Method and device for calculating algae cultivation space requirements under carbon neutrality goals

Abstract

The present invention discloses a method and device for calculating algae cultivation space requirements under the carbon neutrality goal, including: determining the total annual demand for algae carbon sinks under the carbon neutrality goal; calculating the carbon removal contribution ratio required by each cultivated algae under the carbon neutrality goal based on the current cultivation structure; calculating the carbon removal amount required by each cultivated algae under the carbon neutrality goal based on the annual demand total and the carbon removal contribution ratio; converting the carbon removal amount into dry weight production demand based on a large algae carbon sink calculation formula; and calculating the cultivation space demand corresponding to the dry weight production demand by constructing a historical production-area model. This method solves the core problems of large long-term prediction errors, weak model generalization ability, and insufficient adaptation to seaweed heterogeneity in related technologies, providing a precise decision-making tool for seaweed cultivation space planning driven by carbon neutrality goals.

Description

Technical Field

[0001] The present application relates to the fields of environmental engineering and biotechnology, and in particular to a method and device for calculating algae cultivation space requirements under the goal of carbon neutrality. Background Art

[0002] Carbon sink calculation methods are key technologies for assessing the carbon absorption capacity of ecosystems. Their development context is closely tied to global climate change and carbon neutrality goals. Existing technologies primarily address different scales and precision requirements, combining multidisciplinary approaches such as ecology, remote sensing, meteorology, and model simulation. Current carbon sink calculation techniques primarily encompass the following methods:

[0003] In terrestrial ecosystems, (1) the inventory method is based on fixed plot observations and soil stratification sampling, combined with elemental analyzers to determine organic carbon content, but the temporal and spatial resolution is limited; (2) the eddy covariance method monitors CO2 flux through high-frequency sensors, relies on global flux network site data, and has high equipment costs; (3) the remote sensing inversion model uses MODIS / Landsat satellite data to drive the light energy utilization model to estimate net primary productivity, but is significantly affected by cloud interference.

[0004] In terms of marine carbon sinks, (1) biogeochemical models simulate the biological pump flux and couple regional ocean models to analyze the vertical transport of carbon; (2) sediment traps and isotope tracing techniques quantify carbon deposition flux, but the cost of ship-based observations is high; (3) seaweed carbon sink accounting is based on the C / N ratio of algal tissue and remote sensing inversion to assess carbon sequestration, but the sedimentation storage ratio is controversial. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to provide a method and device for calculating the space demand for algae cultivation under the carbon neutrality goal, so as to solve the core problems existing in the related technologies, such as large long-term prediction errors, weak model generalization ability, and insufficient adaptation to seaweed heterogeneity, and provide an accurate decision-making tool for seaweed cultivation space planning driven by the carbon neutrality goal.

[0006] According to a first aspect of an embodiment of the present application, a method for calculating algae cultivation space requirements under a carbon neutrality goal is provided, comprising:

[0007] Determine the total annual demand for algae carbon sinks under the carbon neutrality goal;

[0008] Based on the current aquaculture structure, calculate the carbon removal contribution ratio that each aquaculture algae needs to bear under the carbon neutrality goal;

[0009] Calculate the carbon removal amount that each cultivated algae needs to undertake under the carbon neutrality goal based on the total annual demand and the carbon removal contribution ratio;

[0010] Based on the macroalgae carbon sink calculation formula, the carbon removal amount is converted into dry weight production requirements;

[0011] By constructing a historical yield-area model, the farming space requirement corresponding to the dry weight yield requirement is calculated;

[0012] The formula used in the macroalgae carbon sink calculation method is as follows:

[0013]

[0014] Where, is the carbon sequestration capacity of macroalgae; is the wet weight of the i-th cultured algae; is the conversion factor from wet weight to dry weight of the i-th algae; is the dry weight carbon content of the i-th algae.

[0015] According to a second aspect of an embodiment of the present application, there is provided a device for calculating algae cultivation space requirements under a carbon neutrality goal, comprising:

[0016] A determination module for determining the total annual demand for algae carbon sinks under the carbon neutrality goal;

[0017] The first calculation module is used to calculate the carbon removal contribution ratio that each cultured algae needs to bear under the carbon neutrality goal based on the current aquaculture structure;

[0018] A second calculation module is used to calculate the carbon removal amount that each cultivated algae needs to undertake under the carbon neutrality goal based on the annual total demand and the carbon removal contribution ratio;

[0019] a conversion module, configured to convert the carbon removal amount into a dry weight production requirement based on a macroalgae carbon sink calculation formula;

[0020] A third calculation module is used to calculate the breeding space requirement corresponding to the dry weight yield requirement by constructing a historical yield-area model;

[0021] The formula used in the macroalgae carbon sink calculation method is as follows:

[0022]

[0023] Where, is the carbon sequestration capacity of macroalgae; is the wet weight of the i-th cultured algae; is the conversion factor from wet weight to dry weight of the i-th algae; is the dry weight carbon content of the i-th algae.

[0024] According to a third aspect of the embodiments of the present application, there is provided an electronic device, including:

[0025] one or more processors;

[0026] a memory for storing one or more programs;

[0027] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in the first aspect.

[0028] The technical solutions provided by the embodiments of the present application may have the following beneficial effects:

[0029] It can be seen from the above embodiments that this application determines the total annual demand for algae carbon sinks under the carbon neutrality target, calculates the carbon removal contribution ratio of each cultured algae under the carbon neutrality target based on the current breeding structure, calculates the carbon removal amount that each cultured algae needs to undertake under the carbon neutrality target based on the annual demand total and the carbon removal contribution ratio, and converts the carbon removal amount into dry weight production demand based on the large algae carbon sink calculation formula. By constructing a historical production-area model, the breeding space demand corresponding to the dry weight production demand is calculated to form a standardized carbon-production-area conversion system, which solves the core problems of large long-term prediction errors, weak model generalization ability, and insufficient adaptation to seaweed heterogeneity in related technologies, and provides accurate decision-making tools for seaweed breeding space planning driven by carbon neutrality targets.

[0030] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0032] Figure 1 The present invention is a flowchart showing a method for calculating algae cultivation space requirements under a carbon neutrality goal according to an exemplary embodiment.

[0033] Figure 2 is the algae carbon removal contribution ratio C shown according to an exemplary embodiment. r Dynamic smooth trajectory diagram.

[0034] Figure 3 The present invention shows the time series modeling of the yield of kelp and hijiki according to an exemplary embodiment.

[0035] Figure 4 It is a structural schematic diagram of a device for calculating algae cultivation space requirements under the carbon neutrality goal according to an exemplary embodiment.

[0036] Figure 5 The figure is a schematic structural diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0037] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0038] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0039] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0040] Explanation of terms:

[0041] Carbon neutrality: Through energy conservation and emission reduction, carbon sink offset and other means, the CO2 emitted by human activities in a specific period of time is balanced with its absorption, achieving the goal of net zero carbon emissions.

[0042] Carbon sink: refers to the process or carrier that absorbs and stores CO2 through natural or artificial systems (such as forests, oceans, and carbon capture technology), thereby reducing the concentration of greenhouse gases in the atmosphere.

[0043] Algae-derived carbon sink: A form of carbon sink, which refers to the conversion of CO2 and dissolved inorganic carbon (DIC) in seawater into dissolved organic carbon (DOC) and particulate organic carbon (POC) through photosynthesis by large algae, and then converted into highly biologically inert and difficult to decompose dissolved organic carbon (RDOC) through the microbial carbon pump (MCP) mechanism. This carbon can be stored in seawater for a long time, forming a stable and inert dissolved carbon pool in the aquaculture carbon sink.

[0044] Figure 1 is a flow chart showing a method for calculating algae cultivation space requirements under a carbon neutrality goal according to an exemplary embodiment. Figure 1 As shown, the method is applied in a terminal and may include the following steps:

[0045] S1: Determine the total annual demand for algae carbon sinks under the carbon neutrality goal;

[0046] Specifically, according to the research of Fuhrman et al., in order to achieve the goal of carbon neutrality, the total amount of CO2 that needs to be stored by plant carbon sinks each year is 2~3Gt. This study assumes that the total carbon removal capacity (Total carbon removal, T c ) is 2.5 Gt, which is the same as the study assumption of Gao et al.

[0047] S2: Based on the current aquaculture structure, calculate the carbon removal contribution ratio that each aquaculture algae needs to bear under the carbon neutrality goal; this step includes the following sub-steps:

[0048] S21: Calculate the carbon removal of different algae in each historical year based on the macroalgae carbon sink calculation formula;

[0049] Specifically, given that prior to 2003, statistics on marine algae aquaculture in my country primarily focused on kelp and laver, this example selected data from 2003 to 2023 as the research period to ensure comprehensiveness and data reliability. Key aquaculture data, including aquaculture species, production, and area, were sourced from the China Fisheries Statistical Yearbook.

[0050] This example measures the carbon sink capacity of different algae based on the calculation method for the carbon sink capacity of large algae in the "Marine Carbon Sink Accounting Method" (HY / T 0349-2022, China).

[0051] The formula used in the macroalgae carbon sink calculation method is as follows:

[0052]

[0053] Where, is the carbon sequestration capacity of macroalgae; is the wet weight of the i-th cultured algae; is the conversion factor from wet weight to dry weight of the i-th algae; is the dry weight carbon content of the i-th algae.

[0054] The China Fisheries Statistical Yearbook records the aquaculture data of 7 algae species, including production data and area. All production data are calculated in dry weight. The algae species involved in this embodiment include kelp (Saccharina japonica), kelp (Undaria pinnatifida), seaweed (Pyropia spp.), Gracilaria (Gracilaria spp.), Eucheuma (Eucheuma spp.), Sargassum fusiforme (Sargassum fusiforme) and other algae. Among them, moss (Ulva spp.) and agar-agar (Gelidium spp.) are classified as "other algae" for calculation due to their low aquaculture production and missing data. The production data of the above algae can be obtained through the China Fisheries Statistical Yearbook. The production data of each algae = * .

[0055] Obtaining the dry weight carbon content of different algae , see Table 1, and put it together with the yield data into the formula of the macroalgae carbon sink calculation method to calculate the macroalgae carbon sink .

[0056] Table 1. Dry weight carbon content of different algae ;

[0057]

[0058] Without considering long-term carbon fixation, the carbon sink and carbon removal are equal, so the carbon removal of different algae in each historical year is obtained, see Table 2.

[0059] Table 2. Carbon removal by different algae in each historical year (2003-2023);

[0060]

[0061] S22: Calculate the carbon removal contribution ratio C of different algae in each historical year based on the ratio of carbon removal of different algae in each historical year to the total carbon removal in the corresponding year. r ';

[0062] Specifically, in order to quantify the carbon removal contribution of each cultured algae under the carbon neutrality goal, the algae carbon sequestration contribution ratio (C r ) This key indicator. r It is numerically equal to the ratio of the carbon removal of different algae in each year to the total carbon removal in that year.

[0063] The carbon removal amount of different algae in each historical year obtained in step S21, and the total carbon removal amount in the corresponding year are the sum of the carbon removal amounts of different algae in each historical year (ie, Total in Table 2).

[0064] Then, the carbon removal amount of different algae in each historical year was divided by the total carbon removal amount in the corresponding year to obtain the carbon removal contribution ratio C of different algae in each historical year. r ', see Table 3.

[0065] Table 3. Carbon removal contribution ratios of different algae r '(2003-2023);

[0066]

[0067] S23: Using a double cross-validation framework to predict the carbon removal contribution ratio C of each cultivated algae under the carbon neutrality target r ,include:

[0068] Path 1 (time series extrapolation modeling): Based on the carbon removal contribution ratio of algae in each historical year C r ', predict the carbon removal contribution ratio C that each cultured algae needs to bear under the carbon neutrality goal r ;

[0069] Path 2 (component analysis modeling): Based on the carbon removal of different algae in each historical year, the carbon removal of each algae under the carbon neutrality target is predicted. According to the ratio of the carbon removal of each algae under the carbon neutrality target to the total carbon removal in the corresponding year, the carbon removal contribution ratio C of each cultivated algae under the carbon neutrality target is calculated. r .

[0070] Since the algae carbon sink contribution ratio (C r The sample time span of the 2003-2023 period is relatively small, and the time series model has an error accumulation effect in long-term extrapolation prediction. A single prediction method may lead to biased results. To improve the robustness and scientificity of the prediction results, this embodiment adopts a dual cross-validation framework to directly predict (Direct Prediction, Path 1) the carbon sink contribution ratio (C r ), and combined with component analysis modeling (Indirect Prediction, path 2) to infer C r Through hybrid modeling strategies, we systematically optimize forecast robustness and reduce model uncertainty.

[0071] In the above prediction process, it is necessary to select a suitable prediction model or method, which can be selected from the Regression Analysis Method (RAM), Exponential Smoothing Algorithm (ESA), Grey Model (GM(1,1)) and Autoregressive Integrated Moving Average (ARIMA) model, etc.

[0072] In order to select the optimal prediction model or method and ensure the robustness of the prediction results, this embodiment establishes a three-level evaluation system:

[0073] (1) Historical data cross-validation: Perform a single rolling validation of historical data for path 1 and path 2, and calculate the root mean square error (RMSE), mean absolute percentage error (MAPE) and goodness of fit (R) of each model validation set. 2 ).

[0074] (2) Physical constraint verification: verify the predicted carbon removal contribution ratio C r Does it meet C r ∈[0,1] boundary conditions.

[0075] (3) Optimal model selection criteria: Based on the prediction performance indicators, the prediction model optimization rules are established for each type of algae. The optimization rules are as follows: ① The validation set with the smallest RMSE and R 2 > 0.8; ② When the RMSE difference is <5%, the model with the smaller MAPE is selected; ③ Candidate models that fail the physical constraint verification are excluded; and the optimal prediction model is selected according to the optimization rules. Table 4 shows the results of the algae path and model selection.

[0076] Table 4. Study algae pathways and model selection results;

[0077]

[0078] In order to eliminate short-term fluctuations and highlight long-term trends, the model prediction results can be post-processed. Specifically, the cross-cycle sliding mean processing is implemented on the prediction values ​​​​from 2025 to 2060, and the systematic deviations between models are corrected through the sum normalization method. Figure 2 is the algae carbon sink contribution ratio (C r , %) dynamic smooth trajectory (2025-2060).

[0079] This application uses a double cross-validation framework to predict the carbon removal contribution ratio C that each cultivated algae needs to bear under the carbon neutrality goal. r, avoiding the bias problem caused by the single prediction method relying on the linear extrapolation of historical data or subjective weight allocation. Through the mutual verification and calibration of the results of the two paths, the carbon removal contribution ratio C r The prediction accuracy is high, ensuring the carbon removal amount C of each algae under the carbon neutrality goal i Scientific distribution.

[0080] S3: Calculating the carbon removal amount based on the annual total demand and the carbon removal contribution ratio;

[0081] Specifically, the formula for calculating carbon removal is as follows:

[0082] ;

[0083] Where C i is the carbon removal capacity of the i-th cultured algae; T c is the total annual demand; C r is the carbon removal contribution ratio.

[0084] S4: Based on the macroalgae carbon sink calculation formula, convert the carbon removal amount into dry weight production requirements; this step includes the following sub-steps:

[0085] S41: Based on the carbon sink calculation formula for large seaweed, the production requirement formula for each algae under the carbon neutrality goal is analytically derived. The production requirement formula is as follows:

[0086] ;

[0087] Where, P i is the dry weight yield requirement of the i-th cultured algae, C i is the carbon removal capacity of the i-th cultured algae; is the conversion factor from wet weight to dry weight of the i-th cultured algae; is the dry weight carbon content of the i-th cultured algae;

[0088] S42: Calculate the dry weight yield requirement of each algae according to the carbon removal amount and yield requirement formula.

[0089] Calculating the dry weight yield requirements of each algae species is one of the important steps in forming a standardized carbon-yield-area conversion system. Based on the calculation results of dry weight yield requirements, the aquaculture space requirements of different algae species are further quantified.

[0090] S5: Calculate the farming space requirement corresponding to the dry weight production requirement by constructing a historical production-area model; this step includes the following sub-steps:

[0091] S51: For algae species with significant elasticity coefficients (P < 0.05), an elasticity coefficient model was used to construct a historical yield-area model. The elasticity coefficient model is as follows:

[0092] ;

[0093] Among them, A i is the aquaculture area requirement corresponding to the dry weight production demand of the i-th algae species; E represents the elasticity coefficient, α is the constant term, and the least squares method is used for parameter estimation; P i is the dry weight yield requirement of the i-th algae species;

[0094] For different algae, different elastic coefficients E and constant terms α were selected to obtain their respective elastic coefficient models; the model confidence test was performed on each elastic coefficient model, see Table 5.

[0095] Table 5. Model parameter selection and model confidence test for different algae.

[0096]

[0097] For algae species with insignificant elasticity coefficients (P > 0.05), a three-level progressive strategy was used to establish a historical yield-area model.

[0098] In one embodiment, before constructing the historical production-area model, a box plot method can be used to eliminate outliers, aiming to improve data quality and model robustness.

[0099] In one embodiment, the three-level progressive strategy is as follows: 1. nonlinear area-yield model; 2. non-parametric method; 3. yield time series modeling.

[0100] By constructing a historical yield-area model that combines an elasticity coefficient model with a three-level progressive strategy, we can avoid the problem that traditional static models are unable to reflect the differences in yield-area of ​​different algae, and ultimately achieve accurate quantification of the space requirements for different algae cultivation.

[0101] In this example, for algae that do not meet the elastic coefficient model assumptions (undaria, sargassum, and other algae), polynomial, exponential, and power function nonlinear models were established in sequence. Only the area-yield quadratic polynomial model for 'other algae' met the first-level screening criteria (R 2 = 0.55 > 0.5). The nonlinear model of kelp and sargassum was not significant (R 2 <0.5, and further nonparametric modeling was performed using locally weighted regression (LOESS). The optimal bandwidth was determined by cross-validation, but it was still not applicable to the two types of algae data (Wakame R 2 = 0.22; Sargassum fusiforme R 2 = -1.55). Finally, the yield (yield / area) of Undaria pinnatifida and Sargassum fusiformis from 2003 to 2023 was extracted to explore the time series modeling method.

[0102] Figure 3 Modeling of the yield time series of kelp and sargassum, including (a) interannual yield variation trend; (b) residual autocorrelation analysis of kelp yield (lagged 10); (c) linear fitting results of sargassum yield (RMSE = 1.55, R 2 = 0.92). The interannual trends in yield (tons / hectare) of Undaria pinnatifida and Sargassum fusiformis from 2003 to 2023 are shown in Figure 3 (a) in Figure 1. Nepotism products exhibit random fluctuations with no significant temporal trend (mean = 24.78, standard deviation = 5.28, CV = 21.3%). The ADF test indicates that the series is non-stationary (p = 0.41), but the residual analysis shows that its lag 10 autocorrelation is not significant ( Figure 3 (b) in the figure), and the Ljung-Box test p = 0.060 > 0.05, the residual is white noise, and the constant model (Y = 24.8) is supported. The production of Yangqi menu has a stable growth trend. After five-fold cross-validation, the linear model is preferred ( Figure 3 (c), R 2 = 0.92, RMSE = 1.55).

[0103] The historical yield-area models for each algae are as follows: the elasticity coefficient model is used for kelp, laver, Gracilaria, and Eucheuma; the quadratic polynomial model is used for other algae; and the yield time series model is used for Undaria and Sargassum.

[0104] S52: Calculating the breeding area requirement corresponding to the dry weight yield requirement based on the historical yield-area model.

[0105] By deconstructing the correlation between the area and production of various algae aquaculture species during the period 2003–2022, a historical production-area model was constructed, and then the theoretical minimum aquaculture area that relies on seaweed carbon sequestration was derived (see Table 6).

[0106] Table 6. Production demand parameters of major economic algae (2025-2060);

[0107]

[0108] Calculations indicate that under the carbon neutrality goal, the total area required for algae cultivation will be 7,191,860 hectares per year, 3.25 times the total marine aquaculture area in China in 2023 (2,214,870 hectares) and nearly 50 times the total algae cultivation area in 2023 (149,570 hectares). Analysis of algae cultivation space requirements under the carbon neutrality goal indicates that large-scale algae cultivation must prioritize addressing spatial constraints and urgently expand aquaculture areas to deeper and deeper waters. Furthermore, relying solely on seaweed for carbon sequestration must simultaneously overcome the dual challenges of surging economic costs (e.g., offshore infrastructure construction) and exceeding ecological carrying capacity.

[0109] Corresponding to the aforementioned embodiment of the method for calculating the algae cultivation space demand under the carbon neutrality goal, the present application also provides an embodiment of a device for calculating the algae cultivation space demand under the carbon neutrality goal.

[0110] Figure 4 This is a block diagram of a device for calculating algae cultivation space requirements under a carbon neutrality goal according to an exemplary embodiment. Figure 4 , the device comprises:

[0111] Determine Module 1, which is used to determine the total annual demand for algae carbon sinks under the carbon neutrality goal;

[0112] The first calculation module 2 is used to calculate the carbon removal contribution ratio that each cultured algae needs to bear under the carbon neutrality goal based on the current culture structure;

[0113] The second calculation module 3 is used to calculate the carbon removal amount that each cultivated algae needs to undertake under the carbon neutrality target based on the annual total demand and the carbon removal contribution ratio;

[0114] A conversion module 4 is used to convert the carbon removal amount into dry weight production requirements based on a macroalgae carbon sink calculation formula;

[0115] The third calculation module 5 is used to calculate the breeding space requirement corresponding to the dry weight yield requirement by constructing a historical yield-area model.

[0116] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0117] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the partial description of the method embodiments. The device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0118] Accordingly, the present application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method for calculating the algae cultivation space requirement under the carbon neutrality goal. Figure 5 As shown, a hardware structure diagram of a device for calculating algae cultivation space requirements under the carbon neutrality goal provided by an embodiment of the present invention is provided, in addition to Figure 5 In addition to the processor and memory shown, any device with data processing capabilities in which the apparatus in the embodiment is located may also include other hardware according to the actual functions of the device with data processing capabilities, which will not be described in detail.

[0119] Accordingly, the present application also provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the method for calculating the algae cultivation space requirement under the carbon neutrality target as described above. The computer-readable storage medium can be an internal storage unit of any device with data processing capabilities described in any of the aforementioned embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), an SD card, a flash card, etc. equipped on the device. Furthermore, the computer-readable storage medium can also include both an internal storage unit and an external storage device of any device with data processing capabilities. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and can also be used to temporarily store data that has been output or is to be output.

[0120] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the contents disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered merely as exemplary, and the true scope and spirit of the present application are indicated by the claims.

[0121] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for calculating algae cultivation space requirements under the carbon neutrality goal, characterized in that: include: Determine the total annual demand for algae carbon sinks under the carbon neutrality goal; Based on the current aquaculture structure, calculate the carbon removal contribution ratio that each aquaculture algae needs to bear under the carbon neutrality goal; Calculate the carbon removal amount that each cultivated algae needs to undertake under the carbon neutrality goal based on the total annual demand and the carbon removal contribution ratio; Based on the macroalgae carbon sink calculation formula, the carbon removal amount is converted into dry weight production requirements; By constructing a historical yield-area model, the farming space requirement corresponding to the dry weight yield requirement is calculated; The calculation formula for the macroalgae carbon sink is as follows: ； Where, is the carbon sequestration capacity of macroalgae; For the i Wet weight of cultured algae; For the i Conversion factor from wet weight to dry weight of algae species; For the i Carbon content of dry weight of algae; Among them, based on the current aquaculture structure, the carbon removal contribution ratio that each aquaculture algae needs to bear under the carbon neutrality goal is calculated, including: According to the carbon sink calculation formula of macroalgae, the carbon removal amount of different algae in each historical year was calculated; The carbon removal contribution ratio of different algae in each historical year was calculated based on the ratio of the carbon removal amount of different algae in each historical year to the total carbon removal amount in the corresponding year; Among them, a double cross-validation framework is used to predict the carbon removal contribution ratio that each cultured algae needs to bear under the carbon neutrality goal, including: Path 1: Based on the carbon removal contribution ratios of different algae in various historical years, predict the carbon removal contribution ratios that each cultivated algae needs to bear under the carbon neutrality goal; Path 2: Based on the carbon removal amounts of different algae in each historical year, the carbon removal amount of each algae under the carbon neutrality target is predicted. The carbon removal contribution ratio that each cultivated algae needs to bear under the carbon neutrality target is calculated based on the ratio of the carbon removal amount of each algae under the carbon neutrality target to the total carbon removal amount in the corresponding year; The optimal prediction model used in the prediction is determined through the following three-level evaluation system: (1) Perform a single rolling validation of historical data for Path 1 and Path 2, and calculate the prediction performance indicators of the validation set of each prediction model; (2) Verify whether the predicted carbon removal contribution ratio meets the boundary conditions; (3) establishing a prediction model optimization rule for each type of algae based on the prediction performance index, and then selecting the optimal prediction model based on the optimization rule; The calculation of the aquaculture area requirement corresponding to the dry weight production requirement by constructing a historical production-area model includes: For aquaculture algae with significant elasticity coefficients, an elasticity coefficient model is used to construct a historical production-area model. The elasticity coefficient model is as follows: ； Where, A i For the i The cultivation area requirement corresponding to the dry weight production demand of cultivated algae; E Characterizes the elastic modulus, α is a constant term; P i For the i dry weight yield requirements of algae species; For aquaculture algae with insignificant elasticity coefficient, a three-level progressive strategy was used to establish a historical production-area model; Calculating the aquaculture area requirement corresponding to the dry weight production requirement based on the historical production-area model; Among them, the three-level progressive strategy is as follows:

1. Nonlinear area-yield model; 2. Non-parametric method; 3. Yield time series modeling.

2. The method according to claim 1, characterized in that The calculation formula for the carbon removal amount is as follows: ； Where, C i For the i Carbon removal by cultured algae; T c is the total annual demand; C r is the carbon removal contribution ratio.

3. The method according to claim 1, characterized in that Based on the macroalgae carbon sequestration calculation formula, the carbon removal amount is converted into dry weight production requirements, including: Based on the calculation formula of large seaweed carbon sequestration, the production demand formula of each algae under the carbon neutrality goal was analytically derived, and the production demand formula is as follows: ； Where, P i For the i Dry weight yield requirements for cultivated algae, C i For the i Carbon removal by cultured algae; For the i Conversion factor from wet weight to dry weight of cultivated algae; For the i The dry weight carbon content of the cultivated algae; The dry weight yield requirement of each algae is calculated based on the carbon removal amount and yield requirement formula.

4. A device for calculating algae cultivation space requirements under the carbon neutrality goal, characterized in that: include: A determination module for determining the total annual demand for algae carbon sinks under the carbon neutrality goal; The first calculation module is used to calculate the carbon removal contribution ratio that each cultured algae needs to bear under the carbon neutrality goal based on the current aquaculture structure; A second calculation module is used to calculate the carbon removal amount that each cultivated algae needs to undertake under the carbon neutrality goal based on the annual total demand and the carbon removal contribution ratio; a conversion module, configured to convert the carbon removal amount into a dry weight production requirement based on a macroalgae carbon sink calculation formula; A third calculation module is used to calculate the breeding space requirement corresponding to the dry weight yield requirement by constructing a historical yield-area model; The calculation formula for the macroalgae carbon sink is as follows: ； Where, is the carbon sequestration capacity of macroalgae; For the i Wet weight of cultured algae; For the i Conversion factor from wet weight to dry weight of algae species; For the i Carbon content of dry weight of algae; Among them, based on the current aquaculture structure, the carbon removal contribution ratio that each aquaculture algae needs to bear under the carbon neutrality goal is calculated, including: According to the carbon sink calculation formula of macroalgae, the carbon removal amount of different algae in each historical year was calculated; The carbon removal contribution ratio of different algae in each historical year was calculated based on the ratio of the carbon removal amount of different algae in each historical year to the total carbon removal amount in the corresponding year; Among them, a double cross-validation framework is used to predict the carbon removal contribution ratio that each cultured algae needs to bear under the carbon neutrality goal, including: Path 1: Based on the carbon removal contribution ratios of different algae in various historical years, predict the carbon removal contribution ratios that each cultivated algae needs to bear under the carbon neutrality goal; Path 2: Based on the carbon removal amounts of different algae in each historical year, the carbon removal amount of each algae under the carbon neutrality target is predicted. The carbon removal contribution ratio that each cultivated algae needs to bear under the carbon neutrality target is calculated based on the ratio of the carbon removal amount of each algae under the carbon neutrality target to the total carbon removal amount in the corresponding year; The optimal prediction model used in the prediction is determined through the following three-level evaluation system: (1) Perform a single rolling validation of historical data for Path 1 and Path 2, and calculate the prediction performance indicators of the validation set of each prediction model; (2) Verify whether the predicted carbon removal contribution ratio meets the boundary conditions; (3) establishing a prediction model optimization rule for each type of algae based on the prediction performance index, and then selecting the optimal prediction model based on the optimization rule; The calculation of the aquaculture area requirement corresponding to the dry weight production requirement by constructing a historical production-area model includes: For aquaculture algae with significant elasticity coefficients, an elasticity coefficient model is used to construct a historical production-area model. The elasticity coefficient model is as follows: ； Where, A i For the i The cultivation area requirement corresponding to the dry weight production demand of cultivated algae; E Characterizes the elastic modulus, α is a constant term; P i For the i dry weight yield requirements of algae species; For aquaculture algae with insignificant elasticity coefficient, a three-level progressive strategy was used to establish a historical production-area model; Calculating the aquaculture area requirement corresponding to the dry weight production requirement based on the historical production-area model; Among them, the three-level progressive strategy is as follows:

1. Nonlinear area-yield model; 2. Non-parametric method; 3. Yield time series modeling.

5. An electronic device, characterized in that: include: one or more processors; a memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 3.

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