batch and semi-continuous anaerobic digestion systems

Renewable Ener,q) Vol. 2, No. 4~5, pp. 391~400, 1992 0960-1481/92 $5.00+.00 Printed in Great Britain. Pergamon Press Ltd

BATCH AND SEMI-CONTINUOUS ANAEROBIC DIGESTION SYSTEMS

R. B. S. CHOWDHURY

Department of Biochemistry, University of Rajshahi, Bangladesh

and

D. J. FULFORD

Department of Engineering, University of Reading, Reading RG6 2AY, U.K.

( Receff:ed 31 May 199 l, accepted 14 November 1991 )

Abstraet--A first order kinetic model, developed to predict the behaviour of both batch and semi- continuous anaerobic digestion systems, was tested under laboratory conditions. Two and a half litre glass reactors, using cattle-dung as a feedstock, were run in both batch and semi-continuous modes in temperature-controlled water baths at 35~C. The kinetic model defined constants which could be used to evaluate both systems. The daily gas production data from the batch systems suggested that two rate constants were required to explain them : a higher rate at shorter retention times and a lower rate for longer times. The values of the kinetic rate constant defined for the semi-continuous reactors were considerably higher than those defined for the batch reactors, while the gas production constant was lower. The model offers an effective way to predict the gas production from full-scale digesters running at 35'C, although constants derived from one mode of running should not be used for the other.

1. INTRODUCTION

There are two ways in which a low-rate, low-technology, anaerobic digestion system can be run [1]. In developing countries, such as Bangladesh, both batch and semi-continuous biogas digesters are being used. A batch system is fed with a fixed amount of feedstock, made into a slurry with water and a starter (usually slurry from a working digester), which is allowed to ferment for a period from 30 to 180 days. A semi- continuous system is fed at regular intervals (usually daily) with a slurry of feedstock and water, a similar amount of digested effluent being removed at the same time.

The aim of the experimental work reported in this paper was to compare the two approaches, using kinetic models that related to both. Several kinetic models have been derived in order to define system parameters by which digestion can be analysed [2-4]. A first-order kinetic equation is a simple approach and can be adapted to define compatible reaction constants for both systems, allowing them to be compared. The results from the semi-continuous reactors were also analysed according to the Contois model developed by Chan and Hashimoto.

2. THEORY

The first order model assumes that the rate of substrate removal is proportional to the substrate concentration :

dS d~ = - k . S, (1)

where k is the rate constant (d ~) and S is the substrate concentration (kg m 3).

Lau-Wong [2] used this basic assumption to develop models for both batch and semi-continuous systems.

2.1. Batch first order model For the batch process, eqn (1) is integrated between

an initial time (t = to) and a final time (t = t) :

S = So" exp ( - k" ( t - to)), (2)

where So is the substrate concentration at time t = to. This initial period of time (to) is called the ' lag' time

and is the time required for digestion to start. The value of the lag time depends on the feedstock and the amount of starter added to the reactor [5].

Equation (2) can be rewritten

In S~I = - k ' t + k - t , , (3)

By plotting In (S/So) against t as a straight line, one can obtain k from the slope and k- to from the intercept.

The second assumption made in the first-order model is that the cumulative gas production (G') is proportional to the concentration of feedstock destroyed :

391

392 R. B. S. CHOWDHURY and D. J. FULFORD

G' = C . f . V . ( S 0 - S), (4)

where C is the yield constant : the volume of biogas or methane produced per unit mass of digestible feedstock destroyed (m 3 kg ~), f i s the digestible fraction in the total mass of feedstock and V is the working volume of the reactor (m3).

The value for the instantaneous substrate concentration (S) from eqn (4) can be substituted in eqn (2) giving

G" = C'f" V'S0" { 1 - e x p [ - k ' ( t - t o ) ] } , (5)

o r

G C ' f ' S o = { 1 - e x p [ - k ' ( t - t o ) l } , (6)

where G = G'/V is the cumulative specific gas production (m 3 m-3). Rearranging eqn (6) gives

In ( 1 - C . ~ 0 S d 0 ) = - k ' t + k ' t o , (7)

where Sd0 = S0"f, is the concentration of digestible feedstock.

Plotting In (1-G/C'Sao) against t, as a straight line, one obtains k from the slope and k" to from the intercept.

Unfortunately, the value of Sd0, the initial digestible feedstock concentration, is very difficult to measure. The nearest measurable parameters are the volatile solids concentration and the chemical oxygen demand. The initial volatile solids concentration (Sv0) is obtained by drying a sample of feedstock and then heating it to 600°C in air in a well ventilated furnace. The proportion of the dry sample that remains (the refractory fraction) is weighed, giving the volatile fraction by subtraction. The chemical oxygen demand (So0) is obtained by oxidizing a sample of the feedstock, and measuring the amount of oxidizing agent required.

Both measures give only an approximation to the actual digestible feedstock concentration.

2.2. The semi-continuous first order model For a completely mixed continuous reactor, with-

out recycling of feedstock, a mass balance for the substrate can be written :

dS d~ = v" So -v" S - k " S" V, (8)

where

v = flow rate of slurry, m 3 d - So = influent substrate concentration, kg m - 3 S = effluent substrate concentration, kg m 3

k = rate constant, d 1 and V = volume of the reactor, m 3.

If the reactor is in a steady state : dS/dt = 0, so :

v ' ( S 0 - S ) - k ' S " V = 0,

o r

S o - S = k" S" R, (9)

where R = V/v, the hydraulic retention time (HRT). So

So S - (lO)

( l + k . R )

The daily gas production (g) is proportional to the loss in substrate concentration times the substrate feed rate :

g = C ' f " ( S 0 - S)" v,

where the other variables have the same meaning as before.

So

V g = C- f . (So - S) "~ . (! 1)

Substituting the value of S from eqn (11) into eqn (10) and rearranging:

k 9 = C" V ' f ' S o (12)

( l + k ' R )

o r

C" V'f" So 1 R - (13)

g

Again f ' S o = Sao, the digestible substrate concentration, to which approximations can be made: Svo, the volatile solids concentration or S~0, the chemical oxygen demand.

When the feed interval for a semi-continuous digester is short compared with the hydraulic retention time, eqn (12) can be used to model the system [2]. A plot of R vs V" Sdo/g should be a straight line with slope C and intercept 1/k.

2.3. Semi-continuous Contois model Chen and Hashimoto [4] used the growth rate of

bacteria to model their behavior in a semi-continuous digester:

/A S/So (14)

/ A m - - x+(1 -to) S/So

where

p = bacteria growth rate, d - J

~m = maximum growth rate, d ~c = growth rate constant,

S~ = influent substrate concentration, kg C O D m

and S = effluent substrate concentration, kg C O D m ~.

The retention time (0) is given by :

I ~c ( S 0 - S ) 0 = + - ,

b~ m P m S

and 0m, the minimum retention time, is

1 0 m = .

~ m

Equation (15) can be rewritten

B

Anaerobic digestion systems

(15)

0 = 0,n+K0m - - (16) Bo--B'

where B is the volume of methane produced per mass of C O D added and B 0 is the value of this variable at infinite retention time. The value of B depends on the retention time (0) :

B = B ~ 1-- , (17)

so by plotting B against 1/0, the value of B 0 is given by the intercept when 1/0 = 0, i.e. 0 = o,•.

The methane production rate (7) is given by

B o S o ( K ) 7 = - 1 . (18)

0 O/OmZl +~

3. E X P E R I M E N T A L W O R K

3.1. Apparatus The water baths were made from plastic bowls

through which water was pumped from a heater (Fig. I). A mercury contact thermometer was used to measure the water temperature in the baths and to control the heater through a relay. The thermometer was set to 3 5 C .

393

The digestion vessels were 2 l glass conical flasks closed by rubber bungs. The bungs had pipes for gas removal and for feeding and removal of slurry, so they could be operated in both batch and semi-continuous mode. The slurry feed pipes were also closed by small rubber bungs.

The biogas was collected under pressure in plastic bottles, so that water was forced out of the collecting bottles into a second series of bottle, acting as res- ervoirs (Fig. 2). The positive pressure in the bottles (approx. 250 mm water) allowed the gas to be trans- ferred to a measuring gas flask, as well as simulating conditions in rural digesters. The water in both the collecting bottles and the measuring flask contained acid and sodium chloride, to prevent carbon dioxide from dissolving, as well as blue dye, to allow the liquid level to be easily observed.

The feedstock was dairy cattle dung collected from the National Institute for Dairying (NIRD) , Reading. The cattle were British Friesian cows, fed on a maize silage based diet. The dung was diluted with tap water to give a slurry with about 6.6% volatile solids by weight. The slurry used to feed the semi-continuous reactors was homogenised with an electric liquidiser.

3.2. Experimenta/procedure Four reactors were run as batch digesters. Each

reactor was fed with a defined amount of slurry (see Table I), mixed with water and 15% starter. The reactors were placed in the temperature controlled water bath and allowed to ferment for periods between 28 and 90 days.

Six reactors were run as semi-continuous digesters with HRTs of 10, 15, 20, 30, 40 and 60 days. A volume of slurry (defined by the value of the HRT) was with- drawn from each reactor each day and replaced with the same volume of fresh feedstock, via the slurry sampling tube.

All reactors were mixed by shaking the glass flasks by hand once a day for about 2-3 min. This procedure simulates that adopted for rural digesters, which are normally mixed only once or twice a day [6].

The gas produced by each reactor was measured

Table t. Characteristics of the batch digester leeds

Run Working no. volume (ml/

1 1500 2 1500 3 1600 4 1800

Starter T.S. V.S. Alkilin. (%) (%) (%) pH (rag/l)

15.0 9.26 7.5 7 . 7 0 4873.10 15.0 9.26 7.5 7 .70 4873.10 15.0 7.69 6.35 6.60 2375.00 15.0 18.24 6.84 7 . 6 0 7829.71


Adjustable contact [thermometer

Gas pipe )

Glass flas . . . , . - . . . Slurry

Power

Water )ump

Fig. 1. Layout diagram of temperature-controlled water baths.

daily, by displacing the gas from the collecting bottles into a measuring cylinder. The gas volume was measured at zero gauge pressure and at room temperature. Volume readings were corrected to 0°C. Each week the gas quality was checked using a gas chro- matograph, set up so that the ratio of methane to carbon dioxide could be easily calculated [7]. The mean methane content was found to be 61% at 35°C.

The slurry quality was also checked regularly, by measuring the pH, using a meter, and the alkalinity, by titration. The total solids, volatile solids and COD of the fresh and digested slurry were also measured, so the concentration of digestible substrate could be assessed before and after digestion.

The temperature of the slurry in a sample number of reactors was continuously monitored using a chart recorder to check the temperature control system was functioning effectively. The mean working temperature was calculated to be 33.5°C.

4. RESULTS AND DISCUSSION

4.1. Batch data used in first order model A linear regression program was written in BASIC

for an Apple computer, using eqn (7) for the daily data

from the batch reactors for cumulative gas production (Fig. 3). The values of the logarithm of the gas production function (In (1 - G / C " Sdo)) were plotted out against digestion time (Fig. 4). The value for the gas production constant C was calculated from eqn (4) for each reactor, using measurements of VS and COD of the slurry at different times. Values of the overall kinetic constant (k) were defined for each of the four reactors, using both volatile solids and COD as a basis for the measure of substrate concentration (Table 2).

The graphs suggest that the data points lie on two separate lines, with different slopes, suggesting that two different rate constants are involved. The data were reanalysed, one set over an initial time period (about 31 days for Figs 3 and 4) to give one value for a rate constant (k~) and lag time (too and a second set over a later time period (32-90 days) to give second rate constant (k2) and lag time (t02) values. The initial rate constant was consistently much higher than the final one (Table 2).

The substrate concentration values predicted by eqn (2), using the above constants, are plotted out as lines in Fig. 3 for both VS and COD. The cumulative specific gas production values, as predicted by eqn

Wai b o t


r | u _ a . . . . . . . . . . .

!!:!! -21. 2

il/:ii

- - - - . -

A c i d u l b r i n e

Fig. 2. Layout diagram of gas measuring system.

G a s m e a s u r i n g c y l i n d e r

395

(6), are also plotted, and show reasonable agreement with the measured data.

This result agrees with conclusions drawn by

Maramba [8], who identified the possibility of different reaction rates in his much simpler analysis of the batch digestion of hog manure. His data

25 ; 10 Cumulative

, gas production

2O 8

o ' 6 - z - -~ " - . j

> ~- o o

E £ 10 4 ~ > o ~

5 2

i / C O D data

0 20 40 60 80 Time for digestion (days)

Fig. 3. Cumulative gas production for a batch reactor. Lines based on first order model, eqn (5), using constants

as defined in Table 2, Run 1.

Time for d igest ion (days) 0 20 40 60

0 i , i i

Q - , O 3

E -0.4 E .o J::

2 -05 o

Regression l ines . . . . Overall

- - - Initial and f inal

VS date

COD data

O7

Fig. 4. Logarithmic plot of batch reactor gas production data.

Lines based on first order model, eqn (7) using constants as defined in Table 2, Run 1.


Table 2, Results from batch biogas digesters

Ret. D.S. Gas Change ov Rate Lag Reg. Run time So C time in con. time coeff. no. (day) (kg m 3) (m 3 kg- 1) (days) fn k to r

I VS 90 75,0 0.858 o 0.00411 - 18.9 0,884 COD 93.75 0.456 o 0.00714 - 15.9 0.905

VS 31 i 0.0089 1.16 0.992 COD i 0.0144 1.45 0.992

VS f 0.00219 92.5 0.978 COD f 0.0041 -75 .9 0.982

2 VS 60 75.0 0.922 o 0.00522 5.24 0.931 COD 93.75 0.502 o 0.00841 -4 .57 0.940

VS 3l i 0.00785 1.37 0.992 COD i 0.01224 1.60 0.991

VS f 0.00227 - 71.7 0.983 COD f 0.00390 -62 .7 0.985

3 VS COD

VS COD

VS COD

4 VS COD

VS COD

VS COl)

5 VS

58 63.5 0.758 79.38 0.472

28 68.4 0.926 85.5 0.516

55 99.96 1.563

o 0.00972 - 7.7 0.888 o 0.01399 6.5 0.903

26 i 0.0182 1.98 0.980 i 0.0250 2.17 0.978 f 0.00433 - 70.5 0.975 f 0.00674 -- 59.4 0.978

25

34

o 0.01407 1.67 0.974 o 0.02207 1.94 0.976 i 0.01526 2.20 0.983 i 0.02372 2.40 0.982 f 0.00312 77.15 0.991 f 0.00539 67.54 0.993

o 0.01264 - 6 . 0 0.915 i 0.01733 --0.48 0.991 f 0.00232 - 206.0 0.990

VS : based on volatile solid measurements as substrate concentration. COD : based on chemical oxygen demand measurements as substrate concentration. o : results based on overall regression line. i: results using initial regression line. 1": results using final regression line. 5 : results from hog manure data [5].

were analysed using cqn (7) to conf i rm the accuracy o f his sugges t ions (Fig. 5). Again , the predic ted wtlues o f the cumula t ive specilic gas p roduc t i on tit the measured vahles taken i )om M a r a m b a ' s g raph fairly well, using thc cons t an t s given in Table 2, ' r u n 5"'.

The t ~ o ra~es p robab ly relc~te to the complex i ty o f the c o m p o s i t i o n o f an imal dung. S impler subst ra tes , that have a l rcady been parliall5 d iges ted in the ant- trial's gut are immedia te ly avai lable to ac id- for ln ing and m e t h a n o g e n i c bacter ia . The ra te- l imit ing step in the digestion o f these substrales is p robably methano- genesis [1},

M o r e complex subs t ra tcs , :such as l igno-ccllulose, nmst be hydrolysed befbrc they can be broken d o w n by acid-formers and methanogens . The process lk)r which

the rate l imit ing s tep is hydrolys is only become obvi-

ous when the s impler subs t ra tes have been consumed .

4.2. Semi-cot*timtous data used in.first order model F o u r o f the s emi -con t inuous reac tors (H RTs o f 20,

30, 40 and 60 days) were s tar ted as ba tch diges ters and run for 15 days before daily feeding ;~as con> menced [6]. The o the r t;~o reac tors ( H R T s o f 10 and 15 days) were run as con t inua t ions o f o the r semi- c o n t i n u o u s reac tors by chang ing the feed rate.

The stability o f the reactors was assessed by measuring the dai ly gas p r o d u c t i o n as well as the total alkalinity, VS and C O D o f the effluent slurry. W h e n a reac tor a p p e a r e d to have reached a s table s tate con- di t ion (usually af ter 2 H R T s [8]), readings were taken over several days and an average specific daily gas

80

i

I

0 - 0

~ 20

. /

i YJ i / /; I / '

0 10


, / /

, /

- - i ~ i q 20 30 40 50

Time for digestion (days)

Fig. 5. Plot of batch reactor hog manure data [5]. Lines based on first order model, eqn (5) using constants as

defined in Table 2, Run 5.

production per mass of digestible substrate (VS or COD) was calculated (g/(v" Sdo)). The values for this variable are plotted against HRT in Fig. 6.

The data were tested using a linear regression analysis based on eqn (12) (Fig. 7). The values for the gas production co6stant (C) and the kinetic rate constant

397

(k) from this analysis are given in Table 3. The regression lines are plotted in Fig. 7 and the predicted specific daily gas production plotted as lines in Fig. 6. The agreement is reasonable, although the measurements for an HRT of 20 days lie some distance from the graph.

The value of the kinetic rate constant was compared with that obtained by Lau-Wong, whose data were obtained from family-sized biogas plants in Nepal [2]. The present studies suggest a higher value for this parameter, but the difference was probably due to the feed the cattle were receiving. The data in the present study were based on dung from high-yield dairy cattle fed on protein-rich maize silage, while the dung used in the Nepal study came from cattle and bufl'alo fed on locally available dry grass with a much Mgher cellulose content.

Pfeffer's work on the digestion of domestic refuse [3] suggests the possibility of there being two reaction rates for senti-continuous digesters, a lower rate constant being obscrked for longer retention times. It is possible that the 60 day HRT could lie on a line with a different slope, but this is not clear from the graphs. The 20 HRT result also lies below the best-fit lines, bul this is likely, to be the result ofa rand~m variation.

I~ " 2O

,~ I ._~ ~

E 10 • o [

R5

o L 0

' L

' , o , m , •

cl " - - . " " " z - .

VS data C O D data

I ! T ! 10 20 30 40 50 60

R e t e n t i o n t i m e ( d a y s )

Fig. 6. Specific daily gas production for s c reactors. Lines based on first order model, eqn (12), using constants

as defined in Table 3.

4O

2O {

E

2: i o

! /

J ,

!

i 20 J

,~ r

, ~ VS data A

, ; COD data

. . . . . . --7.,- 100 150 200 250

Inverse specific daily gas P r o d u c t i o n { V S o) ( k g m :~)

g

Fig. 7. L inea r p int o f s c reaclor gas production da ta . Lines based on first order model, using constants as defined

in Tab le 3.

Table 3. Results from semi-continuous biogas digesters

Yield const. (C) Rate const. (k) Temp. -

( C ) ( m 3 k g V S ~) ( m ~ k g C O D -~) ( d ) ( V S ) (d I)(COD) Ref.

35.5 0.381 0.329 0 .0833 0.0805 7* 30.1 0 .450 0 .052 2

~'Pl'esenl work .


Table 4. Comparison of mean batch and semi-continuous results

Mode

Yield const. (C) Rate const. (k)

(m 3 kg VS-') (m 3 kg COD ') (d ') (VS) (d- ' ) (COD)

Batch -total 0.866 0.487 0.00828 0.01290 init. 0.01255 0.01884 final - - 0.00298 0.00503

Semi-contin. 0.381 0.329 0.0833 0.0805

Table 5. Contois analysis of semi-continuous data

Contois Minimum Max. growth Ultimate rate retention rate of specific

constant time bacteria gas prodn. Data used (to) (0m, d) (#m, d t) (B0, m 3 kg COD i)

All 0.217 14.2 0.0702 0.191 All, less 20 days 0.635 8.69 0.115 0.199

4.3. Conto& model The data from the semi-continuous digesters were

analysed according to the Contois model suggested by Chan and Hashimoto [4]. Using the data from all the reactors, the fit with the model seemed to be poor [7], with very odd looking gas production predictions. When the data from the 20 day retention reactor are ignored, the fit seems to be better (Fig. 8) and suggests the 15 day retention reactor is operating at an optimum.

4.4. Comparison of mode& When the values of the constants derived from the

first order batch and semi-continuous models are compared (Table 4), it can be seen that the kinetic

.~_ 08

O2 if)

/

t 1 lo

i F i

2o 30 4O

Retention time (days)

Fig. 8. Specific daily gas production for s~ reactors. Lines based on Contois model, eqn (18) using constants as

defined in Table 5 using all data except that for 20 days.

constant from the semi ~:ontinuous model is much higher than even the short retention value from the batch data. However, the gas production constant is higher for the batch mode of digestion. This result confirms reports from Boshoff [9] and Hills [101.

The immediate result of this difference is that data from laboratory trials using batch digesters cannot be directly used to predict the performance of semi- continuous digesters or vice versa. Laborator-. tria[~ must use the same mode of digestion as the full-scale systems for which feedstocks are being tested. Semi- continuous digesters appear to produce gas faster than batch digesters, but may not be as efficient at using all of the available substrate.

The Contois model appears to be more accurate than the first order model, predicting the reduction of specific gas production at low retention times caused by the removal of bacteria at a faster rate than they can replicate. However, it is a less robust model, giving meaningless results when poor quality data are used (such as the data from the 20 day reactor). It is more complex than the first order model, requiring more calculations and graph plotting, so may be less appro- priate for use by biogas technicians in developing countries such as Bangladesh.

4.5. Use of the models fi}r biogas plant design The main value of a model for biogas programmes

in a developing country is that biogas production from full-scale plants can be predicted, given the plant size and feed rate. A set of experiments on a given feedstock, similar to those described in this paper, will allow full-scale plants to be designed for that


feedstock as long as the experiments use the same mode of digest ion (batch or semi-cont inuous) as the

full-scale plant . For example, take a fa rmer with a semi-cont inuous

biogas plant of working volume 6 m 3, fed with dung f rom five cattle, each giving an average of 10 kg of wet dung a day. The volatile solids for the mixed slurry is 7.5% (as per Table 1), which gives a value for the feedstock concent ra t ion (So) of 75 kg m 3 (assuming slurry has a density of 1000 kg m 3). The wet dung is usually mixed with the same volume of water to get this concentra t ion , so the daily feed volume is 0.1 m 3 and the re tent ion time (R) is 6/0.1 = 60 days.

Using the cons tants f rom Table 3 and eqn (12) :

k B g = CVSvo

(1 + k " R) B0

0.0833 C = 0.381 x 6 :,< 75 × f

(1 +0.0833 x 60) G

= 2.38m3" G' g k

This value seems a little high for gas p roduc t ion f rom R typical th i rd world digesters, but the cons tants were S derived from experiments using dung f rom cattle fed So on a high prote in diet. Catt le in a count ry such as Sd0

t Bangladesh, fed on poore r quali ty grass or straw with

t0 no concentra tes would produce dung with a much V lower digestability. The gas p roduc t ion predicted by v the Contois model, using the constants in Table 5 and I' eqn (18), is 7 = 0.28 m 3 m 3 d - I or a total of 1.68 m 3 x

0 d ~ for the 6 m3 digester. 0,,,

// ]2m

5. CONCLUSIONS

The first-order models, for bo th batch and semi- con t inuous modes of opera t ion of anaerobic digesters, appear to be valid. Da ta f rom the laboratory-scale reactors fitted these models fairly closely. The Contois model is also valid, but much more sensitive to unreliable data.

Kinetic rate and gas p roduc t ion constants have been determined for bo th ba tch and semi-cont inuous labora tory anaerobic digesters run at 33.5°C, based on the first order model. These models can be used to predict the gas p roduc t ion from full-scale digesters run in similar ways with similar feedstocks at the same temperature.

The values of these constants are different for the two modes of operat ion. Da ta derived from one mode of opera t ion of a digester canno t be used to predict the per formance of similar digesters run in the other mode. The rate of reaction for semi-cont inuous reactors was found to be higher than for batch reactors,

399

a l though the gas p roduc t ion cons tan t was lower. Two

distinct rates of react ion were found for ba tch digest ion: a higher rate at low re tent ion times, with a

lower rate at longer times. Similar cons tants have also been determined for the

Contois model for semi-cont inuous digesters. This model, while being a more accurate representat ion of the details of the process of anaerobic digestion, is less suitable than the first order model for use by technicians in developing countries to design biogas

plants.

NOMENCLATURE

volume of methane produced per mass of COD added, m 3 kg t the value of B at infinite time, m 3 kg first order yield constant, m 3 kg digestible fraction of the feedstock cumulative specific gas production, m 3 m 3 cumulative gas production, m 3 first order gas production rate, m 3 d first order rate constant, d- first order hydraulic retention time, d substrate concentration, kg m 3 substrate concentration at time t = to, kg m 3 concentration of digestible feedstock, kg m 3 time, d 'lag' time, d working volume of the reactor, m 3 flow rate of slurry, m 3 d Contois methane production rate, m 3 m 3 d Contois growth rate constant Contois retention time, d minimum retention time, d bacteria growth rate, d maximum growth rate, d ~.

REFERENCES

1. C. G. Gunnerson and D. A. Stuckey, Principles and Practice for Biogas Systems, UNDP Resource Recovery Report No. 5; World Bank Technical Paper 49, New York (1986).

2. M. Lau-Wong, The effect of operational parameters on system dynamics. UNESCI/COSTED Conference, Kathmandu, 2 Chap. 6. DCS, Butwal, Nepal (1982).

3. J. T. Pfeffer, Temperature effects on anaerobic fermentation of domestic refuse. Biotech. Bioen 9. 16, 77l 787 (1974).

4. Y. R. Chen and A. G. Hashimoto, Kinetics of methane fermentation. Biotech and Bioeng. Symposium, 8, 269- 282 (1978).

5. Sr. F. D. Maramba, Biogas and waste recycling. Maya Farms Division, Liberty Flour Mills Inc., Metro Manila, Philippines (1978).

6. D. J. Fulford, Running a Biogas Programme: A Hand- book. Intermediate Technology, London (1988).

7. R. B. S. Chowdhury, Kinetic studies of anaerobic digestion, comparing the performances of batch and semi-


continuous systems. M. Phil. Thesis, Reading Univer- sity, U.K. (1987).

8. B. F. Pain, R. West, B. Oliver and D. L. Hawkes, Meso- phylic anaerobic digestion of dairy cow slurry on a farm scale. J. Agric. Eng. Res. 29, 249-256 (1984).

9. W. H. Boshoff (1965) in E1-Shawarby S. 1., Shabaan N. A., EI-Gohary F. and EI-Halwagi M. M., Study of optimum operating conditions for the anaerobic digestion of some organic wastes. Proceedings of the Inter-

national Conference, National Research Centre, Cairo, Egypt (Nov. 1984).

10. D. J. Hills (1982) in El-Shawarby S. 1., Shabaan N. A., El-Gohary F. and E1-Halwagi M. M., Study of optimum operating conditions for the anaerobic digestion of some organic wastes. Proceedings of the International Con- ference, National Research Centre, Cairo, Egypt (Nov. 1984).

batch and semi-continuous anaerobic digestion systems

Documents