CN107145725A - A kind of method for analyzing anaerobic digestion of kitchen wastes methane phase ability - Google Patents
A kind of method for analyzing anaerobic digestion of kitchen wastes methane phase ability Download PDFInfo
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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
Technical field
The present invention relates to a kind of method for analyzing anaerobic digestion of kitchen wastes methane phase ability, belong to organic solid castoff
Processing technology field.
Background technology
The main component of kitchen garbage is carbohydrate, protein-based, fats and cellulose substances, because region, season
With the difference of eating habit, the content of each component may have very big difference in kitchen garbage, and there is also difference for its methane phase performance.
In addition, the characteristics of producing methane of each component relatively stablize, can by determine the content of each component in a certain actual kitchen garbage come
Simulate and predict its characteristics of producing methane.Although some document reports are studied on kitchen garbage and its aerogenesis of component,
Rarely have the influence on each component to kitchen garbage aerogenesis and the research report of correlation model.
To obtain the Methane production potential of organic matter, conventional method is to carry out Methane production potential experiment, but the experiment is time-consuming
It is longer, it usually needs 30-60 days.And the result of Methane production potential can quickly be obtained using mathematical modeling, such as Buswell is public
Formula, it is according to the methane production of the chemical characteristic computational theory of substrate, but the class model can not provide relevant degradation of substrates
Dynamic information.
The content of the invention
In order to solve the above problems, the invention provides a kind of kinetic simulation for assessing anaerobic digestion of kitchen wastes methane phase
Type, including (a), (b), (c), (d), (e);
(a), y (t)=8.66+1.63 × B1×P1(t)+1.01×B2×P2(t)+1.16×B3×P3(t)+1.3×B4
×P4(t);
(b)P1(t)=496.94 × (1-e-0.147×t);
(c)P2(t)=422.06 × (1-e-0.122×t);
(d)P3(t)=431.25 × (1-e-0.178×t);
(e)
P1(t)、P2(t)、P3(t)、P4(t) aerogenesis of starch, cellulose, protein and fat in t is represented respectively
Amount;Y (t) represents the methane production of t kitchen garbage;Bi(i=1,2,3,4) starch, albumen in kitchen garbage are represented respectively
The percentage composition of matter, cellulose and fat;E is natural logrithm;T is the digestion reaction time.
Second object of the present invention is to provide a kind of method for assessing kitchen garbage methane phase ability, and methods described is should
The kinetic model is used, according to the percentage composition of starch in kitchen garbage, protein, fat and cellulose, is substituted into described dynamic
In mechanical model, calculate kitchen garbage methane production and change with time and maximum methane production.
In one embodiment of the invention, the kitchen garbage TS is that 20~30%, VS is 20~25%, and starch contains
Measure as 20~40%, protein content is 15~25%, fat content is 15~25%, content of cellulose is 15~30%.
In one embodiment of the invention, the kitchen garbage TS is that 24.13%, VS is 22.60%, content of starch
For 31.87g/gTS, protein content is 21.02g/gTS, and fat content is 17.56g/gTS, and content of cellulose is 23.21g/
gTS。
In one embodiment of the invention, the kitchen garbage TS is 25.95g/gTS, and VS is 24.46g/gTS, is formed sediment
Powder content is 35.61g/gTS, and protein content is 18.72g/gTS, and fat content is 19.11g/gTS, and content of cellulose is
20.82g/gTS。
Third object of the present invention is to provide a kind of method of methane phase, and methods described is to apply the kinetic simulation
Type, according to the percentage composition of starch in kitchen garbage, protein, fat and cellulose, substitutes into the kinetic model, calculates
Kitchen garbage methane production ferments accordingly for the fermentation time needed for maximum methane production 80~100% at 35~37 DEG C
Time.
In one embodiment of the invention, methods described seed sludge carries out anaerobic fermentation;The property of the sludge
For TS13~18%, VS 11~16%.
In one embodiment of the invention, methods described seed sludge carries out anaerobic fermentation;The property of the sludge
For TS16.21%, VS 14.22%.
In one embodiment, the anaerobic digestion is carried out at 37 DEG C.
In one embodiment, the TS ratios of the inoculum/substrate are 2.66, and solid content is 8.06%, and initial pH is
8.87。
In one embodiment, the regulation solid content is water use regulation;Adjustment pH is to use NaOH solution and/or HCl
Solution is adjusted.
In one embodiment, the fermentation is carried out in Methane production potential test system (AMPTS II).
In one embodiment, the amount of substrate is 8gTS, and the substrate is rice, meat and vegetables.
The present invention also provides application of the kinetic model in terms of kitchen garbage of degrading.
Beneficial effect:The kinetic model for the assessment anaerobic digestion of kitchen wastes methane phase that the present invention is provided can be according to meal
Starch, protein, fat, the content of cellulose of kitchen rubbish assess the process and maximum methane production of its methane phase, with dynamics
The kitchen garbage methane production theoretical value of model evaluation and the relative error of actual production are up to 0.14%, and assessment result is accurate.
Brief description of the drawings
Fig. 1 is the aerogenesis and fit solution of the characteristic components such as starch, protein, fat, cellulose;
Fig. 2 is kitchen garbage each component reaction rate situation;
Fig. 3 is kitchen garbage each component content and aerogenesis situation;
Fig. 4 is simulation kitchen garbage aerogenesis and fit solution;
Fig. 5 is actual kitchen garbage aerogenesis and fit solution.
Embodiment
Experimental provision uses full-automatic Biochemical Methane Potential analysis system (AMPTS), is inoculated with TS 16.21%, VS's 14.22%
Sludge carries out anaerobic fermentation;The TS ratios of inoculum and substrate are 2.66, and water use regulation solid content is 8 ± 1%, adjust initial pH and are
8.0~9.0;Reaction temperature is 37 DEG C, and gas volume is by AMPTS v5.0 software statistics.Starch, protein, lipid, cellulose
The side in GB 5009.9-2016, GB50095-2010, GB5009.6-85, GBT5009.10-2003 files is respectively adopted in content
Method is measured.
Table 1 is the component and composition situation of different component substrate, is divided into two groups:One group is characterized material experiment, respectively
It is that substrate carries out anaerobic digestion reaction with rice (R1), bean curd (R2), fat meat (R3) and green vegetables (R4);Another group with kitchen garbage
Material is characterized, is with two kinds of actual kitchen garbages (R5, R6) originated and three kinds of simulation kitchen garbages (R7, R8, R9) respectively
Substrate carries out anaerobic digestion reaction.Wherein, kitchen garbage R5 content of starch is 31.87g/gTS, and protein content is
21.02g/gTS, fat content is 17.56g/gTS, and content of cellulose is 23.21g/gTS;Kitchen garbage R6 content of starch is
35.61g/gTS, protein content is 18.72g/gTS, and fat content is 19.11g/gTS, and content of cellulose is 20.82g/
gTS。
The component and composition situation of the different component substrate of table 1
Fitting with amendment Gompertz models or First order dynamic model to the accumulation aerogenesis situation of property material raw material
As a result.
P (t)=P × (1-exp (- k × t)) (1)
P (t)-t cumulative methane yield, mL/gTS in above equation;P- maximum methane productions, mL/gTS;Rm- maximum
Methane phase speed, mL/gTS/d;E- natural logrithms, are 2.718;λ-lag phase;The t- digestion reaction times;K- one-level degradation of substrates
Speed.
In addition, for methane production, reaction rate is described with First order kinetic constant.
Embodiment 1
Table 2, table 3 are respectively the accumulation for correcting Gompertz models and First order dynamic model to different characteristic raw material of substance
The fitting result of aerogenesis situation.
Table 2 corrects Gompertz model parameters
The First order dynamic model parameter of table 3
By correcting Gompertz models and First order dynamic model fitting, starch, cellulose, protein and fatty accumulation
Aerogenesis situation can be represented with following formula respectively:
P1(t)=496.94 × (1-e-0.147×t) (3);
P2(t)=422.06 × (1-e-0.122×t) (4);
P3(t)=431.25 × (1-e-0.178×t) (5);
P in formula1(t)、P2(t)、P3(t)、P4(t) production of starch, cellulose, protein and fat in t is represented respectively
Tolerance.
Fig. 1 is characterized the fit solution of photosynthetic matter accumulation aerogenesis and correspondence model, the corresponding models fitting of each property material
Effect is fine, all R2More than 0.99.After anaerobic reaction 22 days, starch, cellulose, protein and fatty reality are tired out
Product yield is 467.44mL/gTS, 383.91mL/gTS, 424.53mL/gTS, 334.57mL/gTS respectively, pre- using formula 3~6
It is respectively 477.36mL/gTS, 392.60mL/gTS, 422.66mL/gTS, 338.52mL/gTS, relative error point to survey methane content
Not Wei 2.12%, 2.26%, 0.44%, 1.18%, the maximum Biochemical Methane Potential of prediction be respectively 496.94mL/gTS,
422.06mL/gTS, 431.25mL/gTS, 410.28mL/gTS, biodegradability is respectively 94.06%, 90.97%,
98.44%th, 81.55%.
Embodiment 2
Fig. 2 is the hydrolysis rate k values and final cumulative methane yield of each group raw material.As shown in Figure 2, kitchen garbage is simulated
Cumulative methane yield apparently higher than each property material cumulative methane yield.R8 accumulation methane production is 535.69mL/
5.21% and 2.51% is respectively increased in gTS, the accumulation methane production than R7 and R9, meanwhile, compared with R7 and R9, R8 has higher
K values, be 0.129.The accumulation methane phase ability of kitchen garbage is in the range of 500-540mL/gTS, and the accumulation of property material
Methane production is in the range of 330-470mL/gTS, the methane production of the methane production of kitchen garbage apparently higher than property material.By
Fig. 2 has also been found that, although the methane production of kitchen garbage is higher than property material, still, and kinetic constant is not necessarily all higher than spy
Material is levied, some are even below property material, the kinetic constant of kitchen garbage is simulated between 0.1~0.13, less than rice
With the k values of bean curd, and the k values of actual kitchen garbage be 0.168 and 0.189.The methane production of actual kitchen garbage and simulation are eaten
The methane production difference of kitchen rubbish is little.
Embodiment 3
The component of kitchen garbage is divided into carbohydrate, protein and fatty three class, with the content of carbohydrate
Increase, the methane production increase of kitchen garbage, but when the content of carbohydrate reaches 70%, with carbohydrate content
Increase, the methane production of kitchen garbage reduces on the contrary.When fat content be less than 30% when, the methane production of kitchen garbage with
Fat content is proportional, and during more than 30%, methane production and the fat content of kitchen garbage are in inverse ratio.Carbohydrate contains
Measure as 50%-70%, the content of protein is 25%-50%, fat in 20%-30%, the methane production of kitchen garbage compared with
It is high.
Embodiment 4
By the methane phase data of 3 groups of self-control kitchen garbage ts and each component theory methane production in corresponding kitchen garbage
Data, totally 3 × 23=69 groups data carry out main effect correlation analysis and obtain, rice, bean curd, fat meat, the theoretical production first of green vegetables
The Pearson relevance values of the methane production of alkane amount and kitchen garbage are respectively 0.925,0.922,0.846,0.902, illustrate it
With the methane production of kitchen garbage be in strong correlation.Therefore, multiple linear regression equations fitting point is carried out using equation (7)
Analysis, obtains relevant parameter as shown in table 4.
Y (t)=A0+A1×B1×P1(t)+A2×B2×P2(t)+A3×B3×P3(t)+A4×B4×P4(t) (7)
Wherein, the methane production of y (t)-t kitchen garbage;Ai- multiple linear regression coefficient;BiFormed sediment in-kitchen garbage
Powder, protein, cellulose and fatty percentage composition;Pi(t)-t starch, protein, cellulose and fatty methane phase
Amount;
The multiple linear regression coefficient of table 4 and fitting parameter
As shown in Table 4, model fitting parameter R2For 0.99 ≈ 1, P values are 0.0000<0.01, illustrate according in kitchen garbage
Starch, protein, cellulose and fatty content can be good at predicting the aerogenesis situation of kitchen garbage, prediction expression such as side
Shown in formula (8).
Y (t)=8.66+1.63 × B1×P1(t)+1.01×B2×P2(t)+1.16×B3×P3(t)+1.3×B4×P4
(t) (8)
Fig. 4 is simulation kitchen garbage and the accumulation aerogenesis and the fit solution with equation (8) of actual kitchen garbage.By scheming
4 understand, equation (8) can describe to simulate the methane phase process of kitchen garbage well.
The aerogenesis situation of actual kitchen garbage is fitted using equation (8), is compared with actual aerogenesis situation,
As a result as shown in figure 5, equation (8) can describe the methane phase process of actual kitchen garbage, two kinds of actual kitchen rubbish well
The fitting R of rubbish2Kitchen garbage A and kitchen garbage B accumulation methane production is respectively after respectively 0.950 and 0.951,22 days
527.47mL/gTS and 522.1mL/gTS, equation (8) match value is respectively 528.22mL/gTS and 545.29mL/gTS, relatively
Error is respectively 0.14% and 4.44%.
Although the present invention is disclosed as above with preferred embodiment, it is not limited to the present invention, any to be familiar with this skill
The people of art, without departing from the spirit and scope of the present invention, can do various changes and modification, therefore the protection model of the present invention
Enclose being defined of being defined by claims.
Claims (9)
1. a kind of method for analyzing kitchen garbage methane phase ability, it is characterised in that according to starch in kitchen garbage, protein,
Fat and cellulose percentage composition, substitute into kinetic model in, calculate kitchen garbage methane production change with time and/or
Maximum methane production;The kinetic model includes (a), (b), (c), (d), (e);
(a), y (t)=8.66+1.63 × B1×P1(t)+1.01×B2×P2(t)+1.16×B3×P3(t)+1.3×B4×P4
(t);
(b), P1(t)=496.94 × (1-e-0.147×t);
(c), P2(t)=422.06 × (1-e-0.122×t);
(d), P3(t)=431.25 × (1-e-0.178×t);
(e),
P1(t)、P2(t)、P3(t)、P4(t) gas production of starch, cellulose, protein and fat in t is represented respectively;y(t)
Represent the methane production of t kitchen garbage;B1、B2、B3、B4, respectively represent kitchen garbage in starch, protein, cellulose and
The percentage composition of fat;E is natural logrithm;T is the digestion reaction time.
2. according to the method described in claim 1, it is characterised in that the kitchen garbage TS be 20~30%, VS be 20~
25%.
3. according to the method described in claim 1, it is characterised in that by mass percentage, content of starch is 20~40%, egg
White matter content is 15~25%, and fat content is 15~25%, and content of cellulose is 15~30%.
4. a kind of method of methane phase, it is characterised in that determine the hundred of starch in kitchen garbage, protein, fat and cellulose
Divide content, substitute into the kinetic model described in claim 1, it is the maximum institute of methane production 80~100% to calculate methane production
The time needed, and in 35~37 DEG C of anaerobic fermentations corresponding time.
5. method according to claim 4, it is characterised in that methods described seed sludge carries out anaerobic fermentation;The dirt
The TS of mud is that 13~18%, VS is 11~16%.
6. method according to claim 5, it is characterised in that the TS ratios of inoculum and substrate are 2.5~2.8, solid content
For 6~10%.
7. method according to claim 5, it is characterised in that regulation pH is 6~9.
8. a kind of kinetic model for analyzing anaerobic digestion of kitchen wastes methane phase, it is characterised in that including (a), (b), (c),
(d), (e);
(a), y (t)=8.66+1.63 × B1×P1(t)+1.01×B2×P2(t)+1.16×B3×P3(t)+1.3×B4×P4
(t);
(b), P1(t)=496.94 × (1-e-0.147×t);
(c), P2(t)=422.06 × (1-e-0.122×t);
(d), P3(t)=431.25 × (1-e-0.178×t);
(e),
P1(t)、P2(t)、P3(t)、P4(t) gas production of starch, cellulose, protein and fat in t is represented respectively;y(t)
Represent the methane production of t kitchen garbage;B1、B2、B3、B4, respectively represent kitchen garbage in starch, protein, cellulose and
The percentage composition of fat;E is natural logrithm;T is the digestion reaction time.
9. application of the kinetic model in terms of kitchen garbage of degrading described in claim 8.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112863612A (en) * | 2021-01-19 | 2021-05-28 | 中国科学院生态环境研究中心 | Optimization method of dry anaerobic digestion mixing ratio of multi-component material |
CN115254921A (en) * | 2022-05-10 | 2022-11-01 | 嘉兴市绿能环保科技有限公司 | Kitchen waste treatment process |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090126276A1 (en) * | 2006-04-11 | 2009-05-21 | Thermo Technologies, Llc | Methods and Apparatus for Solid Carbonaceous Materials Synthesis Gas Generation |
CN101484440A (en) * | 2006-07-06 | 2009-07-15 | 艾尼纳制药公司 | Modulators of metabolism and the treatment of disorders related thereto |
CN105132469A (en) * | 2015-09-09 | 2015-12-09 | 北京盈和瑞环保工程有限公司 | Method for using lignocellulose to produce biogas |
CN106430817A (en) * | 2016-09-18 | 2017-02-22 | 哈尔滨工业大学深圳研究生院 | Pre-treatment system for quick mechanical removal of water from household refuse and treatment method thereof |
-
2017
- 2017-04-26 CN CN201710280403.XA patent/CN107145725A/en active Pending
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090126276A1 (en) * | 2006-04-11 | 2009-05-21 | Thermo Technologies, Llc | Methods and Apparatus for Solid Carbonaceous Materials Synthesis Gas Generation |
CN101484440A (en) * | 2006-07-06 | 2009-07-15 | 艾尼纳制药公司 | Modulators of metabolism and the treatment of disorders related thereto |
CN105132469A (en) * | 2015-09-09 | 2015-12-09 | 北京盈和瑞环保工程有限公司 | Method for using lignocellulose to produce biogas |
CN106430817A (en) * | 2016-09-18 | 2017-02-22 | 哈尔滨工业大学深圳研究生院 | Pre-treatment system for quick mechanical removal of water from household refuse and treatment method thereof |
Non-Patent Citations (5)
Title |
---|
GAO SHUMEI 等: "Evaluation the anaerobic digestion performance of solid residual kitchen waste by NaHCO3 buffering", 《ENERGY CONVERSION AND MANAGEMENT》 * |
GAO SHUMEI等: "Kinetics Modeling of Anaerobic Fermentative Production of Methane from Kitchen Waste Solid Residual", 《3RD INTERNATIONAL CONFERENCE ON ENERGY, ENVIRONMENT AND SUSTAINABLE DEVELOPMENT (EESD 2013)》 * |
夏嵩 等: "餐厨垃圾厌氧发酵产沼气潜力及其动力学研究", 《能源研究与管理》 * |
孙义: "餐厨垃圾厌氧干发酵处理产甲烷潜力及动力学研究", 《工业安全与环保》 * |
李东 等: "有机垃圾组分中温厌氧消化产甲烷动力学研究", 《太阳能学报》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112863612A (en) * | 2021-01-19 | 2021-05-28 | 中国科学院生态环境研究中心 | Optimization method of dry anaerobic digestion mixing ratio of multi-component material |
CN115254921A (en) * | 2022-05-10 | 2022-11-01 | 嘉兴市绿能环保科技有限公司 | Kitchen waste treatment process |
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Application publication date: 20170908 |