Carbon sequestration statistical method and system based on monitoring and evaluation of carbon sequestration potential of laver aquaculture

Abstract

The present invention discloses a carbon sink statistical method and system based on monitoring and evaluating the carbon sink potential of laver cultivation, comprising: real-time collection of environmental parameter data by a multi-parameter sensor array deployed in the cultivation area; construction of a carbon flux assessment model based on the laver cultivation biomass; simulation of the migration and transformation process of carbon elements in the "algae-water-sediment" system through a three-dimensional carbon transfer path tracing algorithm to obtain a three-dimensional carbon flux dynamic matrix; construction of a carbon sink spatiotemporal distribution model, and correction of the carbon sink spatiotemporal distribution based on the environmental data of the laver cultivation area; extraction of carbon element accumulation curves in different time dimensions, and construction of a carbon sink potential assessment function based on the laver growth cycle; establishment of a hierarchical judgment system, construction of three-level carbon sink capacity grades and their corresponding environmental parameter threshold combinations. The advantages of the present invention are: accurate assessment of the carbon storage potential of the laver cultivation area through real-time environmental data collection, carbon flux assessment, three-dimensional path simulation and spatiotemporal distribution correction.

Description

Technical Field

[0001] The present invention relates to contract optimization and early warning, and in particular to a carbon sink statistical method and system based on monitoring and evaluation of carbon sink potential of laver cultivation. Background Art

[0002] Monitoring and assessing the carbon sequestration potential of laver aquaculture uses scientific carbon sequestration statistical methods to evaluate laver aquaculture's ability to absorb and fix atmospheric carbon dioxide. Laver aquaculture not only efficiently absorbs carbon dioxide but also improves water quality and promotes the sustainable development of the marine ecosystem. Regular monitoring of laver aquaculture growth and carbon sequestration capacity can provide data support for governments and businesses in formulating carbon trading policies and carbon reduction targets.

[0003] The carbon sink statistical methods and systems currently available on the market for monitoring and evaluating the carbon sink potential of laver farming usually rely on relatively simple carbon flux estimation models, and lack comprehensive modeling of the complex ecological processes in laver farming areas, especially in terms of the migration and transformation of carbon elements between different environmental media. Many methods do not fully consider the carbon cycle in water bodies and sediments, resulting in poor accuracy and dynamics in carbon sink assessment results. In addition, existing methods usually lack real-time environmental parameter monitoring capabilities, fail to make timely corrections to carbon sink amounts in conjunction with environmental changes, and often fail to reflect changes in carbon sinks in laver farming areas during different seasons or growth cycles. Some methods lack three-dimensional carbon transfer path tracking and precise modeling of spatiotemporal distribution, resulting in relatively rough assessment results that are difficult to support high-precision carbon credit trading or ecological and environmental management decisions. Summary of the Invention

[0004] In order to improve the existing methods and systems, a carbon sequestration statistical method and system based on the monitoring and evaluation of the carbon sequestration potential of laver farming is provided. This method accurately evaluates the carbon sequestration potential of laver farming areas through real-time environmental data collection, carbon flux assessment, three-dimensional path simulation and spatiotemporal distribution correction, and constructs a grading judgment system based on the assessment results to provide scientific support for green development.

[0005] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0006] Carbon sequestration statistical methods based on the monitoring and assessment of carbon sequestration potential of laver aquaculture include:

[0007] Real-time collection of environmental parameter data through multi-parameter sensor arrays deployed in the breeding area;

[0008] Based on environmental parameter data and combined with laver culture biomass, a carbon flux assessment model is constructed. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the laver photosynthesis process, calculating the respiratory release rate based on the laver biomass and plant respiration model, and calculating the organic carbon decomposition rate based on the laver biomass changes and environmental data combined with the organic decomposition model;

[0009] Based on the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate obtained from the carbon flux assessment model, a three-dimensional carbon transfer path tracing algorithm is used to simulate the migration and transformation process of carbon elements in the "algae-water-sediment" process to obtain a three-dimensional carbon flux dynamic matrix.

[0010] A spatiotemporal distribution model of carbon sequestration was constructed based on a three-dimensional carbon flux dynamic matrix, and the spatiotemporal distribution of carbon sequestration was calibrated in combination with environmental data of laver cultivation areas.

[0011] Based on the calibrated spatiotemporal distribution model of carbon sequestration, carbon accumulation curves in different time dimensions were extracted, and a carbon sequestration potential evaluation function was constructed in combination with the laver growth cycle.

[0012] A grading judgment system is established based on the output value of the carbon sink potential assessment function, and a three-level carbon sink capacity grade and its corresponding environmental parameter threshold combination are constructed.

[0013] Preferably, the carbon flux assessment model is constructed based on the environmental parameter data in combination with the laver culture biomass. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the laver photosynthesis process, calculating the respiratory release rate based on the laver biomass and plant respiration model, and calculating the organic carbon decomposition rate based on the laver biomass change and environmental data combined with the organic decomposition model. Specifically, it includes:

[0014] A photosynthesis rate model was constructed based on the process of laver decomposing organic matter and releasing carbon dioxide, and the photosynthetic carbon fixation rate was calculated.

[0015] The respiratory release rate was calculated by combining the Q10 model of laver biomass and plant respiration;

[0016] Based on the changes in Porphyra biomass and environmental data, combined with the ecological organic decomposition model, the organic carbon decomposition rate was calculated;

[0017] The photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate are integrated to construct a comprehensive carbon flux assessment model.

[0018] Preferably, the photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate obtained based on the carbon flux assessment model simulate the migration and transformation process of carbon elements in "algae-water-sediment" through a three-dimensional carbon transfer path tracking algorithm to obtain a three-dimensional carbon flux dynamic matrix specifically including:

[0019] Based on the spatial scope of the laver cultivation area, determine the algae area, water area and sediment area to be simulated, and construct a three-dimensional spatial model;

[0020] Define the sources of carbon and capture the different transformation and migration processes of carbon based on carbon transport within Porphyra organisms and carbon cycling in sediments;

[0021] The three-dimensional spatial model is divided into multiple cells. Based on the transformation and migration process of carbon elements in each cell, a path tracing algorithm is used to simulate and model the carbon path of carbon elements in the "algae-water-sediment" process.

[0022] According to the division of three-dimensional space, a carbon flux matrix of each cell is constructed, which includes the inflow and outflow of carbon in each cell;

[0023] Based on the dynamic flux changes of carbon elements in each grid cell, a three-dimensional carbon flux dynamic matrix is ​​obtained.

[0024] Preferably, the construction of a carbon sequestration spatiotemporal distribution model based on a three-dimensional carbon flux dynamic matrix and correction of the carbon sequestration spatiotemporal distribution in combination with the laver cultivation area environmental data specifically includes:

[0025] Based on the three-dimensional carbon flux dynamic matrix and the periodic changes in the aquaculture area, the dynamic time series data of the three-dimensional carbon flux are obtained;

[0026] Based on the carbon inflow and outflow of each cell in the three-dimensional spatial model of the aquaculture area, the spatial distribution data of carbon elements are obtained;

[0027] Based on the dynamic time series data of three-dimensional carbon flux and the spatial distribution data of carbon elements, the carbon sink amount is calculated and a spatiotemporal distribution model of carbon sink amount is constructed;

[0028] Based on the real-time collected environmental parameter data, the carbon sink calculation of each cell in the model is adjusted according to the environmental characteristics of different regions. Combined with the seasonal change data, the carbon sink change curve over time in the model is adjusted to calibrate the carbon sink spatiotemporal distribution model.

[0029] Preferably, the extracting of carbon element accumulation curves in different time dimensions based on the corrected spatiotemporal distribution model of carbon sequestration and the construction of a carbon sequestration potential evaluation function in combination with the laver growth cycle specifically include:

[0030] Based on the calibrated spatiotemporal distribution model of carbon sequestration, the carbon sequestration output by the model was statistically analyzed according to different time dimensions. For each time period, the total carbon fixation in the laver cultivation area was calculated to obtain carbon accumulation data.

[0031] Based on the carbon accumulation data, the carbon accumulation curves in different time dimensions are constructed and the accumulation curves are smoothed;

[0032] Based on the growth cycles of Porphyra, the photosynthesis rate, respiratory release rate and carbon fixation efficiency of each stage were obtained;

[0033] Combining the growth rate, environmental factors and biomass of Porphyra at each stage, a carbon sequestration potential evaluation function was constructed, and the parameters in the function were optimized based on historical data and field measurement results.

[0034] Preferably, the establishment of a graded judgment system based on the output value of the carbon sink potential assessment function, and the construction of three-level carbon sink capacity grades and their corresponding environmental parameter threshold combinations specifically include:

[0035] Based on the output value of the carbon sequestration potential assessment function, a three-level carbon sequestration capacity rating is constructed, including high capacity, medium capacity and low capacity;

[0036] Based on the carbon sink capacity levels at each level, a combination of environmental parameter thresholds is set to form a graded judgment system.

[0037] Furthermore, a carbon sequestration statistical system based on the monitoring and evaluation of carbon sequestration potential of laver aquaculture is proposed, including:

[0038] Environmental parameter acquisition module: The environmental parameter acquisition module collects environmental parameter data of the laver cultivation area in real time by deploying a multi-parameter sensor array;

[0039] Carbon flux assessment module: The carbon flux assessment module is used to combine environmental parameter data with laver biomass to construct a carbon flux assessment model to obtain photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate;

[0040] Carbon transfer pathway module: The carbon transfer pathway module simulates the migration and transformation process of carbon elements in the "algae-water-sediment" process through a three-dimensional carbon transfer pathway tracking algorithm to obtain a three-dimensional carbon flux dynamic matrix;

[0041] Carbon sequestration spatiotemporal distribution module: The carbon sequestration spatiotemporal distribution module is based on a three-dimensional carbon flux dynamic matrix and combines environmental data to construct and calibrate a carbon sequestration spatiotemporal distribution model;

[0042] Carbon sink potential assessment module: The carbon sink potential assessment module extracts the accumulation curve of carbon elements based on the calibrated spatiotemporal distribution model of carbon sinks and constructs a carbon sink potential assessment function in combination with the laver growth cycle;

[0043] Carbon sink capacity classification and determination module: The carbon sink capacity classification and determination module establishes a three-level classification system for carbon sink capacity based on the output value of the carbon sink potential assessment function, and corresponds to the environmental parameter threshold combination;

[0044] Processor: The processor is used to process the calculation process of each formula and the construction calculation process of each model.

[0045] Compared with the prior art, the advantages of the present invention are:

[0046] By collecting environmental parameter data in real time and combining it with laver biomass, a carbon flux assessment model was constructed, which can accurately calculate the photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate, and comprehensively reflect the carbon storage and release process in the laver cultivation area. A three-dimensional carbon transfer path tracking algorithm was used to simulate the dynamic migration and transformation of carbon elements in the "algae-water body-sediment" to further accurately obtain the spatiotemporal distribution characteristics of the carbon flux. In addition, correcting the carbon sink amount in combination with environmental data helps to improve the timeliness and accuracy of the model. By extracting the carbon element accumulation curves in different time dimensions and combining it with the growth cycle of laver, a carbon sink potential assessment function was constructed, which achieved a scientific assessment of the carbon sink potential of the laver cultivation area. Finally, through a graded judgment system, different carbon sink capacity levels were delineated according to the carbon sink potential assessment results, providing a clear combination of environmental parameter thresholds. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of the method proposed in the present invention;

[0048] Figure 2 This is a schematic diagram of the carbon flux assessment model proposed in the present invention;

[0049] Figure 3 This is a schematic diagram of the three-dimensional carbon flux dynamic matrix proposed in the present invention;

[0050] Figure 4 This is a schematic diagram of the spatiotemporal distribution model of carbon sequestration proposed in the present invention;

[0051] Figure 5 This is a schematic diagram of the carbon sequestration potential evaluation function proposed in the present invention;

[0052] Figure 6 This is a schematic diagram of the grading judgment system proposed in the present invention;

[0053] Figure 7 This is a diagram of the architecture of the electronic equipment in this solution;

[0054] Figure 8 This is a schematic diagram of the computer-readable storage medium structure in this solution. DETAILED DESCRIPTION

[0055] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0056] The carbon sequestration statistics system based on the monitoring and assessment of carbon sequestration potential of laver aquaculture includes:

[0057] Environmental parameter acquisition module: The environmental parameter acquisition module collects environmental parameter data of the laver cultivation area in real time by deploying a multi-parameter sensor array;

[0058] Carbon flux assessment module: The carbon flux assessment module is used to combine environmental parameter data with laver biomass to construct a carbon flux assessment model to obtain photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate;

[0059] Carbon transfer pathway module: The carbon transfer pathway module simulates the migration and transformation process of carbon elements in the "algae-water-sediment" process through a three-dimensional carbon transfer pathway tracking algorithm to obtain a three-dimensional carbon flux dynamic matrix;

[0060] Carbon sequestration spatiotemporal distribution module: The carbon sequestration spatiotemporal distribution module is based on a three-dimensional carbon flux dynamic matrix and combines environmental data to construct and calibrate a carbon sequestration spatiotemporal distribution model;

[0061] Carbon sink potential assessment module: The carbon sink potential assessment module extracts the accumulation curve of carbon elements based on the calibrated spatiotemporal distribution model of carbon sinks and constructs a carbon sink potential assessment function in combination with the laver growth cycle;

[0062] Carbon sink capacity classification and determination module: The carbon sink capacity classification and determination module establishes a three-level classification system for carbon sink capacity based on the output value of the carbon sink potential assessment function, and corresponds to the environmental parameter threshold combination;

[0063] Processor: The processor is used to process the calculation process of each formula and the construction calculation process of each model.

[0064] See Figure 1 As shown in the figure, the carbon sequestration statistical method based on the monitoring and assessment of the carbon sequestration potential of laver aquaculture includes:

[0065] Step 1: Real-time collection of environmental parameter data through a multi-parameter sensor array deployed in the aquaculture area;

[0066] Step 2: Based on the environmental parameter data and combined with the laver culture biomass, a carbon flux assessment model is constructed. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the laver photosynthesis process, calculating the respiratory release rate based on the laver biomass and plant respiration model, and calculating the organic carbon decomposition rate based on the laver biomass changes and environmental data combined with the organic decomposition model;

[0067] Step 3: Based on the photosynthetic carbon fixation rate, respiratory release rate, and organic carbon decomposition rate obtained from the carbon flux assessment model, a three-dimensional carbon transfer path tracing algorithm is used to simulate the migration and transformation process of carbon elements in the "algae-water-sediment" process to obtain a three-dimensional carbon flux dynamic matrix;

[0068] Step 4: Construct a spatiotemporal distribution model of carbon sequestration based on the three-dimensional carbon flux dynamic matrix, and calibrate the spatiotemporal distribution of carbon sequestration based on the environmental data of the laver cultivation area;

[0069] Step 5: Based on the calibrated spatiotemporal distribution model of carbon sequestration, extract the carbon accumulation curves in different time dimensions and construct a carbon sequestration potential evaluation function based on the laver growth cycle;

[0070] Step 6: Establish a grading judgment system based on the output value of the carbon sink potential assessment function, and construct three-level carbon sink capacity grades and their corresponding environmental parameter threshold combinations.

[0071] See Figure 2 As shown, based on environmental parameter data and combined with laver cultivation biomass, a carbon flux assessment model is constructed. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the laver photosynthesis process, calculating the respiratory release rate based on the laver biomass and plant respiration model, and calculating the organic carbon decomposition rate based on the laver biomass change and environmental data combined with the organic decomposition model. Specifically, it includes:

[0072] A photosynthesis rate model was constructed based on the process of laver decomposing organic matter and releasing carbon dioxide, and the photosynthetic carbon fixation rate was calculated.

[0073] The respiratory release rate was calculated by combining the Q10 model of laver biomass and plant respiration;

[0074] Based on the changes in Porphyra biomass and environmental data, combined with the ecological organic decomposition model, the organic carbon decomposition rate was calculated;

[0075] The photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate are integrated to construct a comprehensive carbon flux assessment model.

[0076] Specifically, the photosynthesis rate is the rate at which laver fixes carbon dioxide through photosynthesis, and the formula is:

[0077] ;

[0078] in, is the photosynthesis rate, It is a function of photosynthetically active radiation, usually related to the ambient light intensity. This function can be expressed as a linear or exponential function. ,in is photosynthetically active radiation, is the light saturation constant, which reflects the ability of laver to absorb light. for photosynthesis efficiency;

[0079] The respiratory release rate of laver is the amount of carbon dioxide released by the plant's respiration. The plant's respiratory rate changes with temperature. The Q10 model is often used to express this relationship. The formula is:

[0080] ;

[0081] in, is the respiration rate at temperature T, At the reference temperature The respiratory rate under the condition of temperature, Q10 is the coefficient of influence of temperature on the respiratory rate;

[0082] The calculation of respiratory release rate involves the influence of laver biomass and temperature. The respiratory release rate of laver is obtained by combining the laver biomass with the Q10 model.

[0083] The organic carbon decomposition rate describes the rate at which organic matter in Porphyra releases carbon dioxide during decomposition, a process that is usually affected by factors such as temperature, humidity, Porphyra biomass, and microbial activity.

[0084] The photosynthesis rate, respiratory release rate and organic carbon decomposition rate are integrated to build a comprehensive carbon flux model.

[0085] See Figure 3 As shown in the figure, based on the photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate obtained by the carbon flux assessment model, the migration and transformation process of carbon elements in "algae-water-sediment" is simulated through the three-dimensional carbon transfer path tracking algorithm to obtain the three-dimensional carbon flux dynamic matrix, which specifically includes:

[0086] Based on the spatial scope of the laver cultivation area, determine the algae area, water area and sediment area to be simulated, and construct a three-dimensional spatial model;

[0087] Define the sources of carbon and capture the different transformation and migration processes of carbon based on carbon transport within Porphyra organisms and carbon cycling in sediments;

[0088] The three-dimensional spatial model is divided into multiple cells. Based on the transformation and migration process of carbon elements in each cell, a path tracing algorithm is used to simulate and model the carbon path of carbon elements in the "algae-water-sediment" process.

[0089] According to the division of three-dimensional space, a carbon flux matrix of each cell is constructed, which includes the inflow and outflow of carbon in each cell;

[0090] Based on the dynamic flux changes of carbon elements in each grid cell, a three-dimensional carbon flux dynamic matrix is ​​obtained.

[0091] Specifically, the algae zone refers to the water surface area where laver grows, including the laver organisms and the area directly affected. The water zone refers to the water layer in the water area where laver grows, mainly involving the transmission and exchange of dissolved organic matter and carbon dioxide. The sediment zone refers to the sediment layer at the bottom of the water body, mainly involving the decomposition and accumulation of organic carbon.

[0092] Sources of carbon include photosynthesis: seaweed absorbs carbon dioxide from water and fixes it into organic matter; plant respiration: seaweed's own metabolic processes release carbon dioxide; organic carbon decomposition: seaweed and other organic matter decompose in sediments and release carbon dioxide;

[0093] The carbon transformation and migration process includes: carbon transformation in algae: photosynthesis of laver fixes carbon dioxide, while respiration releases carbon dioxide; carbon exchange in water: exchange of carbon dioxide between water and the atmosphere and dissolution and release of organic carbon in water; carbon cycle in sediments: decomposition of organic matter in sediments releases carbon dioxide, while organic carbon is redeposited;

[0094] The path tracing algorithm is used to simulate the migration of carbon in the algae-water-sediment system. In each cell, based on the source and transformation process of carbon, the migration of carbon can be expressed by the following formula:

[0095] ;

[0096] in, For the cell The carbon content in is the carbon inflow into the cell, is the carbon outflow of the cell;

[0097] Based on the path tracing algorithm, the source and flow of carbon are obtained, and the transformation process of carbon between different regions is simulated;

[0098] According to the migration and transformation process of carbon, a carbon flux matrix is ​​established in each grid cell. The carbon flux matrix of each grid cell contains the inflow and outflow of carbon, and a three-dimensional carbon flux dynamic matrix is ​​constructed.

[0099] See Figure 4 As shown in the figure, a spatiotemporal distribution model of carbon sequestration is constructed based on the three-dimensional carbon flux dynamic matrix, and the spatiotemporal distribution of carbon sequestration is corrected in combination with the environmental data of laver cultivation areas. The specific steps include:

[0100] Based on the three-dimensional carbon flux dynamic matrix and the periodic changes in the aquaculture area, the dynamic time series data of the three-dimensional carbon flux are obtained;

[0101] Based on the carbon inflow and outflow of each cell in the three-dimensional spatial model of the aquaculture area, the spatial distribution data of carbon elements are obtained;

[0102] Based on the dynamic time series data of three-dimensional carbon flux and the spatial distribution data of carbon elements, the carbon sink amount is calculated and a spatiotemporal distribution model of carbon sink amount is constructed;

[0103] Based on the real-time collected environmental parameter data, the carbon sink calculation of each cell in the model is adjusted according to the environmental characteristics of different regions. Combined with the seasonal change data, the carbon sink change curve over time in the model is adjusted to calibrate the carbon sink spatiotemporal distribution model.

[0104] Specifically, the carbon flux of each grid cell at different time steps is obtained through the aforementioned three-dimensional carbon flux matrix, and modeling is performed using time series data. Based on the dynamic time series data of the three-dimensional carbon flux, the carbon inflow and outflow of each grid cell are obtained. The dynamic changes of carbon in space are discretized using numerical methods to obtain the distribution of carbon elements in three-dimensional space.

[0105] The carbon sink is calculated based on the carbon flow in each grid cell. The carbon sink is the accumulation of carbon in a certain spatial area per unit time. By integrating time series and spatial distribution data, a spatiotemporal distribution model of the carbon sink is constructed. Based on the real-time collected environmental parameter data, the carbon sink calculation of each cell is corrected.

[0106] Seasonal changes can be adjusted by adding a seasonal correction factor to adjust the change in carbon sequestration over time. The formula is:

[0107] ;

[0108] in, is the seasonal correction factor, It is a periodic function that reflects the influence of seasonal changes.

[0109] See Figure 5 As shown in the figure, based on the calibrated spatiotemporal distribution model of carbon sequestration, the carbon accumulation curves of different time dimensions are extracted, and the carbon sequestration potential evaluation function is constructed in combination with the laver growth cycle. Specifically, the following are included:

[0110] Based on the calibrated spatiotemporal distribution model of carbon sequestration, the carbon sequestration output by the model was statistically analyzed according to different time dimensions. For each time period, the total carbon fixation in the laver cultivation area was calculated to obtain carbon accumulation data.

[0111] Based on the carbon accumulation data, the carbon accumulation curves in different time dimensions are constructed and the accumulation curves are smoothed;

[0112] Based on the growth cycles of Porphyra, the photosynthesis rate, respiratory release rate and carbon fixation efficiency of each stage were obtained;

[0113] Combining the growth rate, environmental factors and biomass of Porphyra at each stage, a carbon sequestration potential evaluation function was constructed, and the parameters in the function were optimized based on historical data and field measurement results.

[0114] Specifically, carbon sink data were extracted based on the calibrated spatiotemporal distribution model. These data represent the carbon sink of each grid cell at different time points. The carbon sink data were statistically analyzed according to different time dimensions, and the changes in carbon accumulation data over time were plotted as a carbon accumulation curve. This curve shows the carbon accumulation in the laver cultivation area at different time periods.

[0115] The photosynthesis rate is the rate at which laver fixes carbon dioxide through photosynthesis during its growth. The photosynthesis rate can be modeled based on environmental parameters such as light intensity, temperature, laver biomass, and the laver's photosynthetic characteristics. The laver's respiration rate is the rate at which carbon dioxide is released during its metabolic activities. The carbon fixation efficiency represents the ratio between the amount of carbon fixed by laver through photosynthesis and the amount of carbon released through respiration.

[0116] Based on the growth cycle of laver, environmental factors such as light, temperature, nutrient concentration, and biomass, a carbon sequestration potential evaluation function was constructed. The parameters in the carbon sequestration potential evaluation function were optimized through historical data and field measurement results. The optimized carbon sequestration potential evaluation function can more accurately predict the carbon absorption and carbon fixation capacity of laver farming areas under different environmental and management conditions.

[0117] See Figure 6 As shown in the figure, a hierarchical judgment system is established based on the output value of the carbon sink potential assessment function, and a three-level carbon sink capacity level and its corresponding environmental parameter threshold combination are constructed, specifically including:

[0118] Based on the output value of the carbon sequestration potential assessment function, a three-level carbon sequestration capacity rating is constructed, including high capacity, medium capacity and low capacity;

[0119] Based on the carbon sink capacity levels at each level, a combination of environmental parameter thresholds is set to form a graded judgment system.

[0120] Specifically, the level of carbon sink capacity is determined based on the output value of the carbon sink potential assessment function, and the carbon sink potential is divided into three levels: the first-level carbon sink capacity refers to areas with strong carbon sink potential, which can absorb and store a large amount of carbon; the second-level carbon sink capacity refers to areas with medium carbon sink potential, with average carbon absorption and storage capacity; the third-level carbon sink capacity refers to areas with weak carbon sink potential, with low carbon absorption and storage capacity;

[0121] Light intensity has a significant impact on laver photosynthesis, with higher light intensity generally corresponding to higher carbon sequestration potential. Water temperature also has a significant impact on laver growth rate and photosynthesis, with suitable water temperature generally increasing carbon sequestration potential. Moderate salinity and good water quality (low nitrogen and phosphorus content) contribute to the healthy growth of laver, thereby improving its carbon sequestration capacity.

[0122] According to the specific data of environmental parameters, different threshold ranges are set, corresponding to the primary, secondary and tertiary carbon sink capacities respectively. According to the measured environmental data and the output value of the carbon sink potential assessment function, the carbon sink capacity level of each region is determined in turn.

[0123] Furthermore, the method according to the embodiment of the present application can also be used with the aid of Figure 7 The electronic device architecture shown in FIG. Figure 7 As shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to a network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store the carbon sequestration statistical method and system based on the monitoring and evaluation of the carbon sequestration potential of laver aquaculture provided in this application. The electronic device 500 may also include a terminal interface 508. Of course, Figure 7 The architecture shown is only exemplary and can be omitted according to actual needs when implementing different devices. Figure 7 One or more components of an electronic device are shown.

[0124] Figure 8 This is a schematic diagram of the computer-readable storage medium structure provided by an embodiment of the present application. Figure 8 As shown, a computer-readable storage medium 600 according to one embodiment of the present application is shown. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are executed by the processor, the carbon sink statistics method and system based on the monitoring and evaluation of the carbon sink potential of laver farming according to the embodiment of the present application described with reference to the above figures can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0125] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0126] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0127] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A carbon sequestration statistical method based on the monitoring and evaluation of carbon sequestration potential of laver aquaculture is characterized by: include: Real-time collection of environmental parameter data through multi-parameter sensor arrays deployed in the breeding area; Based on environmental parameter data and combined with laver culture biomass, a carbon flux assessment model is constructed. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the laver photosynthesis process, calculating the respiratory release rate based on the laver biomass and plant respiration model, and calculating the organic carbon decomposition rate based on the laver biomass changes and environmental data combined with the organic decomposition model; Based on the spatial scope of the laver cultivation area, determine the algae area, water area and sediment area to be simulated, and construct a three-dimensional spatial model; Define the sources of carbon and capture the different transformation and migration processes of carbon based on carbon transport within Porphyra organisms and carbon cycling in sediments; The three-dimensional spatial model is divided into multiple cells. Based on the transformation and migration process of carbon elements in each cell, a path tracing algorithm is used to simulate and model the carbon path of the algae-water-sediment. According to the division of three-dimensional space, a carbon flux matrix of each cell is constructed, which includes the inflow and outflow of carbon in each cell; Based on the dynamic flux changes of carbon elements in each grid cell, a three-dimensional carbon flux dynamic matrix is ​​obtained; Based on the three-dimensional carbon flux dynamic matrix and the periodic changes in the aquaculture area, the dynamic time series data of the three-dimensional carbon flux are obtained; Based on the carbon inflow and outflow of each cell in the three-dimensional spatial model of the aquaculture area, the spatial distribution data of carbon elements are obtained; Based on the dynamic time series data of three-dimensional carbon flux and the spatial distribution data of carbon elements, the carbon sink amount is calculated and a spatiotemporal distribution model of carbon sink amount is constructed; Based on real-time collected environmental parameter data, the carbon sequestration calculation of each cell in the model is adjusted according to the environmental characteristics of different regions. In combination with seasonal variation data, the temporal variation curve of carbon sequestration in the model is adjusted to calibrate the spatiotemporal distribution model of carbon sequestration. Based on the calibrated spatiotemporal distribution model of carbon sequestration, carbon accumulation curves in different time dimensions were extracted, and a carbon sequestration potential evaluation function was constructed in combination with the laver growth cycle. A grading judgment system is established based on the output value of the carbon sink potential assessment function, and a three-level carbon sink capacity grade and its corresponding environmental parameter threshold combination are constructed.

2. The carbon sink statistical method based on the carbon sink potential monitoring and evaluation of laver cultivation according to claim 1 is characterized in that: Based on the environmental parameter data and combined with the laver culture biomass, a carbon flux assessment model is constructed. The carbon flux assessment model includes: calculating the photosynthetic carbon fixation rate based on the laver photosynthesis process, calculating the respiratory release rate based on the laver biomass and plant respiration model, and calculating the organic carbon decomposition rate based on the laver biomass change and environmental data combined with the organic decomposition model. Specifically, the model includes: A photosynthesis rate model was constructed based on the process of laver decomposing organic matter and releasing carbon dioxide, and the photosynthetic carbon fixation rate was calculated. The respiratory release rate was calculated by combining the Q10 model of laver biomass and plant respiration; Based on the changes in Porphyra biomass and environmental data, combined with the ecological organic decomposition model, the organic carbon decomposition rate was calculated; The photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate are integrated to construct a comprehensive carbon flux assessment model.

3. The carbon sink statistical method based on the carbon sink potential monitoring and evaluation of laver cultivation according to claim 1 is characterized in that: The carbon sequestration potential evaluation function is constructed based on the corrected spatiotemporal distribution model of carbon sequestration, extracting carbon element accumulation curves in different time dimensions, and combining the laver growth cycle to form the carbon sequestration potential evaluation function. Specifically, the method includes: Based on the calibrated spatiotemporal distribution model of carbon sequestration, the carbon sequestration output by the model was statistically analyzed according to different time dimensions. For each time period, the total carbon fixation in the laver cultivation area was calculated to obtain carbon accumulation data. Based on the carbon accumulation data, the carbon accumulation curves in different time dimensions are constructed and the accumulation curves are smoothed; Based on the growth cycles of Porphyra, the photosynthesis rate, respiratory release rate and carbon fixation efficiency of each stage were obtained; Combining the growth rate, environmental factors and biomass of Porphyra at each stage, a carbon sequestration potential evaluation function was constructed, and the parameters in the function were optimized based on historical data and field measurement results.

4. The carbon sink statistical method based on the carbon sink potential monitoring and evaluation of laver cultivation according to claim 1 is characterized in that: The establishment of a grading judgment system based on the output value of the carbon sink potential assessment function, and the construction of three-level carbon sink capacity grades and their corresponding environmental parameter threshold combinations specifically include: Based on the output value of the carbon sequestration potential assessment function, a three-level carbon sequestration capacity rating is constructed, including high capacity, medium capacity and low capacity; Based on the carbon sink capacity levels at each level, a combination of environmental parameter thresholds is set to form a graded judgment system.

5. A carbon sink statistics system based on monitoring and evaluation of carbon sink potential of laver aquaculture, used to implement the carbon sink statistics method based on monitoring and evaluation of carbon sink potential of laver aquaculture according to any one of claims 1 to 4, characterized in that: include: Environmental parameter acquisition module: The environmental parameter acquisition module collects environmental parameter data of the laver cultivation area in real time by deploying a multi-parameter sensor array; Carbon flux assessment module: The carbon flux assessment module is used to combine environmental parameter data with laver biomass to construct a carbon flux assessment model to obtain photosynthetic carbon fixation rate, respiratory release rate and organic carbon decomposition rate; Carbon transfer pathway module: The module uses a three-dimensional carbon transfer pathway tracking algorithm to simulate the migration and transformation process of carbon elements in the "algae-water-sediment" process, and obtains a three-dimensional carbon flux dynamic matrix; Carbon sequestration spatiotemporal distribution module: The carbon sequestration spatiotemporal distribution module is based on a three-dimensional carbon flux dynamic matrix and combines environmental data to construct and calibrate a carbon sequestration spatiotemporal distribution model; Carbon sink potential assessment module: The carbon sink potential assessment module extracts the accumulation curve of carbon elements based on the calibrated spatiotemporal distribution model of carbon sinks and constructs a carbon sink potential assessment function in combination with the laver growth cycle; Carbon sink capacity classification and determination module: The carbon sink capacity classification and determination module establishes a three-level classification system for carbon sink capacity based on the output value of the carbon sink potential assessment function, and corresponds to the environmental parameter threshold combination; Processor: The processor is used to process the calculation process of each formula and the construction calculation process of each model.

6. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the carbon sequestration statistics method based on the monitoring and evaluation of the carbon sequestration potential of laver farming as described in any one of claims 1-4.

7. A computer-readable storage medium storing computer-readable instructions, characterized in that: When the computer-readable instructions are executed by a processor, the carbon sequestration statistics method based on monitoring and evaluation of carbon sequestration potential of laver farming according to any one of claims 1 to 4 is implemented.

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