Building engineering carbon emission intelligent analysis system and method

Abstract

The invention discloses a building engineering carbon emission intelligent analysis system and method, and relates to the technical field of building carbon emission measurement and analysis, and the method comprises the following steps: obtaining building engineering related data, and carrying out the data preprocessing of the building engineering related data; carbon emission factors related to constructional engineering are collected, and a carbon emission factor library is constructed; calculating the carbon emission of the constructional engineering based on the carbon emission factor library and the related data of the constructional engineering, and analyzing and processing the carbon emission of the constructional engineering; constructing a carbon emission prediction model, carrying out model training, and predicting the carbon emission of the constructional engineering after the model training is completed; the method is used for solving the problem that an existing building carbon emission measurement and analysis technology lacks a technology which can simply and quickly measure and analyze the carbon emission in the building material transportation process and the building construction process in the building engineering in combination with environmental factors and can predict the carbon emission in the building construction process in real time at the same time in the existing building carbon emission measurement and analysis technology.

Description

Technical Field

[0001] The present invention relates to the technical field of building carbon emission measurement and analysis, and specifically to a system and method for intelligent analysis of building engineering carbon emissions. Background Art

[0002] Building carbon emission measurement and analysis technology refers to the technical means used to evaluate the greenhouse gas emissions generated by buildings during the construction cycle; building carbon emission measurement technology mainly focuses on the carbon emissions of buildings during the construction process, including three stages: building materials production, building materials transportation and building construction; the purpose of this technology is to accurately measure the carbon emissions of buildings and provide a scientific basis for energy conservation and emission reduction.

[0003] The existing widely used building carbon emission measurement and analysis technologies include material balance method, actual measurement method and carbon emission coefficient method. The carbon emission coefficient method is a method of multiplying the activity data of carbon emission source units with the statistical average of carbon emissions generated under normal technical standards and management conditions to obtain carbon emissions. However, the existing carbon emission coefficient method is used to measure building carbon emissions due to the influence of factors such as technical level and human influence, and its uncertainty is large. In addition, building carbon emissions will be affected by a combination of environmental factors, of which temperature and rainfall are two key meteorological factors. In the construction materials transportation stage, the existing methods often use transportation mileage as activity data, and then multiply it by the carbon emission factor to obtain carbon emissions, ignoring the impact of environmental factors. In addition, the transportation mileage of construction projects is often difficult to accurately count, and the carbon emission factors of different types of transportation tools are often different, even for the same type. The carbon emission factors of different types of transportation tools under different cargo weights are also different; this will cause a large error between the calculated carbon emissions and the actual carbon emissions. For example, in the patent application with publication number CN117575139A, a carbon emission monitoring system for the construction process is disclosed. Although this solution classifies the carbon emission factors when calculating the carbon emissions in the construction materials transportation stage, it does not consider environmental factors, the cargo weight of the transportation tools, mileage errors and other factors; and the carbon emissions of construction equipment in the construction process are often difficult to count separately; and there is no method for real-time prediction of carbon emissions in the construction stage; therefore, the existing construction carbon emission measurement and analysis technology lacks a technology that can combine environmental factors in the construction project to simply and quickly measure and analyze the carbon emissions in the building materials transportation process and the construction process, and at the same time make real-time predictions of carbon emissions in the construction process. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems in the prior art to a certain extent. It collects relevant data on construction projects, establishes a carbon emission factor library, calculates the carbon emissions in the building materials production stage, the building materials transportation stage and the building construction stage of the construction project, and establishes a carbon emission prediction model to make real-time predictions on the carbon emissions in the building construction stage, so as to solve the problem that the existing building carbon emission measurement and analysis technology lacks a technology that can combine environmental factors in a simple and fast way to measure and analyze the carbon emissions in the building materials transportation process and the building construction process in the construction project, and at the same time make real-time predictions on the carbon emissions in the building construction process.

[0005] To achieve the above objectives, in a first aspect, the present application provides a construction engineering carbon emission intelligent analysis system, including a data acquisition module, a carbon emission factor module, a carbon emission accounting module and a carbon emission prediction module;

[0006] The data acquisition module includes an acquisition unit and a processing unit, wherein the acquisition unit is used to acquire construction engineering related data, and the processing unit is used to perform data preprocessing on the construction engineering related data;

[0007] The carbon emission factor module is used to collect carbon emission factors related to construction projects and build a carbon emission factor library;

[0008] The carbon emission accounting module includes a calculation unit and an analysis unit. The calculation unit calculates the carbon emission of the construction project based on the carbon emission factor library and the relevant data of the construction project, and the analysis unit is used to analyze and process the carbon emission of the construction project;

[0009] The carbon emission prediction module includes a model building unit and a data prediction unit. The model building unit is used to build a carbon emission prediction model and perform model training, and the data prediction unit is used to predict the carbon emissions of construction projects.

[0010] Furthermore, the collection unit is configured with a collection strategy, which includes:

[0011] Obtain daily energy consumption data, environmental data, and labor data during the building materials transportation stage and the building construction stage;

[0012] Energy consumption data include: daily fossil fuel consumption and electricity energy consumption. Daily fossil fuel consumption includes: fossil fuel consumption generated by transportation, fossil fuel consumption generated by construction equipment, and fossil fuel consumption generated by living equipment; daily electricity energy consumption includes: electricity energy consumption generated by construction equipment and electricity energy consumption generated by living equipment;

[0013] Environmental data include: daily average temperature and rainfall;

[0014] Manual data includes: the types of work done by staff every day, and the specific number of people doing each type of work.

[0015] Furthermore, the processing unit is configured with a processing strategy, and the processing strategy includes:

[0016] The types of work of the staff in the building materials transportation stage and the construction stage are divided into light labor work and heavy labor work according to the labor intensity, and the number of light labor work and heavy labor work in the building materials transportation stage and the construction stage are obtained according to the specific number of people in each type of work;

[0017] The daily energy consumption data, environmental data and labor data of the building materials transportation stage and the construction stage are sorted and stored according to the acquisition date, and then classified according to the construction project stage to which the date belongs, to obtain the building materials transportation data and construction data.

[0018] Furthermore, the carbon emission factor module is configured with a factor collection construction strategy, which includes:

[0019] Collect fuel carbon emission factors: obtain the types of fossil fuels used in construction projects, and obtain the corresponding average lower calorific value, carbonization rate and carbon content per unit calorific value of the fossil fuels, and calculate the fuel carbon emission factors of the fossil fuels;

[0020] Collect electricity carbon emission factors: According to the grid area where the construction project is actually located, obtain the average carbon dioxide emission factor of the grid area and mark it as the electricity carbon emission factor;

[0021] Collect building materials carbon emission factors: obtain the types of building materials used in the construction process, and obtain the corresponding building materials carbon emission factors based on the types of building materials used;

[0022] Collect artificial carbon emission factors: obtain carbon emission factors for light labor work and heavy labor work respectively;

[0023] The fuel carbon emission factors and electricity carbon emission factors are marked as energy carbon emission factors, and the energy carbon emission factors, collected artificial carbon emission factors and building materials carbon emission factors are classified and stored and marked as a carbon emission factor library.

[0024] Furthermore, the calculation unit is configured with a carbon emission calculation strategy, which includes:

[0025] Calculate carbon emissions during the building materials transportation stage: Calculate fuel carbon emissions, electricity carbon emissions and labor carbon emissions during the building materials transportation stage based on building materials transportation data, fuel carbon emission factors, electricity carbon emission factors and labor carbon emission factors; the fuel carbon emission calculation formula is as follows: Among them C YR(a) represents the fuel carbon emission on day a during the construction materials transportation stage, R1 ka represents the consumption of the kth fuel on day a, F k represents the carbon emission factor of the kth fuel; the calculation formula for electricity carbon emissions is as follows: C YD (a) = D1 a *U; where C YD (a) represents the electricity carbon emissions on day a during the building materials transportation stage, D1 a represents the amount of electricity consumed on day a during the building materials transportation phase, and U represents the carbon emission factor of electricity; the calculation formula for artificial carbon emissions is as follows: YG (a) = G1 1a *B1+G1 2a *B2, where C YG (a) represents the artificial carbon emissions on day a during the construction materials transportation stage, G1 1a represents the number of people doing light labor on day a of the building materials transportation stage, B1 represents the carbon emission factor of light labor; G1 2a represents the number of people doing heavy labor in the construction materials transportation stage, and B2 represents the carbon emission factor of heavy labor;

[0026] Then calculate the carbon emissions in the transportation stage through the carbon emissions calculation formula. The carbon emissions calculation formula in the transportation stage is as follows: Among them C YS represents the carbon emissions during the building materials transportation stage, and A represents the total number of days during the building materials transportation stage.

[0027] Furthermore, the carbon emission calculation strategy also includes:

[0028] Calculate carbon emissions during the construction phase: Calculate fuel carbon emissions, electricity carbon emissions and labor carbon emissions during the construction phase based on construction data, fuel carbon emission factors, electricity carbon emission factors and labor carbon emission factors; the fuel carbon emission calculation formula is as follows: Among them C JR (b) represents the fuel carbon emission on day b during the construction phase, R2 kb represents the consumption of the kth fuel on day b; the calculation formula for electricity carbon emissions is as follows: C JD (b) = D2 b *U; where C JD (b) represents the carbon emissions of electricity on day b during the construction phase, D2 B represents the electricity consumed on day b during the construction phase; the artificial carbon emission calculation formula is as follows C JG (b) = G2 1b *B1+G2 2b *B2, where C JG (b) represents the artificial carbon emissions on day b during the construction materials transportation phase, G21b Represents the number of people doing light labor on day b during the construction phase; G2 2b The number of people representing heavy labor work during the construction phase;

[0029] Then, the carbon emissions during the construction phase are calculated using the carbon emissions calculation formula during the construction phase. The carbon emissions calculation formula during the construction phase is as follows: Among them C JS represents the carbon emissions during the construction phase, and N represents the total number of days during the construction phase;

[0030] The carbon emissions during the construction phase and the environmental data during the construction phase are combined and stored according to date and marked as the first construction carbon emissions data.

[0031] Furthermore, the analysis unit is configured with a carbon emission analysis strategy, which includes:

[0032] Correlation analysis between carbon emissions and temperature: Based on the environmental data of the building materials transportation stage and the construction stage, the daily average temperature is used as the horizontal axis and the carbon emissions are used as the vertical axis to draw scatter plots for the building materials transportation stage and the construction stage respectively; using computer software, the average temperature and carbon emissions of the building materials transportation stage and the construction stage are fitted and regressed respectively to obtain the fitted regression model of average temperature and carbon emissions;

[0033] The temperature is divided into different temperature ranges, including low temperature range, medium temperature range and high temperature range, and the average carbon emissions in the material transportation and construction stages in each temperature range are calculated respectively; Correlation analysis between carbon emissions and rainfall: According to the size of rainfall, the daily rainfall is divided into different categories, including no rain, light rain, moderate rain and heavy rain; for each rainfall category, the average and standard deviation of carbon emissions in the building materials transportation stage and the construction stage under each rainfall category are calculated respectively:

[0034] Consider the continuous rainfall of Q0 days as a rainfall event, record the start date, end date, total rainfall and the corresponding total carbon emissions in the building materials transportation stage or construction stage of each rainfall event; calculate the change in carbon emissions corresponding to the unit rainfall in each rainfall event;

[0035] According to the total rainfall of the rainfall event, the rainfall lag time Q1 is set, and the value range of Q1 is [1, 3]. The changes in carbon emissions within the lag time are counted.

[0036] Furthermore, the model building unit is configured with a model building strategy, and the model building strategy includes:

[0037] Based on the first construction carbon emission data, the average temperature, rainfall, fuel carbon emission, electricity carbon emission and artificial carbon emission on the same date are connected in series to form a carbon emission data vector, which is marked as the second carbon emission data;

[0038] The second emission data is divided into a carbon emission training set and a carbon emission test set in a ratio of 8:2;

[0039] The mean absolute percentage error and root mean square error are set as model evaluation indicators; the mean absolute percentage error calculation formula is as follows: The root mean square error calculation formula is as follows: where Y v represents the actual carbon emissions on day v, represents the carbon emissions predicted by the model on day v, V represents the total number of days predicted by the model; set the model qualification thresholds ma and rm;

[0040] Set the model training hyperparameters, set the learning rate to x1, the number of model training rounds to x2, the number of encoder layers to x3, and the number of decoder layers to x1. Use the carbon emission training set to train the Informer model according to the set model training hyperparameters. After the post-training is completed, use the carbon emission test set to test the trained Informer model, output the evaluation index, and judge whether MA and RM satisfy MA≤ma and RM≤rm. If MA≤ma and RM≤rm are satisfied, save the trained Informer model and mark it as a carbon emission prediction model. If MA≤ma and RM≤rm are not satisfied, use the carbon emission training set to train the trained Informer model again until the output evaluation indicators MA and RM satisfy MA≤ma and RM≤rm to obtain the carbon emission prediction model.

[0041] Furthermore, the data prediction unit is configured with a carbon emission prediction strategy, which includes:

[0042] According to the prediction requirements, a period of historical carbon emission data of the construction phase is obtained, and the fuel carbon emissions, electricity carbon emissions and labor carbon emissions of the same date are connected in series to form a carbon emission data vector, which is then input into the carbon emission prediction model to obtain the carbon emission prediction results.

[0043] In a second aspect, the present application provides a method for intelligent analysis of carbon emissions from construction projects, comprising the following steps:

[0044] Acquire construction project related data and perform data preprocessing on the construction project related data;

[0045] Collect carbon emission factors related to construction projects and build a carbon emission factor library;

[0046] Calculate the carbon emissions of construction projects based on the carbon emission factor library and relevant data of construction projects, and analyze and process the carbon emissions of construction projects;

[0047] Build a carbon emission prediction model and conduct model training. After completion, predict the carbon emissions of construction projects.

[0048] Beneficial effects of the present invention: The present invention obtains construction project related data and performs data preprocessing on the construction project related data; collects carbon emission factors related to the construction project and constructs a carbon emission factor library; calculates the carbon emissions of the construction project based on the carbon emission factor library and the construction project related data, and analyzes and processes the carbon emissions of the construction project; constructs a carbon emission prediction model and performs model training, and predicts the carbon emissions of the construction project after completion; can simply, quickly and accurately calculate the carbon emissions in the construction material transportation process and the construction process in the construction project, and at the same time, make real-time predictions on the carbon emissions in the construction process;

[0049] The present invention tests the carbon emissions in the building materials transportation stage and the construction stage by collecting energy consumption, because the consumption is relatively easy to obtain and measure; through simple calculations, the estimated value of carbon emissions can be quickly obtained, and there is a clear physical relationship between energy consumption and carbon emissions, which can ensure the accuracy of the calculation results; by establishing a carbon emission prediction model to predict carbon emissions in the construction stage, the degree of impact of construction projects on the environment can be intuitively displayed, and the prediction results can provide decision-making basis for construction units, helping them to choose more environmentally friendly and low-carbon construction plans to reduce the overall carbon emissions of construction projects; the carbon emissions of construction projects are analyzed in combination with temperature and rainfall. The combined influence of temperature and rainfall in construction projects plays an important role in carbon emissions. Combining temperature and rainfall can improve the accuracy of carbon emission analysis, the reliability of carbon emission prediction and the effectiveness of strategy formulation. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a functional block diagram of the system of the present invention;

[0051] Figure 2 is a flow chart of the method steps of the present invention;

[0052] Figure 3 This is a schematic diagram of the building materials transportation data structure of the present invention;

[0053] Figure 4 It is a schematic diagram of the building construction data structure of the present invention;

[0054] Figure 5 It is a schematic structural diagram of the electronic device of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] Example 1, please refer to Figure 1 As shown, in the first aspect, the present application provides a construction engineering carbon emission intelligent analysis system, including a data acquisition module, a carbon emission factor module, a carbon emission accounting module and a carbon emission prediction module;

[0057] The data acquisition module includes a collection unit and a processing unit, the collection unit is used to obtain construction engineering related data, and the processing unit is used to perform data preprocessing on the construction engineering related data;

[0058] The collection unit is configured with a collection strategy, which includes:

[0059] Obtain daily energy consumption data, environmental data, and labor data during the building materials transportation stage and the building construction stage;

[0060] Energy consumption data include: daily fossil fuel consumption and electricity consumption. Daily fossil fuel consumption includes: fossil fuel consumption caused by transportation, fossil fuel consumption caused by construction equipment, and fossil fuel consumption caused by living equipment; daily electricity consumption includes: electricity consumption caused by construction equipment and electricity consumption caused by living equipment; because carbon emissions in the construction materials transportation stage mainly come from fossil fuel consumption and electricity consumption, calculating carbon emissions in the construction materials transportation stage based on fossil fuel consumption and electricity consumption can improve the accuracy and efficiency of carbon emission calculations;

[0061] Environmental data include: daily average temperature and rainfall;

[0062] The manual data include: the types of work performed by the staff each day, and the specific number of people in each type of work;

[0063] The processing unit is configured with a processing strategy, which includes: dividing the types of work of the staff in the building material transportation stage and the construction stage into light labor work and heavy labor work according to the labor intensity, and obtaining the number of light labor work and heavy labor work in the building material transportation stage and the construction stage according to the specific number of people in each type of work; in this embodiment, light labor work refers to the work of the arms and torso and the work of the hips and legs, such as transportation work such as trucks and construction equipment; heavy work refers to continuous arm movements and compound work of the arms and torso, such as carrying heavy objects, shoveling, digging, etc.;

[0064] See also Figure 3 and Figure 4 As shown, the average temperature, rainfall, fossil fuel consumption, electricity energy consumption, number of light labor workers and number of heavy labor workers in the construction material transportation stage and the construction stage are sorted and stored according to the acquisition date, and then classified according to the construction project stage to which the date belongs, to obtain the building material transportation data and construction data; each stage contains several dates, and each date contains various consumptions and various labor workers;

[0065] In a specific embodiment, excessively high or low temperatures will affect the energy consumption of construction equipment and the performance of building materials. For example, when the temperature exceeds 30°C, the cooling fan of the construction equipment may continue to run at high speed, resulting in increased electricity or fuel consumption of the equipment, thereby increasing carbon emissions. In a low temperature environment, the setting time of concrete is prolonged, and it may be necessary to heat and insulate it, which also consumes energy. The amount of rainfall will affect the progress of the construction phase and building materials. For example, rainfall will cause open-air construction to be interrupted, and rainfall may damage building materials. For example, powdered materials such as cement will clump when exposed to water, lose their use value, and need to be re-purchased.

[0066] The carbon emission factor module is used to collect carbon emission factors related to construction projects and build a carbon emission factor library;

[0067] The carbon emission factor module is configured with a factor collection construction strategy, which includes: Collecting fuel carbon emission factors: Obtain the types of fossil fuels used in construction projects, including natural gas, crude oil, general kerosene, diesel, coke, fuel oil and gasoline; please refer to Table 1, and obtain the corresponding average low calorific value, carbonization rate and unit calorific value carbon content of the fossil fuel, and calculate the fuel carbon emission factor of the fossil fuel; the calculation formula is as follows: NCV i is the average lower calorific value of the i-th fossil fuel; FC i is the net consumption of the ith fossil fuel; CC i is the carbon content per unit calorific value of the i-th fossil fuel; OFi is the carbon oxidation rate of the i-th fossil fuel; 44 / 12 is the conversion coefficient of carbon C into carbon dioxide CO2, that is, the relative atomic weight of CO2 / C, the atomic weight of C is 12, and the atomic weight of CO2 is 44; let FC i is 1 kg or 1 cubic meter, the carbon emission factor of a certain fossil fuel can be calculated; for example, according to Table 1, the carbon emission factor of gasoline is calculated.

[0068] E 汽油 =43124*0.98*18.9*10 -6 *1=2.93kgCO2 / kg;

[0069] Table 1: Average lower calorific value, carbon oxidation rate and carbon content per unit calorific value of fossil fuels

[0070]

[0071] Collect electricity carbon emission factors: According to the grid area where the construction project is actually located, obtain the average carbon dioxide emission factor of the grid area, marked as the electricity carbon emission factor; according to the province where the construction project is actually located, obtain the average carbon dioxide emission factor of the province as the electricity carbon emission factor. In this embodiment, the electricity carbon emission factor is the average carbon dioxide emission factor of a provincial grid, and the value is 0.763kgCO2 / kWh

[0072] Collect carbon emission factors of building materials: obtain the types of building materials used in the construction process, and obtain the corresponding carbon emission factors of building materials according to the types of building materials used; you can sort out the carbon emission factors of commonly used building materials by consulting relevant standards and literature, for example, the carbon emission factor of C30 concrete is 295kgCO2 / m 3 The carbon emission factor of granite is 3.15kgCO2 / m 3 , the carbon emission factor of PVC pipe is 9740kgCO2 / t;

[0073] Collect artificial carbon emission factors: obtain carbon emission factors for light labor work and heavy labor work respectively; artificial carbon emission is mainly carbon emission generated by workers performing on-site labor during the construction process, mainly from carbon dioxide produced by respiration, food digestion and metabolism, and intestinal microbial fermentation; in this embodiment, the carbon emission factor for light labor work is 2.24kgCO2 / person·work day, and the carbon emission factor for heavy labor work is 2.83kgCO2 / person·work day;

[0074] The fuel carbon emission factor and the electricity carbon emission factor are marked as energy carbon emission factors, and the energy carbon emission factor, the collected artificial carbon emission factor and the building material carbon emission factor are classified and stored and marked as a carbon emission factor library;

[0075] In the specific implementation process, the carbon emission factor is a coefficient that quantifies greenhouse gas emissions caused by production or consumption activities, usually expressed in units of activity; the carbon emission factor, also known as the carbon emission coefficient, is an indicator used to estimate the amount of carbon dioxide emitted in a specific activity or process; therefore, determining the carbon emission factor is a key link in summarizing the carbon emissions of prefabricated buildings; to ensure the accuracy of the calculation, it is very important to choose a reasonable carbon emission coefficient.

[0076] The carbon emission accounting module includes a calculation unit and an analysis unit. The calculation unit calculates the carbon emission of the construction project based on the carbon emission factor library and the relevant data of the construction project, and the analysis unit is used to analyze and process the carbon emission of the construction project;

[0077] The calculation unit is configured with a carbon emission calculation strategy, which includes:

[0078] Calculate carbon emissions during the building materials transportation stage: Calculate fuel carbon emissions, electricity carbon emissions, and labor carbon emissions during the building materials transportation stage based on building materials transportation data, fuel carbon emission factors, electricity carbon emission factors, and labor carbon emission factors; the fuel carbon emission calculation formula is as follows: Among them C YR (a) represents the fuel carbon emission on day a during the construction materials transportation stage, R1 ka represents the consumption of the kth fuel on day a, F k represents the carbon emission factor of the kth fuel; the calculation formula for electricity carbon emissions is as follows: C YD (a) = D1 a *U; where C YD (a) represents the electricity carbon emissions on day a during the building materials transportation stage, D1 a represents the amount of electricity consumed on day a during the building materials transportation phase, and U represents the carbon emission factor of electricity; the calculation formula for artificial carbon emissions is as follows: YG (a) = G1 1a *B1+G1 2a *B2, where C YG (a) represents the artificial carbon emissions on day a during the construction materials transportation stage, G1 1a represents the number of people doing light labor on day a of the building materials transportation stage, B1 represents the carbon emission factor of light labor; G1 2a represents the number of people doing heavy labor in the construction materials transportation stage, and B2 represents the carbon emission factor of heavy labor;

[0079] Then calculate the carbon emissions in the transportation stage through the carbon emissions calculation formula. The carbon emissions calculation formula in the transportation stage is as follows: Among them C YS represents the carbon emissions from the building materials transportation stage, and A represents the total number of days in the building materials transportation stage;

[0080] For example, on a certain day, the transportation of building materials consumed 510m3 of diesel. 3 , gasoline consumption 120m 3 , power consumption is 85kwh, a total of 21 people are working, 12 are light labor, and 9 are heavy labor; and the diesel carbon emission factor is 3.1kgCO2 / m 3 The carbon emission factor of gasoline is 2.93kgCO2 / m 3 , the carbon emission factor of electricity is 0.763kgCO2 / kWh, the carbon emission factor of light labor is 2.24kgCO2 / person·workday, and the carbon emission factor of heavy labor is 2.83kgCO2 / person·workday; the carbon emission of building materials transportation on that day is:

[0081] C YS (a) = C YR (a)+C YD (a)+C YG (a)=(510*3.1+120*2.93)+(85*0.763)+(12*2.24+9*2.83)=2051.725kgCO2;

[0082] Calculate carbon emissions during the construction phase: Calculate fuel carbon emissions, electricity carbon emissions and labor carbon emissions during the construction phase based on construction data, fuel carbon emission factors, electricity carbon emission factors and labor carbon emission factors; the fuel carbon emission calculation formula is as follows: Among them C JR (b) represents the fuel carbon emission on day b during the construction phase, R2 kb represents the consumption of the kth fuel on day b; the calculation formula for electricity carbon emissions is as follows: C JD (b) = D2 b *U; where C JD (b) represents the carbon emissions of electricity on day b during the construction phase, D2 B represents the electricity consumed on day b during the construction phase; the artificial carbon emission calculation formula is as follows C JG (b) = G2 1b *B1+G2 2b *B2, where C JG (b) represents the artificial carbon emissions on day b during the construction materials transportation phase, G2 1b Represents the number of people doing light labor on day b during the construction phase; G2 2b The number of people representing heavy labor work during the construction phase;

[0083] The carbon emissions in the transportation phase are then calculated using the carbon emissions calculation formula for the construction phase. The carbon emissions calculation formula for the construction phase is as follows: Among them C JSrepresents the carbon emissions during the construction phase, and N represents the total number of days during the construction phase;

[0084] For example, on a certain day, construction work consumed 80m diesel. 3 , gasoline consumption 92m 3 , power consumption is 300kwh, a total of 214 people are working, 84 are light labor, 130 are heavy labor; and the diesel carbon emission factor is 3.1kgCO2 / m 3 The carbon emission factor of gasoline is 2.93kgCO2 / m 3 , the carbon emission factor of electricity is 0.763kgCO2 / kWh, the carbon emission factor of light labor is 2.24kgCO2 / person·workday, and the carbon emission factor of heavy labor is 2.83kgCO2 / person·workday; the carbon emission of building materials transportation on that day is:

[0085] C JS (a) = C JR (a)+C JD (a)+C JG (a)=(80*3.1+92*2.93)+(300*0.763)+(84*2.24+130*2.83)=1315.96kgCO2;

[0086] The analysis unit is configured with a carbon emission analysis strategy, which includes:

[0087] Correlation analysis between carbon emissions and temperature: Based on the environmental data of the building materials transportation stage and the construction stage, the daily average temperature is used as the horizontal axis and the carbon emissions are used as the vertical axis to draw scatter plots for the building materials transportation stage and the construction stage respectively; using computer software, the average temperature and carbon emissions of the building materials transportation stage and the construction stage are fitted and regressed respectively to obtain a fitting regression model of average temperature and carbon emissions; for example, in linear regression, the fitting regression model of average temperature x and carbon emissions y is y=a+bx, and the model can quantitatively describe the degree of influence of temperature on carbon emissions; in y=a+bx, the value of b represents the average change in carbon emissions for every degree increase in temperature;

[0088] The temperature is divided into different temperature intervals, including: a low temperature interval, a medium temperature interval and a high temperature interval. In this embodiment, the low temperature interval is below 10°C, the medium temperature interval is [10°C, 25°C], and the high temperature interval is greater than 25°C; the average values ​​of carbon emissions in the material transportation and construction stages in each temperature interval are calculated respectively; by comparing the average values ​​of different intervals, the stage-by-stage impact of temperature on carbon emissions can be intuitively seen; for example, it may be found that the average value of carbon emissions in the construction stage in the high temperature interval is significantly higher than that in the low temperature interval, which may be due to the increase in energy consumption of the cooling system of the construction equipment under high temperature and other reasons;

[0089] Correlation analysis between carbon emissions and rainfall: According to the size of rainfall, daily rainfall is divided into different categories, including: no rain, light rain, moderate rain and heavy rain; in this embodiment, no rain refers to rainfall less than 1mm, light rain refers to rainfall of [1mm, 10mm], light rain refers to rainfall of (10mm, 25mm], and heavy rain refers to rainfall greater than 25mm; for each rainfall category, the mean and standard deviation of carbon emissions in the building materials transportation stage and the construction stage under each rainfall category are calculated respectively; for example, the rainless dates in the entire building materials transportation stage are collected, and the mean and standard deviation of carbon emissions under all rainless dates in the building materials transportation stage are calculated; by comparing the mean and standard deviation of carbon emissions under different rainfall categories, the general impact of rainfall on carbon emissions and the degree of data dispersion can be understood;

[0090] Consider Q0 consecutive days of rainfall as a rainfall event, record the start date, end date, total rainfall, and the corresponding total carbon emissions in the building materials transportation stage or the construction stage of each rainfall event; calculate the change in carbon emissions per unit rainfall in each rainfall event; in this embodiment, Q0 is 2 days, that is, 2 consecutive days of rainfall are considered as a rainfall event; for example, the total rainfall of a rainfall event is 38 mm, and the total carbon emissions increase by 48CO2 / m 3 , then the change in carbon emissions per unit rainfall is 48 / 38=12.6; by analyzing multiple rainfall events, we can understand the dynamic change of carbon emissions during rainfall;

[0091] According to the total rainfall of the rainfall event, the rainfall hysteresis time Q1 is set, and the value range of Q1 is [1, 3], and the changes in carbon emissions within the hysteresis time are counted; in this embodiment, when the total rainfall of the rainfall event is [0, 25ml], Q1=1 day, when it is (25, 50ml], Q1=2 days, and when the total rainfall is greater than 50mm, Q1=3 days; the setting of Q1 should take into account that the impact of rainfall on carbon emissions may have a hysteresis, for example, the cleaning of accumulated water on the construction site after rainfall may be carried out within a few days after the rain stops; determine the possible hysteresis time; count the changes in carbon emissions within the hysteresis time, for example, count the changes in carbon emissions in the material transportation and construction stages on the first, second, and third days after the rain stops; observe whether there is a delayed increase in carbon emissions after rainfall, and analyze its relationship with the amount of rainfall;

[0092] In the specific implementation process, there is a clear physical relationship between energy consumption and carbon emissions, that is, every certain amount of energy consumed will produce a corresponding amount of carbon emissions; this relationship can be quantified through scientific methods to ensure the accuracy of the calculation results; and the construction progress and resource usage of construction projects will be dynamically adjusted due to weather changes; the impact of temperature and rainfall on carbon emissions in construction projects is not isolated, but intertwined; for example, if there is no rainfall in hot weather, it may lead to an increase in the amount of water used for concrete maintenance at the construction site because the water evaporates quickly; and if there is rainfall, the frequency of artificial watering may be reduced, thereby changing the energy consumption and carbon emissions of water resource utilization related equipment; by combining these two factors, the real impact of complex environmental conditions on carbon emissions during the actual construction process can be more accurately reflected; considering that carbon emissions from construction projects are affected by the interaction of multiple factors, combining temperature and rainfall can construct a more accurate and realistic prediction model.

[0093] The carbon emission prediction module includes a model building unit and a data prediction unit. The model building unit is used to build a carbon emission prediction model and perform model training. The data prediction unit is used to predict the carbon emissions of construction projects.

[0094] Based on the first construction carbon emission data, the average temperature, rainfall, fuel carbon emission, electricity carbon emission and artificial carbon emission on the same date are connected in series to form a carbon emission data vector, which is marked as the second carbon emission data. In this embodiment, the carbon emission data vector is in the form of [T(b), M(b), C JR (b), C JD (b), C JG (b)]; where T(b) represents the average temperature on the bth day, and M(b) represents the rainfall on the bth day; marked as the second carbon emission data; the second emission data is divided into a carbon emission training set and a carbon emission test set in a ratio of 8:2;

[0095] The mean absolute percentage error and root mean square error are set as model evaluation indicators; the mean absolute percentage error calculation formula is as follows: The root mean square error calculation formula is as follows: where Y v represents the actual carbon emissions on day v, represents the carbon emissions predicted by the model on day v, and V represents the total number of days predicted by the model; set the model qualification thresholds ma and rm; in this embodiment, ma = 0.8, rm = 0.8;

[0096] Set the model training hyperparameters, set the learning rate to x1, the number of model training rounds to x2, the number of encoder layers to x3, and the number of decoder layers to x1. In this embodiment, the model training hyperparameter settings include: setting the learning rate x1 to 0.001, setting the number of model training times x2 to 200, setting the number of encoder layers x3 to 2, and setting the number of decoder layers x4 to 2;

[0097] The Informer model is trained using the carbon emission training set according to the set model training hyperparameters. After the post-training is completed, the trained Informer model is tested using the carbon emission test set, and the evaluation indicators MA and RM are output to determine whether MA and RM satisfy MA≤ma and RM≤rm. If MA≤ma and RM≤rm are satisfied, the trained Informer model is saved and marked as a carbon emission prediction model. If MA≤ma and RM≤rm are not satisfied, the trained Informer model is trained again using the carbon emission training set until the output evaluation indicators MA and RM satisfy MA≤ma and RM≤rm, and a carbon emission prediction model is obtained. For example, the model qualification thresholds ma=0.8 and rm=0.8 are set. After the model training is completed, the model is tested using the carbon emission test set, and the evaluation indicators MA and RM of the model are output. When the evaluation indicators output by the model satisfy MA≤0.8 and RM≤0.8, the model is qualified and marked as an emission prediction model. When the evaluation indicators output by the model do not satisfy MA≤0.8 and RM≤0.8, the model is unqualified, and the model training is performed again.

[0098] The data prediction unit is equipped with a carbon emission prediction strategy, which includes: obtaining a period of historical carbon emission data of the construction phase according to the prediction requirements. For example, if the carbon emission of the construction phase in the next 7 days needs to be predicted, it is necessary to obtain the carbon emission data and environmental data of the construction phase in the past 30 days, and connect the fuel carbon emission, electricity carbon emission and artificial carbon emission of the same date in series to form a carbon emission data vector, and then input it into the carbon emission prediction model to obtain the carbon emission prediction result;

[0099] In the specific implementation process, the Informer model is an efficient time series prediction model improved based on the Transformer model. It mainly consists of two parts, the encoder and the decoder. It has high prediction accuracy, computational efficiency and good generalization ability in time series prediction. The smaller the mean absolute percentage error and the root mean square error of the model output, the better the performance of the model, that is, the higher the prediction accuracy. To ensure the accuracy of the prediction, the longer the prediction time is, the more historical data is required. The model is established based on temperature, rainfall and carbon emissions, which can better capture the intrinsic connection between changes in weather conditions and carbon emissions, thereby more accurately predicting carbon emissions under different weather combinations. The model combining temperature and rainfall can effectively reduce the prediction error and provide a more reliable decision-making basis for carbon emission management in construction projects.

[0100] Example 2, please refer to Figure 2 As shown, in the second aspect, the present application provides a method for intelligent analysis of carbon emissions from construction projects, comprising the following steps:

[0101] Step S1, obtaining construction project related data, and performing data preprocessing on the construction project related data; Step S1 includes the following sub-steps:

[0102] Step S101, obtaining daily energy consumption data, environmental data and labor data during the building materials transportation stage and the building construction stage;

[0103] Step S102, the energy consumption data includes: daily fossil fuel consumption and electric energy consumption, the daily fossil fuel consumption includes: fossil fuel consumption generated by transportation, fossil fuel consumption generated by construction equipment, and fossil fuel consumption generated by living equipment; the daily electric energy consumption includes: electric energy consumption generated by construction equipment and electric energy consumption generated by living equipment;

[0104] Step S103, environmental data includes: daily average temperature and rainfall;

[0105] Step S104, the manual data includes: the types of work of the staff every day, and the specific number of people in each type of work;

[0106] Step S105, classifying the types of work of the staff in the building materials transportation stage and the construction stage into light labor work and heavy labor work according to the labor intensity, and obtaining the number of light labor workers and heavy labor workers in the building materials transportation stage and the construction stage according to the specific number of people in each type of work;

[0107] Step S106, the energy consumption data, environmental data and labor data of each day in the building material transportation stage and the building construction stage are sorted and stored according to the acquisition date, and then classified according to the construction project stage to which the date belongs, to obtain the building material transportation data and the building construction data.

[0108] Step S2, collecting carbon emission factors related to construction projects and building a carbon emission factor library; Step S2 includes the following sub-steps:

[0109] Step S201, collecting fuel carbon emission factors: obtaining the types of fossil fuels used in the construction project, and obtaining the average lower calorific value, carbonization rate and carbon content per unit calorific value of the corresponding fossil fuels, and calculating the fuel carbon emission factors of the fossil fuels;

[0110] Step S202, collecting the electricity carbon emission factor: according to the power grid area to which the actual location of the construction project belongs, obtaining the average carbon dioxide emission factor of the power grid area, and marking it as the electricity carbon emission factor;

[0111] Step S203, collecting building material carbon emission factors: obtaining the types of building materials used in the construction process, and obtaining corresponding building material carbon emission factors according to the types of building materials used;

[0112] Step S204, collecting artificial carbon emission factors: obtaining carbon emission factors of light labor work and heavy labor work respectively;

[0113] Step S205, marking the fuel carbon emission factor and the electricity carbon emission factor as energy carbon emission factors, and classifying and storing the energy carbon emission factor, the collected artificial carbon emission factor and the building material carbon emission factor, and marking them as a carbon emission factor library.

[0114] Step S3, calculating the carbon emissions of the construction project based on the carbon emission factor library and the relevant data of the construction project, and analyzing and processing the carbon emissions of the construction project; Step S3 includes the following sub-steps:

[0115] Step S301, calculate the carbon emissions in the building materials transportation stage: calculate the fuel carbon emissions, electricity carbon emissions and labor carbon emissions in the building materials transportation stage based on the building materials transportation data, fuel carbon emission factors, electricity carbon emission factors and labor carbon emission factors; Step S302 includes the following sub-steps:

[0116] Step S3011, the fuel carbon emission calculation formula is as follows: Among them C YR (a) represents the fuel carbon emission on day a during the construction materials transportation stage, R1 ka represents the consumption of the kth fuel on day a, F k represents the carbon emission factor of the kth fuel;

[0117] Step S3012, the calculation formula of electricity carbon emission is as follows: C YD (a) = D1 a *U; where C YD (a) represents the electricity carbon emissions on day a during the building materials transportation stage, D1 a represents the amount of electricity consumed on day a during the building materials transportation phase, and U represents the carbon emission factor of electricity;

[0118] Step S3013, the artificial carbon emission calculation formula is as follows: YG (a) = G1 1a *B1+G1 2a *B2, where C YG (a) represents the artificial carbon emissions on day a during the construction materials transportation stage, G1 1a represents the number of people doing light labor on day a of the building materials transportation stage, B1 represents the carbon emission factor of light labor; G1 2a represents the number of people doing heavy labor in the construction materials transportation stage, and B2 represents the carbon emission factor of heavy labor;

[0119] Step S3014, the carbon emissions in the transportation stage are calculated using the carbon emissions calculation formula in the transportation stage. The carbon emissions calculation formula in the transportation stage is as follows: Among them C YS represents the carbon emissions from the building materials transportation stage, and A represents the total number of days in the building materials transportation stage;

[0120] Step S302, calculate the carbon emissions during the construction phase: calculate the fuel carbon emissions, electricity carbon emissions and labor carbon emissions during the construction phase based on the construction data, fuel carbon emission factors, electricity carbon emission factors and labor carbon emission factors; Step S303 includes the following sub-steps:

[0121] Step S3021, the fuel carbon emission calculation formula is as follows: Among them C JR (b) represents the fuel carbon emission on day b during the construction phase, R2 kb represents the consumption of the kth fuel on day b;

[0122] Step S3022, the calculation formula of electricity carbon emissions is as follows: C JD (b) = D2 b *U; where C JD (b) represents the carbon emissions of electricity on day b during the construction phase, D2 B represents the electricity consumed on day b during the construction phase;

[0123] Step S3023, the artificial carbon emission calculation formula is as follows: JG (b) = G2 1b *B1+G22b *B2, where C JG (b) represents the artificial carbon emissions on day b during the construction materials transportation phase, G2 1b Represents the number of people doing light labor on day b during the construction phase; G2 2b The number of people representing heavy labor work during the construction phase;

[0124] Step S3024, the carbon emissions in the transportation phase are calculated using the carbon emissions calculation formula in the construction phase. The carbon emissions calculation formula in the construction phase is as follows: Among them C JS represents the carbon emissions during the construction phase, and N represents the total number of days during the construction phase;

[0125] Step S303, the carbon emissions during the construction phase and the environmental data during the construction phase are combined and stored according to the date, and marked as the first construction carbon emissions data;

[0126] Step S304, correlation analysis between carbon emissions and temperature; Step S304 includes the following sub-steps:

[0127] Step S3041, based on the environmental data of the building materials transportation stage and the building construction stage, the daily average temperature is used as the horizontal axis and the carbon emission is used as the vertical axis to draw a scatter plot for the building materials transportation stage and the building construction stage respectively;

[0128] Step S3042, using computer software, respectively, the average temperature and carbon emissions in the building materials transportation stage and the building construction stage are fitted and regressed to obtain a fitted regression model of the average temperature and carbon emissions;

[0129] Step S3043, the air temperature is divided into different temperature intervals, including: a low temperature interval, a medium temperature interval, and a high temperature interval, and the average carbon emissions of the material transportation and construction stages in each temperature interval are calculated respectively;

[0130] Step S305, correlation analysis between carbon emissions and rainfall; Step S305 includes the following sub-steps:

[0131] Step S3051, dividing the daily rainfall into different categories according to the amount of rainfall, including: no rain, light rain, moderate rain and heavy rain;

[0132] Step S3052, for each rainfall category, respectively calculate the average and standard deviation of carbon emissions in the building materials transportation stage and the building construction stage under each rainfall category:

[0133] Step S3053, consider the continuous rainfall of Q0 days as a rainfall event, record the start date, end date, total rainfall and the corresponding total carbon emissions in the building materials transportation stage or the building construction stage of each rainfall event; calculate the carbon emission change corresponding to the unit rainfall in each rainfall event;

[0134] Step S3054: according to the total rainfall of the rainfall event, set the rainfall lag time Q1, where the value range of Q1 is [1, 3], and count the changes in carbon emissions within the lag time.

[0135] Step S4, constructing a carbon emission prediction model and performing model training, and after completion, predicting the carbon emissions of the construction project; Step S4 includes the following sub-steps:

[0136] Step S401, based on the first construction carbon emission data, the average temperature, rainfall, fuel carbon emission, electricity carbon emission and manual carbon emission on the same date are connected in series to form a carbon emission data vector, which is marked as the second carbon emission data;

[0137] Step S402, dividing the second emission data into a carbon emission training set and a carbon emission test set in a ratio of 8:2;

[0138] Step S403, setting the mean absolute percentage error and the root mean square error as model evaluation indicators; the mean absolute percentage error calculation formula is as follows: The root mean square error calculation formula is as follows: where Y v represents the actual carbon emissions on day v, represents the carbon emissions predicted by the model on day v, V represents the total number of days predicted by the model; set the model qualification thresholds ma and rm;

[0139] Step S404, setting model training hyperparameters, setting the learning rate to x1, the number of model training rounds to x2, the number of encoder layers to x3, and the number of decoder layers to x1, and performing model training on the Informer model using the carbon emission training set according to the set model training hyperparameters;

[0140] Step S405, after the post-training is completed, the trained Informer model is tested using the carbon emission test set, and the evaluation index is output to determine whether MA and RM satisfy MA≤ma and RM≤rm. If MA≤ma and RM≤rm are satisfied, the trained Informer model is saved and marked as a carbon emission prediction model. If MA≤ma and RM≤rm are not satisfied, the trained Informer model is retrained using the carbon emission training set until the output evaluation indexes MA and RM satisfy MA≤ma and RM≤rm, thereby obtaining a carbon emission prediction model.

[0141] Step S406, according to the prediction requirements, obtain a period of historical carbon emission data of the construction stage, and connect the fuel carbon emissions, electricity carbon emissions and manual carbon emissions of the same date in series to form a carbon emission data vector, which is then input into the carbon emission prediction model to obtain the carbon emission prediction result.

[0142] Example 3, please refer to Figure 5 As shown, Figure 5 The structural schematic diagram of an electronic device is illustrated, and the electronic device may include: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus. The memory stores computer-readable instructions, and the processor can call the instructions in the memory. When the computer-readable instructions are executed by the processor, the steps in a method for intelligent analysis of carbon emissions of a construction project are executed to achieve the following functions: obtaining data related to the construction project and preprocessing the data related to the construction project; collecting carbon emission factors related to the construction project and building a carbon emission factor library; calculating the carbon emissions of the construction project based on the carbon emission factor library and the data related to the construction project, and analyzing and processing the carbon emissions of the construction project; building a carbon emission prediction model, and training the model, and predicting the carbon emissions of the construction project after completion.

[0143] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk.

[0144] Embodiment 4, the present application also provides a computer-readable storage medium, the present application provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned intelligent analysis method for carbon emissions of construction projects are executed to achieve the following functions: obtain construction project-related data, and perform data preprocessing on the construction project-related data; collect carbon emission factors related to the construction project, and construct a carbon emission factor library; calculate the carbon emissions of the construction project based on the carbon emission factor library and the construction project-related data, and analyze and process the carbon emissions of the construction project; construct a carbon emission prediction model, and perform model training, and after completion, predict the carbon emissions of the construction project.

[0145] Through the description of the above implementation methods, the embodiments of the present invention can be provided as methods, systems or computer program products. Based on such an understanding, the above technical solutions can be essentially or partly contributed to the prior art in the form of software products, which can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and include several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0146] In the embodiments provided in the present application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or units can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of systems, modules and units can be electrical, mechanical or other forms.

[0147] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An intelligent analysis system for carbon emissions from construction projects, characterized in that: It includes data acquisition module, carbon emission factor module, carbon emission accounting module and carbon emission prediction module; The data acquisition module includes a collection unit and a processing unit, the collection unit is used to obtain construction engineering related data, and the processing unit is used to perform data preprocessing on the construction engineering related data; The carbon emission factor module is used to collect carbon emission factors related to construction projects and build a carbon emission factor library; The carbon emission accounting module includes a calculation unit and an analysis unit. The calculation unit calculates the carbon emission of the construction project based on the carbon emission factor library and the relevant data of the construction project. The analysis unit is used to analyze and process the carbon emission of the construction project. The carbon emission prediction module includes a model building unit and a data prediction unit. The model building unit is used to build a carbon emission prediction model and perform model training, and the data prediction unit is used to predict the carbon emissions of the construction project.

2. According to claim 1, a construction engineering carbon emission intelligent analysis system is characterized in that: The collection unit is configured with a collection strategy, which includes: Obtain daily energy consumption data, environmental data, and labor data during the building materials transportation stage and the building construction stage; Energy consumption data include: daily fossil fuel consumption and electricity energy consumption. Daily fossil fuel consumption includes: fossil fuel consumption generated by transportation, fossil fuel consumption generated by construction equipment, and fossil fuel consumption generated by living equipment; daily electricity energy consumption includes: electricity energy consumption generated by construction equipment and electricity energy consumption generated by living equipment; Environmental data include: daily average temperature and rainfall; Manual data includes: the types of work done by staff every day, and the specific number of people doing each type of work.

3. The intelligent analysis system for carbon emissions from construction projects according to claim 2 is characterized in that: The processing unit is configured with a processing strategy, which includes: The types of work of the staff in the building materials transportation stage and the construction stage are divided into light labor work and heavy labor work according to the labor intensity, and the number of light labor work and heavy labor work in the building materials transportation stage and the construction stage are obtained according to the specific number of people in each type of work; The daily energy consumption data, environmental data and labor data of the building materials transportation stage and the construction stage are sorted and stored according to the acquisition date, and then classified according to the construction project stage to which the date belongs, to obtain the building materials transportation data and construction data.

4. The intelligent analysis system for carbon emissions from construction projects according to claim 3 is characterized in that: The carbon emission factor module is configured with a factor collection and construction strategy, which includes: Collect fuel carbon emission factors: obtain the types of fossil fuels used in construction projects, and obtain the corresponding average lower calorific value, carbonization rate and carbon content per unit calorific value of the fossil fuels, and calculate the fuel carbon emission factors of the fossil fuels; Collect electricity carbon emission factors: According to the grid area where the construction project is actually located, obtain the average carbon dioxide emission factor of the grid area and mark it as the electricity carbon emission factor; Collect building materials carbon emission factors: obtain the types of building materials used in the construction process, and obtain the corresponding building materials carbon emission factors based on the types of building materials used; Collect artificial carbon emission factors: obtain carbon emission factors for light labor work and heavy labor work respectively; The fuel carbon emission factors and electricity carbon emission factors are marked as energy carbon emission factors, and the energy carbon emission factors, collected artificial carbon emission factors and building materials carbon emission factors are classified and stored and marked as a carbon emission factor library.

5. The intelligent analysis system for carbon emissions from construction projects according to claim 4 is characterized in that: The calculation unit is configured with a carbon emission calculation strategy, which includes: Calculate carbon emissions during the building materials transportation stage: Calculate fuel carbon emissions, electricity carbon emissions and labor carbon emissions during the building materials transportation stage based on building materials transportation data, fuel carbon emission factors, electricity carbon emission factors and labor carbon emission factors; the fuel carbon emission calculation formula is as follows: Among them C YR (a) represents the fuel carbon emission on day a during the construction materials transportation stage, R1 ka represents the consumption of the kth fuel on day a, F k represents the carbon emission factor of the kth fuel; the calculation formula for electricity carbon emissions is as follows: C YD (a) = D1 a *U; where C YD (a) represents the electricity carbon emissions on day a during the building materials transportation stage, D1 a represents the amount of electricity consumed on day a during the building materials transportation phase, and U represents the carbon emission factor of electricity; the calculation formula for artificial carbon emissions is as follows: YG (a) = G1 1a *B1+G1 2a *B2, where C YG (a) represents the artificial carbon emissions on day a during the construction materials transportation stage, G1 1a represents the number of people doing light labor on day a of the building materials transportation stage, B1 represents the carbon emission factor of light labor; G1 2a represents the number of people doing heavy labor in the construction materials transportation stage, and B2 represents the carbon emission factor of heavy labor; Then calculate the carbon emissions in the transportation stage through the carbon emissions calculation formula. The carbon emissions calculation formula in the transportation stage is as follows: Among them C YS represents the carbon emissions during the building materials transportation stage, and A represents the total number of days during the building materials transportation stage.

6. The intelligent analysis system for carbon emissions from construction projects according to claim 5 is characterized in that: Carbon emission calculation strategies also include: Calculate carbon emissions during the construction phase: Calculate fuel carbon emissions, electricity carbon emissions and labor carbon emissions during the construction phase based on construction data, fuel carbon emission factors, electricity carbon emission factors and labor carbon emission factors; the fuel carbon emission calculation formula is as follows: Among them C JR (b) represents the fuel carbon emission on day b during the construction phase, R2 kb represents the consumption of the kth fuel on day b; the calculation formula for electricity carbon emissions is as follows: C JD (b) = D2 b *U; where C JD (b) represents the carbon emissions of electricity on day b during the construction phase, D2 B represents the electricity consumed on day b during the construction phase; the artificial carbon emission calculation formula is as follows C JG (b) = G2 1b *B1+G2 2b *B2, where C JG (b) represents the artificial carbon emissions on day b during the construction materials transportation phase, G2 1b Represents the number of people doing light labor on day b during the construction phase; G2 2b The number of people representing heavy labor work during the construction phase; Then, the carbon emissions during the construction phase are calculated using the carbon emissions calculation formula during the construction phase. The carbon emissions calculation formula during the construction phase is as follows: Among them C JS represents the carbon emissions during the construction phase, and N represents the total number of days during the construction phase; The carbon emissions during the construction phase and the environmental data during the construction phase are combined and stored according to date and marked as the first construction carbon emissions data.

7. The intelligent analysis system for carbon emissions from construction projects according to claim 6 is characterized in that: The analysis unit is configured with a carbon emission analysis strategy, which includes: Correlation analysis between carbon emissions and temperature: Based on the environmental data of the building materials transportation stage and the construction stage, the daily average temperature is used as the horizontal axis and the carbon emissions are used as the vertical axis to draw scatter plots for the building materials transportation stage and the construction stage respectively; using computer software, the average temperature and carbon emissions of the building materials transportation stage and the construction stage are fitted and regressed respectively to obtain the fitted regression model of average temperature and carbon emissions; The temperature is divided into different temperature ranges, including low temperature range, medium temperature range and high temperature range, and the average carbon emissions in the material transportation and construction stages in each temperature range are calculated respectively; Correlation analysis between carbon emissions and rainfall: According to the size of rainfall, the daily rainfall is divided into different categories, including no rain, light rain, moderate rain and heavy rain; for each rainfall category, the average and standard deviation of carbon emissions in the building materials transportation stage and the construction stage under each rainfall category are calculated respectively: Consider the continuous rainfall of Q0 days as a rainfall event, record the start date, end date, total rainfall and the corresponding total carbon emissions in the building materials transportation stage or construction stage of each rainfall event; calculate the change in carbon emissions corresponding to the unit rainfall in each rainfall event; According to the total rainfall of the rainfall event, the rainfall lag time Q1 is set, and the value range of Q1 is [1, 3]. The changes in carbon emissions within the lag time are counted.

8. The intelligent analysis system for carbon emissions from construction projects according to claim 7 is characterized in that: The model building unit is configured with a model building strategy, which includes: Based on the first construction carbon emission data, the average temperature, rainfall, fuel carbon emission, electricity carbon emission and artificial carbon emission on the same date are connected in series to form a carbon emission data vector, which is marked as the second carbon emission data; The second emission data is divided into a carbon emission training set and a carbon emission test set in a ratio of 8:2; The mean absolute percentage error and root mean square error are set as model evaluation indicators; the mean absolute percentage error calculation formula is as follows: The root mean square error calculation formula is as follows: where Y v represents the actual carbon emissions on day v, represents the carbon emissions predicted by the model on day v, V represents the total number of days predicted by the model; set the model qualification thresholds ma and rm; Set the model training hyperparameters, set the learning rate to x1, the number of model training rounds to x2, the number of encoder layers to x3, and the number of decoder layers to x1. Use the carbon emission training set to train the Informer model according to the set model training hyperparameters. After the post-training is completed, use the carbon emission test set to test the trained Informer model, output the evaluation index, and judge whether MA and RM satisfy MA≤ma and RM≤rm. If MA≤ma and RM≤rm are satisfied, save the trained Informer model and mark it as a carbon emission prediction model. If MA≤ma and RM≤rm are not satisfied, use the carbon emission training set to train the trained Informer model again until the output evaluation indicators MA and RM satisfy MA≤ma and RM≤rm to obtain the carbon emission prediction model.

9. The intelligent analysis system for carbon emissions from construction projects according to claim 8 is characterized in that: The data prediction unit is configured with a carbon emission prediction strategy, which includes: According to the prediction requirements, a period of historical carbon emission data of the construction phase is obtained, and the fuel carbon emissions, electricity carbon emissions and labor carbon emissions of the same date are connected in series to form a carbon emission data vector, which is then input into the carbon emission prediction model to obtain the carbon emission prediction results.

10. A method for intelligent analysis of carbon emissions from construction projects, used to implement a system for intelligent analysis of carbon emissions from construction projects as claimed in any one of claims 1 to 9, characterized in that: The steps include: Acquire construction project related data and perform data preprocessing on the construction project related data; Collect carbon emission factors related to construction projects and build a carbon emission factor library; Calculate the carbon emissions of construction projects based on the carbon emission factor library and relevant data of construction projects, and analyze and process the carbon emissions of construction projects; Build a carbon emission prediction model and conduct model training. After completion, predict the carbon emissions of construction projects.

Images