Collaborative evaluation method for building pollution reduction and carbon reduction based on lca and dynamic weight analysis

Abstract

The application 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.The application systematically identifies and quantifies the influence parameters of the design, construction and operation stages of the whole life cycle of a building, and realizes the collaborative and unified evaluation of pollution reduction and carbon reduction through dynamic weight reconstruction analysis and a function-coupled LCA model, so that the environmental performance of the building in the whole life cycle can be accurately reflected as a whole.Meanwhile, the application can simultaneously consider the interaction between indexes, the energy consumption and pollutant transmission between stages, and the time sensitivity of emission, convert the complex multi-index and multi-stage environmental influence into a comprehensive collaborative effect value, and form an operable environmental performance grade through hierarchical determination.

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 have not yet formed a collaborative pollution reduction and carbon reduction evaluation system covering the whole chain of "building design - construction - operation and maintenance", 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:

[0004] 1. How to determine the grades and weights of the comprehensive index system selected for building design, construction and operation;

[0005] 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;

[0006] 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 the 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

[0007] The application provides a building pollution reduction and carbon reduction collaborative evaluation method based on LCA and dynamic weight analysis, which systematically identifies 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, and establishes a standardized building pollution reduction and carbon reduction collaborative effect evaluation framework.

[0008] The building pollution reduction and carbon reduction collaborative evaluation method based on LCA and dynamic weight analysis comprises the following steps:

[0009] 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 values to the influence intensity of each index value in different life cycle stages to obtain the action degree value of each index;

[0010] 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 assigns values to the influence intensity of each index value in different life cycle stages to obtain the action degree value of each index. In implementation, first, the original influence parameters are systematically collected according to the inventory stage (design, construction, operation) of ISO-LCA; the design stage takes 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; the construction stage takes the construction dust concentration, construction noise limit value, low-carbon machine tool usage rate, and wastewater recycling rate; the operation stage takes 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. For each original parameter, data cleaning and consistency conversion (such as unified time scale, functional unit “per m²•year”) should be performed first, and a deterministic standardization method (such as range normalization or z-score standardization, record which one and keep the upper and lower limits) is adopted to obtain the standardized index value of the stage.

[0011] The assignment of the action degree value adopts a deterministic process of multi-evidence fusion based on raw material data: the absolute contribution degree of the index (for example, the proportion of the index in the stage load) is obtained from 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 expert qualitative judgment (using a scaling score instead of fuzzy language) with a certain 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.

[0012] S2. Calculate each index value by 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;

[0013] 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 degree of action value, a dynamic weight reconstruction function is constructed with dynamic weight as output. 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 value (and the coupling effect between indexes). Specifically, the relative correction factor in the stage is calculated, which takes the action 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.

[0014] S3. According to the output dynamic weight and the action value, an initial LCA model is constructed, and a stage correlation 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;

[0015] Specifically, according to the output dynamic weight and the action value, an initial LCA model is constructed, and a stage correlation 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 correlation 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.

[0016] 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.

[0017] 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 full 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 into low synergistic, medium synergistic and high synergistic grades. 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.

[0018] The beneficial effects of the application are:

[0019] (1) The present application systematically identifies and quantifies the influence parameters of the design, construction and operation stages of the building full 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 in the whole life cycle. At the same time, through the present application, the interaction between indicators, the energy consumption and pollutant transfer between stages, and the time sensitivity of emissions can be considered simultaneously, and the complex multi-indicator and multi-stage environmental impact can be converted into a comprehensive synergistic effect value, and an operable environmental performance grade can be formed through grading.

[0020] (2) The present application quantifies the key indicators of pollution and carbon emissions in the design, construction and operation and maintenance stages of the building, realizes precise control of the full life cycle environmental impact, and its application will significantly reduce the building energy consumption carbon emission intensity and the total amount of pollutant emissions. At the same time, the system has verifiability, efficiency and scalability, and can provide scientific decision-making basis for building full life cycle low-carbon operation and maintenance management. BRIEF DESCRIPTION OF DRAWINGS

[0021] 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 present application is shown in the figure.

[0022] Figure 2The environmental load grade and the synergistic joint determination schematic diagram of the building pollution reduction and carbon reduction synergistic evaluation method based on LCA and dynamic weight analysis proposed in embodiment two of the present application are shown in the figure. DETAILED DESCRIPTION

[0023] The technical solutions of the present application are described in further detail below in combination with the drawings, but the protection scope of the present application is not limited to the following description.

[0024] In order to make the purpose, technical solutions and advantages of the present application clearer and more understandable, the present application is further described in detail in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application, that is, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0025] Therefore, the detailed description of the embodiments of the present application provided in the 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 creative labor are within the scope of protection of the present application. It should be noted that the relationship 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.

[0026] Moreover, the term "comprising", "including" 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 another identical element in the process, method, article or mechanical equipment including the element.

[0027] The features and performances of the present application are further described in detail below in combination with the embodiments.

[0028] Embodiment one

[0029] Among them, such as Figure 1 The building pollution reduction and carbon reduction synergistic evaluation method based on LCA and dynamic weight analysis includes the following steps:

[0030] 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 value the influence intensity of each index value in different life cycle stages to obtain the action degree value of each index;

[0031] S2. Calculate each index value through the analytic hierarchy process to obtain the initial weight, and construct a dynamic weight reconstruction function with the dynamic weight as the output according to the initial weight and the action degree value;

[0032] S3. According to the output dynamic weight and the action degree value, construct an initial LCA model, and introduce a stage correlation matrix for representing the energy consumption transfer and pollutant superposition relationship between different life cycle stages and a time sequence correction coefficient for reflecting the difference of the emission time on the environmental impact, to construct a function coupling LCA model;

[0033] S4. According to the function coupling LCA model, calculate the total synergistic pollution reduction and carbon reduction effect value, and grade the total synergistic pollution reduction and carbon reduction effect value according to the preset threshold.

[0034] 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 full life cycle are obtained through the data acquisition system, and the original data is cleaned, normalized and standardized, so that different types of environmental, energy consumption and emission data can be compared 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 action degree value of each parameter is obtained through weighted calculation, which is used to form the inter-stage correlation matrix to quantify the mutual influence between different stages. After obtaining the action degree value, the system calls the analytic hierarchy process to preliminarily calculate the index weight, and combines the action degree value and the interaction effect between parameters to build a dynamic weight reconstruction model. 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 the stage, and the importance and change trend of each index in the life cycle can be truly reflected. Further, the dynamic weight, action degree value and index value are input into the functional coupling life cycle evaluation model, and the model internally calculates the energy consumption transfer and emission superposition effect between stages through the stage correlation matrix, and adjusts the emission influence at different time points by combining the time sequence correction coefficient, so as to realize the coupling and correction of the environmental load of each stage. During the model execution process, the system will gradually calculate the functional coupling environmental load of each stage, and obtain the total synergistic pollution reduction and carbon reduction effect value by summation, and further combine the dynamic weight and the action degree value to weight the load of each stage, and generate the integrated total synergistic effect data. Further, the system compares the total synergistic effect value with the preset threshold to grade 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, providing specific and operable decision basis for building scheme optimization, construction management improvement and operation and maintenance.

[0035] Further, in the step S1:

[0036] The influence parameters of the design stage include at least unit area implicit carbon estimation value, 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 decisions made in the design stage directly determine the basic level of building materials, energy consumption strategies and pollution control schemes, wherein the unit area implicit carbon estimation value 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, and 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 stages, and the sponge facility coverage rate reflects the rainwater management and ecological emission reduction potential;

[0037] The impact parameters of the construction stage include at least construction dust emission concentration, construction waste recycling rate, construction noise diurnal limit value, low-carbon machine tool utilization 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 a building, and each index directly reflects the environmental pressure of the construction process. The construction dust emission concentration and the construction noise limit value reflect the impact 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 tool utilization rate affects the energy efficiency of construction, and the wastewater recycling rate represents water resource conservation and emission control.

[0038] The impact parameters of the operation stage include at least annual carbon emission intensity per unit area, 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 utilization rate. Specifically, the operation stage is the dominant stage of building life cycle energy consumption and emission, and each index reflects the building operation efficiency and environmental impact. The annual carbon emission intensity per unit area quantifies the carbon emission level of the operation stage, the photovoltaic power generation self-sufficiency rate and the non-traditional water source utilization rate reflect the renewable energy and water resource utilization efficiency, the heating and ventilation system energy efficiency ratio measures the energy consumption efficiency, the indoor PM2.5 annual concentration reflects the air quality index, and the reclaimed water utilization rate reflects the water recycling level.

[0039] 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:

[0040] S101. According to historical data, reference literature and expert experience, identify the main influencing factors of each index in each stage;

[0041] S102. Take the main influencing factors as index weighting factors, and calculate the action degree value combined with the index value;

[0042] S103. Output the action degree value of all indexes in each stage, wherein the output value is in matrix form, i.e.:

[0043] ;

[0044] Wherein, the matrix of the action degree value of all indexes in each stage is represented by , the action degree value of the first index in the life cycle design stage is represented by , the action degree value of the first index in the life cycle construction stage is represented by , and the action degree value of the first index in the life cycle operation stage is represented by .

[0045] Specifically, the indicators of different life cycle stages have different contributions to the synergistic effect of building pollution reduction and carbon reduction, and relying solely 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 influenced by material availability and construction feasibility, and the energy efficiency ratio of the heating and ventilation system at the operation stage is influenced by equipment selection and operation and maintenance level. Identifying the main influencing factors can combine the environmental and carbon emission effects of 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 the influence intensity of the indicator needs to be combined for weighted processing. By assigning a weighted factor (the weight reflects the relative importance of the factor to the indicator effect at this stage) to each indicator and multiplying it by the normalized indicator value, the action degree 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 emissions of the stage; further, in order to facilitate dynamic weight reconstruction and calculation of the function-coupled LCA model, the action degree value of each indicator needs to be represented in a structured manner. The action degree values of each indicator at the design, construction, and operation stages are organized in matrix form, with each row corresponding to an indicator and each column corresponding to a life cycle stage.

[0046] Further, in the step S102, the specific calculation process of the action degree value is represented as:

[0047] ;

[0048] wherein, the represents the action degree value of the i-th indicator at the life cycle stage t, the represents the indicator value of the i-th indicator at the stage t, the represents the indicator weighting factor of the i-th indicator at the stage t, the represents the indicator value of the j-th indicator at the stage t, the represents the indicator weighting factor of the j-th indicator at the stage t, and the represents the summation of all indicators j at the life cycle stage t.

[0049] 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 weighted factors. Specifically, for each main influencing factor, determine its relative importance to the index in the stage to form a set of weighted factors; then, combine the weighted factors with the corresponding factor values to obtain the comprehensive effect of the index in the stage; through normalization and summary processing, integrate the effect into the effective coupling relationship between the index value and the weighted factor.

[0050] 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:

[0051] 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.

[0052] 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 stage differences. 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;

[0053] S203. Output the dynamic weights of all indexes in each stage, wherein the output value is in matrix form, that is:

[0054] ;

[0055] Wherein, the represents the matrix of the dynamic weights of all indexes in each stage, and the represents the dynamic weight of the first index under the life cycle design stage, and the first index is the first index in the life cycle design stage. represents the dynamic weight of the first index under the life cycle construction stage, and the first index is the first index in the life cycle construction stage. represents the dynamic weight of the first index under the life cycle operation stage, and the first index is the first index in the life cycle operation stage; in order to facilitate subsequent function coupling LCA calculation, the dynamic weight of each index needs to be structured, and the dynamic weight of each index in the design, construction and operation stages is organized into a matrix form, each row corresponding to an index and each column corresponding to a life cycle stage, and the matrix is input to the function coupling LCA model as a dynamic weight matrix; through matrix representation, the relative contribution of each index in each stage can be expressed.

[0056] Further, the specific calculation process of the relative correction factor of the index in the stage in the step S201 is represented as:

[0057] ;

[0058] wherein the relative correction factor of the index i in the stage t is represented as: represents the relative correction factor of the index i in the stage t, the action degree value of the i-th index under the life cycle stage t is represented as: represents the action degree value of the i-th index under the life cycle stage t, the coupling coefficient of the j-th index to the i-th index under the stage t, that is, the interaction relationship is represented as: represents the action degree value of the j-th index under the life cycle stage t, and the comprehensive action of other indexes in the stage to the index i is represented as: represents the action degree value of the j-th index under the life cycle stage t, and the comprehensive action of other indexes in the stage to the index i is represented as: represents the action degree value of the j-th index under the life cycle stage t, and the comprehensive action of other indexes in the stage to the index i is represented as:

[0059] Further, the dynamic weight reconstruction function in the step S202 is specifically represented as:

[0060] ;

[0061] wherein the dynamic weight of the i-th index under the stage t, that is, the output of the dynamic weight reconstruction function is represented as: represents the dynamic weight of the i-th index under the stage t, that is, the output of the dynamic weight reconstruction function, the initial weight of the i-th index is represented as: represents the initial weight of the i-th index, the relative correction factor of the index i in the stage t is represented as: represents the initial weight of the i-th index, the relative correction factor of the index i in the stage t is represented as: represents the initial weight of the j-th index, and the relative correction factor of the index j in the stage t is represented as: represents the initial weight of the j-th index, and the relative correction factor of the index j in the stage t is represented as: represents the sum of the initial weight and the correction factor of all indexes under the stage t.

[0062] Further, the step S3 specifically includes the following sub-steps:

[0063] S301. Associate the dynamic weights, the degree of influence values, and the index values ​​as the input vector for the initial LCA model, and construct the initial LCA model, i.e.:

[0064] ;

[0065] Among them, the This represents the environmental load of the i-th indicator in stage t. The dynamic weight of the i-th indicator in stage t is represented by the following. This represents the influence value of the i-th indicator at stage t of the life cycle, while the j-th indicator value represents the indicator value at stage t. Specifically, the environmental load of indicators at each stage of the entire life cycle is affected not only by the indicator's own value but also by the indicator's importance (dynamic weight) and influence intensity (influence value) within that stage. This is achieved by adjusting the dynamic weight of each indicator. Degree of effect With index value By establishing correlations, the environmental load of the i-th indicator in stage t can be calculated, thereby quantifying the contribution of each indicator to environmental load and carbon emissions in a specific stage. At the same time, considering the relative importance and intensity of the indicators within the stage, an initial LCA model input vector reflecting the actual impact can be constructed.

[0066] S302. Based on the initial LCA model, calculate the corresponding environmental load for each stage's indicators, and calculate the total stage load based on the environmental load for each stage, i.e.:

[0067] ;

[0068] Among them, the The term 't' represents the total load of stage 't'. Specifically, after calculating the weighted load of each indicator in the initial LCA model, the total environmental load of each indicator within the stage can be obtained, thus reflecting the actual contribution of that stage to the synergistic effect of pollution reduction and carbon reduction throughout the building's life cycle. The total load of the stage is the basic input of the functionally coupled LCA model. By calculating the total load for the design, construction, and operation stages respectively, the contribution of each stage to pollution reduction and carbon reduction throughout the building's life cycle can be evaluated.

[0069] S303. Functional coupling correction is achieved by introducing a stage correlation matrix, i.e. The timing of the stage-coupled load is corrected by introducing a timing correction factor. Construct a functionally coupled LCA model;

[0070] Among them, the This represents the associated environmental load after functional coupling correction through the stage association matrix. The term represents the stage correlation coefficient, the denotes the total load of stage k, and denotes the functionally coupled environmental load of stage k, which is the total load of stage k coupled with the time sequence correction coefficient, and denotes the time sequence correction coefficient of stage t, which is an adjustment factor reflecting the adjustment of emission time difference on environmental impact; specifically, the stages of the life cycle are not independent, the decisions in the design stage will affect the energy consumption and emissions in the construction stage, and the construction behavior in the construction stage will have a delayed impact on the energy consumption and pollution level in the operation stage. By introducing the stage correlation matrix, the energy consumption transfer and pollutant superposition relationship between different stages can be quantified, and the mutual influence of the stage environmental load is corrected; at the same time, the time sequence correction coefficient is introduced to reflect the emission time sequence effect, so that the environmental load is closer to the actual release in the time dimension. The functionally coupled LCA model can output the stage environmental load after correlation and time sequence correction, provide an accurate basis for the overall collaborative pollution reduction and carbon reduction effect calculation, and realize the collaborative quantification evaluation of pollution reduction and carbon reduction in the whole life cycle.

[0071] Further, the construction process of the stage correlation matrix includes the following sub-steps:

[0072] S311. Build a stage index, collect corresponding energy consumption transfer, pollutant transfer, and carbon emission superposition data for each pair of stages; specifically, there is a close correlation between different stages in the whole life cycle, for example, the material selection in the design stage will affect the construction energy consumption and construction dust emission in the construction stage, and the equipment use efficiency in the construction stage will affect the energy consumption level in the operation stage. In order to quantify the above cross-stage influence, the design, construction, and operation stages need to be indexed and numbered, the stage mapping relationship is established, and the actual or simulated energy consumption transfer data, pollutant transfer data, and carbon emission superposition data are collected for each pair of stages. These data come from historical project statistics, experimental measurements, or the results of building simulation software, and the purpose is to obtain the actual physical and environmental impact transfer between stages;

[0073] S312. Calculate the stage correlation coefficient of each pair of stages through the corresponding energy consumption transfer, pollutant transfer, and carbon emission superposition data; specifically, normalize the collected cross-stage data, and calculate the actual influence of stage k on stage t according to the total load proportion of the stage, so as to obtain the stage correlation coefficient. The correlation coefficient can quantify the degree of interaction between stages, and the larger the value, the more obvious the environmental load contribution of stage k to stage t. The energy consumption transfer, pollutant transfer, and carbon emission superposition effect are unified into a quantifiable correlation coefficient.

[0074] S313. The stage correlation coefficients are arranged in matrix form, i.e., a stage correlation matrix; specifically, for the convenience of calculation and model input, all stage correlation coefficients are arranged in 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 the stages in the whole life cycle, provides structured data for the functional coupling LCA model, and enables the model to collaboratively correct the environmental load of each stage.

[0075] Specifically, the energy consumption transfer, pollutant transfer, and carbon emission superposition data include the actual consumption of material selection in the construction stage, the influence of the design scheme on the construction method, the influence of the construction process emission on the maintenance or energy consumption in the operation stage, etc., and are mainly obtained through measured data, simulation models, reference literature, or expert experience.

[0076] 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 an exemplary calculation is as follows:

[0077] .

[0078] Further, the stage correlation coefficients are arranged in matrix form as follows:

[0079] .

[0080] Further, the step S4 specifically includes the following sub-steps:

[0081] S401. Through the functional coupling LCA model, the functional coupling environmental load of each stage after correlation and timing correction is output, and is summed to calculate the total collaborative pollution reduction and carbon reduction effect value, i.e., , wherein, the total collaborative pollution reduction and carbon reduction effect value is specifically represented as: represents the total collaborative pollution reduction and carbon reduction effect value; specifically, the functional coupling LCA model integrates the stage correlation matrix and the timing correction coefficient, can perform functional coupling and time correction on the index environmental load of the design, construction, and operation stages, thereby reflecting the actual environmental impact of each stage in the whole life cycle; by summing the environmental load of each stage after coupling correction, the total collaborative pollution reduction and carbon reduction effect value is obtained, which comprehensively reflects the energy consumption transfer, pollutant superposition, and carbon emission timing effect between stages, and is a core index for measuring the collaborative effect of pollution reduction and carbon reduction in the whole life cycle of the building;

[0082] S402. Based on the overall synergistic pollution reduction and carbon reduction effect value, dynamic weights, and degree of effect values, calculate the weighted load and sum them to obtain the stage-weighted environmental load; that is:

[0083] ;

[0084] ;

[0085] Among them, the This represents the weighted environmental load of the i-th indicator in stage t. This represents the weighted environmental load for stage t;

[0086] S403. Integrate the weighted loads of each stage into an overall pollution reduction and carbon reduction synergistic effect, and classify the overall pollution reduction and carbon reduction synergistic effect according to a preset threshold; that is:

[0087] ;

[0088] Among them, the It represents the overall synergistic effect of pollution reduction and carbon reduction; specifically, this value comprehensively considers the importance and intensity of the indicators at each stage to achieve a quantitative assessment of the synergistic effect of building pollution reduction and carbon reduction; based on the preset level thresholds (such as high, medium and low synergistic effect ranges), the overall effect is graded and judged, which can clearly indicate the pollution reduction and carbon reduction performance level of buildings in the design, construction and operation stages.

[0089] Example 2

[0090] Furthermore, as a preferred embodiment of the above embodiments, in step S4, the process of classifying and determining the overall pollution reduction and carbon reduction synergy effect according to a preset threshold is incorporated into the unified quantitative model for pollution reduction and carbon reduction synergy for joint classification, wherein the unified quantitative model for pollution reduction and carbon reduction synergy is expressed as:

[0091] ;

[0092] in, Indicates the degree of synergy; ER (GHG) Indicates greenhouse gas emission reductions; ER (AP) This indicates the amount of air pollution emission reduction; Greenhouse gas emission reductions; This represents the baseline emissions of greenhouse gases. Emission reduction of air pollutants; This represents the baseline emissions of air pollutants.

[0093] The specific implementation process is as follows:

[0094] In determining the overall level, through The specific process for determining the environmental load level is as follows: The overall environmental load value is calculated using the functionally coupled linear comfort area (LCA) calculation. Using this as a benchmark, the ratio is compared with a set benchmark value (such as the industry average emission intensity or carbon intensity control target). For example, it is divided into four levels: Excellent, Good, Medium, and Poor. Specifically, Excellent (overall environmental load value less than 60% of the benchmark value) means the environmental load is significantly lower than the benchmark level, with outstanding pollution reduction and carbon reduction effects, corresponding to the highest level in green buildings; Good (overall environmental load value greater than or equal to 60% and less than 90% of the benchmark value) means the environmental load is better than the industry average, with strong synergistic effects in pollution reduction and carbon reduction, but there is still room for further optimization; Medium (overall environmental load value greater than or equal to 90% and less than 110% of the benchmark value) means the environmental load is close to the benchmark value, generally within an acceptable range, but lacks obvious synergistic advantages; Poor (overall environmental load value greater than or equal to 110% of the benchmark value) means the environmental load is higher than the benchmark level, showing insufficient pollution reduction or carbon reduction effects, and even the risk of superposition of pollutants and carbon emissions. Determine synergy (priority) – only when the overall level is low and Within the ideal range (>1), the scheme is considered to achieve both good carbon reduction and pollution reduction; if the overall level is low but... If the value is ≤0, then the risk of carbon reduction increasing pollution is indicated, and further optimization is needed.

[0095] Establish a two-dimensional ranking matrix: the horizontal axis is... Level, vertical axis is Coordination intervals generate decision categories, for example, such as Figure 2 .

[0096] Through the above implementation scheme, in the classification determination in step S4, the determination result is not only based on the overall synergistic effect value, but also takes into account the relative contribution between different emission reduction targets, thereby improving the accuracy and rationality of the classification evaluation.

[0097] The above description is merely a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the concept described herein through the above teachings or related technologies or knowledge. Modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weighting analysis, characterized in that, Includes the following steps: S1. Obtain the impact parameters in the three stages of the building's entire life cycle: design, construction, and operation. Then, convert the impact parameters into index values ​​through normalization and standardization. Assign values ​​to the impact intensity of each index value in different life cycle stages to obtain the degree of influence of each index. S2. Calculate the values ​​of each indicator using the analytic hierarchy process (AHP) to obtain the initial weights, and construct a dynamic weight reconstruction function with dynamic weights as the output based on the initial weights and the degree of influence. S3. Based on the output dynamic weights and degree of influence, construct an initial LCA model, and introduce a stage correlation matrix to represent the relationship between energy transfer and pollutant superposition between different life cycle stages and a time-series correction coefficient to reflect the differences in the environmental impact of emission time, and construct a functionally coupled LCA model. S4. Based on the functionally coupled LCA model, the overall synergistic pollution reduction and carbon reduction effect value is calculated, and the overall synergistic pollution reduction and carbon reduction effect value is classified and determined according to the preset threshold. Specifically, step S2, which involves constructing a dynamic weight reconstruction function with dynamic weights as the output based on the initial weights and the degree of influence, includes the following sub-steps: S201. Calculate the relative correction factor of the indicator within the stage based on the interaction between the degree of effect value and the indicator value; S202. Based on the relative correction factor and the initial weights, construct a dynamic weight reconstruction function, and calculate the dynamic weights using the dynamic weight reconstruction function; S203. Output the dynamic weights of all indicators at each stage, where the output values ​​are in matrix form, i.e.: ； Among them, the A matrix representing the dynamic weights of all indicators at each stage, the aforementioned This represents the dynamic weight of the first indicator during the lifecycle design phase. This represents the dynamic weight of the first indicator during the lifecycle construction phase. This indicates the dynamic weight of the first indicator during the lifecycle operation phase.

2. The synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weight analysis as described in claim 1, characterized in that, In step S1: The impact parameters in the design phase should include at least the estimated carbon per unit area, renewable energy allocation rate, green building material usage rate, light transmittance of energy-saving glass, simulated energy consumption, simulated carbon emissions, and sponge city facility coverage rate. The impact parameters during the construction phase should include at least the concentration of construction dust emissions, the recycling rate of construction waste, the daytime limit of construction noise, the utilization rate of low-carbon equipment, the wastewater recycling rate, and the recycling rate of construction waste. The impact parameters during the operational phase should at least include annual carbon emission intensity per unit area, photovoltaic power generation self-sufficiency rate, non-traditional water source utilization rate, HVAC system energy efficiency ratio, and indoor air quality. Annual average concentration and water reuse rate.

3. The synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weight analysis as described in claim 1, characterized in that, In step S1, assigning values ​​to the influence intensity of each indicator at different life cycle stages to obtain the degree of influence of each indicator specifically includes the following sub-steps: S101. Based on historical data, references, and expert experience, identify the main influencing factors for each indicator at each stage; S102. Use the main influencing factors as weighting factors for the indicators, and combine them with the indicator values ​​to calculate the degree of influence. S103. Output the degree of influence of all indicators at each stage, where the output values ​​are in matrix form, i.e.: ； Among them, the A matrix representing the degree of influence of all indicators at each stage, the aforementioned This indicates the degree of influence of the first indicator during the lifecycle design phase. This indicates the degree of influence of the first indicator during the construction phase of the lifecycle. This indicates the degree of influence of the first indicator during the lifecycle operation phase.

4. The synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weight analysis as described in claim 3, characterized in that, In step S102, the specific calculation process for the degree of effect value is expressed as follows: ； Among them, the This represents the degree of influence of the i-th indicator at lifecycle stage t. This represents the value of the i-th indicator in stage t. This represents the weighting factor of the i-th indicator in stage t. This represents the value of the j-th indicator in stage t. This represents the weighting factor of the j-th indicator in stage t. This represents the summation of all indicators j under lifecycle stage t.

5. The synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weight analysis as described in claim 1, characterized in that, In step S201, the specific calculation process for the relative correction factor of the index within the stage is as follows: ； Among them, the The relative correction factor of index i within stage t, the This represents the degree of influence of the i-th indicator at lifecycle stage t. This represents the coupling coefficient between the j-th indicator and the i-th indicator at stage t, i.e., the interaction relationship. This represents the degree of influence of the j-th indicator at lifecycle stage t. This indicates the combined effect of other indicators on indicator i within a given period.

6. The synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weight analysis as described in claim 1, characterized in that, In step S202, the dynamic weight reconstruction function is specifically expressed as follows: ； Among them, the This represents the dynamic weight of the i-th indicator at stage t, i.e., the output of the dynamic weight reconstruction function. The initial weight of the i-th indicator is represented by the following: The relative correction factor of index i within stage t, the This represents the initial weight of the j-th indicator. This represents the relative correction factor of index j within stage t. This represents the sum of the products of the initial weights and correction factors of all indicators at stage t.

7. The synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weight analysis as described in claim 1, characterized in that, Step S3 specifically includes the following sub-steps: S301. Associate the dynamic weights, the degree of influence values, and the index values ​​as the input vector for the initial LCA model to construct the initial LCA model; S302. Based on the initial LCA model, calculate the corresponding environmental load for each stage, and calculate the total load for each stage based on the environmental load for each stage. S303. Functional coupling correction by introducing a stage correlation matrix; By introducing a timing correction coefficient to correct the timing of the stage-coupled load, a functionally coupled LCA model is constructed.

8. The synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weight analysis as described in claim 7, characterized in that, The process of constructing the stage association matrix includes the following sub-steps: S311. Construct a phase index and collect corresponding energy transfer, pollutant transport, and carbon emission superposition data for each pair of phases; S312. Calculate the stage correlation coefficient for each pair of stages using the corresponding superimposed data of energy transfer, pollutant transport, and carbon emissions; S313. Organize the correlation coefficients of each stage into a matrix form, i.e., the stage correlation matrix.

9. The synergistic evaluation method for building pollution reduction and carbon reduction based on LCA and dynamic weight analysis as described in claim 1, characterized in that, Step S4 specifically includes the following sub-steps: S401. Using the functionally coupled LCA model, output the functionally coupled environmental loads of each stage after correlation and time-series correction, and sum them to calculate the overall synergistic pollution reduction and carbon reduction effect value. S402. Based on the overall synergistic pollution reduction and carbon reduction effect value, dynamic weight, and degree of effect value, calculate the weighted load and sum them to obtain the stage weighted environmental load; S403. Integrate the weighted loads of each stage into the overall pollution reduction and carbon reduction synergistic effect, and classify and determine the overall pollution reduction and carbon reduction synergistic effect according to the preset threshold.

Images