Water-gas interface CO2 exchange real-time monitoring method and system based on Internet of Things

Abstract

The invention relates to the technical field of physical analysis, and particularly discloses a water-gas interface CO2 exchange real-time monitoring method and system based on the Internet of Things, and the method comprises the steps: environment influence index judgment, sensor monitoring correction optimization and CO2 abnormal node feedback: firstly, obtaining the environment data of a region to which each node sensor of a water-gas interface belongs; the method comprises the following steps: firstly, determining environmental influence indexes, matching monitoring stability reference evaluation values, secondly, acquiring monitoring stability data of a sensor, verifying the monitoring stability data with the reference values, uploading a verification result to a CO2 monitoring management and control platform based on the Internet of Things, determining whether to optimize the monitoring performance of the sensor, and finally, monitoring CO2 exchange flux in real time and evaluating emission influence degree indexes. And comparing with a predefined defined index, counting abnormal nodes and feeding back, so that the abnormal CO2 emission condition of the water-gas interface can be found in time, and the real-time performance, the correctness and the scientificity of monitoring the CO2 exchange flux of the water-gas interface are ensured.

Description

Technical Field

[0001] The present invention relates to the field of physical analysis technology, and in particular to a method and system for real-time monitoring of CO2 exchange at a water-gas interface based on the Internet of Things. Background Art

[0002] As CO2 emissions continue to increase, it has caused a series of environmental problems such as global warming, which has had a serious impact on high-quality development. Therefore, the monitoring and control of CO2 has become one of the important tasks of global environmental protection and energy conservation and emission reduction today. In inland water bodies such as lakes, reservoirs, and rivers, organic carbon will produce greenhouse gases such as CO2 through the metabolic decomposition of microorganisms. These gases will be discharged into the atmosphere through the water-air interface by diffusion, bubbles, etc., that is, CO2 exchange at the water-air interface is an important part of greenhouse gas emissions. Real-time monitoring of it helps to accurately assess greenhouse gas emissions.

[0003] For example, the invention patent with announcement number CN114878748B announces a CO2 emissions monitoring method and monitoring system, which obtains first data and second data; uses the area weighted average method to process the first data to obtain third data; uses time interpolation and spatial convolution methods to process the second data to obtain fourth data; matches the third data with the fourth data according to the 1km grid and time to form a training data set, and uses machine learning methods to model the full-domain NO2 column concentration spatiotemporal distribution to fill in the target area; matches the filled NO2 column concentration spatiotemporal distribution with wind speed and direction, and uses the line density fitting method to calculate the average NOx emissions under each wind direction; combines the NOx emissions with the CO2-NOx ratio factor to obtain CO2 emissions.

[0004] For example, the invention patent with announcement number CN116381176B announces a greenhouse gas monitoring system for irrigation area water bodies based on low-cost sensors and intelligent algorithms. The low-cost sensor monitoring system monitors the water environment parameters (flow, water temperature, water depth, pH, nitrate nitrogen, ammonia nitrogen, CO2 dissolved concentration) and atmospheric environment parameters (CO2 gas concentration) of ponds and rivers in the irrigation area in real time. A dissolved N2O intelligent algorithm is constructed based on the water environment parameters and the measured data set of dissolved N2O. The greenhouse gas water-air interface exchange model is used to realize the synchronous monitoring of dissolved N2O and CO2 and their emission fluxes in the irrigation area water environment. The OneNET cloud server is used to realize timed remote control and visualization of changes in water quality, dissolved N2O and CO2 emission fluxes of the irrigation area water ecosystem.

[0005] In combination with the above technical solutions, it is found that there are CO2 monitoring technical solutions, whose monitoring process is relatively cumbersome and complicated, so that the CO2 monitoring technical solution is insufficiently flexible and not very applicable, and the overly complicated process when acquiring data can easily lead to large deviations in the data, ultimately affecting the accurate monitoring of CO2. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for real-time monitoring of CO2 exchange at a water-air interface based on the Internet of Things, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides a real-time monitoring method for CO2 exchange at a water-air interface based on the Internet of Things, including: environmental impact index determination: obtaining environmental data of the area to which each node sensor of the water-air interface belongs, determining the environmental impact index of the area to which each node sensor belongs, and thereby matching to obtain a monitoring stability reference evaluation value corresponding to each node sensor; sensor monitoring correction optimization: obtaining monitoring stability data of each node sensor of the water-air interface, determining the monitoring stability evaluation value of each node sensor of the water-air interface, verifying it with the monitoring stability reference evaluation value corresponding to each node sensor, and based on the Internet of Things, the monitoring The evaluation and verification results are uploaded to the water-air interface CO2 exchange monitoring and control platform. The platform determines whether to monitor and calibrate the sensors at each node based on the verification results. CO2 abnormal node feedback: Real-time monitoring of the CO2 exchange at the water-air interface is carried out through the sensors at each node, and the CO2 monitoring data of the area to which each node sensor belongs is obtained. The CO2 emission impact index of the area to which each node sensor at the water-air interface belongs is evaluated and compared with the predefined CO2 emission impact definition index. The CO2 abnormal nodes at the water-air interface are counted, and feedback is provided to several CO2 abnormal nodes at the water-air interface to finally complete the real-time monitoring of CO2 exchange at the water-air interface.

[0008] As a further method, the environmental impact index of the area to which each node sensor belongs is determined, and the specific determination process is: the environmental data of the area to which each node sensor of the water-air interface belongs, specifically including the CO2 partial pressure difference of the water-air interface in the area to which each node sensor of the water-air interface belongs during the impact assessment period, the average value of the ambient temperature in the area to which each node sensor of the water-air interface belongs during the impact assessment period, the average value of the ambient humidity in the area to which each node sensor of the water-air interface belongs during the impact assessment period, the maximum value of the ambient wind speed in the area to which each node sensor of the water-air interface belongs during the impact assessment period, and the ambient electromagnetic interference signal value in the area to which each node sensor of the water-air interface belongs during the impact assessment period; from the water-air The CO2 reference partial pressure difference of the water-air interface, the average environmental adaptation temperature and the average environmental adaptation humidity are extracted from the interface information database; the CO2 partial pressure difference of the water-air interface in the area where the sensors at each node of the water-air interface belong during the impact assessment period, the average environmental temperature in the area where the sensors at each node of the water-air interface belong during the impact assessment period, the average environmental humidity in the area where the sensors at each node of the water-air interface belong during the impact assessment period, the maximum environmental wind speed in the area where the sensors at each node of the water-air interface belong during the impact assessment period and the environmental electromagnetic interference signal value in the area where the sensors at each node of the water-air interface belong during the impact assessment period are comprehensively analyzed to obtain the environmental impact index of the area to which each node sensor belongs.

[0009] As a further method, the monitoring stability evaluation value of each node sensor of the water-air interface is determined, and the specific determination process is: the monitoring stability data of each node sensor of the water-air interface specifically includes the operating response time of each node sensor of the water-air interface within the stable evaluation period, the maximum value of the electromagnetic interference signal borne by each node sensor of the water-air interface within the stable evaluation period, the CO2 partial pressure difference of the water-air interface of each node sensor of the water-air interface within the stable evaluation period, the average ambient wind speed of each node sensor of the water-air interface within the stable evaluation period, and the monitoring stability data of each node sensor of the water-air interface within the stable evaluation period. Repeatability evaluation value; extract the operation response definition time from the water-air interface information database; according to the operation response time of each node sensor of the water-air interface within the stable evaluation period, the maximum value of the electromagnetic interference signal of each node sensor of the water-air interface within the stable evaluation period, the CO2 partial pressure difference of each node sensor of the water-air interface within the stable evaluation period, the average value of the ambient wind speed of each node sensor of the water-air interface within the stable evaluation period and the repeatability evaluation value of each node sensor of the water-air interface within the stable evaluation period, the monitoring stability evaluation value of each node sensor of the water-air interface is obtained.

[0010] As a further method, the determination whether to perform monitoring correction optimization on each node sensor is specifically carried out as follows: the monitoring evaluation verification result is the first monitoring evaluation verification result or the second monitoring evaluation verification result; the first monitoring evaluation verification result is that the monitoring stability evaluation value of a node sensor at the water-air interface is greater than or equal to the monitoring stability reference evaluation value corresponding to the node sensor; the second monitoring evaluation verification result is that the monitoring stability evaluation value of a node sensor at the water-air interface is less than the monitoring stability reference evaluation value corresponding to the node sensor; if the CO2 monitoring and control platform receives the first monitoring evaluation verification result, there is no need to perform monitoring correction optimization on the node sensor; if the CO2 monitoring and control platform receives the second monitoring evaluation verification result, it is necessary to perform monitoring correction optimization on the node sensor.

[0011] As a further method, the CO2 emission impact index of the area to which each node sensor of the water-air interface belongs is evaluated. The specific evaluation process is: obtain the corresponding area of ​​the area to which each node sensor belongs, and perform ratio processing on the water-interface CO2 partial pressure difference of the area to which each node sensor belongs during the monitoring period and the corresponding area of ​​the area to which each node sensor belongs, so as to obtain the emission density of CO2 monitoring in the area to which each node sensor belongs during the monitoring period; obtain the average pH value of the water body in the area to which each node sensor belongs; match the monitoring accuracy corresponding to each predefined monitoring stability evaluation value interval according to the monitoring stability evaluation value of each node sensor of the water-air interface, so as to obtain the monitoring accuracy of the corresponding sensor in the area to which each node sensor belongs; according to the CO2 emission coefficient of the area to which each node sensor belongs at each monitoring time point, the CO2 emission density of the area to which each node sensor belongs during the monitoring period, the average pH value of the water body in the area to which each node sensor belongs, and the monitoring accuracy of the corresponding sensor in the area to which each node sensor belongs, the CO2 emission impact index of the area to which each node sensor belongs at the water-air interface is obtained by comprehensive analysis, and the specific method is as follows:

[0012]

[0013] In the formula, PF q is the CO2 emission impact index of the area to which the qth node sensor of the water-air interface belongs, q is the number of the area to which each node sensor belongs, q = 1, 2, 3, ..., Q, Q is the total amount of the area to which the node sensor belongs, V qt is the CO2 emission coefficient of the area to which the qth node sensor belongs at the tth monitoring time point, t is the time variable, t∈[t0, t1], t0 is the start monitoring time point, t1 is the end monitoring time point, PN q is the emission density of CO2 monitored in the area where the qth node sensor belongs during the monitoring period, PH qis the average pH value of the water body in the area where the qth node sensor belongs, ZQ q is the monitoring accuracy of the sensor corresponding to the area to which the qth node sensor belongs, y6 is the emission influencing parameter corresponding to the emission coefficient predefined in the water-air interface information database, y7 is the emission influencing parameter corresponding to the emission density predefined in the water-air interface information database, y8 is the emission influencing parameter corresponding to the average pH value of the water body predefined in the water-air interface information database, and y9 is the emission influencing parameter corresponding to the monitoring accuracy predefined in the water-air interface information database.

[0014] As a further method, the feedback is given to several CO2 abnormal nodes at the water-air interface. The specific feedback process is: if the CO2 emission impact index of the area to which a node sensor of the water-air interface belongs is greater than the CO2 emission impact definition index, then the area to which the water-air interface node sensor corresponding to the CO2 emission impact index belongs is recorded as the CO2 abnormal node of the water-air interface, so as to count several CO2 abnormal nodes of the water-air interface corresponding to the CO2 emission impact index greater than the CO2 emission impact definition index, and feedback is given to several CO2 abnormal nodes of the water-air interface.

[0015] The second aspect of the present invention provides a real-time monitoring system for CO2 exchange at a water-air interface based on the Internet of Things, including: an environmental impact index determination module, which is used to obtain environmental data of the area to which each node sensor of the water-air interface belongs, determine the environmental impact index of the area to which each node sensor belongs, and thereby obtain the monitoring stability reference evaluation value corresponding to each node sensor; a sensor monitoring correction optimization module, which is used to obtain the monitoring stability data of each node sensor of the water-air interface, determine the monitoring stability evaluation value of each node sensor of the water-air interface, verify it with the monitoring stability reference evaluation value corresponding to each node sensor, and upload the monitoring evaluation verification result to the water based on the Internet of Things. -Air interface CO2 exchange monitoring and control platform, the platform determines whether to monitor, correct and optimize the sensors at each node according to the verification results; CO2 abnormal node feedback module is used to monitor the CO2 exchange at the water-air interface in real time through the sensors at each node, obtain the CO2 monitoring data of the area to which each node sensor belongs, evaluate the CO2 emission impact degree index of the area to which each node sensor at the water-air interface belongs, compare it with the predefined CO2 emission impact degree definition index, count the CO2 abnormal nodes at the water-air interface, and use this to provide feedback on several CO2 abnormal nodes at the water-air interface, and finally complete the real-time monitoring of CO2 exchange at the water-air interface.

[0016] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0017] (1) The present invention provides a method and system for real-time monitoring of CO2 exchange at the water-air interface based on the Internet of Things. First, the environmental data of the area to which the sensors of each node of the water-air interface belong is obtained, the environmental impact index is determined, and the monitoring stability reference evaluation value is matched. Secondly, the sensor monitoring stability data is obtained, and the data is verified with the reference value. The verification result is uploaded to the water-air interface CO2 exchange monitoring and control platform based on the Internet of Things to determine whether to correct and optimize the monitoring results of the sensor to ensure the accuracy and reliability of the CO2 monitoring results. Finally, the CO2 exchange is monitored in real time, the emission impact index is evaluated, and compared with the predefined index. The abnormal nodes are counted and fed back, thereby completing the real-time monitoring of CO2 exchange at the water-air interface, which helps to timely discover abnormal CO2 emissions at the water-air interface and ensure the timeliness of CO2 monitoring.

[0018] (2) The present invention obtains the environmental data of the area to which each node sensor of the water-air interface belongs and determines the environmental impact index of the area to which each node sensor belongs. It can accurately evaluate the environmental conditions of each area and its impact on the monitoring performance of the sensor, so that the sensor can efficiently respond to environmental changes and provide a higher-performance sensor device for subsequent CO2 monitoring.

[0019] (3) The present invention monitors the CO2 exchange at the water-air interface in real time through each node sensor, and obtains the CO2 monitoring data of the area to which each node sensor belongs. In this way, the abnormal changes in CO2 emissions can be quickly captured, and the CO2 emission impact index of the area to which each node sensor of the water-air interface belongs can be evaluated. The specific impact of CO2 emissions in different node areas on the environment can be quantified, thereby improving the efficiency of real-time monitoring of CO2. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0021] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.

[0022] Figure 2 It is a schematic diagram of system module connection of the present invention.

[0023] Figure 3 This is a graph showing changes in monitoring data. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0025] Reference Figure 1 As shown, the first aspect of the present invention provides a real-time monitoring method for CO2 exchange at a water-air interface based on the Internet of Things, including: environmental impact index determination: obtaining environmental data of the area to which each node sensor of the water-air interface belongs, determining the environmental impact index of the area to which each node sensor belongs, and thereby matching to obtain the monitoring stability reference evaluation value corresponding to each node sensor.

[0026] The above-mentioned water-air interface refers to the boundary area where the water body and the atmosphere contact and exchange with each other, such as the interface between lakes, oceans or wetlands and the atmosphere. In this area, various physical, chemical and biological processes such as gas dissolution, volatilization, and heat exchange occur. In these processes, carbon dioxide will be exchanged between the water phase and the gas phase. For example, on the ocean surface, carbon dioxide can dissolve into seawater from the atmosphere, and can also be released from seawater into the atmosphere.

[0027] Each node sensor refers to a device placed at a specific location for monitoring CO2 parameters. The node sensor at the water-air interface can sense the CO2 information at that location in real time, including but not limited to CO2 concentration, rate, emission, etc. These sensors can transmit data to the data monitoring platform via wired or wireless means for CO2 emission control or utilization.

[0028] Specifically, the environmental impact index of the area to which each node sensor belongs is determined, and the specific determination process is as follows:

[0029] The environmental data of the area to which each node sensor of the water-air interface belongs specifically include the CO2 partial pressure difference of the water-air interface in the area to which each node sensor of the water-air interface belongs during the impact assessment period, the average environmental temperature of the area to which each node sensor of the water-air interface belongs during the impact assessment period, the average environmental humidity of the area to which each node sensor of the water-air interface belongs during the impact assessment period, the maximum environmental wind speed of the area to which each node sensor of the water-air interface belongs during the impact assessment period, and the environmental electromagnetic interference signal value of the area to which each node sensor of the water-air interface belongs during the impact assessment period.

[0030] The above-mentioned impact assessment period refers to a specific period of time, which is used to evaluate the specific impact that environmental factors in the area where the sensors at each node of the water-air interface are located may have on these sensors. The impact assessment period is determined by the monitoring personnel through a comprehensive analysis of factors such as the monitoring environment, sensor status, and actual monitoring needs.

[0031] The CO2 partial pressure difference at the water-air interface can be detected by an infrared carbon dioxide detector, the ambient temperature value can be measured by a thermometer, the ambient humidity value can be measured by a hygrometer, the ambient electromagnetic interference signal value can be detected by a spectrum analyzer, and the ambient wind speed can be measured by an anemometer.

[0032] The water-air interface CO2 reference partial pressure difference, the mean environmental adaptation temperature and the mean environmental adaptation humidity are extracted from the water-air interface information database.

[0033] The CO2 partial pressure difference of the water-air interface in the area where each node sensor of the water-air interface belongs during the impact assessment period, the average value of the ambient temperature in the area where each node sensor of the water-air interface belongs during the impact assessment period, the average value of the ambient humidity in the area where each node sensor of the water-air interface belongs during the impact assessment period, the maximum value of the ambient wind speed in the area where each node sensor of the water-air interface belongs during the impact assessment period, and the ambient electromagnetic interference signal value in the area where each node sensor of the water-air interface belongs during the impact assessment period are comprehensively analyzed to obtain the environmental impact index of the area where each node sensor belongs. The specific method is as follows:

[0034]

[0035] In the formula, HJ q is the environmental impact index of the area to which the qth node sensor belongs, q is the number of the area to which each node sensor belongs, q = 1, 2, 3, ..., Q, Q is the total amount of the area to which the node sensor belongs, HL is the water-air interface CO2 partial pressure difference of the area to which the qth node sensor belongs during the impact assessment period, HL′ is the water-air interface CO2 reference partial pressure difference, FS q is the maximum ambient wind speed in the area of ​​the qth node sensor at the water-air interface during the impact assessment period, GR q is the maximum value of the electromagnetic interference signal in the area of ​​the qth node sensor at the water-air interface during the impact assessment period, W q is the mean value of the ambient temperature of the area where the qth node sensor of the water-air interface belongs during the impact assessment period, W′ is the ambient temperature reference value, S qis the mean value of the ambient humidity in the area of ​​the qth node sensor of the water-air interface during the impact assessment period, S′ is the ambient humidity reference value, y2 is the environmental impact factor corresponding to the maximum ambient wind speed predefined in the water-air interface information library, y1 is the environmental impact factor corresponding to the maximum electromagnetic interference signal predefined in the water-air interface information library, and e is a natural constant

[0036] In this embodiment, the environmental impact index of the area to which each node sensor belongs is used to measure and evaluate the quantitative parameters of the environmental conditions in the area where the sensor is located and its changes that may have various impacts on the sensors in the area. The larger the environmental impact index of the area to which the node sensor belongs, the greater the impact of the environmental factors in the area on the sensor, and the greater the negative impact on the stability monitoring of the sensor.

[0037] It should be explained that the environmental impact indicators of the areas to which the above-mentioned node sensors belong can also be obtained by analyzing environmental data such as atmospheric temperature, humidity, air pressure, wind speed, wind direction, rainfall, light intensity, water flow rate, water depth, etc. in a specific embodiment.

[0038] It should be explained that the above-mentioned CO2 partial pressure difference at the water-air interface refers to the difference between the partial pressure of CO2 in the water phase (such as seawater) and the partial pressure of CO2 in the gas phase (such as the atmosphere) in the area where the node sensor belongs during the impact assessment period. This difference reflects the potential for CO2 to transfer from one side to the other; the CO2 reference partial pressure difference at the water-air interface refers to the pre-set adaptation value of the CO2 partial pressure difference at the water-air interface; the maximum value of the ambient wind speed refers to the highest value of the ambient wind speed monitored in the area where the node sensor of the water-air interface is located; the maximum value of the electromagnetic interference signal refers to the highest value of the ambient electromagnetic interference signal monitored in the area where the node sensor of the water-air interface is located; the mean ambient temperature refers to the average value of the ambient temperature monitored in the area where the node sensor of the water-air interface is located; the reference value of the ambient temperature refers to the adaptation value corresponding to the pre-defined ambient temperature; the mean ambient humidity refers to the average value of the ambient humidity monitored in the area where the node sensor of the water-air interface is located; the reference value of the ambient humidity refers to the adaptation value corresponding to the pre-defined ambient humidity.

[0039] The environmental impact factors corresponding to the above-mentioned maximum environmental wind speed and the environmental impact factors corresponding to the maximum electromagnetic interference signal are both obtained from the water-air interface information library. For example, the maximum environmental wind speed and the environmental impact factors corresponding to the maximum environmental wind speed preset in the water-air interface information library form a mapping set, and the real-time maximum environmental wind speed is brought into the mapping set to obtain the environmental impact factors corresponding to the maximum environmental wind speed, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship; the maximum electromagnetic interference signal and the environmental impact factors corresponding to the maximum electromagnetic interference signal preset in the water-air interface information library form a mapping set, and the real-time maximum electromagnetic interference signal is brought into the mapping set to obtain the environmental impact factors corresponding to the maximum electromagnetic interference signal, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, the value ranges of the environmental impact factors corresponding to the maximum environmental CO2 concentration, the environmental impact factors corresponding to the maximum environmental wind speed, and the environmental impact factors corresponding to the maximum electromagnetic interference signal are all (0, 1).

[0040] In this embodiment, if there is a higher water-air interface CO2 reference partial pressure difference in the sensor area and the CO2 concentration in the water body is higher, then the larger partial pressure difference will promote the release of CO2 from the water body into the atmosphere, resulting in an increase in the CO2 concentration in the atmosphere, which will affect the accuracy and reliability of the sensor's monitoring of the water-air interface CO2 in this area. A smaller partial pressure difference may limit the CO2 absorption process, resulting in an increase in the CO2 concentration in the water body, which will also affect the accuracy of the sensor's monitoring of the water-air interface CO2 in this area. Both ambient temperature and ambient humidity will have an impact on the accuracy of the sensor. When the temperature is too high or too low, the parameters of the sensor element may change, affecting its measurement accuracy. When the humidity is high, the sensor may become damp and damage the circuit. Or it may affect optical components, etc. When the humidity is low, the air is drier, which may also have a negative impact on the monitoring performance of the sensor; when the ambient temperature is high and deviates from the reference value, the interference intensity of the radio in the environment may increase, thereby increasing the ambient electromagnetic interference signal, because the increase in temperature will increase the activity and conductivity of air molecules, thereby affecting the distribution and intensity of the electromagnetic field; similarly, wind speed may also have a certain impact on the electromagnetic interference signal value. In the sensor area, changes in wind speed may change the intensity of the electromagnetic field in the regional space, thereby affecting the electromagnetic interference signal value; in summary, the increase in ambient wind speed and electromagnetic interference signal value, the reference partial pressure difference of CO2 at the water-air interface, ambient temperature and ambient humidity that are too low or too high will all increase the impact of the regional environment on the sensor monitoring performance.

[0041] Furthermore, the matching obtains the monitoring stability reference evaluation value corresponding to each node sensor, and the specific matching process is:

[0042] The environmental impact indicators of the area to which each node sensor belongs are matched with the monitoring stability reference evaluation values ​​corresponding to each environmental impact indicator interval predefined in the water-air interface information library. The specific matching process is: obtain the mapping set between the environmental impact indicators of the area to which each node sensor belongs and the monitoring stability reference evaluation values ​​from the water-air interface information library, determine the specific interval of the environmental impact indicators of the area to which each node sensor belongs, and assign the monitoring stability reference evaluation value corresponding to the interval to each node sensor corresponding to the environmental impact indicator of the area to which it belongs, so as to obtain the monitoring stability reference evaluation value corresponding to each node sensor by matching.

[0043] Sensor monitoring, correction and optimization: obtain the monitoring stability data of the sensors at each node of the water-air interface, determine the monitoring stability evaluation value of the sensors at each node of the water-air interface, verify it with the monitoring stability reference evaluation value corresponding to each node sensor, and upload the monitoring and evaluation verification results to the water-air interface CO2 exchange monitoring and control platform based on the Internet of Things. The platform determines whether to perform monitoring, correction and optimization on each node sensor based on the verification results.

[0044] The above-mentioned water-air interface CO2 exchange monitoring and control platform is an integrated system for monitoring, collecting, analyzing and controlling carbon dioxide related data. Its core function is to obtain CO2 related data in the water-air interface through various sensors, such as infrared gas sensors, chemical absorption sensors, etc. These sensors are distributed in different geographical locations of the water-air interface. After the data is collected, the platform will store and organize it. For example, the data is stored according to different monitoring points, time series, etc. for subsequent query and analysis. At the same time, the platform will display the data in real time on the corresponding data display interface, showing the location and emission information of different monitoring points so that monitoring personnel can quickly understand the current status of CO2 emissions in the monitoring area.

[0045] Specifically, the monitoring stability evaluation value of each node sensor of the water-air interface is determined by the following specific determination process:

[0046] The monitoring stability data of the sensors at each node of the water-air interface specifically include the operating response time of the sensors at each node of the water-air interface within the stable evaluation period, the maximum value of the electromagnetic interference signal borne by the sensors at each node of the water-air interface within the stable evaluation period, the CO2 partial pressure difference at the water-air interface of the sensors at each node of the water-air interface within the stable evaluation period, the average ambient wind speed of the sensors at each node of the water-air interface within the stable evaluation period, and the repeatability evaluation value of the sensors at each node of the water-air interface within the stable evaluation period.

[0047] The repeatability evaluation value of the above-mentioned water-air interface node sensors within a stable evaluation period is specifically that within the stable evaluation period, under the same conditions such as the sensor's operating response time, ambient temperature average, ambient humidity and other parameters, a certain node sensor measures the same input signal multiple times, and standard deviation processing is performed on the measurement results of the multiple input signals to obtain the repeatability evaluation value of the water-air interface node sensors within the stable evaluation period.

[0048] The above-mentioned stability assessment period refers to a period of time used to evaluate the monitoring stability of the sensor. The stability assessment period is determined by the monitoring personnel based on a comprehensive analysis of factors such as the sensor status, actual monitoring needs, and the water-air interface status.

[0049] The above-mentioned operation response time, electromagnetic interference signal, CO2 partial pressure difference at the water-air interface and average ambient wind speed can all be extracted from the monitoring report of the sensor.

[0050] The operational response definition duration is extracted from the water-air interface information database.

[0051] Based on the comprehensive analysis of the operation response time of each node sensor of the water-air interface within the stable evaluation period, the maximum value of the electromagnetic interference signal borne by each node sensor of the water-air interface within the stable evaluation period, the CO2 partial pressure difference of each node sensor of the water-air interface within the stable evaluation period, and the repeatability evaluation value of each node sensor of the water-air interface within the stable evaluation period, the monitoring stability evaluation value of each node sensor of the water-air interface is obtained. The specific method is as follows:

[0052]

[0053] Where, WD g is the monitoring stability evaluation value of the g-th node sensor at the water-air interface, g is the number of each node sensor, g = 1, 2, 3, ..., G, G is the total number of node sensors, is the preset value for monitoring stability assessment of the g-th node sensor at the predefined water-air interface, T g is the operating response time of the g-th node sensor at the water-air interface during the stable evaluation period, T′ g The operation response duration corresponding to the g-th node sensor of the water-air interface is defined as DC g is the electromagnetic interference signal value of the g-th node sensor at the water-air interface during the stable evaluation period, HL q is the CO2 partial pressure difference of the water-air interface at the g-th node sensor during the stable evaluation period, HL′ is the CO2 reference partial pressure difference of the water-air interface, CF gis the repeatability evaluation value of the g-th node sensor of the water-air interface within the stable evaluation period, y3 is the stability evaluation influence factor corresponding to the electromagnetic interference signal value predefined in the water-air interface information library, y4 is the stability evaluation influence factor corresponding to the CO2 partial pressure deviation value of the water-air interface predefined in the water-air interface information library, y5 is the stability evaluation influence factor corresponding to the repeatability evaluation value predefined in the water-air interface information library, and e is a natural constant.

[0054] It should be explained that the numbers of the above-mentioned g node sensors and the numbers of the areas to which the above-mentioned q node sensors belong are in a one-to-one correspondence.

[0055] In this embodiment, the monitoring stability evaluation value of each node sensor at the water-air interface is used to measure the stability of the accuracy of the sensor measurement data. The larger the monitoring stability evaluation value, the greater the stability of the node sensor and the more accurate the performance in the real-time monitoring process of CO2.

[0056] It needs to be explained that the above-mentioned monitoring stability assessment preset value means that when the operating response time of a node sensor is longer than the operating response defined time, the monitoring stability assessment value of the node sensor takes the monitoring stability assessment preset value, and the monitoring stability assessment preset value is a pre-set limiting value of the monitoring stability assessment value.

[0057] The operation response time refers to the time from the time the sensor receives the monitoring command to the time the sensor actually starts to perform the monitoring task within the stable evaluation period, that is, the reaction time of the node sensor during the operation process; the operation response limit time refers to the maximum value of the operation response time pre-set for the node sensor.

[0058] What needs to be explained in this embodiment is that if the operating response time of the node sensor is too long, greater than the operating response limit time, that is, the maximum value of the operating response time, it means that the node sensor has a serious problem in the reaction speed of one of the most critical stability performance indicators. In this embodiment, the monitoring stability evaluation value is directly set to the preset value to correct and optimize the node sensor, which can quickly focus on solving this key performance bottleneck and avoid the delay of monitoring data due to the slow response of the sensor, thereby affecting the timeliness of the entire system; the operating response time is a key performance indicator for the evaluation of monitoring stability, and its abnormality may mask the normal performance of other parameters. For example, the accuracy of a sensor may be within the normal range, but if its response time is too long, even high-precision data will lose its value due to poor timeliness. Therefore, the problem of operating response time has a higher priority in this embodiment. Direct optimization without considering other factors can reduce the complex evaluation and trade-off process. Solving more prominent problems first can make the optimization process more direct and efficient.

[0059] The electromagnetic interference signal value refers to the total value of the electromagnetic interference signals generated by external equipment and the electromagnetic interference generated by its own operation that the node sensor withstands during the stable evaluation period, reflecting the anti-interference ability of the node sensor; the CO2 partial pressure difference at the water-air interface refers to the difference between the partial pressure of CO2 in the water phase (such as seawater) and the partial pressure of CO2 in the gas phase (such as the atmosphere) monitored by the node sensor during the stable evaluation period; the repeatability evaluation value refers to the repeatability of the measurement results of the node sensor for multiple measurements of the same input signal, which can be the CO2 concentration, during the stable evaluation period, reflecting the stability of the node sensor during operation, thereby evaluating the measurement accuracy of the node sensor and helping to understand the performance of the sensor in long-term operation. In practical applications, stable sensors can provide more reliable data and reduce false alarms or omissions caused by sensor failures or errors.

[0060] The stability assessment influence factor corresponding to the above-mentioned water-air interface CO2 partial pressure deviation value, the stability assessment influence factor corresponding to the repeatability assessment value, and the stability assessment influence factor corresponding to the electromagnetic interference signal value are all obtained from the water-air interface information library. For example, the water-air interface CO2 partial pressure deviation value and the stability assessment influence factor corresponding to the water-air interface CO2 partial pressure deviation value preset in the water-air interface information library form a mapping set, and the real-time water-air interface CO2 partial pressure deviation value is brought into the mapping set to obtain the stability assessment influence factor corresponding to the water-air interface CO2 partial pressure deviation value, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship; the repeatability assessment value and the stability assessment influence factor corresponding to the repeatability assessment value preset in the water-air interface information library form a mapping set. , the real-time repeatability evaluation value is brought into the mapping set to obtain the stability evaluation influence factor corresponding to the repeatability evaluation value, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship; the electromagnetic interference signal value and the stability evaluation influence factor corresponding to the electromagnetic interference signal value preset in the water-air interface information library form a mapping set, and the real-time electromagnetic interference signal value is brought into the mapping set to obtain the stability evaluation influence factor corresponding to the electromagnetic interference signal value, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, the value ranges of the stability evaluation influence factor corresponding to the CO2 partial pressure deviation value of the water-air interface, the stability evaluation influence factor corresponding to the repeatability evaluation value, and the stability evaluation influence factor corresponding to the electromagnetic interference signal value are all (0, 1).

[0061] In this embodiment, if the sensor is subjected to strong electromagnetic interference during the monitoring process, its measurement results may be affected, resulting in a decrease in the repeatability evaluation value. Therefore, improving the sensor's electromagnetic interference signal value helps to maintain its measurement stability and repeatability in a strong electromagnetic interference environment; the larger the CO2 partial pressure deviation value at the water-air interface, the further the CO2 partial pressure value at the water-air interface is from the CO2 reference partial pressure value at the water-air interface, so that the CO2 release process is more intense, resulting in a substantial increase in the CO2 concentration in the atmosphere during the stable evaluation process, thereby affecting the monitoring stability of the sensor; in summary, these parameters are actually closely related and jointly affect the monitoring stability of the sensor.

[0062] Furthermore, the determination of whether to perform monitoring correction optimization on each node sensor is specifically carried out as follows:

[0063] The monitoring and evaluation verification result is the first monitoring and evaluation verification result or the second monitoring and evaluation verification result.

[0064] The first monitoring evaluation verification result is that the monitoring stability evaluation value of a node sensor of the water-air interface is greater than or equal to the monitoring stability reference evaluation value corresponding to the node sensor predefined in the water-air interface information library.

[0065] The second monitoring and evaluation verification result is that the monitoring stability evaluation value of a node sensor at the water-air interface is less than the monitoring stability reference evaluation value corresponding to the node sensor.

[0066] It should be explained that the preset value of the monitoring stability assessment of a node sensor at the water-air interface is also smaller than the monitoring stability reference assessment value corresponding to the node sensor.

[0067] If the CO2 monitoring and control platform receives the first monitoring, evaluation and verification result, there is no need to perform monitoring, correction and optimization on the node sensor. If the CO2 monitoring and control platform receives the second monitoring, evaluation and verification result, it is necessary to perform monitoring, correction and optimization on the node sensor.

[0068] The above-mentioned monitoring, correction and optimization of node sensors can specifically include single-point grounding of the sensor's signal processor to improve the speed and accuracy of signal processing, thereby reducing the sensor's response time; wrapping the sensor with a metal shielding layer to reduce the impact of external electromagnetic fields, electrostatic fields and other interference sources on the sensor, and improving the sensor's ability to withstand electromagnetic interference; calibrating and calibrating the sensor to ensure the accuracy and stability of its measurement results, and improving the repeatability evaluation value of the node sensor.

[0069] Through the above-mentioned monitoring, correction and optimization operations, the sensor has a faster reaction time and can respond to environmental changes or input signals more quickly, thereby reducing the response time of the entire sensor; at the same time, it reduces measurement errors caused by environmental changes or interference, and enhances the stability and reliability of the sensor; and can more accurately reflect the true value of CO2 at the water-air interface, improve the accuracy and credibility of the data, help reduce the false alarm rate of the sensor, improve the overall reliability of CO2 monitoring, and ensure that the system can continue to operate stably.

[0070] CO2 abnormal node feedback: Real-time monitoring of CO2 exchange at the water-air interface is carried out through sensors at each node, and CO2 monitoring data of the area to which each node sensor belongs is obtained. The CO2 emission impact index of the area to which each node sensor at the water-air interface belongs is evaluated, and compared with the predefined CO2 emission impact definition index. The CO2 abnormal nodes at the water-air interface are counted, and feedback is provided to several CO2 abnormal nodes at the water-air interface to finally complete the real-time monitoring of CO2 exchange at the water-air interface.

[0071] Specifically, the CO2 monitoring data of the area to which each node sensor belongs specifically includes the CO2 emission coefficient of the area to which each node sensor belongs at each monitoring time point and the water-interface CO2 partial pressure difference of the area to which each node sensor belongs during the monitoring period.

[0072] The above-mentioned monitoring period refers to a period of time used by the sensor to monitor the real-time exchange of CO2 in the water-air interface. The monitoring time points are specifically several monitoring time points that divide the monitoring period into time points. The division method can be divided into 30 seconds in sequence. The monitoring period is determined by the monitoring personnel based on a comprehensive analysis of factors such as the state of the water-air interface, the state of the sensor, and actual monitoring needs.

[0073] The above emission coefficient and water-interface CO2 partial pressure difference can be extracted from the sensor's monitoring report.

[0074] In a specific embodiment, through the water-air interface CO2 real-time monitoring equipment, there is actual usage information in the three monitoring points of Chehe, Jiusi and Baiwang, such as Figure 3 As shown, Figure 3 To monitor the data change graph, including sub-graph b and sub-graph c, Figure 3 The horizontal axis is the monitoring time in days, the vertical axis sub-graph b is the CO2 concentration at the water interface (Water_CO2) in milligrams per liter (mg / L), and sub-graph c is the water depth in meters (m).

[0075] Depend on Figure 3It can be seen that sub-figure b: Water_CO2 (mg / L) shows the changes in the concentration of carbon dioxide in the water body. The carbon dioxide concentration in the water body of Chehe River shows a higher peak at certain times, while the carbon dioxide concentration in the water bodies of Jiusi and Baiwang is relatively stable; sub-figure c: Water Depth (m), this figure shows the changes in water depth at the monitoring sites. The water depth of Chehe River changes more obviously, with several large fluctuations, while the water depth of Jiusi and Baiwang changes relatively little.

[0076] Furthermore, the evaluation process of evaluating the CO2 emission impact index of the area to which each node sensor of the water-air interface belongs is as follows:

[0077] The corresponding area of ​​the area to which each node sensor belongs is obtained, where the corresponding area can be extracted from the sensor deployment report. The water-interface CO2 partial pressure difference of the area to which each node sensor belongs during the monitoring period is processed with the corresponding area of ​​the area to which each node sensor belongs, and the emission density of CO2 monitoring in the area to which each node sensor belongs during the monitoring period is obtained.

[0078] The average pH value of the water body in the area where each node sensor belongs is obtained. The pH value of the water body can be detected by an acid-base indicator.

[0079] According to the monitoring stability evaluation value of each node sensor of the water-air interface, it is matched with the monitoring accuracy corresponding to each monitoring stability evaluation value interval predefined in the water-air interface information library. The specific matching process is: obtain the mapping set between the monitoring stability evaluation value of each node sensor of the water-air interface and the monitoring accuracy from the water-air interface information library, determine the specific interval of the monitoring stability evaluation value of each node sensor of the water-air interface, and assign the monitoring stability evaluation value corresponding to the interval to each node sensor corresponding to the monitoring stability evaluation value, so as to obtain the monitoring accuracy of the sensor corresponding to the area to which each node sensor belongs.

[0080] The CO2 emission impact index of the area to which each node sensor belongs at the water-air interface is obtained by comprehensive analysis of the CO2 emission coefficient of the area to which each node sensor belongs during the monitoring period, the emission density of CO2 monitoring in the area to which each node sensor belongs during the monitoring period, the average pH value of the water body in the area to which each node sensor belongs, and the monitoring accuracy of the corresponding sensor in the area to which each node sensor belongs. The specific method is as follows:

[0081]

[0082] In the formula, PF q is the CO2 emission impact index of the area to which the qth node sensor of the water-air interface belongs, q is the number of the area to which each node sensor belongs, q = 1, 2, 3, ..., Q, Q is the total amount of the area to which the node sensor belongs, V qtis the CO2 emission coefficient of the area to which the qth node sensor belongs at the tth monitoring time point, t is the time variable, t∈[t0, t1], t0 is the start monitoring time point, t1 is the end monitoring time point, PN q is the emission density of CO2 monitored in the area where the qth node sensor belongs during the monitoring period, PH q is the average pH value of the water body in the area where the qth node sensor belongs, ZQ q is the monitoring accuracy of the sensor corresponding to the area to which the qth node sensor belongs, y5 is the emission influencing parameter corresponding to the emission coefficient predefined in the water-air interface information database, y6 is the emission influencing parameter corresponding to the emission density predefined in the water-air interface information database, y7 is the emission influencing parameter corresponding to the average pH value of the water body predefined in the water-air interface information database, and y8 is the emission influencing parameter corresponding to the monitoring accuracy predefined in the water-air interface information database.

[0083] In this embodiment, the CO2 emission impact index of each node on the water-air interface is used to measure the degree of impact that carbon dioxide emissions may have on the environment or ecosystem at each monitoring node on the water-air interface. If the CO2 emission impact index of a node is high, it means that the CO2 emissions of the node are relatively abnormal and the possible impact is relatively serious, and feedback on the CO2 monitoring process of the node is required.

[0084] It needs to be explained that the above-mentioned emission coefficient refers to the amount of CO2 emissions released from the water body to the atmosphere monitored by the node sensor at a certain monitoring time point. It is a dynamic indicator to measure the CO2 emission rate in the sensor monitoring area; the emission density is used to describe the concentration of CO2 emissions in the node sensor monitoring area; the average pH value of the water body refers to the average value of the pH of the water body in the sensor interface area where the water body and the atmosphere are in contact with each other. This interface is the key area for the dissolution and escape of carbon dioxide between the water body and the air. The pH value of the water body reflects the hydrogen ion concentration in the water and is used to measure the acidity and alkalinity of the water body; the monitoring accuracy refers to the degree of consistency between the sensor measurement results and the actual state of CO2 emissions.

[0085] The emission influencing parameters corresponding to the above-mentioned emission coefficient, the emission influencing parameters corresponding to the emission density, the emission influencing parameters corresponding to the average pH value of the water body, and the emission influencing parameters corresponding to the monitoring accuracy are all obtained in the water-air interface information library. For example, the emission coefficient and the emission influencing parameters corresponding to the preset emission coefficient in the water-air interface information library form a mapping set, and the real-time emission coefficient is brought into the mapping set to obtain the emission influencing parameters corresponding to the emission coefficient, wherein the mapping relationship may be a one-to-one correspondence or a many-to-one relationship; the emission density and the emission influencing parameters corresponding to the preset emission density in the water-air interface information library form a mapping set, and the real-time emission density is brought into the mapping set to obtain the emission influencing parameters corresponding to the emission density, wherein the mapping relationship may be a one-to-one correspondence or a many-to-one relationship; the average pH value of the water body The emission influencing parameters corresponding to the preset average pH value of the water body in the water-air interface information library form a mapping set, and the real-time average pH value of the water body is brought into the mapping set to obtain the emission influencing parameters corresponding to the average pH value of the water body, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship; the emission influencing parameters corresponding to the monitoring accuracy rate preset in the water-air interface information library form a mapping set, and the real-time monitoring accuracy rate is brought into the mapping set to obtain the emission influencing parameters corresponding to the monitoring accuracy rate, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this embodiment, the emission influencing parameters corresponding to the emission coefficient, the emission influencing parameters corresponding to the emission density, the emission influencing parameters corresponding to the average pH value of the water body, and the emission influencing parameters corresponding to the monitoring accuracy rate all have a value range of (0, 1).

[0086] In this embodiment, when the corresponding area of ​​the sensor monitoring area is constant and the monitoring period is constant, there is a positive correlation between the CO2 emission coefficient and the emission density, that is, the higher the emission coefficient, the greater the emission density; the pH of the water body has an important influence on the solubility and emission of CO2. In acidic water bodies, the solubility of CO2 is higher, which may increase the emission of CO2; while alkaline water bodies may reduce the emission of CO2. When the CO2 emission increases, the pH value of the water body may decrease. This is because CO2 will form carbonic acid after dissolving in water, and then dissociate into hydrogen ions and bicarbonate ions, causing acidification of the water body, which has a more serious negative impact on the water body; the monitoring accuracy of the sensor directly affects the reliability and accuracy of the data, and is the basis for evaluating parameters such as the CO2 emission coefficient and emission density. If the monitoring accuracy of the sensor is low, it means that the monitored data may have large errors, resulting in an erroneous assessment of the CO2 emission status and affecting the feedback of real-time monitoring of CO2.

[0087] Specifically, the feedback is given to several CO2 abnormal nodes at the water-air interface, and the specific feedback process is as follows:

[0088] If the CO2 emission impact index of the area to which a node sensor of the water-air interface belongs is greater than the CO2 emission impact definition index predefined in the water-air interface information library, the water-air interface node corresponding to the CO2 emission impact index is recorded as the CO2 abnormal node of the water-air interface, and a number of CO2 abnormal nodes of the water-air interface corresponding to the CO2 emission impact index greater than the CO2 emission impact definition index are counted, and feedback is given to the several CO2 abnormal nodes of the water-air interface.

[0089] If the CO2 emission impact index of the area to which a node sensor at the water-air interface belongs is less than or equal to the CO2 emission impact definition index, the CO2 emission data of the area to which the node sensor belongs shall be stored in the CO2 monitoring and control platform. The CO2 emission data may specifically include the CO2 emission coefficient, emission density, and location of the area to which the node sensor belongs.

[0090] Furthermore, the plurality of CO2 abnormal nodes provide feedback, specifically, provide an abnormal CO2 emission warning for the plurality of CO2 abnormal nodes.

[0091] The above-mentioned warning can be specifically when the intelligent warning subsystem of the CO2 monitoring and control platform detects that the CO2 emission impact index of a node on the water-air interface is greater than the CO2 emission impact definition index, then a warning is triggered for the CO2 abnormal node on the water-air interface, and warning information is automatically generated, including the location of the abnormal node, CO2 concentration value, warning time, etc. The CO2 monitoring and control platform will promptly notify the monitoring personnel of the warning information, and the notification can be made through SMS, email, telephone, etc., to ensure timely communication of the information.

[0092] The above-mentioned intelligent early warning subsystem is based on artificial intelligence technology. Through real-time monitoring and analysis of monitoring data, it can promptly detect potential security threats or abnormal situations and send early warning information to monitoring personnel.

[0093] Reference Figure 2 As shown, the second aspect of the present invention provides a real-time monitoring system for CO2 exchange at a water-air interface based on the Internet of Things, comprising: an environmental impact index determination module, a sensor monitoring correction optimization module, and a CO2 abnormal node feedback module.

[0094] The second aspect of the present invention provides a real-time monitoring system for CO2 exchange at the water-air interface based on the Internet of Things, which also includes: a water-air interface information library, which is used to store the CO2 reference partial pressure difference at the water-air interface, the average environmental adaptation temperature, the average environmental adaptation humidity, the operating response definition time, and the preset values ​​of various factors.

[0095] The environmental impact index determination module is connected to the sensor monitoring correction optimization module, the sensor monitoring correction optimization module is connected to the CO2 abnormal node feedback module, and the environmental impact index determination module, the sensor monitoring correction optimization module and the CO2 abnormal node feedback module are all connected to the water-air interface information library.

[0096] The environmental impact index determination module is used to obtain environmental data of the area to which each node sensor of the water-air interface belongs, determine the environmental impact index of the area to which each node sensor belongs, and thereby match and obtain the monitoring stability reference evaluation value corresponding to each node sensor.

[0097] The sensor monitoring, correction and optimization module is used to obtain the monitoring stability data of each node sensor of the water-air interface, determine the monitoring stability evaluation value of each node sensor of the water-air interface, verify it with the monitoring stability reference evaluation value corresponding to each node sensor, and upload the monitoring evaluation verification result to the water-air interface CO2 exchange monitoring and control platform based on the Internet of Things. The platform determines whether to perform monitoring, correction and optimization on each node sensor based on the verification result.

[0098] The CO2 abnormal node feedback module is used to monitor the CO2 exchange at the water-air interface in real time through each node sensor, obtain CO2 monitoring data of the area to which each node sensor belongs, evaluate the CO2 emission impact degree index of the area to which each node sensor at the water-air interface belongs, compare it with the predefined CO2 emission impact degree definition index, and count the CO2 abnormal nodes at the water-air interface, so as to feedback several CO2 abnormal nodes at the water-air interface, and finally complete the real-time monitoring of CO2 exchange at the water-air interface.

[0099] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A real-time monitoring method for CO2 exchange at a water-air interface based on the Internet of Things, characterized in that: include: Environmental impact index determination: Obtain environmental data of the area to which each node sensor of the water-air interface belongs, determine the environmental impact index of the area to which each node sensor belongs, and thereby match and obtain the monitoring stability reference evaluation value corresponding to each node sensor; Sensor monitoring, calibration and optimization: Obtain the monitoring stability data of sensors at each node of the water-air interface, determine the monitoring stability evaluation value of sensors at each node of the water-air interface, perform verification with the monitoring stability reference evaluation value corresponding to each node sensor, and upload the monitoring and evaluation verification results to the water-air interface CO2 exchange monitoring and control platform based on the Internet of Things. The platform determines whether to perform monitoring, calibration and optimization on sensors at each node based on the verification results; Feedback of abnormal CO2 nodes: Real-time monitoring of CO2 exchange at the water-air interface is carried out through sensors at each node, and monitoring data of CO2 exchange at the water-air interface in the area to which each node sensor belongs is obtained. The CO2 emission impact index of the area to which each node sensor at the water-air interface belongs is evaluated, and compared with the predefined CO2 emission impact index, and the CO2 abnormal nodes at the water-air interface are counted. In this way, feedback is provided to several abnormal CO2 nodes at the water-air interface, and finally real-time monitoring of CO2 exchange at the water-air interface is completed.

2. According to claim 1, the method for real-time monitoring of CO2 exchange at the water-air interface based on the Internet of Things is characterized by: The specific determination process of determining the environmental impact index of the area to which each node sensor belongs is as follows: The environmental data of the area to which each node sensor of the water-air interface belongs specifically include the CO2 partial pressure difference of the water-air interface in the area to which each node sensor of the water-air interface belongs within the impact assessment period, the average value of the ambient temperature in the area to which each node sensor of the water-air interface belongs within the impact assessment period, the average value of the ambient humidity in the area to which each node sensor of the water-air interface belongs within the impact assessment period, the maximum value of the ambient wind speed in the area to which each node sensor of the water-air interface belongs within the impact assessment period, and the ambient electromagnetic interference signal value in the area to which each node sensor of the water-air interface belongs within the impact assessment period; The water-air interface CO2 reference partial pressure difference, the mean value of the environment adaptation temperature and the mean value of the environment adaptation humidity were extracted from the water-air interface information database; The CO2 partial pressure difference of the water-air interface in the area where the sensors at each node of the water-air interface belong during the impact assessment period, the mean ambient temperature of the area where the sensors at each node of the water-air interface belong during the impact assessment period, the mean ambient humidity of the area where the sensors at each node of the water-air interface belong during the impact assessment period, the maximum ambient wind speed of the area where the sensors at each node of the water-air interface belong during the impact assessment period, and the ambient electromagnetic interference signal value of the area where the sensors at each node of the water-air interface belong during the impact assessment period are comprehensively analyzed to obtain the environmental impact index of the area to which each node sensor belongs.

3. According to claim 2, the method for real-time monitoring of CO2 exchange at the water-air interface based on the Internet of Things is characterized by: The matching obtains the monitoring stability reference evaluation value corresponding to each node sensor, and the specific matching process is: The environmental impact index of the area to which each node sensor belongs is matched with the monitoring stability reference evaluation value corresponding to each predefined environmental impact index interval, so as to obtain the monitoring stability reference evaluation value corresponding to each node sensor.

4. According to claim 3, the method for real-time monitoring of CO2 exchange at the water-air interface based on the Internet of Things is characterized by: The specific determination process of determining the monitoring stability evaluation value of each node sensor of the water-air interface is as follows: The monitoring stability data of the sensors at each node of the water-air interface specifically include the operation response time of the sensors at each node of the water-air interface within the stable evaluation period, the maximum value of the electromagnetic interference signal borne by the sensors at each node of the water-air interface within the stable evaluation period, the CO2 partial pressure difference at the water-air interface of the sensors at each node of the water-air interface within the stable evaluation period, the average value of the ambient wind speed of the sensors at each node of the water-air interface within the stable evaluation period, and the repeatability evaluation value of the sensors at each node of the water-air interface within the stable evaluation period; The operation response definition time is extracted from the water-air interface information database; Based on the comprehensive analysis of the operating response time of each node sensor at the water-air interface within the stable evaluation period, the maximum value of the electromagnetic interference signal borne by each node sensor at the water-air interface within the stable evaluation period, the CO2 partial pressure difference at the water-air interface of each node sensor at the water-air interface within the stable evaluation period, the average ambient wind speed of each node sensor at the water-air interface within the stable evaluation period and the repeatability evaluation value of each node sensor at the water-air interface within the stable evaluation period, the monitoring stability evaluation value of each node sensor at the water-air interface is obtained.

5. According to the method for real-time monitoring of CO2 exchange at the water-air interface based on the Internet of Things in claim 1, it is characterized by: The specific process of determining whether to perform monitoring, correction and optimization on each node sensor is as follows: The monitoring and evaluation verification result is the first monitoring and evaluation verification result or the second monitoring and evaluation verification result; The first monitoring evaluation verification result is that the monitoring stability evaluation value of a certain node sensor of the water-air interface is greater than or equal to the monitoring stability reference evaluation value corresponding to the node sensor; The second monitoring evaluation verification result is that the monitoring stability evaluation value of a certain node sensor of the water-air interface is less than the monitoring stability reference evaluation value corresponding to the node sensor; If the CO2 monitoring and control platform receives the first monitoring, evaluation and verification result, there is no need to perform monitoring, correction and optimization on the node sensor. If the CO2 monitoring and control platform receives the second monitoring, evaluation and verification result, it is necessary to perform monitoring, correction and optimization on the node sensor.

6. The method for real-time monitoring of CO2 exchange at a water-air interface based on the Internet of Things according to claim 1, characterized in that: The CO2 monitoring data of the area to which each node sensor belongs specifically includes the CO2 emission coefficient of the area to which each node sensor belongs at each monitoring time point and the water-interface CO2 partial pressure difference of the area to which each node sensor belongs during the monitoring period.

7. The method for real-time monitoring of CO2 exchange at a water-air interface based on the Internet of Things according to claim 6, characterized in that: The specific evaluation process of evaluating the CO2 emission impact index of the area to which each node sensor of the water-air interface belongs is as follows: Obtain the corresponding area of ​​the area to which each node sensor belongs, perform ratio processing on the water-interface CO2 partial pressure difference of the area to which each node sensor belongs during the monitoring period and the corresponding area of ​​the area to which each node sensor belongs, and obtain the emission density of CO2 monitoring in the area to which each node sensor belongs during the monitoring period; Get the average pH value of the water body in the area where each node sensor belongs; According to the monitoring stability evaluation value of each node sensor of the water-air interface, the monitoring accuracy corresponding to each predefined monitoring stability evaluation value interval is matched, so as to obtain the monitoring accuracy of the sensor corresponding to the area to which each node sensor belongs; The CO2 emission impact index of the area to which each node sensor belongs at each monitoring time point is obtained by comprehensive analysis of the CO2 emission coefficient of the area to which each node sensor belongs at each monitoring time point, the emission density of CO2 monitoring in the area to which each node sensor belongs during the monitoring period, the average pH value of the water body in the area to which each node sensor belongs, and the monitoring accuracy of the corresponding sensor in the area to which each node sensor belongs. The specific method is as follows: In the formula, PF q is the CO2 emission impact index of the area to which the qth node sensor of the water-air interface belongs, q is the number of the area to which each node sensor belongs, q = 1, 2, 3, ..., Q, Q is the total amount of the area to which the node sensor belongs, V qt is the CO2 emission coefficient of the area to which the qth node sensor belongs at the tth monitoring time point, t is the time variable, t∈[t0, t1], t0 is the start monitoring time point, t1 is the end monitoring time point, PN q is the emission density of CO2 monitored in the area where the qth node sensor belongs during the monitoring period, PH q is the average pH value of the water body in the area where the qth node sensor belongs, ZQ q is the monitoring accuracy of the sensor corresponding to the area to which the qth node sensor belongs, y6 is the emission influencing parameter corresponding to the emission coefficient predefined in the water-air interface information database, y7 is the emission influencing parameter corresponding to the emission density predefined in the water-air interface information database, y8 is the emission influencing parameter corresponding to the average pH value of the water body predefined in the water-air interface information database, and y9 is the emission influencing parameter corresponding to the monitoring accuracy predefined in the water-air interface information database.

8. The method for real-time monitoring of CO2 exchange at a water-air interface based on the Internet of Things according to claim 7, characterized in that: The feedback of several CO2 abnormal nodes at the water-air interface is performed in the following specific feedback process: If the CO2 emission impact index of the area to which a node sensor of the water-air interface belongs is greater than the CO2 emission impact definition index, then the area to which the water-air interface node sensor corresponding to the CO2 emission impact index belongs is recorded as the CO2 abnormal node of the water-air interface, and thereby a number of CO2 abnormal nodes of the water-air interface corresponding to the CO2 emission impact index greater than the CO2 emission impact definition index are counted, and feedback is given to the several CO2 abnormal nodes of the water-air interface.

9. The method for real-time monitoring of CO2 exchange at a water-air interface based on the Internet of Things according to claim 1, characterized in that: The plurality of CO2 abnormal nodes provide feedback, specifically providing an abnormal CO2 emission warning to the plurality of CO2 abnormal nodes.

10. A system using the method for real-time monitoring of CO2 exchange at a water-air interface based on the Internet of Things as claimed in any one of claims 1 to 9, characterized in that: The environmental impact index determination module is used to obtain the environmental data of the area to which each node sensor of the water-air interface belongs, determine the environmental impact index of the area to which each node sensor belongs, and thereby match and obtain the monitoring stability reference evaluation value corresponding to each node sensor; The sensor monitoring, correction and optimization module is used to obtain the monitoring stability data of the sensors at each node of the water-air interface, determine the monitoring stability evaluation value of the sensors at each node of the water-air interface, verify it with the monitoring stability reference evaluation value corresponding to each node sensor, and upload the monitoring evaluation verification results to the water-air interface CO2 exchange monitoring and control platform based on the Internet of Things. The platform determines whether to perform monitoring, correction and optimization on each node sensor based on the verification results; The CO2 abnormal node feedback module is used to monitor the CO2 exchange at the water-air interface in real time through the sensors of each node, obtain the CO2 monitoring data of the area to which each node sensor belongs, evaluate the CO2 emission impact index of the area to which each node sensor of the water-air interface belongs, compare it with the predefined CO2 emission impact definition index, and count the CO2 abnormal nodes at the water-air interface, so as to feedback several CO2 abnormal nodes at the water-air interface, and finally complete the real-time monitoring of CO2 exchange at the water-air interface.

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