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Determination of gas composition in a biogas plant using a
Raman-based sensor system
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2014 Meas. Sci. Technol. 25 075503
(http://iopscience.iop.org/0957-0233/25/7/075503)
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1 © 2014 IOP Publishing Ltd Printed in the UK
1. Introduction
Due to the decreasing availability of fossil fuels and the
increasing demand for cleaner sources of energy, renewable forms of
energy are becoming more and more important. For instance, in
Germany the amount of renewables in the com-plete energy
consumption was 12.7% in the year 2010 and should increase to 18%
by 2020 [1]. One of these renewable sources of energy is biogas,
which is produced by the anaer-obic fermentation of biomass.
Compared to other alternative forms of energy, such as solar or
wind, biogas offers several
advantages, including the possibility of storage and
indepen-dence of geographic location and weather condition.
Biogas mainly contains methane and carbon dioxide, but also
small amounts of nitrogen, hydrogen and carbon mon-oxide, as well
as traces of sulfur compounds and ammonia. Thus, it’s composition
and properties, such as calorific value and density, can strongly
differ from that of natural gas. This has to be taken into account
when the gas is injected into the existing gas supply network. In
order to meet strict require-ments concerning gas composition,
density and calorific value, the gas may have to be purified before
injection [2, 3]. This typically includes filtering,
desulfurization, drying and the removal of carbon dioxide [2, 4].
The methane content is increased up to 96% and a Wobbe index,
similar to that of natural gas, can be reached. The Wobbe index is
the ratio of
Measurement Science and Technology
Determination of gas composition in a biogas plant using a
Raman-based sensor system
S C Eichmann1,2, J Kiefer2,3,8, J Benz4, T Kempf5, A
Leipertz1,2 and T Seeger6,7
1 Lehrstuhl für Technische Thermodynamik (LTT), Erlangen,
Germany2 Erlangen Graduate School in Advanced Optical Technologies
(SAOT), Erlangen, Germany3 School of Engineering, University of
Aberdeen, Aberdeen, UK4 Erdgas Südwest GmbH, Ettlingen, Germany5
EnBW Energie Baden Württemberg AG, Karlsruhe, Germany6 Lehrstuhl
für Technische Thermodynamik (TTS), Siegen, Germany
E-mail: [email protected]
Received 9 February 2014, revised 8 April 2014Accepted for
publication 14 May 2014Published 16 June 2014
AbstractWe propose a gas sensor, based on spontaneous Raman
scattering, for the compositional analysis of typical biogas
mixtures and present a description of the sensor, as well as of the
calibration procedure, which allows the quantification of
condensable gases. Moreover, we carry out a comprehensive
characterization of the system, in order to determine the
measurement uncertainty, as well as influences of temperature and
pressure fluctuation. Finally, the sensor is applied at different
locations inside a plant in which biogas is produced from renewable
raw materials. The composition is monitored after fermenting, after
purification and after the final conditioning, where natural gas is
added. The Raman sensor is able to detect all the relevant gas
components, i.e. CH4, CO2, N2 and H2O, and report their individual
concentrations over time. The results were compared to reference
data from a conventional gas analyzer and good agreement was
obtained.
Keywords: spontaneous Raman scattering, concentration
measurements, biogas composition
(Some figures may appear in colour only in the online
journal)
S C Eichmann et al
Printed in the UK
075503
mSt
© 2014 IOP Publishing Ltd
2014
25
meas. Sci. technol.
mSt
0957-0233
doi:10.1088/0957-0233/25/7/075503
Papers
7
measurement Science and technology
JB
7 Author to whom any correspondence should be
addressed.Lehrstuhl für Technische Thermodynamik, Universität
Siegen, Paul-Bonatz-Str. 9–11, 57068 Siegen, Germany.8 Present
address: Technische Thermodynamik, Universität Bremen, Germany.
0957-0233/14/075503+9$33.00
doi:10.1088/0957-0233/25/7/075503Meas. Sci. Technol. 25 (2014)
075503 (9pp)
mailto:[email protected]://dx.doi.org/10.1088/0957-0233/25/7/075503
-
S C Eichmann et al
2
the calorific value of a gas per unit volume and the square root
of its relative density under the same reference conditions. It is
used in practice as an unambiguous reference value to assess the
safe interchangeability of gaseous fuel. Another way to improve gas
quality is to mix the biogas with natural gas. In either case, the
final product gas composition and Wobbe index have to be monitored
before the gas can be fed into the supply net in order to ensure
the appropriate gas quality. The monitoring is usually done by a
gas chromatograph in combi-nation with a mass spectrometer (GC-MS
[5]).
Besides determining the final gas quality, monitoring of the gas
composition is of interest at different locations of the production
process in a biogas plant. Biogas fermentation is a very complex
process which depends for instance on the activity of the
bioorganism, the substrate quality and the culti-vation
temperature. As a consequence, the composition of the biogas may
vary significantly [4]. To investigate and to opti-mize the
fermentation, purification and mixing sub-processes it is necessary
to determine the gas composition at different locations in the
biogas plant.
In principle, the measurement can be done by gas chro-matography
[6], but this method has several disadvantages: it periodically
requires time-consuming calibration; it needs a continuous flow of
a carrier gas (for instance, helium); and, if the common flame
ionization detector is used, a continuous flow of hydrogen [7]. Due
to this required periphery, a flex-ible application at different
locations is rather complicated. Moreover, the high operational and
investment costs of a GC have to be considered. Another standard
technique for gas analysis is absorption spectroscopy, which
utilizes the dependency between the absorption of certain light
wave-lengths and the number density of the target molecules (see
e.g. [8]). The use of this technique for simultaneous detection of
multiple species has been demonstrated by several groups [9–12].
However, with the increasing number of gas compo-nents the
experimental set-up becomes rather complicated, as the detection of
each species requires a specific wavelength of light. Possible
approaches to meet this requirement include the use of
supercontinuum (SC) radiation sources, but exten-sive
characterization of the system and time-consuming evalu-ation
procedures may be necessary. To date, the use of SC absorption for
concentration measurements has only been investigated for a limited
number of different gas mixtures [13–15]. Another challenge for
absorption spectroscopy is the simultaneous detection of
hydrocarbon species, in particular when longer alkanes such as
propane and butane are present; so far, mainly small hydrocarbons
have been studied [12, 16]. Moreover, some key molecules in
technical fuel gases, such as the homonuclear gases hydrogen and
nitrogen, do not exhibit suitable transitions for absorption
spectroscopy and hence cannot be detected at all.
In order to overcome all the above-mentioned problems, we
propose the use of a Raman-based sensor system for gas analysis at
different stages of a biogas production process. Raman spectroscopy
can probe virtually all molecular species simultaneously with a
single light source. It allows relative concentration measurements
independent of the laser power and small misalignments in the
optical set-up. Moreover, a
one-off calibration is sufficient and the linear relationship
between the molar concentration and the Raman signal inten-sity
allows fast data evaluation.
The applicability of spontaneous Raman scattering for the
compositional analysis of multiple species mixtures has already
been shown by several groups [17–20]. In previous work, we
demonstrated the application of a compact, portable Raman gas
sensor for the analysis of natural and synthesis gas [21, 22].
However, as the composition of biogas strongly differs from natural
and synthesis gas, new measurement and calibration protocols have
to be developed. This includes the selection of an appropriate
spectral range for the data evaluation and the implementation of
additional gas species to the calibration procedure. For the
selection of an appro-priate spectral detection range it is not
only important that this range includes Raman transitions of all
relevant gas com-ponents, but also that the signal intensities of
the different species are considered. Ideally, the resulting Raman
signal intensities of all components should be in the same order of
magnitude. This ensures that they can be monitored by the detection
system with the required accuracy. The implemen-tation of new
components in our in-house-developed evalu-ation software is in
principle possible if calibration data are available. For
non-condensable gases, standard calibration mixtures are
commercially available over broad concentra-tion ranges. However,
this is not the case for many conden-sable gases. Although
calibration mixtures are commercially available for H2O, its
content is usually in the range of some hundred ppm, which is
several magnitudes smaller than the concentrations typical for
biogas and also below the detection limit of our sensor system.
Hence, such standard calibration mixtures are of limited use and
there is a need for an appro-priate calibration procedure.
In order to implement water, a number of experimental challenges
need to be taken into account. As the concentration of H2O is
usually close to the saturation vapor pressure, small changes in
ambient temperature may lead to condensation. This has to be
prevented for several reasons: condensation of water vapor changes
the H2O content in the gas phase and the measurement result is
falsified; water droplets in the measure-ment volume would
complicate the measurement due to the strong elastic scattering of
laser light from the droplet sur-faces; condensate on the surface
of cell windows may cause window damage and reduce the optical
transmission perfor-mance. Eventually, the varying process
conditions have to be considered. It is well known that the
intensity and the spectral shape of an individual Raman transition
depend on pressure and temperature. Depending on the desired gas
quality and the deployed micro-organisms, temperatures between 30
and 70 °C may occur during the fermentation process. The pres-sure
is usually near atmospheric conditions. However, pres-sures up to
10 bar may be present in the purification process: for instance,
during CO2 removal in a pressure swing absorp-tion process or the
removal of hydrogen sulfide [2]. Moreover, in order to allow
injection into the gas net the pressure of the product gas has to
be above the pipeline pressure.
In this paper, the applicability of a Raman-based sensor system
for the analysis of biogas is investigated in detail.
Meas. Sci. Technol. 25 (2014) 075503
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S C Eichmann et al
3
A new calibration procedure, which also includes the
cali-bration of water vapor at concentration levels in the order of
several percent is presented. Moreover, we investigate the
influence of pressure and temperature changes on the Raman spectrum
of characteristic biogas mixtures and on the evalu-ated species
concentration within typical temperature and pressure ranges of
biogas fermentation processes and associ-ated purification steps.
Finally, we demonstrate the applica-tion of the sensor in the
biogas plant of ‘Erdgas Süd-West’ in Laupheim, Germany.
Measurements were taken at three different locations inside the
facility and a comparison with reference data from conventional
techniques was carried out.
2. Measurement principle
The basic principles of Raman scattering are described
else-where [23], so only a short explanation will be given here. If
light travels through a gas volume, a small amount of the light is
scattered inelastically. This means that the scattered light is
frequency-shifted with respect to the incident radia-tion. This
process is called spontaneous Raman scattering and the
frequency-shift is characteristic for a given species and the Raman
spectrum can therefore be used for speciation. For the
determination of the species concentration in a gas the linear
relation between the Raman scattered light intensity IR of an
individual Raman line and the number density n can be used
⎜ ⎟⎛⎝
⎞⎠
σΩ
Ω= ∂∂
I kI nLR 0 (1)
where I0 the intensity of the incident laser light, Ω the solid
angle of the detection optics, ∂σ/∂Ω the scattering cross sec-tion
of the species, L the length of the probe volume and n the number
density of the species. The factor k is an experimental constant,
which takes signal losses into account. In order to compensate for
temporal fluctuations, e.g. fluctuations in laser power, it is a
common approach to consider relative signal
intensities. This is done by dividing the Raman signal
inten-sities of two different species, as shown in equation (2). By
doing this, all experimental constants cancel out and the signal
intensity ratio is only dependent on the number densities and the
scattering cross sections of both components.
σ Ω Ωσ Ω Ω
σ Ωσ Ω
= ∂ ∂∂ ∂
= ∂ ∂∂ ∂
⋅I
I
kI n L
kI n L
n
n
( / )
( / )
( / )
( / )R,1
R,2
0 1 1
0 2 2
1
2
1
2 (2)
Table 1 summarizes the vibrational Raman lines of common biogas
and natural gas components together with their scat-tering cross
sections for the excitation with a frequency doubled Nd:YVO4 laser.
Also given in this table are typical concentration ranges of the
individual species in biogas and natural gas. Depending on the
composition natural gas is divided into three groups L, M and H.
The specifications of the different groups are given in technical
standards, e.g. DIN 51624.
It can be seen from table 1 that the Raman lines for all
mol-ecules of interest are in a spectral region between 300 cm−1
and 4000 cm−1 and can easily be detected by the use of
com-mercially available spectrometers. However, also the dynamic
range of the detector is important. For precise measurement, the
maximum signal intensity of the Raman lines of all spe-cies of
interest should have the same order of magnitude. As a first rough
estimate the product of the scattering cross section and the number
density or the volume fraction can be used. Unfortunately, this
value is not similar for all Raman lines considered. For instance,
the v1 band of CH4 at 2915 cm−1 shows a comparatively high Raman
scattering cross section compared to that of CO2 and N2 and CH4 is
typically present at high concentration. As a consequence, the
simultaneous detection of CH4, N2 and H2O is difficult using the v1
band. For this reason, and because of the strong overlap with CH
stretching signals from the other hydrocarbons, it is advanta-geous
to disregard the v1 band. Therefore, the weak v2(CH4) band at 1534
cm−1 is the better choice here.
Table 1. Raman shift, scattering cross section and typical
species concentration for the different biogas and natural gas
components [4, 8, 24–26].
Component
Volume concentration
Vib. Raman shift
Scattering cross sectiona
Typical vol. concentration, natural gasVol. concen-tration,
biogasGroup H Group M Group L
(cm−1) (10−30 cm−1 sr−1) (%) (%) (%) (%)
methane (CH4) 2915 3.95 98.31 86.54 83.35 45–751535 0.05
ethane (C2H6) 2914 6.9 0.5 8.02 3.71
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S C Eichmann et al
4
3. Experimental
A sketch of the gas analyzer is shown in figure 1. In the upper
part, the Raman set-up is placed. It mainly consists of a
frequency-doubled, continuous wave Nd:YVO4 laser with a maximum
output power of 5 W, a heatable gas cell and a detection system.
The laser beam is focused by a lens (f = 100 mm) into the gas cell.
To improve the signal intensity, the laser beam is collimated after
travelling through the cell, retro-reflected by a rectangular prism
and focused back into the cell where it is overlapped with the
initial beam. The scat-tered light is collected at an angle of 90°
with respect to the direction of the incoming laser by a lens with
focal length of 100 mm and separated from elastic stray light using
a color glass filter with a cut-off wavelength of 550 nm. The
signal is coupled into the spectrometer with an achromatic lens (f
= 150 mm), where it is spectrally dispersed and detected with a
resolution of 7 cm−1 by an integrated back-thinned CCD-chip.
The stainless steel gas cell was designed for temperatures up to
523 K and for pressures up to 70 bar. To prevent conden-sation
inside the cell, it was equipped with a heating system consisting
of two heating cartridges, three heating plates for the windows and
a thermocouple with an uncertainty of 5 K.
Electric devices susch as the power supply units, switch relays,
signal converters, USB connectors and the control system of the
cell heating, are located in the lower part of the sensor. The
complete sensor is portable and has a size of 50 × 50 × 40 cm. The
investment costs are comparable to con-ventional gas analyzers and
except electricity there are no operational costs. A more detailed
description of the sensor system is given elsewhere [22].
The Raman spectrum of a characteristic gas mixture in the
spectral range between 500 cm−1 and 4000 cm−1 is shown in figure 2.
It consists of the 2v2 and v1 band of CO2 at 1245 cm−1 and 1388
cm−1, the v1(N2) band at 2331 cm−1, the v2(CH4) band at 1535 cm−1,
the strong v1(CH4) band at 2915 cm−1 and the v1(H2O) band at 3667
cm−1. The v1(CH4) signal is com-paratively strong and limits the
detection of minor species due to the limited dynamic range of the
detector. Therefore the v1(CH4) Raman signal was blocked by a Notch
filter with a bandwidth of 25 nm and a center wavelength of 633
nm.
4. Data evaluation and calibration
For the evaluation of biogas and natural gas Raman spectra, a
strategy is necessary which allows the analysis of overlapping
bands. This was done by a least-squares fit algorithm, based on a
contour fit method. In the first step, a synthetic spectrum was
generated by the superposition of weighted experimental spectra of
pure biogas components and fitted to the spectrum of the gas sample
by optimizing the set of species-specific weighting factors. The
set of species concentrations can then be obtained from this fitted
synthetic spectrum by solving the equation system
⃗ ⃗∑=b n k xi
i i i (3)
with the synthetic spectrum ⃗b , the number density ni, the
spe-cies dependent calibration factor ki, and the spectrum of the
gas component ⃗xi . The index i corresponds to the respective
species. The calibration factors can be determined from a gas
sample with known composition using the same algorithm. In the
present work, a mixture of 93.6% CH4, 2% CO2, 2% N2, 2% C2H6 and
0.4% C3H8 was used for the initial sensor calibration and a second
mixture consisting of 49% CH4, 49% CO2 and 2% N2 was used for
validation.
As commercially available gases do not contain con-densable
gases in a range of several percent, an additional method was
necessary for the calibration of water vapor. This was done by
adjusting saturation conditions for a mixture of nitrogen and water
vapor at defined temperature and pressure conditions. The set-up
for these calibration measurements is shown in figure 3(a). It
mainly consists of a gas circuit loop, a pump for the gas
circulation, and a storage tank filled with water. The whole system
was temperature stabilized at 296 K. The calibration system was
connected to a N2 gas cylinder, a vacuum pump and to the Raman
sensor. N2 was used as carrier gas as it shows a low solubility of
H2O, which is not the case, for example, with CO2.
Initially, the storage tank was filled with water. In the next
step the whole device including the Raman sensor was evac-uated to
the vapor pressure of H2O and then filled with the
Figure 1. Sketch of the Raman sensor. Figure 2. Spectrum of a
biogas (blue line) and the transmission function of the employed
Notch filter (black line).
Meas. Sci. Technol. 25 (2014) 075503
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S C Eichmann et al
5
buffer gas nitrogen to a total pressure of 1 bar. Eventually,
the gas pump was started. In order to monitor the evaporation
pro-cess of water, Raman spectra of the gas were recorded each
minute. After three minutes, no changes in the signal intensity of
H2O with respect to the buffer gas signal were observed, which
indicated saturation and equilibrium conditions. In a next step,
Raman spectra were recorded over a time period of 5 min with an
exposure time of 60 s. Since very low amounts of N2 are present in
biogas, the H2O calibration was related to CO2 using an additional
equimolar N2/CO2 calibration mix-ture (c(N2) = 50%, c(CO2) =
50%).
The calibration was performed at 1 bar and 296 K and therefore
at the same pressure conditions but at a slightly lower temperature
compared to the measurements. The small temperature difference of
16 K between calibration and meas-urement has no effect for the
sensor system used.
For the determination of composition at saturation condi-tions,
the mixture was assumed to be an ideal gas mixture. This is
possible as the concentration of H2O is low com-pared to the
concentration of N2 and the total pressure is relatively low. The
ratio of the molar concentrations (water/nitrogen) x at saturation
conditions can then be calculated from the partial pressure of
water, pH O,S2 , i.e. the saturation vapor pressure at the set
temperature, and the total gas pres-sure ptot by
=−
xp
p p.H O,S
tot H O,S
2
2
(4)
5. Temperature and pressure effects
As Raman spectra are sensitive to temperature and pressure
changes, the different process conditions which might occur during
fermentation and biogas after-treatment have to be taken into
account. In order to develop an appropriate strategy, the
temperature and pressure influence on the Raman spectra and on the
accuracy of the measurement was investigated with relevant gas
mixtures for typical process conditions.
Normalized spectra of a CH4/CO2 mixture (c(CH4) = 50%, c(CO2) =
50%) recorded at 303 K and 343 K are shown in figure 4. In order to
reveal changes with temperature the difference spectrum is plotted
as well. Small but systematic deviations can be found: for
instance, in the relative inten-sity of the 2v2 band of CO2 and the
relative intensity of the S-branch of the v2 band of CH4. To check
if these deviations affect the accuracy of the measurement and
hence make a temperature-dependent calibration necessary, the
spectrum at 303 K was used as calibration data and the spectrum at
343 K was then evaluated. An absolute deviation of 0.5% was found
between the actual and measured concentration. In the tested gas
mixture, this results in a difference in the heating value of 0.2
MJ m−3. As a consequence, for accurate measurements the temperature
effects must be taken into account. Nevertheless, small temperature
fluctuations of a few kelvin, which typi-cally occur during one
measurement period, can be neglected. For precise measurements,
with the present sensor system and the simple two-component gas
mixture, it was found sufficient to have calibration data available
in steps of 10 K.
Next, we investigated the influence of temperature on a gas
mixture containing CO2, CH4, C2H6 and N2 (c(CH4) = 94%, c(CO2) =
2%, c(C2H6) = 2%, c(N2) = 2%). This gas represents a typical
composition of processed biogas. Spectra recorded at 303 K and 343
K are shown in figure 5(a) together with their
Figure 3. Calibration of water vapor; apparatus for calibration
measurements (a), calibration spectra of a N2/CO2 and a N2/H2O gas
mixture (b).
Figure 4. Temperature influence on the spectral shape of a
biogas relevant gas mixture in the temperature range from 303 K to
343 K (p = 1 bar). The black line represents the difference
spectrum.
Meas. Sci. Technol. 25 (2014) 075503
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S C Eichmann et al
6
difference spectrum. Small differences are observed between both
normalized spectra, mainly in the intensity of the S- and O-branch
of the v2(CH4) band. Again, the temperature influ-ence on the
concentration was investigated by calibrating the sensor with the
spectrum recorded at 343 K and then evalu-ating the other data. The
absolute deviation between actual and measured concentration was
0.5% for CH4, 0.2% for CO2, 0.2% for N2 and 0.1% for C2H6. As for
the two-component mixture, it can be concluded that the difference
between cali-bration and measurement temperatures should be 10 K or
less.
The pressure influence on the concentration measure-ments was
investigated between 1 and 10 bar referring to typical conditions
in the biogas after-treatment processes. The resulting spectra
normalized to the absolute intensity of the v2(CH4) band are shown
in figure 5(b). Small differences are observed for the intensities
of the S- and O-branch of CH4. However, the influence of pressure
on the concentration measurement is comparatively small.
Calibrating the sensor at 1 bar and evaluating spectra recorded at
10 bar resulted in absolute concentration deviations of 0.1% for
CH4 and C2H6
Figure 5. Influence of temperature and pressure on the spectral
shape of a gas mixture typical for biomethane; influence of
temperature from 303 K to 343 K (a), influence of pressure from 1
bar to 10 bar (b).
Figure 6. Schematic sketch of the biogas plant.
Figure 7. Spectra from the three different points in the biogas
plant; biogas (a), biomethane (b), mixed gas (c).
Meas. Sci. Technol. 25 (2014) 075503
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S C Eichmann et al
7
and less than 0.1% for N2 and CO2. This is within the
meas-urement uncertainty.
To summarize these results, temperature and pressure levels
typical for the process conditions of biogas production and
treatment plants have an influence on the spectra detected with the
proposed Raman sensor. While the pressure influence in the relevant
range between 1 and 10 bar is in the order of the measurement
uncertainty and hence negligible, temperature effects need to be
taken into account by recording an appro-priate calibration data
set.
6. Application in a biogas plant
The described sensor was applied in the biogas plant of ‘Erdgas
Südwest’ in Laupheim, Germany. A schematic sketch of the plant is
shown in figure 6 and the locations where the sensor system was
applied are indicated. In the fermenter, biogas is produced by the
fermentation of corn and wheat at atmospheric pressure. The
produced biogas mainly consists of CH4 and CO2, but also contains
small amounts of N2 and water vapor. A typical compo-sition is
given in the figure. In the next step, the biogas is purified by
condensation of water vapor and removal of CO2 in a pres-sure swing
adsorption process. The methane content is increased to
approximately 96% and the heating value is now comparable to that
one of natural gas. During the separation of CO2, the pres-sure of
the gas (now called biomethane) is increased to approxi-mately 6
bar. In the last step, natural gas is added in order to insure that
the required gas specifications are met.
The composition of the gas was determined at three dif-ferent
points in the biogas facility: directly after the fermenter
(sampling point 1, biogas) to monitor the biogas production
process and the quality of biogas; after the removal of H2O and CO2
(sampling point 2, biomethane) to monitor the sep-aration steps;
and after the mixing with natural gas (sam-pling point 3, mixed
gas) to monitor the final product gas. The results were compared to
the conventional techniques installed in the plant. At sampling
points 1 and 2, the results from the CH4 and CO2 were compared with
the data from a conventional gas analyzer consisting of a near
infrared pho-tometer (URAS 14, ABB automation Products GmbH) for
the analysis of CH4 and CO2 and a paramagnetic analyzer, which
determines the N2 concentration from the measured O2 concentration.
This gas analyzer required dry gas under atmospheric conditions. At
sampling point 3, absorption measurements were not performed as the
photometer does not allow the simultaneous detection of the
different hydro-carbons. For this reason, the reference composition
at this location was calculated from the known mixture ratio of
natural gas and biomethane.
Figure 8. Species concentration measured at sampling point 1:
concentration results for the wet biogas (a), Raman sensor results
(RS) related to the dry biogas in comparison to near infrared
photometer (NIR-PM) and paramagnetic results (PA) (b).
Figure 9. Concentration results from the analysis of biomethane
(a) and mixed gas (b).
Figure 10. Raman spectra recorded at 1 and 6 bar: biomethane
(a) and mixed gas (b).
Meas. Sci. Technol. 25 (2014) 075503
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S C Eichmann et al
8
For comparison, all measurement systems were operated at a gas
pressure of 1 bar and a temperature of 313 K. The temperature
condition was chosen to avoid condensation; the pressure was
necessary due to the limitation of the used absorption photometer.
Raman measurements were conducted every 60 s and five spectra
accumulated.
In figure 7, normalized Raman spectra, recorded at the three
different sampling points, are shown. The filter transmis-sion
curve of the notch filter is also displayed. The spectrum of the
biogas (see figure 7(a)) consists of the 2v2(CO2) and the v1(CO2)
band, the v2(CH4) band, the v1(N2) band and the v1(H2O) band. No
signals were observed for the v1 transitions of CO and H2 at 2145
cm−1 and 4166 cm−1, respectively. The detection limits were
estimated from a series of test spectra at the same conditions to
be 0.5% for CO and 0.1% for H2. In figure 7(b), the spectrum of
biomethane is shown. Compared to the biogas spectrum, the Raman
signal of CO2 is strongly reduced and the signal of H2O vanished
completely. These changes in the spectrum reveal the changes in gas
composi-tion due to purification. Figure 7(c) shows the spectrum of
the final gas blend. The signal of CO2 is further reduced due to
the smaller content of CO2 in the added natural gas. Moreover,
Raman signals of the C2H6 and C3H8 are observed. Higher
hydrocarbons, such as C4H10 or C5H12, were not detected. The
specification ‘natural gas’ requires a content below 0.1% for these
hydrocarbons. This is below the detection limit of the sensor
system for measurements at ambient pressure.
Figure 8 shows the evaluated concentrations of CH4, CO2, N2 and
H2O at sampling point 1 as a function of process time. The mean
concentrations over the whole period of 50 min was 52.0% for CH4,
44.1% for CO2, 0.6% for N2 and 3.3% for H2O. These are typical
values for this biogas plant. However, comparatively strong
temporal fluctuations are observed for CH4 and CO2. A possible
reason for the magnitude of these fluctuations is the comparatively
low Raman signal of CH4 at this low pressure. In order to compare
the Raman sensor (RS) result with the near infrared photometer
(NIR-PM) and para-magnetic analysis (PA) results, the RS data were
related to dry biogas. In figure 8(b) the results from the
different methods are shown and good agreement is found. Concerning
the NIR-PM results, averaged values over the whole measurement
period were achieved. The absolute deviation between the Raman
results and the reference method were 0.5% for CH4, 0.2% for CO2
and 0.3% for N2. Due to the low signal to noise ratio of the Raman
signals at 1 bar, fluctuations of the concentra-tion values could
be observed, especially for CH4 and CO2. The noise level can be
used to estimate the measurement
uncertainty related to this measurement. For the Raman
meas-urements at 1 bar an absolute uncertainty of ±2% for CH4,
±0.25% for CO2 and ±0.2% for N2 was evaluated. The devia-tion
between the Raman results and the reference method are within these
limits. In addition, a standard deviation of 0.074% for CH4, 0.058%
for CO2 and 0.121% for N2 was achieved.
Figure 9(a) shows the RS results from sampling point 2 together
with the NIR-PM and PA data. The averaged con-centration gained
from the Raman measurement was 96.6% for CH4, 2.8% for CO2 and 0.6%
for N2. In contrast to the measurements at sampling point 1,
comparatively small con-centration fluctuations are observed over
the whole measure-ment period. The absolute deviation between the
RS results, the NIR-PM and the PA results are 0.35% for CH4, 0.23%
for CO2 and 0.02% for N2.
The results from sampling point 3 are displayed in
figure 9(b) together with concentration values calculated from
the biome-thane and natural gas compositions and the mixing ratio.
A mean concentration of 95.1% for CH4, 1.25% for CO2 and N2, 2.1%
for C2H6 and 0.3% for C2H8 was measured by RS. The abso-lute
deviation between both data sets was 0.13% for CH4, 0.32% for CO2,
0.29% for N2, 0.18% for C2H6 and 0.08% for C3H8. Accurate NIR-PM
measurements were not possible, because CH4 could not be
discriminated from other hydrocarbons.
At sampling points 2 and 3 the first set of measurements was
carried out at a pressure of 1 bar in order to meet the
requirements of the NIR-PM system. Additional RS data were recorded
at the higher process pressure of 6 bar with a sampling time of 60
s without any signal accumulation. In figure 10 typical
spectra from sampling point 2 and 3 taken at 1 bar with
accumulation and at 6 bar without accumula-tion are compared.
Despite the reduction of the measure-ment time by a factor of 5, a
significantly improved signal to noise ratio could be achieved at 6
bar. The averaged results from the mixed gas analysis, at both
pressures, were com-pared with the theoretical values from the
volume flows, see table 2. As expected, a better agreement is
achieved for the measurements at 6 bar.
7. Conclusion
In this paper, the applicability of a sensor system-based on
spontaneous Raman scattering for the determination of biogas
composition was characterized and tested. A suitable calibration
and evaluation procedure was developed and the influence of
temperature and pressure on the measured data was investigated
Table 2. Comparison of the averaged Raman results with the
calculated mixed gas values for 1 and 6 bar.
Concentration (%)
1 bar 6 bar
Raman measurement Calculated from volume flows Raman measurement
Calculated from volume flows
CH4 95.27 95.40 95.33 95.44CO2 1.29 1.63 2.05 2.13N2 1.30 1.00
1.18 0.95C2H6 2.14 1.98 1.19 1.23C3H8 0.43 0.35 0.25 0.25
Meas. Sci. Technol. 25 (2014) 075503
-
S C Eichmann et al
9
in the ranges relevant for industrial biogas production plants.
Compared to many established analytical techniques, such as
absorption spectroscopy and gas chromatography, the calibra-tion of
the Raman sensor has to be carried out only once. This means an
important advantage of the proposed analyzer system regarding
maintenance time and operating costs.
It was shown that the influence of pressure in the range between
1 and 10 bar is negligibly small, while temperature changes must be
taken into account in the calibration if they exceed 10 K. Minor
fluctuations of a few kelvin, which typi-cally occur during a
measurement period, can be neglected.
In order to demonstrate its practical applicability, the Raman
sensor system was applied at three different locations in a biogas
plant: after the fermenter, after the purification and after the
final conditioning where natural gas is added. At all sampling
points, all relevant gas components could be moni-tored and the
results showed good agreement with reference data obtained by
NIR-PM and PA. The detection of water vapor and higher hydrocarbons
was only possible with the Raman system. At 1 bar pressure, the
Raman results showed temporal fluctuations, which were partly
attributed to low signal levels. Therefore, the signal-to-noise
ratio needs to be improved if high temporal resolution and accuracy
are required. This can be done, for instance, through multi-pass
arrangements [27–30].
Acknowledgments
The authors gratefully acknowledge funding the research by
ESYTEC Energie- und Systemtechnik GmbH and the Bavar-ian State
Ministry of Sciences, Research and the Arts within the framework of
KW21 and the Erlangen Graduate School in Advanced Optical
Technologies (SAOT) by the German Research Foundation (DFG) in the
framework of the German Excellence Initiative.
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