Category Archives: BIOGAS 1

Effect of % deacetylation (DD) of chitosan

pH 7 is a typical starting pH in a UASB and most other anaerobic digesters (Lettinga et al., 1980). Kaseamchochoung et al. (2006) investigated the effect of %DD of chitosan on anerobic flocculation by using chitosan with different degrees of deactylation: M85 (DD = 85%) and M70 (DD = 70%) at pH 7. Their experimental procedure was as follows. In the flocculation assay, an initial sludge suspension was transferred into a beaker and a chitosan stock solution was added to achieve a concentration of 0 to 45 mg chitosan/ g oven-dried (o. d.) sludge. The suspension was then stirred. The pH of the suspension was adjusted to 5, 6, or 7, with either 1% acetic acid or 3% sodium carbonate, depending on the pH of chitosan added to the suspension. After continuous mixing, the turbidity of supernatant was determined using a turbidimeter. The flocculation was calculated from the decrease in turbidity of supernatant after the treatment with chitosan compared with a reference without chitosan.

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suspension at pH 7 with ionic strength of 0.1 M (from Kasemchochoung et al., 2006. Reprinted with permission from Water Environment Research. Volume 78, No. 11, pp. 2211 to 2214, Copyright © 2006 Water Environment Federation, Alexandria, Virginia.)

Kaseamchochoung et al. (2006) found that at a low concentration (2 mg chitosan/ g o. d. sludge) chitosan M85 gave approximately 90% flocculation, whereas M70 gave only approximately 80% flocculation (Fig. 2). However, at a concentration of 4 mg chitosan/g o. d. sludge the flocculation efficiencies of M70 and M85 became approximately equal at 95% flocculation and then remained approximately equal up to concentrations of 45 mg chitosan/g o. d. sludge (Fig. 2).

Opportunities for the production of compliant gases

In the previous sections, the conditions for injecting processed biogas into a natural gas grid were described in detail. In this chapter, appropriate mixture compositions matching the individual gas types will be determined and the possibilities for conditioning with air and / or propane / butane admixture will be discussed.

Four different methane volume fractions (processing grades) are shown, for a total of three natural gas types as a "target" properties. Depending on the application, LPG admixtures and air admixtures are applied across a large range in order to determine a suitable, practical combination.

The addition of liquid gas or air is to be understood as an additive to the processed biogas (100%). This means that the proportion of the total mixture (100% + X) is lower than the amount added. The depicted LPG addition shows the component added, the value of the Wobbe Index, calorific value and the limits of propane and butane components resulting from the total mixture.

VLPG Zugabe, .

XLPG im Gemisch = ——— :—— (4)

VLPG Zugabe + VBiogas

The type of conditioning selected depends upon economic and technical factors and will ensure that the broadest possible spectrum of combustion values is achieved.

For implementation in practice, it should be noted that the methane volume fractions arising from processing may be subject to fluctuations. Equally, the composition of the LPG may vary and the measuring instruments and the control and regulating equipment will have tolerances, so that error propagation through the system needs to be noted when trying to achieve the desired bandwidth of "target" properties.

Gender implication of rural energy technology

Generally, rural women are greatly involved in managing household energy systems. Rural women are also the ones who are directly affected by the rural energy crisis. As mentioned in previous sections, traditional firewood cooking causes faster depletion of biomass resources and increases the time that women require in collecting firewood. These activities consume a great deal of the time and labour of women and increase the drudgery of women. In addition, the use of traditional energy technologies has a negative impact on women’s health due to the smoke from firewood and their heavy workload. There is

therefore the need for an intervention, that help to reduce women’s labour and time, which could be used for other productive purposes, and to improve the health conditions of women. In this regards, an intervention with anaerobic digestion is needed. Such an intervention should be based on gender concerns both at macro and micro levels in terms of recognizing women’s roles and responsibilities and their priorities regarding rural energy. The focus should be on reducing expenditure of human energy rather than only saving fuel. Hence, it is very important here to consider the practical gender needs, which fulfil the regular energy needs at household level while saving the time and labour of women, and the strategic gender needs, which provides the opportunities for women to be involved in social and economic activities for their self-enhancement and empowerment.

Historical background

Very old sources indicate that using wastewater and so-called renewable resources for the energy supply it is not new, it was already known before the birth of Christ. Even around 3000 BC the Sumerians practiced the anaerobic cleansing of waste. The Roman scholar Pliny described around 50 BC some glimmering lights appearing underneath the surface of swamps (Lee et al., 2010).

In 1776 Alessandro Volta personally collected biogas from the Lake Como to examine it. His findings showed that the formation of gas depends on a fermentation process and that may form an explosive mixture with air. The English physicist Faraday also performed some experiments with marsh gas and identified hydrocarbons as part of this. Around the year 1800, Dalton, Henry and Davy first described the chemical structure of methane, however the final chemical structure of methane (CH4), was first elucidated by Avogadro in 1821 (Horiuchi et al., 2002).

In the second half of 19th century, more systematic and scientific in-depth research was started in France to better understand the process of anaerobic fermentation. The objective was simply suppress the bad odor released by wastewater pools. During their investigations, researchers detected some of the microorganisms which today are known to be essential for the fermentation process. It was Bechamp who identified in 1868 that a mixed population of microorganism is required to convert ethanol into methane, since several end products were formed during the fermentation process, depending on the characteristic of substrate (Lee et al., 2010).

In 1876, Herter reported that acetate found in wastewater, stoichiometrically form methane and carbon dioxide in equal amounts. Louis Pasteur tried in 1884 to produce biogas from horse dung collected from Paris roads. Together with his student Gavon he managed to produce 100 L methane from 1 m3 dung fermented at 35°C. Pasteur claimed that this production rate should be sufficient to cover the energy requirements for the street lighting of Paris. The application of energy from renewable resources started from this time on (Deublein and Steinhauser, 2008).

Data types, accuracy, positioning, time scale/acquisition cycles

The data types and sources are summarized, collected and described in the following table to give a short overview:

Data Type

Data Detail

Source

Accuracy

Time Scale

Pipe

Inner diameter, Length, Roughness, Material class, …

Geogr. Information System (GIS)

0.1 mm 1 m

0.01 mm

actual as possible

Node

Geographic (schematic)

coordinates,

node type (branch, .)

GIS

1 m

Control

equipment

Valve (open/closed) Regulator (pressure/flow control operation mode), (max./min. flow, pressure)

GIS

SCADA

hour, minute

Medium

Gas density,

Gas temperature, Law of pressure loss

PGC

Physical

State

Pressure Flow (intake)

SCADA

0.001 bar 0.1 — 1 m3

per hour per hour

Consumer

Flow (output), Type: RLM, SLP

SCADA, EDM

0.1 m3

per hour, per month, per year

Other/

Derived

Outside air temperature, Consumption history/ forecast, planned intake flow

° C (1 m3)

per hour

Table 2. Data types required for control and simulation

The network model must be as actual as possible and should be updated whenever changes occur in reality. Very sensible with regard to the computation result is the information of actual or historical valve positions (open/ closed); its tracing is indispensible, because wrong position will cause wrong/ deviating results. The size of the network model may extend from some 1000 pipes up to 700 000 pipes (transport system to large distribution system including the transport system). The pressure range of larger networks may go down in several levels from 100 (84) bar to 0.020 bar finally at distribution level.

The data sources of different systems and their type of data which are necessary to build up a network model for simulation is shown schematically below (see figure 5). When computing the calorific value for each node (geographic position x, y) over time (t) the resulting value will be used to support the billing process.

1.4 Control system, full and sparse measurement coverage

In reality the gas networks are operated and surveyed by control systems (SCADA) consisting of a control center and remote control stations including remote control and data transmission. In general, a lot of data is acquired transmitted and stored but there is not always a full coverage for each point in the network. One can rely on:

• Input points: flow, pressure, gas quality

• Output points: flow of consumers (registered continuously)

• Intermediate points: flow, pressure (sparsely)

Intermediate points in the network are sparsely equipped or positioned, strongly depending on operational needs. Transport networks have a more detailed data view than distribution networks.

Ecological evaluation of intercrops

Based on input data for the production of main crops with and without intercrops several ecological footprints were calculated. Corn silage as main crop has a yield of 15 ton per hectare (dry matter) and 4 t (dry matter) per hectare of intercrop. SPI calculation includes

common intercrop system

improved intercrops system

common intercrop system

improved intercrops system

conventional

intercrop

intercrop

main crop

main crop

main crop (no intercrops combination)

LCI input data

workings hours per ton (dry matter)

Tractor (<45 kW), light workload

0.40

0.23

0.04

0.04

0.04

Tractor (<45 kW), normal workload

0.18

0.18

0.00

0.00

0.00

Tractor (<70 kW), normal workload

0.88

0.44

0.55

0.52

0.55

Tractor (<70 kW), heavy workload

0.00

0.00

0.13

0.00

0.13

Tractor (70-110 kW), light workload

0.24

0.24

0.00

0.00

0.00

Tractor (70-110 kW), normal workload

0.36

0.24

0.20

0.28

0.20

kg per ton (dry matter)

fertilizer

Application of N-Fertiliser

9.33

12.67

Application of P-Fertiliser

1.57

1.57

Application of K-Fertilisation

9.29

9.29

Application of Ca-Fertiliser

8.43

8.43

g per ton (dry matter)

pesticides

Herbicide Phenmediapham

0.00

0.00

61.56

61.56

61.56

Herbicide Terbuthylazin SP

0.00

0.00

108.05

108.05

108.05

Herbicide Pyridate SP

0.00

0.00

6.91

6.91

6.91

Table 3. LCI data

machinery working hours, fertilizers, pesticides, agricultural area, and nitrogen fixation by leguminosae and seeds. Input data for the footprint calculation is listed in Table 3 which is derived from (KTBL, n. d.).

In terms of nitrogen fertilizer demand the use of leguminosae in intercrop mixtures reduces the demand of mineral nitrogen fertilizer through nitrogen fixation. Based on these data the ecological footprint results are listed in Table 4.

SPI results [m2 / t (dry matter)]

common intercrop system

improved intercrops system

conventional

main crop

27,217.8

26,374.6

31,528.6

intercrop

13,988.1

9,250.2

Table 4. LCIA results

These footprints are per ton dry matter of intercrop or main crop. In general the lower machinery input for reduced tillage results in an accordingly lower footprint which points out the advantage of this method. This effect becomes more important as the yield of the crop decreases. The yields of intercrops are inevitably lower than of main crops, because of lower temperatures and less sunshine hours. Therefore, the footprint of intercrops sown with direct drilling and harvested with self-loading trailer is 34 % lower than of intercrops grown with conservation tillage and harvested with chopper. The amount of fertilizer for the main crops can be reduced with leguminosae intercrops. For this reason the footprint of the main crop in the reference system is higher than in the first system with intercrops with common tillage. If the effect of reduced nitrogen leaching or nitrous oxide emissions would be considered in the SPI-calculation, the difference would become even bigger.

For an overall assessment of the three systems, biogas produced in the systems with intercrops was processed to natural gas quality and substituted with natural gas in the system without intercrop. With processing the average methane content of biogas from about 60 % is increased to 96 % CH4. Of course, biogas from intercrops can also be used in combined heat and power plants (CHP). Its processing is only obligatory for the comparison with natural gas. Although the footprint per ton dry matter of intercrops, even if they are sown with direct drilling, is bigger than the footprint of main crops, it is much smaller than the footprint of natural gas, it may substitute.

Table 5 illustrates this overall balance per hectare of agriculture area. Biogas purification SPI relies on life cycle data from ecoinvent database (Ecoinvent, n. d.). This balance can be seen as a rough estimation of the footprint reduction potential, if not only agriculture but also natural gas consumption is considered.

Table 5 points out an advantage for intercrop cultivation with direct seeding and harvesting with self-loading trailer in comparison with intercrops grown with conservation tillage and harvest with chopper. The footprint of intercrops used for green fertilizing to increase soil quality, was not calculated in detail. Nevertheless it can be assumed that the footprint is worse than the footprints of intercrops for biogas production, because the efforts for drilling are the same and instead of harvesting energy is needed for their incorporation into the soil.

For natural gas the SPI value is 540.4 m2/Nm3. Although further biogas purification is needed the whole balance points out a footprint reduction potential of 39 — 42 %.

with intercrops

conventional

common intercrop system

improved intercrops system

CH4 yield [m3 / (dry matter)]

1,200

1,200

overall purified biogas [m3/ha]

4,800

4,800

intercrop SPI [m2/ha]

408,266

395,619

472,929

maincrop SPI [m2/ha]

55,952

37,001

0

provision of natural gas [m2 /ha]

0

0

648,480

biogas fermentation process (electricity, heat) [m2 / ha]

21,074

21,074

biogas purification [m2 / ha]

193,500

193,500

0

SPI [m2 / ha]

678,793

647,194

1,121,409

Table 5. Energy balance per hectare

The influence of pH correction on hydrogen production

The untreated "raw" dairy wastewater with low value of pH (4.27) was completely non­active in hydrogen generation by microbiological method. However, we assumed that the same wastewater under controlled pH can generate hydrogen similarly as a sterilized one. Therefore, in order to achieve similar conditions like in bioreactor operating under controlled pH we performed our batch tests in small photoreactors (capacity of 60 ml with working capacity of 30 ml) correcting pH with 0.5M solution of NaOH every 12 h. Medium containing non-sterilized dairy wastewater with concentration of 40 v/v % was inoculated with bacteria at two different concentrations: 0.086g dry wt/l (10 vol.%) or 0.36 g dry wt/l (30 vol.%). Data presented in table 5 indicate that stabilization of the system at pH close to 7 allows for hydrogen generation even from the untreated dairy wastewater. Application of inoculums with concentration at the 0.36 g dry wt/l level generates 3.6 l H2/l. The four-fold dilution of microorganisms reduces the volume of hydrogen to 2.6 l H2/l. Although the starting time was relatively long (about 20 h) savings which could arise from the application of untreated waste can be significant. Performing the same experiment with brewery waste II ( concentration 40 v/v % ) the yield of the generated hydrogen has not been improved. In this case the value of pH rapidly grew to 7.5- 7.9 in the first two days. However, it can not be excluded that in the system with controlled pH this yield could be much higher. Preliminary experiments performed under such conditions confirm this assumption.

Inoculum

Hmax

Rmax, H2

^H2

Y (l H2/l

pH

COD loss

COD loss

Biomass

conc.

(l/l)

(l/l/h)

(h)

waste)

final

(g O2/l)

(%)

(g/l)

0.086

2.58+0.16 0.038+0.005

20.7+3.6

6.0

6.8

3.8

20

2.2

0.36

3.62+0.24 0.056+0.009

17.0+4.5

8.6

6.7

4.6

23

2.8

* expressed in g dry wt/l ** biomass increase

Table 5. Kinetic parameters of cumulative hydrogen production for non-treated 40 % dairy wastewater, with correction of pH for different concentration of inoculums (Seifert, 2010).

The results presented in this section suggest that hydrogen generation can be effectively performed under solar radiation in photobioreactor operating under continuous conditions.

Effect of digestate on soil pH

Odlare et al. (2008) have not found significant change in the pH after 4-year-long biogas residue application rate. The pH of soils were 5.6 and 5.7 in the control and biogas residue treated samples, respectively. Similar results were reported by Fuchs & Schleiss (2008), because they have found an enhance of soil pH for about % unit after harvesting of maize. Because of the alkaline pH of digestates, an increase of the soil pH should be supposed. However, digestate might contain various acidic compounds (e. g. gallic acid). The polycondensation, connection to organic and inorganic colloids and transformation of these acids can have an effect also on the soil chemical properties and finally the decrease of soil pH (Tombacz et al., 1998, 1999), more particularly at the soils with high organic and inorganic colloid contents. Therefore the regular monitoring of soil pH is necessary in case of long-term digestate application.

Chinese digester

The Chinese-type model digester (Fig. 2) is comprised of a cylindrical body, two spherical domes, inlet pit, outlet pit and an inspection opening (Florentino, 2003). The digester is made using cement and bricks and it is a permanent structure. Just as in the Indian digester this has two drains to feed waste and to collect the composted waste.

The biogas is collected in the upper chamber and the waste decomposes in the lower chamber. If the gas pressure exceeds the atmospheric pressure (1 bar) and there is no gas extracted from the dome, then the rot substrate squeezed from the reactor into the filled pipe, but often in the pool of counterpoise. If the produced gas is more than the up used gas, then the slime level will increase. If the up used gas is more than the produced gas during the gas extraction, then the slime level will sink and the rot slime will flow back. The volume of the counterpoise pool must be huge so that the repressed rot substrate can be digested at the highest gas volume. The gas pressure is not constant in the practice. It increases with the quantity of the stored gas. The gas must be regularly produced; therefore the gas pressure organizer or the swimming gas repository room is important.

Owing to the fact that the biogas dome digesters are completely buried underground, the fermentation temperature should be under a day/night temperature change, only in a tolerance range from about ± 2 °С. The difference between summer and winter is large and is subject to the climate zone. The biogas dome digester can be provided with stir. In small family household units, a mix concoction for the biogas dome digester is installed. Different building and construction forms of biogas dome digesters were proved for the Chinese digesters; so that there is a big number of building methods are used.

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3.2 Designs of digester

The most common digester design is cylindrical. Digesters can be classified in horizontal and vertical designs (Fig. 3). Currently, vertical concrete or steel digesters with rotating propellers or immersion pumps for homogenization are widespread. Vertical tanks simply take feedstock in a pipe on one side, whilst digestate overflows through a pipe on the other side. In horizontal plug-flow systems, a more solid feedstock is used as a plug that flows through a horizontal digester at the rate it is fed-in. Vertical tanks are simpler and cheaper to operate, but the feedstock may not reside in the digester for the optimum period of time. Horizontal tanks are more expensive to build and operate, but the feedstock will neither leave the digester too early nor stay inside the digester for an uneconomically long period.

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Fig. 3. Horizontal (a) and vertical (b) digester (Gronauer and Neser, 2003)

Anaerobic digesters can be built either above or under the ground. An alternative is that a part of the digester can be buried. Anaerobic digesters constructed above ground are steel structures to withstand the pressure; therefore, it is simpler and cheaper to build the digester underground. Maintenance is, however, much simpler for digesters built above ground and a black coating will help provide some solar heating.

Newtonian fluids

Ideal fluids (e. g. water, methanol, olive oil and glycerol) perform linearly in rheograms, as illustrated for glycerol in figure 1, and are identified as Newtonian fluids. The Newtonian equation (Eq. 3) illustrates the flow behaviour of an ideal liquid (Schramm, 2000), where q is the viscosity (Pa*s). Dynamic viscosity, also called apparent viscosity, describes a fluid’s resistance of deformation (Pevere & Guibad, 2005). In terms of rheology it is the relation of shear stress over the shear rate (Eq. 4). For Newtonian fluids the dynamic viscosity maintains a constant value meaning a linear relationship between x and y.

Подпись:t = q * y q = x / y

When measuring the dynamic viscosity, the fluid is subjected to a force impact caused by moving a body in the fluid. Resistance to this movement provides a measure of fluid viscosity. The dynamic viscosity can be measured using a rotation rheometer. The device consists of an external fixed cylinder with known radius and an internal cylinder or spindle with known radius and height. The space between the two cylinders is filled with the fluid subjected to dynamic viscosity analysis.

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Fig. 1. Rheogram — flow curve of glycerol (▲) at 20 °C with a linear relationship between shear stress (t; Pa) and shear rate (y; s-1), representing a Newtonian liquid.