life cycle stages to the synergistic effect of building pollution reduction and carbon reduction is different, and pure dependence on indicators cannot accurately reflect their actual role. By collecting historical project data, consulting relevant literature and seeking expert opinions, the key driving factors of each indicator at the design, construction and operation stages can be identified, for example, the green building material usage rate at the design stage is affected by material availability and construction feasibility, and the energy efficiency ratio of the heating and ventilation system at the operation stage is affected by equipment selection and operation and maintenance level. Identifying the main influencing factors can combine the environmental and carbon emission effects of the indicators with actual engineering practice; further, the numerical value of a single indicator cannot fully reflect its contribution to pollution reduction and carbon reduction in the whole life cycle, and needs to be weighted in combination with the influence intensity. By assigning a weighting factor (the weight reflects the relative importance of the factor to the action of the indicator at this stage) to each indicator and multiplying it by the normalized indicator value, the degree of action value of the indicator at the corresponding stage can be calculated, thereby quantifying the actual contribution of each indicator to the environmental load and carbon emission at the stage; further, in order to facilitate dynamic weight reconstruction and calculation of the function-coupled LCA model, the degree of action value of each indicator needs to be represented in a structured manner. The degree of action value of each indicator at the design, construction and operation stages is organized in matrix form, with each row corresponding to an indicator and each column corresponding to a life cycle stage.

[0024] Further, in the step S102, the specific calculation process of the degree of action value is represented as: ; wherein the is a degree of action value of the i-th indicator under the life cycle stage t, the is an indicator value of the i-th indicator at stage t, the is an indicator weighting factor of the i-th indicator at stage t, the is an indicator value of the j-th indicator at stage t, the is an indicator weighting factor of the j-th indicator at stage t, and the is a summation of all indicators j under the life cycle stage t.

[0025] In addition, when there are multiple main influencing factors, in a multi-factor situation, a certain index is simultaneously affected by multiple main influencing factors. For example, the "annual carbon emission intensity per unit area" in the operation stage depends not only on the energy efficiency ratio of the heating system, but also on the photovoltaic power generation self-sufficiency rate, the thermal insulation performance of building materials, and the energy consumption behavior of users. At this time, the index value needs to be considered as the result of the comprehensive action of multiple influencing factors, and the contribution of different factors is described by assigning multiple weighting factors. Specifically, for each main influencing factor, determine its relative importance to the index in this stage to form a set of weighting factors; then, combine the weighting factors with the corresponding factor values to obtain the comprehensive effect of the index in this stage; through normalization and summary processing, integrate the effect into the effective coupling relationship between the index value and the weighting factor.

[0026] Further, the step S2 of constructing a dynamic weight reconstruction function with dynamic weights as output according to the initial weights and the action degree values specifically includes the following sub-steps: S201. According to the interaction relationship between the action degree value and the index value, calculate the relative correction factor of the index in the stage; Specifically, the pollution reduction and carbon reduction effects of the index in each life cycle stage are not completely independent, but there are mutual influence and coupling relationship. For example, the use rate of green building materials in the design stage may affect the construction dust emission in the construction stage, and the photovoltaic power generation self-sufficiency rate in the operation stage may be constrained by the building design scheme. By analyzing the interaction relationship between the index value and the action degree value, the relative influence degree of each index on other indexes in the stage is determined, and the relative correction factor is calculated accordingly. The relative correction factor is used to reflect the actual action intensity adjustment of the index within the stage and across the stages.

[0027] S202. Construct a dynamic weight reconstruction function according to the relative correction factor and the initial weight, and calculate the dynamic weight through the dynamic weight reconstruction function; Specifically, the initial weight is a static weight obtained by evaluating the importance of the index based on the analytic hierarchy process, which cannot reflect the interaction between indexes and the difference between stages. By introducing the relative correction factor, the action intensity of the index in the stage is adjusted to the actual influence level, thereby constructing a dynamic weight reconstruction function. The function takes the initial weight and the relative correction factor as input, and outputs the dynamic weight of each index in the current stage, dynamically reflecting the stage contribution and synergistic effect of the index; S203. Output the dynamic weights of all indexes in each stage, wherein the output value is in matrix form, that is: ; Wherein, the represents the matrix of the dynamic weights of all indexes in each stage, the represents the dynamic weight of the first index in the life cycle design stage, and the Indicates the dynamic weight of the first indicator in the construction phase of the life cycle. It represents the dynamic weight of the first indicator in the operation stage of the life cycle. Specifically, in order to facilitate the subsequent functional coupling LCA calculation, it is necessary to structure the dynamic weight of each indicator. The dynamic weight of each indicator in the design, construction and operation stages is organized into a matrix form, with each row corresponding to an indicator and each column corresponding to a life cycle stage. The matrix is ​​input into the functional coupling LCA model as the dynamic weight matrix. Through matrix representation, the relative contribution of each indicator in each stage can be expressed.

[0028] Furthermore, in step S201, the specific calculation process of the relative correction factor of the calculation index within the stage is expressed as follows: ; Among them, the Represents the relative correction factor of index i in stage t, Indicates the effect degree value of the i-th indicator at the life cycle stage t. It represents the coupling coefficient of the jth indicator to the ith indicator at stage t, that is, the interaction relationship. Indicates the degree of effect of the jth indicator at the life cycle stage t. It represents the comprehensive effect of other indicators on indicator i within the stage.

[0029] Furthermore, in step S202, the dynamic weight reconstruction function is specifically expressed as: ; Among them, the represents the dynamic weight of the i-th indicator at stage t, that is, the output of the dynamic weight reconstruction function. Represents the initial weight of the i-th indicator, Represents the relative correction factor of index i in stage t, Represents the initial weight of the j-th indicator, Represents the relative correction factor of index j in stage t, It represents the sum of the products of the initial weights and correction factors of all indicators in stage t.

[0030] Furthermore, step S3 specifically includes the following sub-steps: S301. Associate the dynamic weight, the degree of action, and the index value as the input vector of the initial LCA model to construct the initial LCA model, namely: ; Among them, the represents the environmental load of the i-th indicator in stage t, denotes the dynamic weight of the i-th indicator at stage t, and the denotes the role degree value of the i-th indicator at stage t of the life cycle, and the indicator value of the j-th indicator at stage t; Specifically, the environmental load of each indicator at each stage of the whole life cycle is affected by the indicator value itself, and is adjusted by the importance (dynamic weight) and role strength (role degree value) of the indicator in the stage. By associating the dynamic weight , role degree value and indicator value of each indicator, the environmental load of the i-th indicator at stage t can be calculated, so as to quantify the contribution of each indicator to the environmental load and carbon emission at a specific stage, while considering the relative importance and role strength of the indicators within the stage, and further constructing an initial LCA model input vector reflecting the actual impact.

[0031] S302. According to the initial LCA model, the corresponding stage environmental load is calculated for each stage indicator, and the total load of each stage is calculated according to the environmental load of each stage, that is: ; wherein the total load of stage t is denoted; Specifically, after the initial LCA model calculates the weighted load of each indicator, the sum of the environmental loads of the indicators within the stage can be obtained, so as to reflect the actual contribution of the stage to the building whole life cycle pollution reduction and carbon reduction synergy effect, and the total load of the stage is the basic input of the functional coupling LCA model. By calculating the total load of the design, construction and operation stages respectively, the contribution of each stage to the whole life cycle pollution reduction and carbon reduction is evaluated.

[0032] S303. The functional coupling correction is performed by introducing a stage correlation matrix, that is ; The time sequence correction is performed on the stage coupling load by introducing a time sequence correction coefficient, that is , to construct a functional coupling LCA model; wherein the correlation environmental load after the functional coupling correction by the stage correlation matrix is denoted, the stage correlation coefficient is denoted, the total load of stage k is denoted, and the functional coupling environmental load after the time sequence correction on the stage coupling load by the time sequence correction coefficient is denoted, and the a time sequence correction coefficient of a stage t, used for reflecting an adjustment factor of environmental influence of emission time difference; specifically, stages in a life cycle are not independent, a decision in a design stage influences energy consumption and emission in a construction stage, and construction behavior in the construction stage has a delayed influence on energy consumption and pollution level in an operation stage. By introducing a stage correlation matrix, energy consumption transfer and pollution superposition relationship between different stages can be quantified to correct mutual influence of stage environmental load; meanwhile, a time sequence correction coefficient is introduced to reflect emission time sequence effect, so that environmental load is closer to actual release in time dimension. The function-coupled LCA model can output stage environmental load after correlation and time sequence correction, provide an accurate basis for overall coordinated pollution reduction and carbon reduction effect calculation, and realize quantitative evaluation of life cycle pollution reduction and carbon reduction coordination.

[0033] Further, the construction process of the stage correlation matrix includes the following sub-steps: S311. Constructing a stage index, collecting corresponding energy consumption transfer, pollution transfer, and carbon emission superposition data for each pair of stages; specifically, different stages in a life cycle are closely related, for example, material selection in a design stage influences construction energy consumption and construction dust emission in a construction stage, and equipment use efficiency in the construction stage influences energy consumption level in an operation stage. In order to quantify the above cross-stage influence, the design, construction, and operation stages need to be indexed and numbered, a stage mapping relationship is established, and actual or simulated energy consumption transfer data, pollution transfer data, and carbon emission superposition data are collected for each pair of stages. These data are derived from historical project statistics, experimental measurement, or results of building simulation software, and the purpose is to obtain actual physical and environmental influence transfer between stages; S312. Calculating a stage correlation coefficient of each pair of stages through corresponding energy consumption transfer, pollution transfer, and carbon emission superposition data; specifically, the collected cross-stage data are normalized, and actual influence of stage k on stage t is calculated according to total load proportion of the stage, so as to obtain the stage correlation coefficient. The stage correlation coefficient can quantify the interaction degree between stages, and a larger value indicates that the environmental load contribution of stage k to stage t is more obvious. Energy consumption transfer, pollution transfer, and carbon emission superposition effect are uniformly converted into a quantifiable correlation coefficient.

[0034] S313. Arranging the stage correlation coefficients into a matrix form, i.e., a stage correlation matrix; specifically, for the convenience of calculation and model input, all stage correlation coefficients are arranged into a matrix form according to the stage index, each row represents an affected stage t, and each column represents an influencing stage k, and the matrix element is The stage correlation matrix can completely express the mutual influence relationship between stages in a life cycle, provide structured data for the function-coupled LCA model, and make the model correct the environmental load of each stage in coordination.

[0035] Specifically, the energy consumption transfer, pollutant transfer, and carbon emission superposition data include actual consumption of material selection in the construction stage, influence of the design scheme on the construction method, influence of the construction process emission on the maintenance or energy consumption in the operation stage, etc., which are mainly obtained through measured data, simulation models, reference literature, or expert experience.

[0036] Further, the stage correlation coefficient is specifically represented as: , wherein, represents that stage t has no influence on stage k; represents that the load of stage t is completely transferred or superimposed on stage k; the stage correlation coefficient is calculated according to the collected energy consumption transfer, pollutant transfer, and carbon emission superposition data, and examples are as follows: .

[0037] Further, the stage correlation coefficients are arranged in matrix form and represented as: .

[0038] Further, the step S4 specifically includes the following sub-steps: S401. Through the functional coupling LCA model, the functional coupling environmental load of each stage after correlation and time sequence correction is output, and summation is performed to calculate the total synergistic pollution reduction and carbon reduction effect value, i.e. , wherein, the total synergistic pollution reduction and carbon reduction effect value is represented as: Specifically, the functional coupling LCA model integrates the stage correlation matrix and the time sequence correction coefficient, can perform functional coupling and time correction on the index environmental load of the design, construction, and operation stages, and thus reflects the actual environmental impact of each stage in the whole life cycle; by summing the environmental load of each stage after coupling and correction, the total synergistic pollution reduction and carbon reduction effect value is obtained, which comprehensively reflects the energy consumption transfer, pollutant superposition, and carbon emission time sequence effect between stages, and is a core index for measuring the synergistic effect of building life cycle pollution reduction and carbon reduction; S402. According to the total synergistic pollution reduction and carbon reduction effect value, the dynamic weight, and the action degree value, the weighted load is calculated and summed to calculate the stage weighted environmental load; i.e. ; ; , wherein, the stage weighted environmental load is represented as: , wherein, the weighted environmental load of stage t is represented as: S403. The stage weighted load is integrated into the total pollution reduction and carbon reduction synergistic effect, and the total pollution reduction and carbon reduction synergistic effect is classified and determined according to a preset threshold; i.e.​ ; wherein, the represents the overall pollution reduction and carbon reduction synergistic effect; specifically, the value comprehensively considers the importance and action intensity of each stage index, realizing the quantitative evaluation of the building pollution reduction and carbon reduction synergistic effect; according to the preset grade threshold (for example, high, medium and low synergistic effect interval), the overall effect is graded and judged, and the performance level of the building in the design, construction and operation stages can be clearly pointed out.

[0039] Embodiment two Further, as a preferred embodiment of the above embodiment, for step S4, the overall pollution reduction and carbon reduction synergistic effect is graded and judged according to the preset threshold, and the joint grading is carried out by incorporating the unified quantitative model of pollution reduction and carbon reduction synergy, which is represented as: ; wherein, represents the synergistic degree; ER (GHG) represents the greenhouse gas emission reduction amount; ER (AP) represents the atmospheric pollution emission reduction amount; the greenhouse gas emission reduction amount; represents the baseline emission amount of greenhouse gas; the atmospheric pollutant emission reduction amount; represents the baseline emission amount of atmospheric pollutant.

[0040] Specific implementation process is: In the overall grade judgment, the environmental load grade is determined by the overall environmental load value calculated by the functional coupling LCA as the baseline, and the ratio comparison is carried out with the set baseline value (such as industry average emission intensity, carbon intensity control target). For example, it is divided into four levels, namely, excellent, good, medium and poor. Specifically, the excellent level (the overall environmental load value is less than 60% of the baseline value) means that the environmental load is significantly lower than the baseline level, and the pollution reduction and carbon reduction effect is outstanding, corresponding to the highest level in green building; the good level (the overall environmental load value is greater than or equal to 60% and less than 90% of the baseline value) means that the environmental load is better than the industry average level, and has strong pollution reduction and carbon reduction synergistic effect, but still has further optimization space; the medium level (the overall environmental load value is greater than or equal to 90% and less than 110% of the baseline value) means that the environmental load is close to the baseline value, and the overall is in the acceptable range, but lacks obvious synergistic advantage; the poor level (the overall environmental load value is greater than or equal to 110% of the baseline value) means that the environmental load is higher than the baseline level, which shows that the pollution reduction or carbon reduction effect is insufficient, and even there is a superimposed risk of pollutants and carbon emissions. Determination of synergy (priority) - only when the overall level is low and In the ideal interval (>1), it is considered that the scheme simultaneously achieves good carbon reduction and pollution reduction; if the overall is low but ≤0, it is marked as a risk of carbon reduction and pollution increase, and further optimization is required.

[0041] A two-dimensional level determination matrix is established: the horizontal axis is the level, and the vertical axis is the synergy interval, to generate a decision category, for example, as Figure 2 .

[0042] Through the above implementation, in the level determination in step S4, the determination result is not only based on the overall synergy effect value, but also considers the relative contribution among different emission reduction objects, so that the accuracy and rationality of the level evaluation are improved.

[0043] The above only describes the preferred embodiments of the present application, and it should be understood that the present application is not limited to the forms disclosed herein, and should not be considered as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concepts described herein by the above teachings or related technical or knowledge. Any modification and change made by those skilled in the art without departing from the spirit and scope of the present application shall be within the protection scope of the claims of the present application.

Claims

1. A method for collaborative evaluation of building pollution reduction and carbon reduction based on LCA and dynamic weight analysis, characterized in that, The method comprises the following steps: S1. Obtain the influence parameters in the design, construction and operation stages of the whole life cycle of the building respectively, and convert the influence parameters into index values through normalization and standardization processing; and assign the influence intensity of each index value in different life cycle stages to obtain the action degree value of each index; S2. Calculate each index value through the analytic hierarchy process to obtain the initial weight, and construct a dynamic weight reconstruction function with dynamic weight as the output according to the initial weight and the action degree value; S3. Construct an initial LCA model according to the output dynamic weight and the action degree value, introduce a stage correlation matrix for representing the energy consumption transfer and pollutant superposition relationship between different life cycle stages, and introduce a time sequence correction coefficient for reflecting the difference of the environmental impact caused by the emission time, and construct a function coupling LCA model; S4. Calculate the total synergistic pollution reduction and carbon reduction effect value according to the function coupling LCA model, and grade the total synergistic pollution reduction and carbon reduction effect value according to a preset threshold.

2. The building pollution reduction and carbon reduction synergy evaluation method based on LCA and dynamic weight analysis according to claim 1, characterized in that, In the step S1: The influence parameters in the design stage at least include unit area implicit carbon estimation value, renewable energy configuration rate, green building material utilization rate, energy-saving glass light transmittance, energy consumption simulation value, carbon emission simulation value and sponge facility coverage rate; The influence parameters in the construction stage at least include construction dust emission concentration, building waste recycling rate, construction noise diurnal limit value, low-carbon machine utilization rate, wastewater recycling rate and construction waste recycling rate; The influence parameters in the operation stage at least include unit area annual carbon emission intensity, photovoltaic power generation self-sufficiency rate, non-traditional water source utilization rate, heating and ventilation system energy efficiency ratio, indoor PM2.5 annual concentration and reclaimed water reuse rate.

3. The LCA and dynamic weight analysis-based building pollution reduction and carbon reduction synergy evaluation method according to claim 1, characterized in that, In the step S1, the influence intensity of each index value in different life cycle stages is assigned to obtain the action degree value of each index, which specifically comprises the following sub-steps: S101. According to historical data, reference literature and expert experience, identify the main influencing factors of each index in each stage; S102. Take the main influencing factors as index weighting factors, and calculate the action degree value in combination with the index value; S103. Output the action degree value of all indexes in each stage, wherein the output value is in matrix form, that is: ； Wherein, the A matrix representing the degree of influence of all indicators at each stage, the A degree of influence of the first indicator at the life cycle design stage, the A degree of influence of the first indicator at the life cycle construction stage, the A degree of influence of the first indicator at the life cycle operation stage.

4. The building pollution reduction and carbon reduction synergy evaluation method based on LCA and dynamic weight analysis according to claim 3, characterized in that, In the step S102, the specific calculation process of the action degree value is represented as: ； wherein the denotes the degree of influence value of the i-th indicator at the life cycle phase t, the denotes the indicator value of the i-th indicator at the phase t, the denotes the indicator weighting factor of the i-th indicator at the phase t, the denotes the indicator value of the j-th indicator at the phase t, the denotes the indicator weighting factor of the j-th indicator at the phase t, the denotes the summation over all indicators j at the life cycle phase t.

5. The LCA and dynamic weight analysis-based building pollution reduction and carbon reduction synergy evaluation method according to claim 1, characterized in that, In the step S2, the dynamic weight reconstruction function with dynamic weight as the output is constructed according to the initial weight and the action degree value, which specifically comprises the following sub-steps: S201. Calculate the relative correction factor of the index in the stage according to the interaction relationship between the action degree value and the index value; S202. Construct the dynamic weight reconstruction function according to the relative correction factor and the initial weight, and calculate the dynamic weight through the dynamic weight reconstruction function; S203. Output the dynamic weight of all indexes in each stage, wherein the output value is in matrix form, that is: ； Wherein, the represents the matrix of dynamic weights of all indexes at each stage, and the represents the dynamic weight of the first index under the life cycle design stage, and the represents the dynamic weight of the first index under the life cycle construction stage, and the represents the dynamic weight of the first index under the life cycle operation stage.

6. The building pollution reduction and carbon reduction synergy evaluation method based on LCA and dynamic weight analysis according to claim 5, characterized in that, In the step S201, the specific calculation process of the relative correction factor of the index in the stage is represented as: ； Wherein, the represents the relative correction factor of the index i in the stage t, and the represents the action degree value of the i-th index in the life cycle stage t, and the represents the coupling coefficient of the j-th index to the i-th index in the stage t, that is, the interaction relationship, and the represents the action degree value of the j-th index in the life cycle stage t, and the represents the comprehensive action of other indexes in the stage to the index i.

7. The building pollution reduction and carbon reduction synergy evaluation method based on LCA and dynamic weight analysis according to claim 5, characterized in that, In the step S202, the dynamic weight reconstruction function is specifically represented as: ； wherein the represents the dynamic weight of the i-th indicator at stage t, i.e. the output of the dynamic weight reconstruction function, the represents the initial weight of the i-th indicator, the represents the relative correction factor of indicator i at stage t, the represents the initial weight of the j-th indicator, the represents the relative correction factor of indicator j at stage t, the represents the sum of the initial weight and correction factor product of all indicators at stage t.

8. The LCA and dynamic weight analysis-based building pollution reduction and carbon reduction synergy evaluation method according to claim 1, characterized in that, The step S3 specifically comprises the following sub-steps: S301. The dynamic weight, the action degree value and the index value are associated as an input vector of an initial LCA model, and the initial LCA model is constructed; S302. According to the initial LCA model, the corresponding stage environmental load of each stage index is calculated, and the total load of each stage is calculated according to the environmental load of each stage; S303. The function coupling correction is performed by introducing the stage correlation matrix; The function coupling LCA model is constructed by introducing the time sequence correction coefficient to correct the stage coupling load in time sequence.

9. The building pollution reduction and carbon reduction synergy evaluation method based on LCA and dynamic weight analysis according to claim 8, characterized in that, The construction process of the stage correlation matrix includes the following sub-steps: S311. A stage index is constructed, and for each pair of stages, the corresponding energy consumption transfer, pollutant transfer and carbon emission superposition data are collected; S312. The stage correlation coefficient of each pair of stages is calculated through the corresponding energy consumption transfer, pollutant transfer and carbon emission superposition data; S313. The stage correlation coefficients are arranged in the form of a matrix, that is, the stage correlation matrix.

10. The LCA and dynamic weight analysis-based building pollution reduction and carbon reduction synergy evaluation method according to claim 1, characterized in that, The step S4 specifically includes the following sub-steps: S401. The function coupling environmental load of each stage after correlation and time sequence correction is output through the function coupling LCA model, and is summed to calculate the total synergistic pollution reduction and carbon reduction effect value; S402. According to the total synergistic pollution reduction and carbon reduction effect value, the dynamic weight and the action degree value, the weighted load is calculated, and is summed to calculate the stage weighted environmental load; S403. The stage weighted load is integrated into the total pollution reduction and carbon reduction synergistic effect, and the total pollution reduction and carbon reduction synergistic effect is classified according to the preset threshold.

Images