CN107145725A - A method for analyzing the methane production capacity of anaerobic digestion of food waste - Google Patents

Abstract

The invention discloses a kind of method for analyzing anaerobic digestion of kitchen wastes methane phase ability, belong to organic solid castoff processing technology field.The present invention aids in analysis of strategies anaerobic digestion of kitchen wastes process using feature, and establishes correlation model based on kitchen garbage self character, the model can very well simulation with predict kitchen garbage methane phase process.The kinetic model for the assessment anaerobic digestion of kitchen wastes methane phase that the present invention is provided can assess the process and maximum methane production of its methane phase according to the starch of kitchen garbage, protein, fat, content of cellulose, the kitchen garbage methane production theoretical value and the relative error of actual production assessed with kinetic model are up to 0.14%, and assessment result is accurate.

Description

A method for analyzing the methane production capacity of anaerobic digestion of food waste

technical field

The invention relates to a method for analyzing the methane production capacity of anaerobic digestion of kitchen waste, and belongs to the technical field of organic solid waste treatment.

Background technique

The main components of food waste are sugars, proteins, fats and cellulose substances. Due to differences in regions, seasons and eating habits, the contents of various components in food waste may vary greatly. There are also differences. In addition, the methanogenic characteristics of each component are relatively stable, and the methanogenic characteristics of each component can be simulated and predicted by measuring the content of each component in an actual food waste. Although some literatures have reported on the gas production of food waste and its components, there are few reports on the effects of various components on the gas production of food waste and related models.

In order to obtain the methanogenic potential of organic matter, the traditional method is to conduct a methanogenic potential experiment, but this experiment takes a long time, usually 30-60 days. However, mathematical models can be used to quickly obtain the results of methane production potential, such as the Buswell formula, which calculates the theoretical methane production amount based on the chemical characteristics of the substrate, but this type of model cannot provide kinetic information about substrate degradation.

Contents of the invention

In order to solve the above problems, the present invention provides a kinetic model for evaluating the anaerobic digestion of food waste to produce methane, including (a), (b), (c), (d), (e);

(a), y(t)＝8.66+1.63×B ₁ ×P ₁ (t)+1.01×B ₂ ×P ₂ (t)+1.16×B ₃ ×P ₃ (t)+1.3×B ₄ ×P ₄ (t);

(b) P ₁ (t)=496.94×(1−e ^−0.147×t );

(c) P ₂ (t)=422.06×(1−e ^−0.122×t );

(d) P ₃ (t)=431.25×(1−e ^−0.178×t );

(e)

P ₁ (t), P ₂ (t), P ₃ (t), and P ₄ (t) respectively represent the gas production of starch, cellulose, protein and fat at time t; y(t) represents the amount of gas produced by food waste at time t methane production; B _i (i=1,2,3,4) respectively represent the percentage of starch, protein, cellulose and fat in the kitchen waste; e is the natural logarithm; t is the digestion reaction time.

The second object of the present invention is to provide a method for evaluating the methane production capacity of food waste, the method is to apply the kinetic model, according to the percentage content of starch, protein, fat and cellulose in the food waste, Substitute it into the kinetic model to calculate the change of the amount of methane produced by kitchen waste over time and the maximum methane production.

In one embodiment of the present invention, the TS of the kitchen waste is 20-30%, the VS is 20-25%, the starch content is 20-40%, the protein content is 15-25%, and the fat content is 15-25%. 25%, and the cellulose content is 15-30%.

In one embodiment of the present invention, the TS of the kitchen waste is 24.13%, the VS is 22.60%, the starch content is 31.87g/gTS, the protein content is 21.02g/gTS, the fat content is 17.56g/gTS, and the fiber The element content is 23.21g/gTS.

In one embodiment of the present invention, the TS of the food waste is 25.95g/gTS, the VS is 24.46g/gTS, the starch content is 35.61g/gTS, the protein content is 18.72g/gTS, and the fat content is 19.11g /gTS, the cellulose content is 20.82g/gTS.

The third object of the present invention is to provide a method for producing methane, the method is to apply the kinetic model, according to the percentage of starch, protein, fat and cellulose in the kitchen waste, into the dynamics In the model, calculate the fermentation time required for the methane production of food waste to reach 80-100% of the maximum methane production, and ferment the corresponding time at 35-37°C.

In one embodiment of the present invention, the method inoculates sludge for anaerobic fermentation; the properties of the sludge are TS13-18%, VS 11-16%.

In one embodiment of the present invention, the method inoculates sludge for anaerobic fermentation; the properties of the sludge are TS 16.21%, VS 14.22%.

In one embodiment, the anaerobic digestion is performed at 37°C.

In one embodiment, the TS ratio of the inoculum/substrate is 2.66, the solid content is 8.06%, and the initial pH is 8.87.

In one embodiment, the adjustment of the solid content is adjusted with water; the adjustment of pH is adjusted with NaOH solution and/or HCl solution.

In one embodiment, the fermentation is performed in a Methanogenic Potential Test System (AMPTS II).

In one embodiment, the amount of the substrate is 8gTS, and the substrate is rice, meat and vegetables.

The invention also provides the application of the kinetic model in degrading kitchen waste.

Beneficial effects: the kinetic model for evaluating the methane production of anaerobic digestion of food waste provided by the present invention can evaluate the process of producing methane and the maximum amount of methane production according to the starch, protein, fat and cellulose content of food waste, and the kinetics The relative error between the theoretical value of methane production of food waste estimated by the model and the actual production can reach 0.14%, and the evaluation result is accurate.

Description of drawings

Figure 1 shows the gas production and fitting of characteristic components such as starch, protein, fat, and cellulose;

Figure 2 is the reaction rate of each component of kitchen waste;

Figure 3 shows the content and gas production of various components of kitchen waste;

Figure 4 shows the gas production and fitting of simulated kitchen waste;

Figure 5 shows the gas production and fitting of the actual kitchen waste.

detailed description

The experimental device adopts the automatic methane potential analysis system (AMPTS), inoculated with TS 16.21%, VS 14.22% sludge for anaerobic fermentation; the TS ratio of the inoculum to the substrate was 2.66, and the solid content was adjusted to 8±1% with water , adjust the initial pH to 8.0-9.0; the reaction temperature is 37°C, and the gas volume is counted by AMPTS v5.0 software. The contents of starch, protein, lipid and cellulose are determined by the methods in GB 5009.9-2016, GB50095-2010, GB5009.6-85 and GBT5009.10-2003 respectively.

Table 1 shows the components and compositions of different components of substrates, which are divided into two groups: one group is the characteristic substance experiment, with rice (R1), tofu (R2), fatty meat (R3) and green vegetables (R4) respectively anaerobic digestion reaction as the substrate; the other group is characterized by food waste, with two sources of actual food waste (R5, R6) and three simulated food wastes (R7, R8, R9) as The substrate undergoes anaerobic digestion. Among them, the starch content of food waste R5 is 31.87g/gTS, the protein content is 21.02g/gTS, the fat content is 17.56g/gTS, and the cellulose content is 23.21g/gTS; the starch content of food waste R6 is 35.61g /gTS, the protein content is 18.72g/gTS, the fat content is 19.11g/gTS, and the cellulose content is 20.82g/gTS.

Table 1 Components and composition of different component substrates

The fitting results of the cumulative gas production of the characteristic material raw materials using the modified Gompertz model or the first-order kinetic model.

P(t)=P×(1-exp(-k×t)) (1)

In the above formula, P(t)-cumulative methane production at time t, mL/gTS; P-maximum methane production, mL/gTS; R _m -maximum methane production rate, mL/gTS/d; e-natural logarithm, as 2.718; λ-lag period; t-digestion reaction time; k-degradation rate of primary substrate.

Furthermore, for methane production, the reaction rate is described by first order kinetic constants.

Example 1

Table 2 and Table 3 respectively show the fitting results of the modified Gompertz model and the first-order kinetic model for the cumulative gas production of raw materials with different characteristics.

Table 2 Modified Gompertz model parameters

Table 3 First order kinetic model parameters

Fitted by the modified Gompertz model and the first-order kinetic model, the cumulative gas production of starch, cellulose, protein and fat can be expressed by the following formulas:

P ₁ (t)=496.94×(1−e ^−0.147×t ) (3);

P ₂ (t)=422.06×(1−e ^−0.122×t ) (4);

P ₃ (t)=431.25×(1−e ^−0.178×t ) (5);

In the formula, P ₁ (t), P ₂ (t), P ₃ (t), and P ₄ (t) represent the gas production of starch, cellulose, protein, and fat at time t, respectively.

Figure 1 shows the cumulative gas production of characteristic substances and the fitting of the corresponding models. The fitting effect of each characteristic substance with the corresponding model is very good, and all R ² are above 0.99. After 22 days of anaerobic reaction, the actual cumulative yields of starch, cellulose, protein, and fat were 467.44mL/gTS, 383.91mL/gTS, 424.53mL/gTS, and 334.57mL/gTS, respectively. Using formulas 3 to 6, the predicted methane amounts were 477.36mL/gTS, 392.60mL/gTS, 422.66mL/gTS, 338.52mL/gTS, the relative errors are 2.12%, 2.26%, 0.44%, 1.18%, respectively, and the predicted maximum methane potential is 496.94mL/gTS, 422.06mL /gTS, 431.25mL/gTS, 410.28mL/gTS, biodegradability were 94.06%, 90.97%, 98.44%, 81.55%.

Example 2

Figure 2 shows the hydrolysis rate k value and the final cumulative methane production of each group of raw materials. It can be seen from Figure 2 that the cumulative methane production of simulated kitchen waste is significantly higher than that of each characteristic substance. The cumulative methane production of R8 was 535.69mL/gTS, which was 5.21% and 2.51% higher than that of R7 and R9, respectively. At the same time, compared with R7 and R9, R8 had a higher k value of 0.129. The cumulative methane production capacity of food waste is in the range of 500-540mL/gTS, while the cumulative methane production capacity of characteristic substances is in the range of 330-470mL/gTS, and the methane production capacity of food waste is significantly higher than that of characteristic substances . It can also be found from Figure 2 that although the amount of methane produced by food waste is higher than that of the characteristic substances, the kinetic constants are not all higher than the characteristic substances, and some are even lower than the characteristic substances. The kinetic constant of the simulated food waste is 0.1 ~0.13, which is lower than the k value of rice and tofu, while the k value of actual food waste is 0.168 and 0.189. There is little difference between the amount of methane produced by the actual food waste and the methane produced by the simulated food waste.

Example 3

The components of food waste were divided into carbohydrates, proteins and fats. As the content of carbohydrates increased, the methane production of food wastes increased, but when the content of carbohydrates reached 70%, with As the content increased, the amount of methane produced by food waste decreased. When the fat content is less than 30%, the amount of methane produced by food waste is directly proportional to the fat content, and when it exceeds 30%, the amount of methane produced by food waste is inversely proportional to the fat content. When the content of carbohydrates is 50%-70%, the content of protein is 25%-50%, and the content of fat is 20%-30%, the amount of methane produced by food waste is relatively high.

Example 4

The methane production data of three groups of self-made food waste at time t and the theoretical methane production data of each component in the corresponding food waste, a total of 3 × 23 = 69 sets of data, were obtained by main effect correlation analysis. Rice, tofu, fatty meat The Pearson correlation values of the theoretical methane production of green vegetables and the methane production of food waste were 0.925, 0.922, 0.846, and 0.902, respectively, indicating that they were strongly correlated with the methane production of food waste. Therefore, Equation (7) was used for the fitting analysis of the multiple linear regression equation, and the corresponding parameters were obtained as shown in Table 4.

y(t)＝A ₀ +A ₁ ×B ₁ ×P ₁ (t)+A ₂ ×B ₂ ×P ₂ (t)+A ₃ ×B ₃ ×P ₃ (t)+A ₄ ×B ₄ × P ₄ (t) (7)

Among them, y(t)-the amount of methane produced by food waste at time t; A _i -multiple linear regression coefficient; B _i -the percentage of starch, protein, cellulose and fat in food waste; P _i (t) - methane production of starch, protein, cellulose and fat at time t;

Table 4 Multiple linear regression coefficients and fitting parameters

It can be seen from Table 4 that the model fitting parameter R ² is 0.99≈1, and the P value is 0.0000<0.01, indicating that the gas production of food waste can be well predicted according to the contents of starch, protein, cellulose and fat in food waste case, the prediction expression is shown in equation (8).

y(t)＝8.66+1.63×B ₁ ×P ₁ (t)+1.01×B ₂ ×P ₂ (t)+1.16×B ₃ ×P ₃ (t)+1.3×B ₄ ×P ₄ (t) (8)

Figure 4 shows the cumulative gas production of simulated kitchen waste and actual kitchen waste and the fitting situation using equation (8). It can be seen from Figure 4 that equation (8) can well describe the methane production process of simulated food waste.

Equation (8) is used to fit the actual gas production of food waste and compared with the actual gas production. The results are shown in Figure 5. Equation (8) can well describe the methane production of actual food waste During the process, the fitting R ² of the two kinds of actual food waste were 0.950 and 0.951, respectively, and the cumulative methane production of food waste A and food waste B after 22 days were 527.47mL/gTS and 522.1mL/gTS, respectively, the equation (8 ) were 528.22mL/gTS and 545.29mL/gTS respectively, and the relative errors were 0.14% and 4.44%.

Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Any person familiar with this technology can make various changes and modifications without departing from the spirit and scope of the present invention. Therefore The scope of protection of the present invention should be defined by the claims.

Claims (9)

1. A method for analyzing the methane production capacity of food waste, characterized in that, according to the percentage content of starch, protein, fat and cellulose in the food waste, it is substituted into the kinetic model, and the amount of methane produced by the food waste is calculated as Time variation and/or maximum methane production; said kinetic model includes (a), (b), (c), (d), (e); (a), y(t)＝8.66+1.63×B ₁ ×P ₁ (t)+1.01×B ₂ ×P ₂ (t)+1.16×B ₃ ×P ₃ (t)+1.3×B ₄ ×P ₄ (t); (b), P ₁ (t)=496.94×(1−e ^−0.147×t ); (c), P ₂ (t)=422.06×(1−e ^−0.122×t ); (d), P ₃ (t)=431.25×(1−e ^−0.178×t ); (e), P ₁ (t), P ₂ (t), P ₃ (t), and P ₄ (t) respectively represent the gas production of starch, cellulose, protein and fat at time t; y(t) represents the amount of gas produced by food waste at time t B ₁ , B ₂ , B ₃ , and B ₄ represent the percentages of starch, protein, cellulose, and fat in food waste, respectively; e is the natural logarithm; t is the digestion reaction time. 2. The method according to claim 1, characterized in that the TS of the food waste is 20-30%, and the VS is 20-25%. 3. The method according to claim 1, characterized in that, by mass percentage, the starch content is 20-40%, the protein content is 15-25%, the fat content is 15-25%, and the cellulose content is 15-25%. 30%. 4. A method for methane production, characterized in that, measure the percentage of starch, protein, fat and cellulose in the kitchen waste, substitute it into the kinetic model described in claim 1, and calculate the methane production amount as the maximum methane The time required for the yield to be 80-100%, and the corresponding time for anaerobic fermentation at 35-37°C. 5. The method according to claim 4, characterized in that, the method is inoculated with sludge for anaerobic fermentation; the TS of the sludge is 13-18%, and the VS is 11-16%. 6. The method according to claim 5, characterized in that the TS ratio of the inoculum to the substrate is 2.5-2.8, and the solid content is 6-10%. 7. The method according to claim 5, characterized in that the pH is adjusted to be 6-9. 8. A kinetic model for analyzing the anaerobic digestion of kitchen waste to produce methane, characterized in that it includes (a), (b), (c), (d), (e); (a), y(t)＝8.66+1.63×B ₁ ×P ₁ (t)+1.01×B ₂ ×P ₂ (t)+1.16×B ₃ ×P ₃ (t)+1.3×B ₄ ×P ₄ (t); (b), P ₁ (t)=496.94×(1−e ^−0.147×t ); (c), P ₂ (t)=422.06×(1−e ^−0.122×t ); (d), P ₃ (t)=431.25×(1−e ^−0.178×t ); (e), P ₁ (t), P ₂ (t), P ₃ (t), and P ₄ (t) respectively represent the gas production of starch, cellulose, protein and fat at time t; y(t) represents the amount of gas produced by food waste at time t B ₁ , B ₂ , B ₃ , and B ₄ represent the percentages of starch, protein, cellulose, and fat in food waste, respectively; e is the natural logarithm; t is the digestion reaction time. 9. The application of the kinetic model described in claim 8 in degrading kitchen waste.