A method and system for estimating the carbon budget of eucalyptus based on the whole life cycle process

Abstract

The present invention relates to a method and system for estimating the carbon budget of eucalyptus based on the whole life cycle process, belonging to the field of forestry carbon neutralization. The method includes: First, characterizing the process of forest products harvested by logging based on the 3-PG model, and adding a carbon emission module for forest products in the production, transportation, processing, use and waste of forest products characterized by the tracking accounting method; Second, evaluating the simulation performance of the improved 3-PG model based on eucalyptus plot data and performing parameter calibration; Finally, simulating the carbon budget process of the whole life cycle of eucalyptus based on the calibrated improved 3-PG model. The present invention can provide simulations of the carbon budget of eucalyptus economic forests at the plot scale and the regional scale, help to clarify the process of carbon storage change in eucalyptus economic forests, and put forward forward-looking optimization strategies for the adjustment of eucalyptus economic forest planting management.

Description

Technical Field

[0001] The present invention belongs to the field of forestry carbon neutralization, and particularly relates to a method and system for estimating the carbon budget of eucalyptus based on the whole life cycle process. Background Art

[0002] Currently, research on the carbon budget of eucalyptus economic forests either starts from the growth process of eucalyptus, studies the carbon fixation simulation during the growth stage, and emphasizes its carbon sink effect. Or it starts from the perspective of forest products, studies the carbon emission process of eucalyptus as forest products, and emphasizes its carbon source effect. The research results of these two categories cannot comprehensively reflect the carbon budget of eucalyptus economic forests throughout the whole life cycle. There has been no report on coupling the growth process and the carbon release process of forest products from the perspective of the whole life cycle and studying their carbon budget as a whole, which limits our comprehensive understanding of the carbon sequestration ability of eucalyptus economic forests. The main reason is that there is no method in the existing research methods that can deeply combine these two processes. As one of the main planted forest tree species, eucalyptus urgently needs to develop an integrated method to comprehensively and scientifically evaluate its carbon budget throughout the whole life cycle. Summary of the Invention

[0003] The purpose of the present invention is to provide a method and system for estimating the carbon budget of eucalyptus based on the whole life cycle process, which can provide simulations of the carbon budget of eucalyptus economic forests at the plot scale and the regional scale, help clarify the process of carbon storage change in eucalyptus economic forests, and put forward forward-looking optimization strategies for the adjustment of eucalyptus economic forest planting management.

[0004] To achieve the above purpose, the technical solution of the present invention is: a method for estimating the carbon budget of eucalyptus based on the whole life cycle process, adding a forest product carbon emission module to the 3-PG model, and evaluating and calibrating the simulation performance of the improved 3-PG model to simulate the carbon budget process of the whole life cycle of eucalyptus; wherein, the forest product carbon emission module is defined as follows:

[0005] (1) Carbon emissions during the growth process of eucalyptus

[0006] Based on the 3-PG model, the loss of vegetation biomass caused by the roots, leaves and external factors of eucalyptus during the growth process of eucalyptus each month is released according to exponential decay, and the calculation method is as follows:

[0007]

[0008] is the carbon emission during the growth process of eucalyptus in the i th year, is the forest product stock volume in the i th year, which is converted from the stem biomass estimated by the carbon fixation during the growth process of eucalyptus, D is the basic density of wood, CFis the carbon content coefficient of eucalyptus wood, HE is the harvest coefficient, is the decomposition coefficient, is the decomposition time;

[0009] (2)Carbon emissions after eucalyptus logging

[0010] (2.1)Carbon emissions from dead vegetation remaining on site after logging

[0011] The dead vegetation remaining on site after logging, namely roots and leaves, will be decomposed for carbon emissions. The carbon emission process is the same as the growth process, showing exponential decay;

[0012] (2.2)Carbon emissions during the transportation and processing of forest products after logging

[0013] The carbon emissions during the transportation and processing processes are estimated using the energy consumption limit per unit product. Different transportation methods and processing processes consume different types of energy, which are uniformly converted into standard coal. The carbon emission calculation is as follows:

[0014]

[0015] represents the carbon emissions during the transportation process in the i th year, CT is the carbon emission coefficient during the wood transportation process, represents the carbon emissions caused by the processing process in the i th year, CP is the carbon emission coefficient during the wood processing process;

[0016] (2.3)Carbon emissions during the use and disposal of forest products after logging

[0017]

[0018]

[0019]

[0020] represents the carbon emissions during the use and disposal of forest products in the i th year, and are the carbon stocks of the used products or the landfilled part of the woody forest products at the beginning of the i th year and the i +1th year respectively; k is the decay constant under the first-order decay method, k =ln2 / tHL where tHL is the half-life of the woody forest products; Inflow ( i ) is thei The carbon amount of newly manufactured products or solid waste flowing into landfills in a year;

[0021] (3) Total carbon emissions

[0022]

[0023] Indicates the i Total annual carbon emissions.

[0024] Furthermore, the method includes the following steps:

[0025] S1. Check the format of the driving basic data, and estimate carbon fixation based on simulating the growth process of eucalyptus using the 3-PG model;

[0026] S2. Add a forest product carbon emission module to the 3-PG model to obtain an improved 3-PG model;

[0027] S3. Conduct parameter sensitivity analysis and parameter calibration of the improved 3-PG model at the plot scale or regional scale;

[0028] S4. Simulate and estimate the carbon budget of the whole life cycle process of eucalyptus based on the baseline scenario or real scenario.

[0029] Furthermore, in S1, the driving basic data includes meteorological data, site conditions, and plot biomass. Among them, the meteorological data includes precipitation, temperature, and solar radiation, the site conditions include altitude, latitude, and soil fertility, and the plot biomass includes the basic biomass of different years.

[0030] Furthermore, in S1, estimating carbon fixation based on simulating the growth process of eucalyptus using the 3-PG model is as follows:

[0031] S11. Net primary productivity

[0032]

[0033] Indicates j The net primary productivity during the growth process of eucalyptus in month Both represent environmental factors, and the values are between 0 and 1; Represents the comprehensive physiological factor; Represents the maximum canopy quantum efficiency, Represents the effective photosynthesis absorbed by plants;

[0034] S12. Carbon fixation amounts of different organs

[0035]

[0036] Among them respectively represent j the carbon sequestration amounts of eucalyptus stems, roots and leaves in each month, respectively represent the coefficients of net primary productivity allocated to stems, roots and leaves, CF is the carbon content coefficient;

[0037] S13. Annual total carbon fixation

[0038]

[0039] LVC all represents the annual total carbon fixation of eucalyptus, j represents the month, m represents the number of months.

[0040] Furthermore, S3 is specifically implemented as follows:

[0041] S31. Parameter sensitivity analysis

[0042] The improved 3-PG model is divided into three parts: carbon fixation, carbon emission and carbon budget; First, the Morris global sensitivity analysis method based on Bayesian statistics is used to conduct parameter sensitivity analysis on the results of carbon fixation, carbon emission and carbon budget, and the parameters with greater influence on the output results in each part of carbon fixation, carbon emission and carbon budget are selected; Then, the local sensitivity analysis method is used for calibration and verification;

[0043] S32. Parameter calibration

[0044] The fitting effect of the improved 3-PG model is evaluated by using the goodness of fit of linear regression between the observed data and the simulated data of the stand indicators in the three parts of carbon fixation, carbon emission and carbon budget. The performance and accuracy of the improved 3-PG model in simulating stand growth are evaluated by using three indicators: coefficient of determination, root mean square error and relative root mean square error.

[0045] The present invention also provides an eucalyptus carbon budget estimation system based on the whole life cycle process adopting the method as described above, including:

[0046] A data input module, used to obtain the driving basic data including meteorological data, site conditions and plot biomass of the target research area;

[0047] An eucalyptus whole life cycle carbon fixation and carbon emission module, used to characterize the carbon fixation and carbon emission in the growth process of eucalyptus, and accordingly divided into three carbon pools, namely live vegetation carbon pool, dead vegetation carbon pool and forest product carbon pool;

[0048] Parameter sensitivity analysis and parameter calibration module, which is used to conduct parameter sensitivity analysis on the model to obtain the parameters that have a greater impact on the results, and to calibrate and verify to obtain the optimal parameters of the model;

[0049] Carbon budget module, which is used to estimate the carbon budget of eucalyptus over its entire life cycle by inputting the data into the model with the optimal parameters obtained from the parameter sensitivity analysis and parameter calibration module in the data input module, and output the carbon budget results corresponding to the target study area.

[0050] Furthermore, the carbon fixation and carbon emission module for the entire life cycle of eucalyptus includes a carbon fixation module and a carbon emission module for forest products. Among them, the carbon fixation module is defined as follows:

[0051] 1) Net primary productivity

[0052]

[0053] represents j the net primary productivity during the growth process of eucalyptus in month both represent environmental factors, and the values are between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants;

[0054] 2) Carbon fixation amounts of different organs

[0055]

[0056] wherein respectively represent j the carbon fixation amounts of the stem, root and leaves of eucalyptus in month respectively represent the coefficients of the net primary productivity allocated to the stem, root and leaves, CF is the carbon content coefficient;

[0057] 3) Total annual carbon fixation amount

[0058]

[0059] LVC all represents the total annual carbon fixation amount of eucalyptus, j represents the month, n represents the number of months.

[0060] Compared with the prior art, the present invention has the following beneficial effects: When calculating the carbon budget of the whole life cycle of eucalyptus, the present invention first simulates the growth process of eucalyptus economic forest based on the existing 3-PG model according to the input driving basic data such as meteorology and site conditions. Secondly, it characterizes the production process of forest products felled from eucalyptus economic forest and the subsequent processes of transportation, processing, use and abandonment. Then, it conducts parameter sensitivity analysis and calibration of the improved model at the plot scale (regional scale). Finally, it simulates the carbon budget simulation and estimation in the whole life cycle of eucalyptus according to the actual situation or by setting different scenarios; the present invention can provide the carbon budget simulation of eucalyptus economic forest at the plot scale and the regional scale, which helps to clarify the change process of carbon storage in eucalyptus economic forest and put forward forward-looking optimization strategies for the management adjustment of eucalyptus economic forest planting. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the steps of the method for estimating the carbon budget of eucalyptus based on the whole life cycle process;

[0062] Figure 2 It is a block diagram of the module composition of the system for estimating the carbon budget of eucalyptus economic forest based on the whole life cycle process;

[0063] Figure 3 It is a schematic diagram of the composition of a computer electronic device;

[0064] Figure 4 It is a specific flowchart for estimating the carbon budget of the whole life cycle of eucalyptus in this example. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] The technical solution of the present invention will be specifically described below with reference to the accompanying drawings.

[0066] The present invention provides a method for estimating the carbon budget of eucalyptus based on the whole life cycle process, adding a forest product carbon emission module to the 3-PG model, and evaluating and calibrating the simulation performance of the improved 3-PG model to simulate the carbon budget process of the whole life cycle of eucalyptus. The main operation steps are as follows: First, based on the original 3-PG model, it characterizes the process of harvested forest products, and adds a forest product carbon emission module based on the tracking accounting method to characterize the production, transportation, processing, use and abandonment of forest products. Secondly, it evaluates the simulation performance of the improved 3-PG model based on the eucalyptus plot data and conducts parameter calibration. Finally, it simulates the carbon budget process of the whole life cycle of eucalyptus based on the calibrated improved 3-PG model.

[0067] As Figure 1 shown, in a preferred embodiment of the present invention, a method for estimating the carbon budget of eucalyptus economic forest based on the whole life cycle process is provided, and its steps include:

[0068] S1. Obtain the meteorological data (including precipitation, temperature, solar radiation, etc.), site conditions (altitude, latitude, soil fertility, etc.), and plot biomass (as the basic biomass data for driving and for comparison and verification) of the target study area. It should be noted that the collection methods, time, and spatial scales of meteorological data in different regions are different, and the meteorological data needs to be converted into monthly-step data according to the simulation area. At the same time, the driving initial and verification biomass data of the simulation area need to be obtained according to the allometric equations local to different regions.

[0069] In the embodiments of the present invention, first, the hourly precipitation (mm), temperature (°C), solar radiation (MJ / m -1 ) and other data of the meteorological station are converted into monthly-scale data. Secondly, the site conditions of the plot are input into the system in the format of a notepad according to the format. Finally, the biomass of the root, stem, and leaf (t / ha) is calculated through the allometric equation. Note that in addition to the initial biomass, the biomass of different years must also be calculated for subsequent comparison and verification in the model simulation.

[0070] The method for estimating carbon fixation based on the 3-PG model to simulate the growth process of eucalyptus is as follows:

[0071] 1.1) Net primary productivity

[0072]

[0073] represents j the net primary productivity during the growth process of eucalyptus in month all represent environmental factors, and the values are between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants;

[0074] 1.2) Carbon fixation amounts of different organs

[0075]

[0076] Among them respectively represent j the carbon fixation amounts of the stem, root, and leaf of eucalyptus in month respectively represent the coefficients of the net primary productivity allocated to the stem, root, and leaf, CF is the carbon-containing coefficient;

[0077] 1.3) Total annual carbon fixation amount

[0078]

[0079] LVC allRepresents the total annual carbon fixation of eucalyptus, j Represents the month, n Represents the number of months;

[0080] S2. Define the carbon emission module of eucalyptus forest products based on the simulated eucalyptus growth process (i.e., estimate carbon emissions), and the specific method is as follows:

[0081] 2.1) Carbon emission settings for the eucalyptus growth process

[0082] During the eucalyptus growth process, the carbon emissions will occur due to the turnover of roots, leaf litter, and the death of vegetation caused by external factors, which will be decomposed. In this example, according to the biomass of roots, leaves, and vegetation caused by external factors simulated by the model for each month, assuming that these lost biomasses are released according to exponential decay, the calculation method is as follows:

[0083]

[0084] Is the carbon emission during the i Year of the eucalyptus growth process, Is the i Year's forest product stock volume (m 3 ), which can be converted from the stem biomass in the carbon fixation part, D Is the basic wood density (Mg / m -3 ), CF Is the carbon content coefficient of eucalyptus wood (m 3 ), HE Is the harvest coefficient, Is the decomposition coefficient, Is the decomposition time;

[0085] 2.2) Carbon emissions after eucalyptus logging

[0086] (1) Carbon emissions from dead vegetation remaining on-site after logging

[0087] The dead vegetation (roots and leaves) remaining on-site after logging will be decomposed for carbon emissions, and the carbon emission process is the same as the growth process, showing exponential decay.

[0088] (2) Carbon emissions during the transportation and processing of forest products after logging

[0089] The transportation and processing of forest products consume fossil energy and emit greenhouse gases such as CO2. Different transportation methods consume different amounts of energy and release different amounts of greenhouse gases. The carbon emissions from transportation in this process are calculated using the carbon emission factor per unit turnover volume of the road freight mode statistics of the Ministry of Transport of China. Different types of forest products have different processing processes, consume different types and amounts of energy, resulting in different carbon emissions. For example, the pulp production process consumes electricity, coal, etc., and the energy consumption is relatively high, while the sawn timber has a relatively low energy consumption. The carbon emissions from the processing process in the present invention are estimated using the energy consumption limit per unit product. Different transportation methods and processing processes consume different types of energy, and the present invention uniformly converts them into standard coal. The carbon emission calculation is as follows:

[0090]

[0091] represents the carbon emissions from the transportation process in the i th year, CT represents the carbon emission coefficient of the wood transportation process (t / m -3 ); represents the carbon emissions caused by the processing process in the i th year, CP represents the carbon emission coefficient of the wood processing process (t / m -3 );

[0092] (3) Carbon emissions during the use and disposal of forest products after logging

[0093]

[0094]

[0095]

[0096] represents the carbon emissions during the use and disposal of forest products in the i th year, and are respectively the carbon storage of the used products or the landfilled part of the woody forest products at the beginning of the i th year and the i th year + 1; k is the decay constant under the first-order decay method, k = ln2 / tHL , where tHL is the half-life of the woody forest products; Inflow ([[]] i ) represents the iThe carbon amount of newly manufactured products or those flowing into solid waste landfills in a year; after the service life of forest products expires, they will be discarded or recycled. Generally, there are three treatment methods for discarded forest products, namely direct combustion, landfilling, and stacking on the ground. The carbon storage release situations of different treatment methods are different. Direct combustion will cause direct release of carbon, while landfilled and open forest products release carbon into the atmosphere in the form of natural decomposition. In the present invention, the proportions of forest product waste treatment methods are determined according to relevant literature materials, and corresponding carbon storage changes are assigned. (a) Direct combustion: Forest products are divided into paper materials, wood-based panels, and sawn timber, and carbon is released according to the proportion of the burned part in their respective waste treatments; (b) Landfilling and open air: The carbon in forest products in landfilling and open air is released into the atmosphere in the form of natural decomposition. The natural decomposition here represents the carbon release of natural decomposition by using the first-order decay method during the use process of forest products.

[0097] (4) Total carbon emissions

[0098]

[0099] Represents the total carbon emissions in the i-th year.

[0100] It should be noted that the parameters involved in the above-mentioned model need to be confirmed according to actual investigations, literature, etc., and the parameters need to be localized to make the simulation effect better.

[0101] S3. Based on the improved 3-PG model (the improved 3-PG model is divided into three parts: carbon fixation, carbon emissions (equivalent to the forest product carbon emission module), and carbon budget), parameter sensitivity analysis and calibration of the model are carried out. The specific methods are as follows:

[0102] (1) Parameter sensitivity analysis

[0103] Due to regional environmental differences or different provenances, some parameters may be different from the default values. Therefore, for different regions, some parameters need to be optimized and calibrated. The present invention uses the Morris global sensitivity analysis method based on Bayesian statistics to conduct parameter sensitivity analysis on the parameters, and divides it into three parts. One part is to conduct parameter sensitivity analysis on the biomass of diameter at breast height, roots, stems, and leaves during the growth process of eucalyptus before felling, that is, the parameter sensitivity analysis of the carbon fixation part; another part is to conduct parameter sensitivity analysis on the carbon emission parameters in the stages of dead vegetation and products after felling; the last part is to conduct parameter sensitivity analysis on the carbon budget of the entire eucalyptus process. The final result takes the average of the sensitivity analysis results of the three parts to ensure the reliability of the sensitivity analysis. And the parameters that have a greater impact on the output results of the above three parts are selected, and the local sensitivity analysis method is used to explore how to affect the output results of the model, further improving the credibility of the sensitivity analysis results. Finally, calibration and verification are carried out on this basis.

[0104] Bayesian statistical methods are based on the prior probability of a hypothesis, the probability of observing different data under a given hypothesis, and the observed data itself. The method is to combine the prior information about the unknown parameter with the sample information, and then, according to Bayes' formula, obtain the posterior information, and then infer the unknown parameter based on the posterior information. The calculation formula for its posterior probability is:

[0105]

[0106] In the formula is the prior distribution of the parameter, D is the observed data, is the prior parameter the probability of the observed data distribution in the distribution case, and is the parameter posterior distribution under the observed data.

[0107] The Morris sensitivity analysis method was first proposed by Max D. Morris in 1991. As a qualitative global sensitivity analysis, it gives the relative magnitude of the sensitivity of model parameters at a relatively low computational cost. It uses the elementary effect (EE) to judge the impact of parameter changes on the model operation results, so as to determine the sensitivity ranking of model parameters. The larger the mean of the elementary effects of the model parameters, the higher the sensitivity of the parameter. Its calculation formula is as follows.

[0108]

[0109] In the formula is the elementary effect value of the i-th model parameter x 1 , x 2 , … , x m is the value of the model parameter; f () is the objective function. The present invention takes the average of the elementary effect values of all sample plots as the final result.

[0110] The local sensitivity analysis method uses the magnitude of the standardized sensitivity coefficient to represent the response of the model output result to the parameter.

[0111]

[0112] Among them, SSC represents the standardized sensitivity coefficient, which is used to represent the sensitivity of the model to the parameter. represents the model output changes with the parameter the absolute change amount, is the parameter change amount, The original model output value, is the original parameter value. In the present invention, the ranges of multiple key parameters are set, all within ±25% based on the default values. All parameters are gradually changed in steps of 0.1%, and 1000 loops are set to evaluate the influence rules of each parameter on the biomass of stems, roots, leaves and diameter at breast height.

[0113] (2) Parameter calibration

[0114] To improve the performance and practicality of the model, in the present invention, 2 / 3 of the input data is used for model calibration and 1 / 3 for model verification. The present invention evaluates the fitting effect of the 3-PG model by using the goodness of fit of linear regression between the observed data and the simulated data of stand indexes such as diameter at breast height, leaf biomass, root biomass, and stem biomass. Three indexes, the coefficient of determination (R2), root mean square error (RMSE), and relative root mean square error (RRMSE), are used to evaluate the performance and accuracy of the 3-PG model in simulating stand growth. The calculation formulas are as follows:

[0115]

[0116]

[0117]

[0118] Among them, is the observed data, is the average value of a series of observed data, is the predicted data, and n is the number of samples. The higher the R2, the smaller the RMSR and RRMSE, and the more accurate the model prediction. In addition, simple linear regression is used to evaluate the performance of the model related to the observation.

[0119] S4. Set the baseline scenario (real scenario) to simulate the carbon budget of the whole life cycle of Eucalyptus. The present invention provides different scenarios to simulate the carbon budget of Eucalyptus (obtained according to literature data, Eucalyptus cultivation regulations and national forestry standards), and users can also set it directly. The baseline scenario (real scenario) provided by the present invention is shown in Table 4. The baseline scenario is a scenario set based on existing statistical data, while the experimental scenario is an experimental scenario based on the baseline scenario under different planting designs, harvesting management and forest product production configurations. Users can design the specific parameter values of the simulation scenario according to their needs.

[0120] The steps of the estimation classification method for the carbon budget of the whole life cycle of Eucalyptus shown in S1~S4 above can essentially be implemented in the form of a computer program (in C++ version).

[0121] In addition, based on the same inventive concept, such as Figure 2As shown in the figure, the present invention provides a system for characterizing the carbon budget of the entire life cycle of eucalyptus based on an improved 3-PG model, which includes:

[0122] A data input module for obtaining meteorological data (including precipitation, temperature, solar radiation, etc.), site conditions (altitude, latitude, soil fertility, etc.), and plot biomass (as the basic biomass data for driving and for comparison and verification) of the target research area;

[0123] An eucalyptus entire life cycle carbon fixation and carbon emission module for characterizing carbon fixation and carbon emission during the growth process of eucalyptus, and accordingly divided into three carbon pools, namely the live vegetation carbon pool, the dead vegetation carbon pool, and the forest product carbon pool;

[0124] A parameter sensitivity analysis and calibration module for performing parameter sensitivity analysis on the model to obtain parameters that have a greater impact on the results, and for calibration and verification, so as to obtain suitable current parameters and better simulation effects.

[0125] A carbon budget module for estimating the entire life carbon budget of eucalyptus by inputting the data in the data input module into the model with the optimal parameters obtained by the parameter sensitivity analysis and parameter calibration module, and outputting the corresponding carbon budget results (plot scale (.xlsx) or spatial distribution map (.tif)) of the target research area.

[0126] Similarly, based on the same inventive concept, the present invention provides a computer program product, including a computer program / instructions, which when executed by a processor, can implement the eucalyptus economic forest carbon budget estimation method based on the entire life cycle process as described above.

[0127] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention.

[0128] Thus, based on the same inventive concept, the present invention provides a computer-readable storage medium corresponding to an eucalyptus economic forest carbon budget estimation method based on the entire life cycle process. A computer program is stored on the storage medium, and when the computer program is executed by a processor, it can implement the eucalyptus economic forest carbon budget estimation method and system based on the entire life cycle process as described above.

[0129] Thus, based on the same inventive concept, asFigure 3 As shown in the figure, the present invention also provides a computer electronic device corresponding to the method for estimating the carbon budget of eucalyptus economic forests based on the whole life cycle process provided in the above embodiments, which includes a memory and a processor;

[0130] The memory is used to store computer programs;

[0131] The processor is used to implement the method for estimating the carbon budget of eucalyptus economic forests based on the whole life cycle process as described above when executing the computer program;

[0132] Specifically, in the computer-readable storage media of the above three embodiments, the stored computer program is executed by the processor, and the steps of S1 to S4 can be executed.

[0133] It can be understood that the above storage medium may include a random access memory (RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory. At the same time, the storage medium may also be various media such as a USB flash drive, a mobile hard disk, a magnetic disk, or an optical disc that can store program codes.

[0134] It can be understood that the above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0135] In addition, it should be noted that those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the above-described system can refer to the corresponding process in the foregoing method embodiments, and will not be repeated here. In the embodiments provided in the present application, the division of steps or modules in the system and method is only a logical function division, and there may be other division methods in actual implementation. For example, multiple modules or steps can be combined or integrated together, and a module or step can also be split. Embodiment

[0136] Next, based on the sample plot data of a forest farm in a certain province as an example, the carbon budget of the whole life cycle of Eucalyptus will be estimated to clearly and completely describe the technical solution of the present invention. The described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0137] In this embodiment, the specific process of a method for estimating the carbon budget of Eucalyptus based on the whole life cycle is as Figure 4 shown, and its steps include:

[0138] Step 1: Obtain the meteorological data (including precipitation, temperature, solar radiation, etc.), site conditions (altitude, latitude, soil fertility, etc.), and sample plot biomass (basic biomass data as the driving force and for comparative verification) of the target research area.

[0139] In this embodiment, the research area is the sample plot of a forest farm in a certain province. The meteorological data is from the actual measurement of a certain meteorological station, and the site conditions are the sample plot survey. The sample plot biomass is estimated according to the allometric growth equation of local Eucalyptus in a certain province.

[0140] First, convert the hourly precipitation (mm), temperature (°C), solar radiation (MJ / m -1 ), etc. data of the meteorological station into monthly-scale data. Secondly, input the site conditions of the sample plot into the system in the format of a notepad according to the format. Finally, calculate the root, stem, and leaf biomass (t / ha) through the allometric growth equation. Note that in addition to the initial biomass, the biomass of different years must also be calculated for subsequent comparative verification in the model simulation.

[0141] The biomass calculation formula is shown in Table 1:

[0142]

[0143] Based on the 3-PG model to simulate the growth process of Eucalyptus for carbon fixation estimation, the specific method is as follows:

[0144] 1.1) Net primary productivity

[0145]

[0146] represents j the net primary productivity during the growth process of Eucalyptus in month both represent environmental factors, and the value is between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants;

[0147] 1.2) Carbon sequestration in different organs

[0148]

[0149] Among them respectively represent j the carbon sequestration of eucalyptus stems, roots and leaves in respectively represent the coefficients of net primary productivity allocated to stems, roots and leaves, CF is the carbon content coefficient;

[0150] 1.3) Annual total carbon sequestration

[0151]

[0152] LVC all represents the annual total carbon sequestration of eucalyptus, j represents the month, n represents the number of months.

[0153] Step 2: Define the carbon emission process module of eucalyptus based on the simulated growth process of eucalyptus (i.e., estimate carbon emissions), and the specific method is as follows:

[0154] 2.1) Carbon emission settings during the growth process of eucalyptus

[0155] The calculation method of carbon emissions during the growth process of eucalyptus is as follows:

[0156]

[0157] is the carbon emission during the growth process of eucalyptus in the i th year, is the volume of forest products in the i th year (m 3 ), which can be converted from the stem biomass in the carbon sequestration part and is an intermediate result value inside the model and is directly used as the input of this model, D is the basic wood density (Mg / m -3 ), taking 0.5901, CF is the carbon content coefficient of eucalyptus wood (m 3 ), taking 0.525, HE is the harvest coefficient, which is deduced by the model itself, is the decomposition coefficient, which has different values for different tree species. In this example, it takes 0.4853, is the decomposition time;

[0158] 2.2) Carbon emissions after eucalyptus logging

[0159] (1) Carbon emissions from dead vegetation remaining on site after logging

[0160] The dead vegetation (roots and leaves) left on the site after logging will be decomposed for carbon emissions, and the carbon emission process, like the growth process, shows exponential decay.

[0161] (2) Carbon emissions during the transportation and processing of forest products after logging

[0162] The carbon emissions are calculated as follows:

[0163]

[0164] represents the carbon emissions during the transportation process in the i th year, CT represents the carbon emission coefficient of wood transportation (t / m -3 ), taking 0.00010281, represents the carbon emissions caused by the processing process in the i th year, CP represents the carbon emission coefficient of wood processing (t / m -3 ), and 0.17, 0.40, and 0.00187 are taken for wood-based panels, paper materials, and sawn timber respectively;

[0165] (3) Carbon emissions from the use of forest products after logging

[0166]

[0167]

[0168]

[0169] represents the carbon emissions during the use and disposal of forest products in the i th year, and are respectively the carbon stocks of the used products or the disposed and landfilled part of the wood forest products at the beginning of the i th year and the i +1th year; k is the decay constant under the first-order decay method, k = ln2 / tHL where tHL is the half-life of the wood forest products, and 20, 2, and 35 are taken for wood-based panels, paper materials, and sawn timber respectively; Inflow ([[]] i ) is the carbon amount of the newly produced products or those flowing into the solid waste landfill in the i th year; CF is the carbon content coefficient of eucalyptus wood (m 3), take 0.525. In this example, the structural ratio of the carbon waste treatment method is paper, the combustion ratio is 0.08, and the open-air or landfill ratio is 0.92; the combustion ratios of wood-based panels and sawn timber are both 0.18, and the open-air or landfill ratio is 0.82.

[0170] (4) Total carbon emissions

[0171]

[0172] represents the total carbon emissions in the i-th year.

[0173] Step 3: Based on the improved 3-PG model (the improved 3-PG model is divided into three parts: carbon fixation, carbon emissions (equivalent to the carbon emissions module of forest products), and carbon budget), conduct parameter sensitivity analysis and calibration on the model. The specific method is as follows:

[0174] In the example, the model verification results of a certain forest farm also show higher simulation accuracy, and the simulation results are closer to the 1:1 line. The regression analysis of each growth index in the sample plot of the forest farm all passes the significance test (p < 0.01). See Table 2. In the model calibration and verification stages, R 2 is between 0.92 - 0.99, and RRMSE is between 7.35% - 13.15%. Among them, the R2 values of stem, leaf, and aboveground biomass are increased by 0.03, 0.03, and 0.05 respectively, and the RRMSEs are decreased by 4.51%, 3.91%, and 4.45% respectively, indicating that the model has good predictive ability for the stand dynamics of this sample plot.

[0175]

[0176] The important parameter tables of carbon fixation and carbon emissions, that is, the carbon budget module in the entire life cycle process, are shown in Table 3:

[0177]

[0178] Step 4: Set the baseline scenario (real scenario) to simulate the carbon budget of the entire life cycle of eucalyptus (obtained according to literature data, eucalyptus cultivation regulations, and national forestry standards). Users can also set it directly. The baseline scenario (real scenario) provided by the present invention is shown in Table 4. The baseline scenario is a scenario set based on existing statistical data. Users can design the specific parameter values of the simulation scenario according to their needs.

[0179]

[0180] In this example, based on the carbon budget of eucalyptus plantations under the baseline scenario, a net carbon sequestration effect is presented, and the carbon sequestration amount is 2.22×10 4t / ha (Table 5). In the product structure of the baseline scenario, wood-based panels and sawn timber are the main sources of carbon sequestration, which are 0.53×10 4 t / ha and 1.76×10 4 t / ha, while paper products show net carbon emission characteristics in the baseline scenario, and their emissions are 0.07×10 4 t / ha. This is mainly because paper products consume a large amount of energy during the processing, resulting in high carbon emissions, and have a short operating cycle, and the carbon sequestration of vegetation growth is small, resulting in net carbon emission characteristics during this period.

[0181]

[0182] The above are the preferred embodiments of the present invention. All changes made according to the technical solution of the present invention, as long as the functions and effects produced do not exceed the scope of the technical solution of the present invention, shall fall within the protection scope of the present invention.

Claims

1. A method for estimating the carbon budget of eucalyptus based on the whole life cycle process, characterized in that, Add a forest product carbon emission module to the 3-PG model, and evaluate and calibrate the simulation performance of the improved 3-PG model to simulate the carbon budget process of the entire life cycle of eucalyptus; among them, the forest product carbon emission module is defined as follows: S01. Determine the carbon emissions during the growth process of eucalyptus; Based on the 3-PG model, simulate the loss of vegetation biomass caused by the roots, leaves and external factors of eucalyptus during the growth process of eucalyptus every month, and the calculation method is as follows: ； Among them, is the carbon emission during the growth process of eucalyptus in the i-th year, is the forest product stock volume in the i-th year, D is the basic wood density, CF is the carbon content coefficient of eucalyptus wood, HE is the harvest coefficient, is the decomposition coefficient, is the decomposition time; S02. Determine the carbon emissions after eucalyptus logging; S021. Determine the carbon emissions during the transportation and processing of forest products after logging; Estimate the carbon emissions during the transportation process and the processing process by using the energy consumption quota per unit product. Different transportation methods and processing processes consume different types of energy, and the calculation process is as follows: ； Among them, represents the carbon emissions during the transportation process in the \(i\)-th year, and CT represents the carbon emission coefficient during the wood transportation process. represents the carbon emissions caused during the processing process in the \(i\)-th year, and CP represents the carbon emission coefficient during the wood processing process. S022. Determine the carbon emissions during the use and disposal of forest products after logging, and the calculation process is as follows: ； ； ； Among them, represents the carbon emissions during the use and disposal of forest products in the i-th year, and are the carbon stocks of the used products or the landfilled part of the woody forest products in the i-th year and the (i + 1)-th year respectively; k is the decay constant under the first-order decay method, k = ln2 / tHL, where tHL is the half-life of the woody forest products; Inflow(i) is the carbon stock of the newly produced products or the products flowing into the solid waste landfill in the i-th year; S03. Determine the total carbon emissions; ； Among them, represents the total carbon emissions in the i-th year.

2. The method for estimating the carbon budget of eucalyptus based on the whole life cycle process according to claim 1, characterized in that, It includes the following steps: S1. Check the format of the driving basic data, simulate the growth process of eucalyptus based on the 3-PG model, and perform carbon fixation calculation; S2. Add a forest product carbon emission module to the 3-PG model to obtain an improved 3-PG model; S3. Conduct parameter sensitivity analysis and parameter calibration on the improved 3-PG model at the plot scale or regional scale; S4. Calculate the carbon budget of the entire life cycle process of eucalyptus based on the baseline scenario or real scenario.

3. The method for estimating the carbon budget of eucalyptus based on the whole life cycle process according to claim 2, characterized in that, In S1, the driving basic data includes meteorological data, site conditions and plot biomass. Among them, the meteorological data includes precipitation, temperature and solar radiation, the site conditions include altitude, latitude and soil fertility, and the plot biomass includes the basic biomass in different years.

4. The method for estimating the carbon budget of eucalyptus based on the whole life cycle process according to claim 2, wherein, In S1, the carbon fixation calculation is as follows: S11. Determine the net primary productivity during the growth process of eucalyptus, and the calculation process is as follows: ； Among them, represents the net primary productivity during the growth process of eucalyptus in the j-th month, respectively represent the first environmental factor, the second environmental factor, the third environmental factor, and the fourth environmental factor, with values between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants. S12. Determine the carbon fixation amount of different organs according to the net primary productivity during the growth process of eucalyptus, and the calculation process is as follows: ； Among them, respectively represent the carbon fixation amounts of eucalyptus stems, roots and leaves in the j-th month, respectively represent the coefficients of net primary productivity allocated to stems, roots and leaves; S13. Determine the total annual carbon fixation amount of eucalyptus according to the carbon fixation amount of different organs, and the calculation process is as follows: ； Among them, LVC all represents the total annual carbon fixation of eucalyptus, j represents the month, and m represents the number of months.

5. The method for estimating the carbon budget of eucalyptus based on the whole life cycle process according to claim 2, characterized in that, S3 is specifically implemented as follows: S31. The improved 3-PG model is divided into three parts: carbon fixation, carbon emission and carbon budget; first, use the Morris global sensitivity analysis method based on Bayesian statistics to conduct parameter sensitivity analysis on the results of carbon fixation, carbon emission and carbon budget respectively, and select the parameters that have a greater impact on the output results in each part of carbon fixation, carbon emission and carbon budget; then, use the local sensitivity analysis method for calibration and verification; S32. Evaluate the fitting effect of the improved 3-PG model by using the goodness of fit of the linear regression between the observed data and the simulated data of the stand indicators in the three parts of carbon fixation, carbon emission and carbon budget, and use three indicators of the coefficient of determination, root mean square error and relative root mean square error to evaluate the performance and accuracy of the improved 3-PG model in simulating stand growth.

6. An eucalyptus carbon budget estimation system based on the whole life cycle process using the method described in claim 1, characterized in that, It includes: A data input module that obtains the driving basic data including meteorological data, site conditions and plot biomass in the target research area; The carbon fixation and carbon emission module for the entire life cycle of Eucalyptus represents the carbon fixation and carbon emission during the growth process of Eucalyptus. Accordingly, it is divided into three carbon pools, namely the living vegetation carbon pool, the dead vegetation carbon pool, and the forest product carbon pool; The parameter sensitivity analysis and parameter calibration module conducts parameter sensitivity analysis on the model to obtain the parameters that have a great impact on the results, and then conducts calibration and verification to obtain the optimal parameters of the model; The carbon budget module estimates the carbon budget of the entire life cycle of Eucalyptus in the model based on the optimal parameters and outputs the corresponding carbon budget results for the target study area.

7. The eucalyptus carbon budget estimation system based on the whole life cycle process according to claim 6, characterized in that, The carbon fixation and carbon emission module for the entire life cycle of Eucalyptus includes a carbon fixation module and a forest product carbon emission module. Among them, the carbon fixation module is defined as follows: Determine the net primary productivity during the growth process of Eucalyptus. The calculation process is as follows: ； Among them, represents the net primary productivity during the growth process of eucalyptus in the j-th month, respectively represent the first environmental factor, the second environmental factor, the third environmental factor, and the fourth environmental factor, with values between 0 and 1; represents the comprehensive physiological factor; represents the maximum canopy quantum efficiency, represents the effective photosynthesis absorbed by plants. Determine the carbon fixation amount of different organs based on the net primary productivity during the growth process of Eucalyptus. The calculation process is as follows: ； Among them, respectively represent the carbon fixation amounts of the eucalyptus stem, root and leaf in the j-th month, respectively represent the coefficients of the net primary productivity allocated to the stem, root and leaf, and CF is the carbon content coefficient of eucalyptus wood; Determine the total annual carbon fixation amount of Eucalyptus based on the carbon fixation amount of different organs. The calculation process is as follows: ； Among them, LVC all represents the total annual carbon fixation of eucalyptus, j represents the month number, and m represents the number of months.

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