A method and system for calculating carbon emissions from freight stations

Abstract

The present invention relates to the technical field of carbon emission analysis, and specifically to a method and system for calculating carbon emission at a freight station; obtaining outlier residual points according to the discrete characteristics of residual points in a residual sequence of a carbon dioxide concentration sequence; determining the concentration abnormality moment according to the time interval characteristics and distribution characteristics of the outlier residual points; obtaining the concentration variation coefficient according to the difference characteristics of carbon dioxide concentration between the concentration abnormal moment and the adjacent historical moment; obtaining the pH variation coefficient according to the pH difference characteristics between the concentration abnormal moment and the adjacent historical moment; obtaining the correlation degree according to the similar characteristics of the concentration variation coefficient and the pH variation coefficient. The present invention adaptively corrects the carbon dioxide concentration according to the correlation degree and the pH variation coefficient to obtain a corrected concentration; obtains a carbon dioxide corrected concentration sequence according to the corrected concentration and performs carbon emission measurement, thereby improving the accuracy of carbon dioxide collection and carbon emission measurement.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission analysis, and in particular to a method and system for calculating carbon emissions at a freight station. Background Art

[0002] Carbon emissions from freight vehicles account for a large proportion of total carbon emissions from automobiles. Freight vehicles are important targets for energy conservation and emission reduction. Measuring carbon emissions at freight stations can help freight stations understand their true carbon emissions, which is beneficial to the carbon reduction work of freight stations. Existing carbon emissions measurements at freight stations usually use the actual measurement method, using sensors to measure the carbon dioxide concentration at the entrance and exit of freight vehicles or in areas with dense freight vehicles. However, since freight stations and freight vehicles are exposed to open air environments, they are easily disturbed by rainy or humid weather during the carbon emission measurement process. Carbon dioxide easily dissolves into water molecules when it encounters water molecules in the air, resulting in errors in the measured carbon dioxide concentration and reduced accuracy, which ultimately affects the measurement of carbon emissions. Summary of the invention

[0003] In order to solve the above-mentioned technical problem that the accuracy of measuring the carbon dioxide concentration in freight terminals is low due to rain and humid weather, the purpose of the present invention is to provide a method and system for measuring carbon emissions in freight terminals. The technical solutions adopted are as follows:

[0004] Obtain the carbon dioxide concentration series and pH series at the freight terminal at the same time;

[0005] Decomposing the carbon dioxide concentration sequence in time series to obtain a residual sequence; obtaining outlier residual points according to the discrete characteristics of the residual points in the residual sequence; obtaining abnormal characteristic values ​​of the outlier residual points according to the time interval characteristics and distribution characteristics of the outlier residual points; obtaining the abnormal concentration moment according to the abnormal characteristic values;

[0006] In the carbon dioxide concentration sequence, a concentration variation coefficient is obtained according to the concentration difference characteristics between the abnormal concentration moment and the adjacent historical moments; in the pH sequence, a pH variation coefficient is obtained according to the pH difference characteristics between the abnormal concentration moment and the adjacent historical moments; and a correlation degree is obtained according to the similar characteristics between the concentration variation coefficient and the pH variation coefficient;

[0007] The carbon dioxide concentration at the time of abnormal concentration is adaptively corrected according to the correlation degree and the pH variation coefficient to obtain the corrected concentration at the time of abnormal concentration; the carbon dioxide concentration sequence is replaced according to the corrected concentration at the time of abnormal concentration to obtain a corrected carbon dioxide concentration sequence; and carbon emissions are calculated according to the corrected carbon dioxide concentration sequence.

[0008] Furthermore, the step of obtaining outlier residual points according to the discrete features of the residual points in the residual sequence includes:

[0009] Calculate the product of the standard deviation of all residual points and a preset value to obtain a first value; calculate the difference between the numerical mean of all residual points and the first value to obtain a left boundary value, calculate the sum of the numerical mean of all residual points and the first value to obtain a right boundary value; construct a closed interval based on the left boundary value and the right boundary value; when the value of any residual point is not within the closed interval, the arbitrary residual point is an outlier residual point.

[0010] Furthermore, the step of obtaining the abnormal characteristic value of the outlier residual point according to the time interval characteristics and distribution characteristics of the outlier residual point includes:

[0011] The sum of the time intervals between the outlier residual point and other adjacent outlier residual points is calculated and normalized to obtain the interval eigenvalue of the outlier residual point; the absolute value of the outlier residual point is calculated and normalized to obtain the deviation eigenvalue; the sum of the interval eigenvalue and the deviation eigenvalue is calculated to obtain the abnormal eigenvalue of the outlier abnormal point.

[0012] Furthermore, the step of obtaining the concentration abnormality time according to the abnormal characteristic value includes:

[0013] When the abnormal characteristic value exceeds a preset threshold, the moment at which the outlier residual point is located is the concentration abnormal moment.

[0014] Furthermore, the step of obtaining the concentration variation coefficient according to the concentration difference characteristics between the abnormal concentration moment and the adjacent historical moments in the carbon dioxide concentration sequence includes:

[0015] The difference between the maximum value and the minimum value in the carbon dioxide concentration sequence is calculated to obtain a concentration change benchmark; the difference between the carbon dioxide concentration at the concentration abnormal moment and the adjacent historical moment in the carbon dioxide concentration sequence is calculated to obtain a concentration change value; the ratio of the concentration change value to the concentration change benchmark is calculated to obtain a concentration change coefficient at the concentration abnormal moment.

[0016] Furthermore, the step of obtaining the pH variation coefficient in the pH sequence according to the pH difference characteristics between the concentration abnormal moment and the adjacent historical moments includes:

[0017] The difference between the maximum value and the minimum value in the pH sequence is calculated to obtain a pH change benchmark; the pH difference between the concentration abnormal moment and the adjacent historical moment is calculated in the pH sequence to obtain a pH change value; the ratio of the pH change value to the pH change benchmark is calculated to obtain a pH change coefficient at the concentration abnormal moment.

[0018] Furthermore, the step of obtaining the correlation degree according to the similarity characteristics between the concentration variation coefficient and the pH variation coefficient comprises:

[0019] The absolute value of the difference between the concentration variation coefficient and the pH variation coefficient is calculated and negatively correlated to obtain the correlation degree of the concentration abnormality moment.

[0020] Furthermore, the step of adaptively correcting the carbon dioxide concentration at the time of abnormal concentration according to the correlation degree and the pH variation coefficient to obtain the corrected concentration at the time of abnormal concentration includes:

[0021] The product of the concentration change benchmark and the pH change coefficient is calculated to obtain a correction factor; the product of the correction factor and the correlation degree is calculated to obtain a correction value; the sum of the carbon dioxide concentration at the time of the concentration abnormality and the correction value is calculated to obtain the corrected concentration at the time of the concentration abnormality.

[0022] Furthermore, the step of replacing the carbon dioxide concentration sequence according to the corrected concentration at the time of abnormal concentration to obtain the carbon dioxide corrected concentration sequence includes:

[0023] The carbon dioxide concentration at the time of abnormal concentration in the carbon dioxide concentration sequence is replaced by the corrected concentration at the corresponding time to obtain the carbon dioxide corrected concentration sequence.

[0024] The present invention also proposes a freight terminal carbon emission calculation system, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any step of a freight terminal carbon emission calculation method.

[0025] The present invention has the following beneficial effects:

[0026] In the present invention, the residual sequence is obtained to characterize the non-seasonal and non-trend data in the carbon dioxide concentration sequence, and then the outlier residual point can be obtained according to the discrete characteristics of the residual point in the residual sequence, and the outlier residual point can characterize the moment of abnormal carbon dioxide concentration. Obtaining the abnormal characteristic value can distinguish the abnormal carbon dioxide concentration caused by rainy and humid weather from the abnormality caused by other factors; further determining the abnormal concentration moment of the abnormal carbon dioxide concentration caused by rainy and humid weather, preliminarily improves the accuracy of subsequent carbon dioxide concentration correction. Obtaining the concentration change coefficient can characterize the change in carbon dioxide concentration at the moment of abnormal concentration, and obtaining the pH change coefficient can characterize the pH change at the moment of abnormal concentration. According to the characteristic that carbon dioxide is acidic when dissolved in water, resulting in a decrease in pH, obtaining the correlation degree can reflect the degree of correlation between the change in carbon dioxide concentration and the change in pH, as well as the degree of subsequent carbon dioxide concentration correction, and further improve the accuracy of carbon dioxide concentration measurement. Obtaining the corrected concentration can adaptively correct the carbon dioxide concentration according to the correlation degree and the pH change coefficient, improve the accuracy of carbon dioxide concentration correction; and finally improve the accuracy of carbon dioxide correction concentration sequence for carbon emission measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 A flow chart of a method for calculating carbon emissions at a freight terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the method and system for measuring carbon emissions at a freight terminal proposed by the present invention, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0030] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0031] The following is a detailed description of a method and system for calculating carbon emissions at a freight station provided by the present invention with reference to the accompanying drawings.

[0032] See also Figure 1 , which shows a flow chart of a method for calculating carbon emissions at a freight station provided by an embodiment of the present invention, the method comprising the following steps:

[0033] Step S1, obtaining the carbon dioxide concentration sequence of the freight terminal and the pH sequence at the same time.

[0034] In the embodiment of the present invention, the implementation scenario is to measure the carbon dioxide concentration in the freight station to improve the accuracy of the measurement. First, the carbon dioxide concentration sequence of the freight station is obtained, and a fixed gas analysis sensor is used to install the sensor at the entrance and exit of the freight vehicle or other suitable locations to capture the concentration of carbon dioxide. In the embodiment of the present invention, the data collection frequency is once every 30 seconds, and the carbon dioxide time series data during the operation time of the freight station in one day is used as the carbon dioxide concentration sequence; the implementer can determine the collection frequency and collection duration according to the implementation scenario. Since carbon dioxide is acidic, it will cause the water vapor to be acidic after dissolving in water molecules in the air. Therefore, a wet test paper that can be automatically replaced is installed at the adjacent position of the sensor. The composition of the test paper is an absorption liquid of ion exchange water, which has a good absorption and dissolution effect on the air; each time the test paper is replaced, the pH value is tested once. The pH value of the test paper can obtain the pH value of the air. The pH value collection frequency is consistent with the collection frequency of the carbon dioxide concentration, and the pH sequence at the same time is obtained.

[0035] Step S2, performing time series decomposition on the carbon dioxide concentration sequence to obtain a residual sequence; obtaining outlier residual points according to the discrete characteristics of the residual points in the residual sequence; obtaining abnormal characteristic values ​​of the outlier residual points according to the time interval characteristics and distribution characteristics of the outlier residual points; and obtaining the abnormal concentration moment according to the abnormal characteristic values.

[0036] In order to improve the measurement accuracy of carbon dioxide concentration, it is necessary to determine the moment when the concentration anomaly occurs; for freight stations with normal frequency of freight vehicles entering and exiting, the carbon dioxide concentration of the freight station will show periodicity and trend with the entry and exit of vehicles, as well as the peak and low peak periods of freight; therefore, the carbon dioxide concentration sequence can be decomposed into a time series to obtain a residual sequence. It should be noted that the use of the STL time series decomposition algorithm for time series decomposition belongs to the prior art, and the specific steps are not repeated. The residual sequence reflects the part that cannot be explained by the trend term and the seasonal term in the time series decomposition process. The farther the value of the residual point in the residual sequence is from the constant 0, the more likely the carbon dioxide concentration at this moment is caused by rainfall and humid weather. Then, outlier residual points can be obtained according to the discrete characteristics of the residual points in the residual sequence; preferably, in an embodiment of the present invention, the step of obtaining outlier residual points includes: calculating the product of the standard deviation of all residual points and a preset value to obtain a first value; in an embodiment of the present invention, the preset value is a constant 3, which can be determined by the implementer according to the implementation scenario. Calculate the difference between the numerical mean of all residual points and the first value to obtain the left boundary value, calculate the sum of the numerical mean of all residual points and the first value to obtain the right boundary value; construct a closed interval based on the left boundary value and the right boundary value; when the value of any residual point is not in the closed interval, any residual point is an outlier residual point. Outlier residual points are obtained through the existing Laida criterion. When the value of a residual point is not in the closed interval, it means that the value of the residual point exceeds the range of three standard deviations above and below the numerical mean, becoming a gross error, which does not meet the situation of random error.

[0037] Furthermore, the obtained outlier residual points are also caused by many factors. Some outlier residual points may be caused by sudden large-scale loading and unloading at freight stations and long-term operation of large equipment; therefore, it is necessary to further analyze the outlier residual points to determine the outlier residual points caused by rain and humid weather. During large-scale loading and unloading at freight stations, the carbon dioxide concentration gradually increases and remains at a high level, with a certain periodicity and trend. The corresponding outlier residual point value is relatively small, and the time interval of the obtained outlier residual points is relatively close. In rainy and humid weather, the concentration of carbon dioxide is abnormally low due to its dissolution in water vapor, which is quite different from the carbon dioxide concentration level when freight vehicles enter and exit, making the absolute value of the outlier residual point caused by this factor larger; and because the sensor is in a fixed position, the water molecules near the position will make the carbon dioxide concentration in the air return to normal levels after absorbing carbon dioxide, making the time interval of the outlier residual points caused by this factor farther. Therefore, the abnormal characteristic value of the outlier residual point can be obtained according to the time interval characteristics and distribution characteristics of the outlier residual point.

[0038] Preferably, in an embodiment of the present invention, the step of obtaining an abnormal characteristic value includes: calculating the sum of the time intervals between the outlier residual point and other adjacent outlier residual points before and after and normalizing them to obtain the interval characteristic value of the outlier residual point; if no other outlier residual point appears before or after the outlier residual point, then only obtaining the interval characteristic value according to the time interval between the outlier residual point and one other outlier residual point; when the interval characteristic value is larger, it means that the time interval between the outlier residual point and the outlier residual point at the most recent moment is farther, and the outlier residual point is more likely to be caused by rain and wet weather. Calculate the absolute value of the value of the outlier residual point and normalize it to obtain the deviation characteristic value; when the deviation characteristic value is larger, it means that the value of the outlier residual point is farther from the constant 0, and the outlier residual point is more likely to be caused by rain and wet weather. Calculate the sum of the interval characteristic value and the deviation characteristic value to obtain the abnormal characteristic value of the outlier abnormal point; when the abnormal characteristic value is larger, it means that the outlier residual point is more likely to be caused by rain and wet weather. Then, the moment of concentration anomaly can be obtained according to the abnormal characteristic value; preferably, in the embodiment of the present invention, the step of obtaining the moment of concentration anomaly includes: when the abnormal characteristic value exceeds a preset threshold, the moment of the outlier residual point is the moment of concentration anomaly; in the embodiment of the present invention, the preset threshold is 0.6, which can be determined by the implementer according to the implementation scenario.

[0039] Step S3, in the carbon dioxide concentration sequence, the concentration variation coefficient is obtained according to the concentration difference characteristics between the concentration abnormal moment and the adjacent historical moments; in the pH sequence, the pH variation coefficient is obtained according to the pH difference characteristics between the concentration abnormal moment and the adjacent historical moments; and the correlation degree is obtained according to the similar characteristics of the concentration variation coefficient and the pH variation coefficient.

[0040] After obtaining the concentration abnormality moment caused by rainfall and humid weather, it is necessary to correct the carbon dioxide concentration data at the concentration abnormality moment to improve the measurement accuracy of carbon dioxide. In rainy and humid weather, the carbon dioxide generated by freight vehicles will dissolve in water molecules in the air to form carbonic acid, resulting in a decrease in the pH measured at the concentration abnormality moment; if the pH change is more correlated with the carbon dioxide concentration change, it means that the carbon dioxide concentration change at the concentration abnormality moment is more likely to be caused by rainfall and humid weather, and the carbon dioxide concentration can be corrected later according to the correlation characteristics and the pH change. First, in the carbon dioxide concentration sequence, the concentration change coefficient is obtained according to the concentration difference characteristics between the concentration abnormal moment and the adjacent historical moment; preferably, in an embodiment of the present invention, the step of obtaining the concentration change coefficient includes: calculating the difference between the maximum value and the minimum value in the carbon dioxide concentration sequence to obtain a concentration change benchmark; calculating the carbon dioxide concentration difference between the concentration abnormal moment and the adjacent historical moment in the carbon dioxide concentration sequence to obtain a concentration change value; the adjacent historical moment is the previous acquisition moment of the concentration abnormal moment. Calculate the ratio of the concentration change value to the concentration change benchmark to obtain the concentration change coefficient at the concentration abnormal moment. The larger the concentration variation coefficient is, the greater the decrease in carbon dioxide concentration at that moment is.

[0041] Further, after obtaining the concentration variation coefficient of carbon dioxide concentration, it is necessary to obtain the pH variation coefficient in the pH sequence according to the pH difference characteristics between the concentration abnormal moment and the adjacent historical moment; preferably, in the embodiment of the present invention, the step of obtaining the pH variation coefficient includes: calculating the difference between the maximum value and the minimum value in the pH sequence to obtain the pH variation benchmark; calculating the pH difference between the concentration abnormal moment and the adjacent historical moment in the pH sequence to obtain the pH variation value; calculating the ratio of the pH variation value to the pH variation benchmark to obtain the pH variation coefficient at the concentration abnormal moment. The larger the pH variation coefficient, the more the pH value at that moment decreases. Then, the correlation between the concentration change coefficient and the pH change coefficient at the same concentration abnormal moment can be analyzed, so the correlation degree is obtained according to the similar characteristics of the concentration change coefficient and the pH change coefficient; preferably, in the embodiment of the present invention, the step of obtaining the correlation degree includes: calculating the absolute value of the difference between the concentration change coefficient and the pH change coefficient and negatively mapping them to obtain the correlation degree at the concentration abnormal moment; the closer the value of the concentration change coefficient is to the pH change coefficient, the greater the correlation degree is, which means that the degree of decrease in carbon dioxide concentration is more similar to the degree of decrease in pH, and the decrease in carbon dioxide concentration at the concentration abnormal moment is more likely to be caused by water molecules dissolved in the air. The formula for obtaining the correlation degree includes:

[0042]

[0043] In the formula, represents the correlation degree at the abnormal concentration time t, represents an exponential function with a natural constant as the base, the purpose is to perform negative correlation mapping, represents the maximum value in the carbon dioxide concentration series, represents the minimum value in the carbon dioxide concentration series, Indicated in The carbon dioxide concentration at the time, represents the carbon dioxide concentration at the abnormal concentration time t, Represents the maximum value in the pH series, Represents the minimum value in the pH series, Indicated in pH at the moment, represents the pH at the time t when the concentration is abnormal, Indicates the concentration change standard, Indicates the concentration change value, represents the concentration variation coefficient, Indicates the pH change benchmark, Indicates the pH change value. Represents the coefficient of variation of pH.

[0044] Step S4, adaptively correcting the carbon dioxide concentration at the time of concentration abnormality according to the correlation degree and the pH change coefficient to obtain the corrected concentration at the time of concentration abnormality; replacing the carbon dioxide concentration sequence according to the corrected concentration at the time of concentration abnormality to obtain the carbon dioxide corrected concentration sequence; and calculating carbon emissions according to the carbon dioxide corrected concentration sequence.

[0045] The greater the correlation at the time of abnormal concentration, the more relevant the reduction in carbon dioxide concentration is to the factors of rainy and humid weather, the more the carbon dioxide concentration needs to be corrected, and the higher the reliability of the correction of carbon dioxide concentration by the decrease in pH. Therefore, the carbon dioxide concentration at the time of abnormal concentration is adaptively corrected according to the correlation and pH change coefficient to obtain the corrected concentration at the time of abnormal concentration; preferably, in an embodiment of the present invention, the step of obtaining the corrected concentration includes: calculating the product of the concentration change reference and the pH change coefficient to obtain the correction factor; the correction factor can map the pH change in the change range of carbon dioxide concentration. Calculate the product of the correction factor and the correlation to obtain the correction value, which reflects the increase in carbon dioxide concentration; when the correlation is greater, it means that the carbon dioxide concentration at the time of abnormal concentration is more affected by rainy and humid weather, and the more it is necessary to increase the collected carbon dioxide concentration; when the correlation is smaller, it means that the carbon dioxide concentration at the time of abnormal concentration is less affected by rainy and humid weather, and there is no need to over-correct the carbon dioxide concentration. The sum of the carbon dioxide concentration at the time of abnormal concentration and the correction value is calculated to obtain the corrected concentration at the time of abnormal concentration; the corrected concentration is adaptively obtained based on the pH change and correlation at the time of abnormal concentration, thereby improving the measurement accuracy of carbon dioxide concentration. The formula for obtaining measurement accuracy includes:

[0046]

[0047] In the formula, represents the corrected concentration at the abnormal concentration time t, represents the correction factor at the abnormal concentration time t, Indicates the correction value at the time t when the concentration is abnormal.

[0048] Furthermore, the carbon dioxide concentration sequence can be replaced according to the corrected concentration at the time of abnormal concentration to obtain a carbon dioxide corrected concentration sequence, specifically including: replacing the carbon dioxide concentration at the time of abnormal concentration in the carbon dioxide concentration sequence with the corrected concentration at the corresponding time to obtain a carbon dioxide corrected concentration sequence. Compared with the measured carbon dioxide concentration sequence, the carbon dioxide corrected concentration sequence can adaptively correct the collected carbon dioxide concentration according to the reduction in pH in rainy and humid weather based on the characteristic that carbon dioxide is soluble in water molecules, thereby improving the accuracy of carbon dioxide concentration measurement. In addition, carbon emissions can be calculated based on the carbon dioxide corrected concentration sequence, making the calculation of carbon emissions more accurate.

[0049] In summary, the embodiment of the present invention provides a method for calculating carbon emissions at a freight station; outlier residual points are obtained based on the discrete characteristics of residual points in the residual sequence of the carbon dioxide concentration sequence; the concentration abnormality moment is determined based on the time interval characteristics and distribution characteristics of the outlier residual points; the concentration variation coefficient is obtained based on the difference characteristics of carbon dioxide concentration between the concentration abnormal moment and the adjacent historical moment; the pH variation coefficient is obtained based on the pH difference characteristics between the concentration abnormal moment and the adjacent historical moment; the correlation is obtained based on the similar characteristics of the concentration variation coefficient and the pH variation coefficient. The present invention adaptively corrects the carbon dioxide concentration based on the correlation and the pH variation coefficient to obtain a corrected concentration; obtains a carbon dioxide corrected concentration sequence based on the corrected concentration and performs carbon emissions calculation, thereby improving the accuracy of carbon dioxide collection and carbon emissions calculation.

[0050] The present invention also proposes a freight terminal carbon emission calculation system, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any step of a freight terminal carbon emission calculation method.

[0051] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0052] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for calculating carbon emissions at a freight station, characterized in that: The method comprises the following steps: Obtain the carbon dioxide concentration series and pH series at the freight terminal at the same time; Decomposing the carbon dioxide concentration sequence in time series to obtain a residual sequence; obtaining outlier residual points according to the discrete characteristics of the residual points in the residual sequence; obtaining abnormal characteristic values ​​of the outlier residual points according to the time interval characteristics and distribution characteristics of the outlier residual points; obtaining the abnormal concentration moment according to the abnormal characteristic values; In the carbon dioxide concentration sequence, a concentration variation coefficient is obtained according to the concentration difference characteristics between the abnormal concentration moment and the adjacent historical moments; in the pH sequence, a pH variation coefficient is obtained according to the pH difference characteristics between the abnormal concentration moment and the adjacent historical moments; and a correlation degree is obtained according to the similar characteristics between the concentration variation coefficient and the pH variation coefficient; Adaptively correct the carbon dioxide concentration at the time of abnormal concentration according to the correlation degree and the pH change coefficient to obtain a corrected concentration at the time of abnormal concentration; replace the carbon dioxide concentration sequence according to the corrected concentration at the time of abnormal concentration to obtain a corrected carbon dioxide concentration sequence; and calculate carbon emissions according to the corrected carbon dioxide concentration sequence; The step of obtaining the correlation degree according to the similarity characteristics between the concentration variation coefficient and the pH variation coefficient comprises: The absolute value of the difference between the concentration variation coefficient and the pH variation coefficient is calculated and negatively correlated to obtain the correlation degree of the concentration abnormality moment.

2. A method for calculating carbon emissions at a freight station according to claim 1, characterized in that: The step of obtaining outlier residual points according to the discrete features of the residual points in the residual sequence comprises: Calculate the product of the standard deviation of all residual points and a preset value to obtain a first value; calculate the difference between the numerical mean of all residual points and the first value to obtain a left boundary value, calculate the sum of the numerical mean of all residual points and the first value to obtain a right boundary value; construct a closed interval based on the left boundary value and the right boundary value; when the value of any residual point is not within the closed interval, the arbitrary residual point is an outlier residual point.

3. A method for calculating carbon emissions at a freight terminal according to claim 1, characterized in that: The step of obtaining the abnormal characteristic value of the outlier residual point according to the time interval characteristics and distribution characteristics of the outlier residual point comprises: The sum of the time intervals between the outlier residual point and other adjacent outlier residual points is calculated and normalized to obtain the interval eigenvalue of the outlier residual point; the absolute value of the outlier residual point is calculated and normalized to obtain the deviation eigenvalue; the sum of the interval eigenvalue and the deviation eigenvalue is calculated to obtain the abnormal eigenvalue of the outlier abnormal point.

4. A method for calculating carbon emissions at a freight station according to claim 1, characterized in that: The step of obtaining the concentration abnormality time according to the abnormal characteristic value comprises: When the abnormal characteristic value exceeds a preset threshold, the moment at which the outlier residual point is located is the concentration abnormal moment.

5. A method for calculating carbon emissions at a freight station according to claim 1, characterized in that: The step of obtaining the concentration variation coefficient according to the concentration difference characteristics between the abnormal concentration moment and the adjacent historical moments in the carbon dioxide concentration sequence comprises: The difference between the maximum value and the minimum value in the carbon dioxide concentration sequence is calculated to obtain a concentration change benchmark; the difference between the carbon dioxide concentration at the concentration abnormal moment and the adjacent historical moment in the carbon dioxide concentration sequence is calculated to obtain a concentration change value; the ratio of the concentration change value to the concentration change benchmark is calculated to obtain a concentration change coefficient at the concentration abnormal moment.

6. A method for calculating carbon emissions at a freight station according to claim 1, characterized in that: The step of obtaining the pH variation coefficient in the pH sequence according to the pH difference characteristics between the concentration abnormal moment and the adjacent historical moments comprises: The difference between the maximum value and the minimum value in the pH sequence is calculated to obtain a pH change benchmark; the pH difference between the concentration abnormal moment and the adjacent historical moment is calculated in the pH sequence to obtain a pH change value; the ratio of the pH change value to the pH change benchmark is calculated to obtain a pH change coefficient at the concentration abnormal moment.

7. A method for calculating carbon emissions at a freight station according to claim 5, characterized in that: The step of adaptively correcting the carbon dioxide concentration at the time of abnormal concentration according to the correlation degree and the pH variation coefficient to obtain the corrected concentration at the time of abnormal concentration includes: The product of the concentration change benchmark and the pH change coefficient is calculated to obtain a correction factor; the product of the correction factor and the correlation degree is calculated to obtain a correction value; the sum of the carbon dioxide concentration at the time of the concentration abnormality and the correction value is calculated to obtain the corrected concentration at the time of the concentration abnormality.

8. A method for calculating carbon emissions at a freight terminal according to claim 1, characterized in that: The step of replacing the carbon dioxide concentration sequence according to the corrected concentration at the time of abnormal concentration to obtain the carbon dioxide corrected concentration sequence comprises: The carbon dioxide concentration at the time of abnormal concentration in the carbon dioxide concentration sequence is replaced by the corrected concentration at the corresponding time to obtain the carbon dioxide corrected concentration sequence.

9. A freight terminal carbon emission measurement system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 8.

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