Method and device for calculating algae culture space demand under carbon neutralization target

Abstract

The invention discloses a method and a device for calculating an algae culture space demand under a carbon neutralization target. The method comprises the following steps: determining the annual total demand of algae carbon sink under the carbon neutralization target; based on the current culture structure, calculating a carbon removal contribution ratio which needs to be borne by each culture algae under a carbon neutralization target; according to the annual total demand and the carbon removal contribution ratio, calculating the carbon removal amount to be borne by each cultured algae under a carbon neutralization target; based on a macroalgae carbon sink calculation formula, converting the carbon removal amount into a dry weight yield demand; and calculating a breeding space demand corresponding to the dry weight yield demand by constructing a historical yield-area model. The core problems of large long-term prediction error, weak model generalization ability and insufficient seaweed heterogeneity adaptation in the prior art are solved, and an accurate decision tool is provided for carbon neutralization target driven seaweed culture space planning.

Description

Technical Field

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

[0002] The carbon sink calculation method is a key technology for evaluating the carbon absorption capacity of ecosystems, and its development background is closely related to global climate change and the goal of carbon neutrality. The existing technologies mainly focus on different scales and accuracy requirements, and combine multidisciplinary methods such as ecology, remote sensing technology, meteorology, and model simulation. The current carbon sink calculation technologies mainly cover the following methods:

[0003] In terrestrial ecosystems, (1) the inventory method is based on fixed plot observations and soil stratified sampling, and combines an elemental analyzer to determine the organic carbon content, but the spatio-temporal resolution is limited; (2) the eddy covariance method monitors the CO 2 flux through high-frequency sensors, relying on data from global flux network sites, and the equipment cost is high; (3) the remote sensing inversion model uses MODIS / Landsat satellite data to drive the light use efficiency model to estimate the net primary productivity, but it is significantly affected by cloud cover.

[0004] In terms of ocean carbon sinks, (1) biogeochemical models simulate the biological pump flux and couple regional ocean models to analyze the vertical carbon transport; (2) sediment traps and isotope tracer techniques quantify the carbon sedimentation flux, but the ship-based observation cost is high; (3) the seaweed carbon sink accounting is based on the C / N ratio of algae tissues and remote sensing inversion to evaluate the carbon sequestration amount, but there is a controversy about the sedimentation and sequestration ratio. Summary of the Invention

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

[0006] According to the first aspect of the embodiments of the present application, a method for calculating the spatial requirements of algae cultivation under the goal of carbon neutrality is provided, including:

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

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

[0009] According to the total annual demand and the carbon removal contribution ratio, calculate the carbon removal amount that each cultivated algae needs to bear under the goal of carbon neutrality;

[0010] Based on the large - scale algae carbon sink calculation formula, convert the carbon removal amount into the dry weight yield requirement;

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

[0012] The formula adopted by the large - scale algae carbon sink calculation method is as follows:

[0013]

[0014] In the formula, is the large - scale algae carbon sink amount; is the wet weight of the i - th cultivated algae; is the conversion coefficient of the i - th algae from wet weight to dry weight; is the dry weight carbon content rate of the i - th algae.

[0015] According to the second aspect of the embodiments of the present application, there is provided a device for calculating the aquaculture space requirement of algae under the carbon neutrality target, including:

[0016] A determination module, configured to determine the total annual demand for the algae carbon sink under the carbon neutrality target;

[0017] A first calculation module, configured to calculate the carbon removal contribution ratio that each cultivated algae needs to bear under the carbon neutrality target based on the current aquaculture structure;

[0018] A second calculation module, configured to calculate the carbon removal amount that each cultivated algae needs to bear under the carbon neutrality target according to the total annual demand and the carbon removal contribution ratio;

[0019] A conversion module, configured to convert the carbon removal amount into the dry weight yield requirement based on the large - scale algae carbon sink calculation formula;

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

[0021] The formula adopted by the large - scale algae carbon sink calculation method is as follows:

[0022]

[0023] In the formula, is the large - scale algae carbon sink amount; is the wet weight of the i - th cultivated algae; is the conversion coefficient of the i - th algae from wet weight to dry weight; is the dry weight carbon content rate of the i - th algae.

[0025] According to the third aspect of the embodiments of the present application, there is provided an electronic device, including:

[0026] One or more processors;

[0027] A memory for storing one or more programs;

[0028] 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.

[0029] The technical solutions provided by the embodiments of the present application may include the following beneficial effects:

[0030] As can be seen from the above embodiments, the present application determines the total annual demand for algal carbon sinks under the carbon neutrality goal, calculates the carbon removal contribution ratio that each cultured alga needs to bear under the carbon neutrality goal based on the current aquaculture structure, calculates the carbon removal amount that each cultured alga needs to bear under the carbon neutrality goal according to the total annual demand and the carbon removal contribution ratio, converts the carbon removal amount into the dry weight yield demand based on the large alga carbon sink calculation formula, calculates the aquaculture space demand corresponding to the dry weight yield demand by constructing a historical yield - area model, forms a standardized carbon - production - area conversion system, solves the core problems of large long - term prediction errors, weak model generalization ability, and insufficient adaptation to seaweed heterogeneity in the related technologies, and provides an accurate decision - making tool for the seaweed aquaculture space planning driven by the carbon neutrality goal.

[0031] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0033] Figure 1 is a flowchart of a method for calculating the algal aquaculture space demand under the carbon neutrality goal shown according to an exemplary embodiment.

[0034] Figure 2 is a dynamic smoothing trajectory diagram of the algal carbon removal contribution ratio C r as shown according to an exemplary embodiment.

[0035] Figure 3 is a single - yield time - series modeling of Undaria pinnatifida and Sargassum fusiforme shown according to an exemplary embodiment.

[0036] Figure 4 is a schematic structural diagram of a device for calculating the algal aquaculture space demand under the carbon neutrality goal shown according to an exemplary embodiment.

[0037] Figure 5It is a schematic structural diagram of an electronic device shown according to an exemplary embodiment. Detailed implementation manners

[0038] Here, the exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0039] The terms used in the present application are for the purpose of describing specific embodiments only and are not intended to limit the present application. The singular forms "a", "the", and "said" used in the present application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0040] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "while" or "in response to determining".

[0041] Term explanation:

[0043] Carbon neutrality: By means of energy conservation, emission reduction, carbon sink offset, etc., the emissions of CO 2 emitted by human activities within a specific period are balanced with its absorption amount, achieving the goal of net-zero carbon emissions.

[0044] Carbon sink: Refers to the process or carrier that absorbs and stores CO 2 , reducing the concentration of greenhouse gases in the atmosphere, through natural or artificial systems (such as forests, oceans, carbon capture technologies).

[0045] Algae-derived carbon sink: A form of carbon sink, which refers to the process by which macroalgae convert CO 2 and dissolved inorganic carbon (DIC) in seawater into dissolved organic carbon (DOC) and particulate organic carbon (POC) through photosynthesis, and then through the microbial carbon pump (MCP) mechanism into refractory dissolved organic carbon (RDOC) with strong biological inertness. This carbon can be stored in seawater for a long time, forming a stable inert dissolved carbon pool in the aquaculture carbon sink.

[0046] Figure 1 is a flowchart of a method for calculating the space requirements for algae cultivation under the carbon neutrality goal, as shown in Figure 1 shown. This method is applied to a terminal and may include the following steps:

[0047] S1: Determine the total annual demand for algal carbon sinks under the carbon neutrality goal;

[0048] Specifically, according to the research prediction of Fuhrman et al., to achieve the carbon neutrality goal, the total amount of CO 2 that needs to be sequestered by plant carbon sinks annually is 2 - 3 Gt. This study assumes that the total carbon removal (Total carbonremoval, T c ) provided by cultivating algae annually is 2.5 Gt, which is the same as the research assumption of Gao et al.

[0049] S2: Based on the current cultivation structure, calculate the carbon removal contribution ratio that each cultivated algae needs to bear under the carbon neutrality goal; This step includes the following sub - steps:

[0050] S21: Calculate the carbon removal amounts of different algae in each historical year according to the formula for calculating the carbon sink of macroalgae;

[0051] Specifically, since before 2003, the statistical data of seawater - cultivated algae in China mainly focused on kelp and laver, to ensure the comprehensiveness of the research and the reliability of the data, this embodiment selects the data from 2003 to 2023 as the research period. Key cultivation data such as cultivation species, yield, and area all come from the China Fisheries Statistical Yearbook.

[0052] This embodiment measures the carbon sink amounts of different algae according to the calculation method of the carbon sink capacity of macroalgae in the "Method for Accounting Marine Carbon Sinks" (HY / T 0349 - 2022, China).

[0053] The formula adopted by the above - mentioned method for calculating the carbon sink of macroalgae is as follows:

[0054]

[0055] In the formula, is the carbon sink amount of macroalgae; is the wet weight of the i - th cultivated algae; is the conversion coefficient from the wet weight to the dry weight of the i - th algae; is the carbon content rate of the dry weight of the i - th algae.

[0056] The "China Fishery Statistical Yearbook" records the aquaculture data of 7 types of algae. The aquaculture data includes production data and area, and all production data are statistically recorded in dry weight units. The types of algae involved in this embodiment include Saccharina japonica, Undaria pinnatifida, Pyropia spp., Gracilaria spp., Eucheuma spp., Sargassum fusiforme, and other algae. Among them, Ulva spp. and Gelidium spp. are classified as "other algae" for calculation due to their low aquaculture production and partial data missing. The production data of the above algae can be obtained through the "China Fishery Statistical Yearbook", and the production data of each type of algae = * 。

[0057] Obtain the carbon content rate of different algae in dry weight , as shown in Table 1. Substitute it into the formula of the large algae carbon sink calculation method together with the production data, and the large algae carbon sink amount can be calculated 。

[0058] Table 1. Carbon content rate of different algae in dry weight ;

[0059]

[0060] Without considering long-term carbon sequestration, the carbon sink amount is equal to the carbon removal amount. Therefore, the carbon removal amounts of different algae in each historical year are obtained, as shown in Table 2.

[0061] Table 2. Carbon removal amounts of different algae in each historical year (2003 - 2023);

[0062]

[0063] S22: Calculate the carbon removal contribution ratio C of different algae in each historical year according to the ratio of the carbon removal amount of different algae in each historical year to the total carbon removal amount in the corresponding year r ’;

[0064] Specifically, to quantify the carbon removal contribution of each aquaculture alga under the carbon neutrality goal, a key indicator of the carbon sequestration contribution ratio (Carbon sequestration contribution ratio, C r ) is introduced. C r numerically equals the ratio of the carbon removal amount of different algae in each year to the total carbon removal amount in that year.

[0065] The carbon removal amounts of different algae in each historical year obtained through step S21, and the total carbon removal amount in the corresponding year is the sum of the carbon removal amounts of different algae in each historical year (i.e., Total in Table 2).

[0066] Then, divide the carbon removal amounts of different algae in each historical year by the total carbon removal amount in the corresponding year to obtain the carbon removal contribution ratio C r ’ in Table 3.

[0067] Table 3. Carbon removal contribution ratio C r ’ (2003 - 2023);

[0068]

[0069] S23: Use a dual cross - validation framework to predict the carbon removal contribution ratio C r that each cultured alga needs to bear under the carbon neutrality goal, including:

[0070] Path 1 (time - series extrapolation modeling): Based on the carbon removal contribution ratio C r ’ of algae in each historical year, predict the carbon removal contribution ratio C r that each cultured alga needs to bear under the carbon neutrality goal;

[0071] Path 2 (component analysis modeling): Based on the carbon removal amounts of different algae in each of the historical years, predict the carbon removal amounts of each alga under the carbon neutrality goal, and calculate the carbon removal contribution ratio C r that each cultured alga needs to bear under the carbon neutrality goal according to the ratio of the carbon removal amount of each alga under the carbon neutrality goal to the total carbon removal amount in the corresponding year.

[0072] Since the sample time span of the algae carbon sink contribution ratio (C r ) is from 2003 to 2023, the historical data volume is small, and there is an error accumulation effect in the long - term extrapolation prediction of the time - series model. A single prediction method may lead to result deviation. To improve the robustness and scientificity of the prediction results, this embodiment uses a dual cross - validation framework (Dual Cross - Validation Framework), directly predicts the carbon sink contribution ratio (C r ) through time - series extrapolation modeling (Direct Prediction, Path 1), and combines component analysis modeling (Indirect Prediction, Path 2) to reverse - infer C r . Through the hybrid modeling strategy, systematically optimize the prediction robustness and reduce the uncertainty of the model.

[0073] In the above prediction process, it is necessary to select a suitable prediction model or method, which can be selected from regression analysis method (RAM), exponential smoothing algorithm (ESA), grey prediction model (GM(1,1)) and autoregressive integrated moving average (ARIMA) model, etc.

[0074] 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:

[0075] (1) Historical data cross-validation: Perform a single rolling validation of historical data on Path 1 and Path 2, and calculate the root mean square error (RMSE), mean absolute percentage error (MAPE), and goodness of fit (R 2 ).

[0076] (2) Physical constraint verification: verify the predicted carbon removal contribution ratio C r Does it meet C r ∈[0,1] boundary conditions.

[0077] (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 model with the smallest RMSE and R 2 > 0.8; ② When the RMSE difference is <5%, select the model with a smaller MAPE; ③ Eliminate candidate models that fail the physical constraint verification; and then select the optimal prediction model according to the optimization rules. Table 4 shows the results of studying algae pathways and model selection.

[0078] Table 4. Study algae pathways and model selection results;

[0079]

[0080] In order to eliminate short-term fluctuations and highlight long-term trends, the model prediction results can be post-processed. Specifically, the cross-period sliding mean processing is implemented on the prediction values ​​for 2025-2060 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).

[0081] 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 deviation problems caused by the linear extrapolation of historical data or subjective weight assignment in a single prediction method. Through the mutual verification and calibration of the results of the two paths, the prediction accuracy of the carbon removal contribution ratio C r is significantly improved, ensuring the scientific allocation of the carbon removal amount C i of each alga under the carbon neutrality goal.

[0082] S3: Calculate the carbon removal amount according to the total annual demand and the carbon removal contribution ratio;

[0083] Specifically, the formula for calculating the carbon removal amount is as follows:

[0084] ;

[0085] In the formula, C i is the carbon removal amount of the i-th cultured alga; T c is the total annual demand; C r is the carbon removal contribution ratio.

[0086] S4: Based on the large alga carbon sink calculation formula, convert the carbon removal amount into the dry weight production demand; this step includes the following sub-steps:

[0087] S41: Based on the large seaweed carbon sink amount calculation formula, analyze and derive the production demand formula of each alga under the carbon neutrality goal, and the production demand formula is as follows:

[0088] ;

[0089] In the formula, P i is the dry weight production demand of the i-th cultured alga, C i is the carbon removal amount of the i-th cultured alga; is the conversion coefficient of the i-th cultured alga from wet weight to dry weight; is the dry weight carbon content rate of the i-th cultured alga;

[0090] S42: Calculate the dry weight production demand of each alga according to the carbon removal amount and the production demand formula.

[0091] The calculation of the dry weight production demand of each alga is one of the important steps in forming a standardized carbon-production-area conversion system, and further quantifies the aquaculture space demand of different algae based on the calculation results of the dry weight production demand.

[0092] S5: Calculate the aquaculture space demand corresponding to the dry weight production demand by constructing a historical yield-area model; this step includes the following sub-steps:

[0093] S51: For algae species with a significant elasticity coefficient (P < 0.05), use the elasticity coefficient model to construct a historical yield-area model, and the elasticity coefficient model is as follows:

[0094] ;

[0095] Among them, A i is the aquaculture area requirement corresponding to the dry weight production requirement of the i-th algae species; E represents the elasticity coefficient, α is a 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;

[0096] For different algae, different elastic coefficients E and constant terms α are selected to obtain their respective elastic coefficient models; the model confidence test is performed on each elastic coefficient model, see Table 5.

[0097] Table 5. Model parameter selection and model confidence test for different algae.

[0098]

[0099] For algae species with insignificant elasticity coefficients (P > 0.05), a three-level progressive strategy was used to establish the historical yield-area model.

[0100] In one embodiment, before constructing the historical production-area model, a box plot method can be used to remove outliers, in order to improve data quality and model robustness.

[0101] 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.

[0102] 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 the traditional static model cannot reflect the differences in yield-area of ​​different algae, and ultimately achieve accurate quantification of the space requirements for different algae cultivation.

[0103] In this embodiment, for algae that do not meet the elastic coefficient model assumptions (undaria, sargassum and other algae), polynomial, exponential and power function nonlinear models are established in turn. Only the area-yield quadratic polynomial model of 'other algae' meets 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 (R 2 = 0.22; Sargassum R 2 = -1.55). Finally, the yield (yield / area) of Undaria pinnatifida and Sargassum fusiformis from 2003 to 2023 was extracted to explore its time series modeling method.

[0104] Figure 3 Modeling the time series of the per-unit yield of Undaria pinnatifida and Sargassum fusiforme, where (a) the interannual change trend of the per-unit yield; (b) the autocorrelation analysis of the per-unit yield residuals of Undaria pinnatifida (lag 10); (c) the linear fitting result of the per-unit yield of Sargassum fusiforme (RMSE = 1.55, R 2 = 0.92). The interannual change trend of the per-unit yield (tons / ha) of Undaria pinnatifida and Sargassum fusiforme from 2003 to 2023 is shown in Figure 3 Figure (a) below. The per-unit yield of Undaria pinnatifida shows characteristics of random fluctuations, without a significant time trend (mean = 24.78, standard deviation = 5.28, CV = 21.3%). The ADF test shows that the series is non-stationary (p = 0.41), but the residual analysis indicates that its autocorrelation at lag 10 is not significant ( Figure 3 Figure (b) below), and the p-value of the Ljung-Box test is 0.060 > 0.05, and the residuals are white noise, supporting the use of a constant model (Y = 24.8). The per-unit yield of Sargassum fusiforme has a stable growth trend, and a linear model is preferentially selected through five-fold cross-validation ( Figure 3 Figure (c) below, R 2 = 0.92, RMSE = 1.55).

[0105] The selection of the historical yield-area models for each alga is as follows: The elastic coefficient model is applicable to Laminaria japonica, Pyropia yezoensis, Gracilaria lemaneiformis, and Eucheuma muricatum; other algae adopt the quadratic polynomial model; Undaria pinnatifida and Sargassum fusiforme are modeled based on the time series of the per-unit yield.

[0106] S52: Calculate the required aquaculture area corresponding to the dry weight yield demand according to the historical yield-area model.

[0107] By deconstructing the relationship between the seawater aquaculture area and yield of each alga from 2003 to 2022, a historical yield-area model is constructed, and then the theoretical minimum value of the aquaculture area relying on seaweed carbon sinks is deduced, as shown in Table 6.

[0108] Table 6. Production demand parameters of major economic algae (2025 - 2060);

[0109]

[0110] According to the calculation results, under the carbon neutrality goal, the total annual demand for the algae farming area is 7,191.86 thousand hectares, which is 3.25 times the total national seawater farming area (2,214.87 thousand hectares) in 2023 and nearly 50 times the total algae farming area (149.57 thousand hectares) in 2023. Based on the analysis of the algae farming space demand under the carbon neutrality goal, large-scale algae farming needs to focus on resolving the contradiction of space constraints and urgently expand the farming area into the deep sea. At the same time, relying on a single seaweed carbon sequestration pathway requires synchronously overcoming the dual challenges of a sharp increase in economic costs (such as deep-sea infrastructure) and exceeding the ecological carrying capacity.

[0111] Corresponding to the embodiment of the method for calculating the algae farming space demand under the carbon neutrality goal described above, the present application also provides an embodiment of an apparatus for calculating the algae farming space demand under the carbon neutrality goal.

[0112] Figure 4 It is a block diagram of an apparatus for calculating the algae farming space demand under the carbon neutrality goal shown according to an exemplary embodiment. Referring to Figure 4 , the apparatus includes:

[0113] Determination module 1, configured to determine the total annual demand for algae carbon sinks under the carbon neutrality goal;

[0114] First calculation module 2, configured to calculate the carbon removal contribution ratio that each farming algae needs to bear under the carbon neutrality goal based on the current farming structure;

[0115] Second calculation module 3, configured to calculate the carbon removal amount that each farming algae needs to bear under the carbon neutrality goal according to the total annual demand and the carbon removal contribution ratio;

[0116] Conversion module 4, configured to convert the carbon removal amount into the dry weight yield demand based on the large algae carbon sink calculation formula;

[0117] Third calculation module 5, configured to calculate the farming space demand corresponding to the dry weight yield demand by constructing a historical yield - area model.

[0118] Regarding the apparatus in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated herein.

[0119] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to the descriptions in the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this application. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0120] Correspondingly, this application also provides an electronic device, including: 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 for calculating the algae cultivation space requirement under the carbon neutrality goal as described above. As Figure 5 shown, it is a hardware structure diagram of any device with data processing capabilities where the device for calculating the algae cultivation space requirement provided by the embodiment of the present invention is located. In addition to Figure 5 the processors and memory shown, any device with data processing capabilities where the device in the embodiment is located usually also includes other hardware according to the actual functions of the device with data processing capabilities, which will not be elaborated here.

[0121] Correspondingly, this application also provides a computer-readable storage medium, on which computer instructions are stored. When the instructions are executed by a processor, the method for calculating the algae cultivation space requirement under the carbon neutrality goal as described above is implemented. The computer-readable storage medium can be an internal storage unit of any device with data processing capabilities described in any of the foregoing 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 Media Card (SMC), an SD card, a Flash Card, etc. equipped on the device. Further, the computer-readable storage medium can also include both the internal storage unit of any device with data processing capabilities and the external storage device. 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 the data that has been output or will be output.

[0122] Other embodiments of the present application will be readily contemplated by those skilled in the art upon consideration of the specification and practice of the disclosure herein. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include known common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and examples are only to be considered as exemplary, and the true scope and spirit of the present application are pointed out by the claims.

[0123] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited 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 cultured algae needs to undertake under the carbon neutrality target based on the total annual demand and the carbon removal contribution ratio; Based on the carbon sink calculation formula of macroalgae, the carbon removal amount is converted into dry weight production demand; By constructing a historical yield-area model, the breeding space requirement corresponding to the dry weight yield requirement is calculated; The calculation formula of macroalgae carbon sink is as follows: ； In the formula, is the carbon sink 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 ith algae.

2. The method according to claim 1, characterized in that 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 large algae, 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 carbon removal of different algae in each historical year to the total carbon removal in the corresponding year; 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 target, 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 cultured algae needs to bear under the carbon neutrality goal; Path 2: Based on the carbon removal amounts of different algae in each historical year, predict the carbon removal amounts of each algae under the carbon neutrality target, and calculate the carbon removal contribution ratio that each farmed algae needs to bear under the carbon neutrality target based on the ratio of the carbon removal amounts of each algae under the carbon neutrality target to the total carbon removal amounts in the corresponding year.

3. The method according to claim 1, characterized in that The calculation formula of the carbon removal amount is as follows: ； In the formula, C i is the carbon removal amount of the i-th cultured algae; T c is the total annual demand; C r is the carbon removal contribution ratio.

4. The method according to claim 2, characterized in that: 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 on 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 according to the prediction performance indicator, and then selecting the optimal prediction model according to the optimization rule.

5. The method according to claim 1, characterized in that Based on the macroalgae carbon sink calculation formula, the carbon removal amount is converted into dry weight production requirements, including: Based on the calculation formula of large seaweed carbon sink, the production demand formula of each algae under the carbon neutrality goal is analytically derived, and the production demand formula is as follows: ； Where P i is the dry weight production requirement of the i-th cultured algae, C i is the carbon removal amount of the i-th cultured algae; is the conversion factor from wet weight to dry weight of the i-th cultured algae; is the carbon content of the dry weight of the i-th cultured algae; According to the carbon removal amount and yield requirement formula, the dry weight yield requirement of each algae is calculated.

6. The method according to claim 1, characterized in that By constructing a historical production-area model, the breeding area demand corresponding to the dry weight production demand is calculated, including: For cultured algae with significant elasticity coefficient, an elasticity coefficient model is used to construct a historical yield-area model. The elasticity coefficient model is as follows: ； In the formula, A i is the aquaculture area requirement corresponding to the dry weight production requirement of the i-th aquaculture algae; E represents the elasticity coefficient, α is the constant term; P i is the dry weight yield requirement of the i-th algae species; For cultivated algae with insignificant elasticity coefficient, a three-level progressive strategy was used to establish a historical yield-area model; The breeding area requirement corresponding to the dry weight yield requirement is calculated based on the historical yield-area model.

7. The method according to claim 6, characterized in that The three-level progressive strategy is as follows:

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

8. A device for calculating algae cultivation space requirements under the carbon neutrality goal, characterized in that: include: A determination module is used to determine the total annual demand for algae carbon sinks under the carbon neutrality target; The first calculation module is used to calculate the carbon removal contribution ratio that each cultured algae needs to bear under the carbon neutrality target based on the current culture structure; The second calculation module is used to calculate the carbon removal amount that each cultured algae needs to undertake under the carbon neutrality target according to the annual total demand and the carbon removal contribution ratio; A conversion module, used to convert the carbon removal amount into dry weight production requirements based on a large algae carbon sink calculation formula; A third calculation module is used to calculate the breeding space demand corresponding to the dry weight yield demand by constructing a historical yield-area model; The calculation formula of macroalgae carbon sink is as follows: ； In the formula, is the carbon sink 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 ith algae.

9. 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 7.

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