Impedance spectroscopy characterization of an interdigital structure for continuous particle measurements in wood-driven heating systems

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Abstract. In the course of the climate change and increased focus on CO2-neutral energy sources, the use of wood-driven small heating systems (SHS) becomes more important. But, their contribution to air pollution, especially particulate matter, is about as high as the emissions from car engines. The specific formation of harmful substances in wood fires and possible countermeasures by continuously operating sensor and control systems are covered. Impedance spectra of interdigital electrode (IDE) structures are taken before and after mounting in wood-driven SHS to get information about the particles in the exhaust stream. It appears that the capacitive parts of the impedance spectra at a fixed frequency are appropriate for a fast signal evaluation. The good correlation with established offline measuring methods is discussed and the capability of thermal regeneration is demonstrated. The offline measurements of this work shall give the experimental basis for the development of online measurements in order to control the particle emissions of wood-driven SHS.

본문

J. Sens. Sens. Syst., 4, 37–44, 2015
www.j-sens-sens-syst.net/4/37/2015/
doi:10.5194/jsss-4-37-2015
© Author(s) 2015. CC Attribution 3.0 License.

# Impedance spectroscopy characterization of an interdigital structure for continuous particle measurements in wood-driven heating systems

A. Weiss 1 , M. Bauer 1 , S. Eichenauer 2 , E. A. Stadlbauer 2 , and C.-D. Kohl 1

1Institute of Applied Physics, JLU Giessen, Giessen, Germany
2Competence Centre for Energy and Environmental Engineering, University of Applied Science THM,
Campus Giessen, Giessen, Germany

_Correspondence to:_ A. Weiss (alexander.weiss@ap.physik.uni-giessen.de)

Received: 31 October 2014 – Revised: 31 December 2014 – Accepted: 8 January 2015 – Published: 5 February 2015

Impedance spectra of interdigital electrode (IDE) structures are taken before and after mounting in wooddriven SHS to get information about the particles in the exhaust stream. It appears that the capacitive parts of the
impedance spectra at a fixed frequency are appropriate for a fast signal evaluation. The good correlation with established offline measuring methods is discussed and the capability of thermal regeneration is demonstrated. The
offline measurements of this work shall give the experimental basis for the development of online measurements
in order to control the particle emissions of wood-driven SHS.

1 Introduction

The utilization of biomass for the generation of electricity
and heat is becoming more important due to an increased
focus on CO2-neutral energy sources. Particularly the sector of small heating systems (SHS) has a rising demand for
wood as an alternative fuel. The denotation “small heating
system” is often interpreted in different ways. In this paper,
it refers to boilers, stoves and furnaces with a nominal power
output of less than 50 kW that are typically used in residential and small industry or business buildings. It also explicitly includes the sector of single-room heating systems, e.g.,
closed fire places. In Germany, roughly half of the SHS are
already wood-driven (approximately 15 million). Their number is growing steadily due to increasing prices of fossil fuels. Especially in rural areas with easy access to the regional
forestry, wood is established as a cost-efficient fuel.

1.1 Types of emissions

This growing number of wood-driven SHS is accompanied
by an additional load of emitted air pollutants. One of them
that is worth focusing on is the fraction of particulate matter
(PM), because it is considerably higher than that of comparable oil or gas burners. According to the German Federal
Environmental Agency, it already exceeds the PM emission
caused by engines (cars, trucks, motorcycles, etc.) in 2003
(GFEA, 2007). The importance of that problem is also underlined by the constitution of the promoting cluster (“emission
reduction in biomass-driven SHS”) by the German Federal
Environment Foundation (GFEF, 2014).

Fine dust is categorized by its aerodynamic particle diameter in the classes PM10 ( _<_ 10 µm), PM2 _._ 5 ( _<_ 2.5 µm) and
ultrafine dusts ( _<_ 0.1 µm). Besides this classification, which
mainly provides information about the possibility of inhaling, the chemical nature of particles is also important for
their effect on human health. Thereby, the primary aerosols

Published by Copernicus Publications on behalf of the AMA Association for Sensor Technology

38 A. Weiss et al.: Impedance spectroscopy characterization of an interdigital structure

are differentiated in soot, which mainly consists of carbon
(black carbon, BC), mineral salts and condensable organic
compounds (COC), also known as tars.

In addition, volatile organic compounds (VOC), ammonia, carbon monoxide and oxides of nitrogen build up during combustion. Besides their direct toxic impact, they also
contribute to the secondary organic aerosols (SOA) as well
as to the inorganic fraction by conversion processes in the
atmosphere (Nussbaumer, 2010).

1.2 Health effects

The health risk of fine dust is primarily caused by its small
particle sizes. While the human body has defense mechanisms against larger particles, fine dust is able to penetrate
the lungs via the respiratory system. PM10 is named “inhalable”, whereas PM2 _._ 5 is already classified as “respirable”.
Ultrafine dust is able to enter the alveoles (alveolar) and is
hardly or even not at all removable. At this point, even in
other respects, nontoxic substances can cause health damage
like coughing, inflammation of the respiratory system, bronchitis or asthma.

Due to the large surface area of the pulmonary tissue, particles can also migrate to the blood and lead to serious diseases
of the cardiovascular system (e.g., heart attack), especially
for long time exposures. Long-term studies show that there
is a correlation between elevated mortality rate, particularly
by respiratory system diseases or lung cancer, and the fine
dust pollution (LUA, 2005).

Klippel and Nussbaumer (2007a) showed that health effects of fine dust depend not only on its particle sizes but
are also mainly influenced by its chemical composition. Accordingly, the weakest health effects are caused by dust that
mostly consists of mineral salts, such as those occurring in
well-adjusted combustion systems. Compared to that, the cell
toxicity of organic dusts from incomplete combustion is approximately 100 times higher. Besides the soot fraction (BC),
they include mostly condensable organic compounds (COC).
Additionally, a large number of different polycyclic aromatic
hydrocarbons (PAH) can be found that are well known for
their high carcinogenic impact. An overview of the health
effects of fine dust is given by Nussbaumer (2012).

1.3 Legal framework

The German 1st Federal Immission Protection Directive
(1st BImSchV) regulates the operation and inspection of
small- and medium-sized heating systems (GFRG, 2010).
The need for a reduction in pollutants is reflected in stricter
emission limits in the latest version of 22 March 2010. Table 1 shows the two-stage lowering of the maximum concentrations of CO and dust allowed. There are some interim arrangements for existing systems. If single-room heating systems do not fulfill the requirements of maximum allowed
emission levels of 0.15 g m −3 dust and 4 g m −3 CO in an in

Table 1. Emission limits for small heating systems according to the
1st BImSchV (GFRG, 2010).

From 22 Mar 2010 From 31 Dec 2014

(31 Dec 2016) a

CO
(g m −3 )

Dust
(mg m −3 )

CO
(g m −3 )

Dust
(mg m −3 )

Single-room heating
system

SHS _>_ 4 kW driven
with natural wood

a Split logs, wood chips; b pellets.

2.0 75 1.25 40
0.4 b 30–50 b 0.25 b 20–30 b

0.8 a

0.8 a 100 a

0.5 b 60 b

100 a 0.5 20

60 b

spection, they have to be upgraded or put out of operation
between 2014 and 2024, depending on the year of installation.

Currently, the 1st BImSchV does not define limits for the
emission of nitrogen oxides (NOx _)_ from wood-driven SHS.
NOx regulations only exist for oil- and gas-driven SHS as
well as for fuels with high nitrogen content like straw and
grain. However, the DINplus seal of quality already limits
the NOx emission of wood-driven SHS to 200 mg Nm −3, underlining their increasing relevance.

2 Characteristics of wood combustion

2.1 Properties of wood

Wood consists for the most part of cellulose and hemicellulose (60–80 % of the dry mass). These polysaccharides
give tensile strength to the wood by its fibrillae. The phenolic macro-molecule lignin contributes about 30 % of the
dry mass. It exhibits molecule masses in the range of 5000
to 10 000 u and, in contrast to the weak parts of the plant, it
gives compression strength to the wood. In addition, there are
some extractives like resins or minerals. The exact composition differs depending on the type of wood and individual
growing conditions.

Besides these constituents, forming the dry mass, a considerable amount of water is present in wood. The wood moisture, which is defined as the ratio of water mass to the wood
dry mass, can measure up to 150 % for fresh chopped trunks.
During drying it is reduced, depending on the ambient conditions. Wood moisture is an important parameter for combustion, because it reduces the lower heating value (LHV) by its
evaporation during combustion.

2.2 Combustion

According to Nussbaumer (2010), the combustion of wood
can be generally divided into three phases. In the first
phase, the wood is dried, causing the residual wood moisture to evaporate. Afterwards, gasification and pyrolysis begin, at which point volatile hydrocarbons are released into
the gas phase and carbonaceous organic compounds (cel

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A. Weiss et al.: Impedance spectroscopy characterization of an interdigital structure 39

lulose, hemicellulose and lignin) start to decompose. Coke,
volatile compounds (CO, H2 and VOC) and condensible organic compounds (COC) originate from this decomposition
process. Under optimal conditions, these products are oxidized to CO2 and H2O in the third phase (Nussbaumer,
2010). Concerning the whole fuel volume, it is important to
notice that all three phases take place at the same time. While
oxidation takes place at one point of the wood, it influences
drying and pyrolysis at another point of it.

2.3 Formation of pollutants

2.3.1 Dust

During combustion with a restricted oxygen supply, particles
form from incompletely burned components. At high temperatures ( _>_ 800 ◦ C), the organic compounds are decomposed to
a degree at which mainly carbonic soot (black carbon, BC)
is generated. On the other hand, if the temperature of the fire
is low, mainly COC arise, because the already formed tars
cannot react any further and condense to particles in the atmosphere. Low fire temperatures can occur for different reasons, e.g., energy consumed by evaporation of high moisture content, retarded exothermal oxidation due to oxygen
deficiency, or due to cooling by an excessive inlet air stream
(Nussbaumer, 2010). In fact, VOC also contribute to the organic aerosols, but their conversion to particles takes place
by secondary reaction in the atmosphere (secondary organic
aerosols, SOA). In this process, the mass of the particles can
exceed the original mass of VOC by a factor of 2, due to the
uptake of further elements (Nussbaumer, 2010).

In contrast to the organic fraction, the emission of mineral
components can also occur in complete combustion. They
form either by evaporation and subsequent condensation in
the cooling phase or are carried away from the ashes by the
exhaust stream. They mainly consist of chlorides, sulfates,
carbonites and oxides of the alkaline metal and alkaline earth
metals (Oser et al., 2003).

2.3.2 Oxides of nitrogen

In contrast to other kinds of combustion systems, the temperatures in wood-driven SHS are low enough that the formation
of NOx from the atmospheric nitrogen (thermal NOx _)_ can be
neglected. In this case, the nitrogen originates from the wood
itself (fuel NOx _)_, where its content is significantly higher
than in fossil fuels. However, the effectively emitted amount
of NOx can be considerably reduced by low-NOx methods
like fuel or air staging. The latter is characterized by the
spatial separation of supply air into primary and secondary
air. Thereby, the primary air area has to be highly substoichiometric to generate an oxygen-deficient reduction zone.
Nitrogen-containing compounds can be reduced to molecular
nitrogen at high temperatures (approximately 1100 ◦ C) combined with a dwell time of at least 0.5 s in this zone. The
complete oxidation of the organic parts is carried out by the

subsequent addition of secondary air (Hasler et al., 2000). A
distinctive reduction zone (0.2 _< λ <_ 0.3) also favors lower
emissions of particulate matter.

2.4 Mode of operation and sensor-controlled operation

A consequence of varying fuel properties (wood moisture,
loading of the combustion chamber, etc.) and the complex
relationships between the operating parameters is a discontinuous combustion with partly high emissions. Hence, the
accepted opinion in research and in the chimney sweeper
trade is that the typical mode of operation of wood-driven
SHS is far away from the optimum. Thus, in general, the actual emissions significantly exceed the values measured under norm conditions. This supports the assumption that the
fraction of wood-fired heating as a source of fine dust is considerably underestimated (Nussbaumer, 2010). Studies in a
German residential area show that wood-fired heating is responsible for up to 57 % of the ambient PM10 pollution under
certain weather conditions (Bari et al., 2011).

Therefore, it is reasonable to adjust the available variables
like primary air, secondary air and fuel supply to the current combustion conditions to achieve minimum emissions.
To evaluate these conditions, a control system needs comprehensive sensor technology for the direct measurement of all
relevant emission quantities. Similar approaches for smallscale biomass furnaces were recently investigated by Bischof
et al. (2013).

3 Sensors

3.1 Systems currently in use

In contrast to large combustion systems or to the control of combustion engines (lambda probe), continuously
working sensor systems are not common in wood-driven
SHS. If continuous systems are present anyway, it is mostly
about temperature-sensitive elements for power management. These can either mechanically control (bimetal, thermostat) the inlet air, causing bad combustion conditions, or
regulate the fuel amount, e.g., in modern pellet combustion
systems. Besides a measurement of the boiler temperature
in water-bearing systems, there is the possibility of placing thermo-elements directly in the combustion chamber. In
some rare cases, lambda probes are used to gauge the needed
amount of inlet air. In contrast to combustion engines, which
usually work in a narrow range around the stoichiometric
mixture (0.9 _< λ <_ 1.1), there are lower values in the reduction zone (0.2 _< λ <_ 0.7) and higher ones in the oxidation
zone (1.4 _< λ)_ .

The sensor systems currently in use with regard to SHS
refer to the measurements observing emission limits that
are regulated by law. In contrast to continuously working
sensor systems, these kinds of snap sample measurements
are not applicable for electronic combustion control. They

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40 A. Weiss et al.: Impedance spectroscopy characterization of an interdigital structure

Figure 1. Ways of conversion of the hydrocarbons to organic dust
components according to Nussbaumer (2010) (Weiss et al., 2014).

are only suitable for the detection of leakages or maladjustments. These 15 min measurements are performed by chimney sweepers and serve for observation of the limits of dust
and CO. Additionally, the temperature, oxygen content and
pressure difference is taken to benchmark the operating status.

Measurement methods regarding PM include mainly
gravimetric ones, but optical (scattered light, photoemission)
and electrostatic methods are in use, too. The gravimetric
methods feature, e.g., filter cartridges that are weighed after sampling or are part of a resonance circuit. The gaseous
measurands (CO, O2 and NOx _)_ are taken by electrochemical
cells in some instruments. The temperature can be measured
by thermocouples (e.g., by type K).

The instruments that are compliant for measurements according to 1st BImSchV exhibit a measurement uncertainty
of 30 to 50 % concerning the dust content. Furthermore, the
costs of EUR 5000 to EUR 20 000 per instrument are a high
investment for the user.

3.2 Sensors for continuous measurements

To use sensors for the control of SHS operating parameters,
the measurement method has to work continuously and must
withstand the rough conditions in combustion systems by its
technical implementation. Low costs per unit are essential for
an economical realization.

In the field of gas sensing, metal oxide gas sensors (MOX)
are suitable for this challenge. For example, tin oxide sensors
for the measurement of CO have already been developed for
fire detection in lignite-fired power plants. Despite the rough
ambient conditions (particularly dust), they achieve lifetimes
of up to 7 years and have been applied successfully in many
power plants (Kohl et al., 2001). Also, the NOx measurement
can be carried out by MOX. Benner et al. (2002) showed that
the used MOX withstand the combustion chamber conditions

Figure 2. Used IDE structure consisting of a ceramic substrate
(Al2O3 _)_ and platinum interdigital electrodes. The electrode width
and distance is 27.5 µm, the length 1400 µm and the number of legs
34 (Weiss et al., 2014).

of a power plant at up to 650 ◦ C. Electrochemical sensors
cannot be operated under these conditions. They are only
suitable in bypass measurements at lower temperatures after exhaust stream cooling. Their lifetime is typically on the
order of 1 to 3 years and thereby shorter than that of MOX.

Direct measurement of the dust emission is crucial for controlled operation, because it cannot be determined just by
the knowledge of other measurands like the CO concentration due to the fact that there is no clear correlation (Klippel and Nussbaumer, 2007b). For this task, common quartz
bulk oscillators (QCM) are not suitable, because the limited
temperature stability of quartz does not allow thermal regeneration. But, other piezoelectric materials like langasite may
also be candidates for high temperature application (Richter
et al., 2008; Richter and Fritze, 2014). Surface acoustic wave
devices are commonly used as sensors in various applications, especially for the detection of mass deposits on its surface. But, under rough and fluctuating conditions – like those
present in SHS - they are hard to operate. Because temperature deviations of only 1 K can be enough to interfere with
the pure sensor response, temperature compensation, e.g., by
a dual-port SAW, is necessary (Mujahid and Dickert, 2014).
Beyond that, the elastic and conductance properties can spoil
the result by a factor of up to 2. Our own approach for a capacitive dust measurement procedure will be detailed in the
following section.

4 Capacitive dust measurement

An approach for dust measurements in wood-driven SHS was
investigated by the authors in a joint research project with
partners from industry and a chimney sweep academy. The
basis of the measurement is a ceramic substrate (Al2O3 _)_ with
platinum interdigital electrodes (IDE); cf. Fig. 2. Compara

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A. Weiss et al.: Impedance spectroscopy characterization of an interdigital structure 41

ble structures as resistive-type dust sensors are also in use for
the monitoring of particulate filters in automotive applications (Bosch, Continental) and are currently under investigation (Bartscherer and Moos, 2013). Recently, they have been
suggested for the detection of conductive smoke deposits in
electrical installations (Cleary, 2014). Resistance measurements of such structures require a minimum level of coverage at which the percolation threshold is reached and a conducting path builds up. The disadvantages are that low levels
of coverage cannot be determined and that only conducting
particles contribute to the signal.

In contrast to the detection of filter damages in cars, where
the relevant timescale is on the order of hours or days, a sensor for the control of wood combustion has to operate on
scales of less than a minute. Quick reaction and the detection of small amounts of dust are crucial for the application.
Therefore, a capacitive approach is deployed. Dust deposited
on and between the electrodes gives rise to the capacitance of
the device by its permeability even when no conduction path
develops.

4.1 Technical realization

To design simple electronics for a capacitive online measurement, it is first necessary to analyze the IDE structure
and dust properties in detail. Therefore, in contrast to the future application, in this proof of principle, all measurements
were conducted in the lab of the university, not online in
SHS. Thus, the fresh IDE structures were first investigated by
impedance spectroscopy (IS), subsequently loaded with dust
in SHS and afterwards characterized by IS again. Impedance
spectra were taken using a Solartron SI1260 in combination
with a Chelsea dielectric interface that facilitates the measurement of small currents and therefore extends the measuring range to small capacitances even at low frequencies.
The complex capacitance _C_ ∗ is calculated from the complex
impedance _Z_ ∗ according to Eq. (1).

_C_ ∗ = _i_ _Y_ - ∗ _ω_ = _i_ - _ω_ 1 · _Z_ ∗ (1)

−Im _(Z)_
Re _(C)_ = _ω(_ Re _(Z)_ 2 + Im _(Z)_ 2 _)_ _._ (2)

The real part of _C_ ∗ is expressed by Eq. (2) and describes
the capacitance of a capacitor in an equivalent circuit model
that is frequency independent for an ideal capacitor-like system. The IDE exhibits only minor frequency dependency in
the range from 1 to 10 5 Hz ( _<_ 0.5 %). Thus, the sensor response _C/C_ 0 for low (no conducting) coverage can easily be
calculated by using one frequency (16.3 kHz), which is important for future device implementations.

The measured base capacitance _C_ 0 (without dust load,
at room temperature) of the IDEs is in the range from 2.5
to 2.9 pF due to minor production fluctuations. A theoretical description of such a system is given by Endres and

Figure 3. Socket mounted IDE structures. Left: fresh; middle: light
loaded (response ∼ 3 %); right: heavily loaded (response 419 %,
percolation threshold exceeded) (Weiss et al., 2014).

Drost (1991) and Endres and Bock (2006), and results in
Eq. (3):

_K_ - _(_

~~�~~ 1 − _(_ _a_ + _a_ _b_ _)_ 2 _)_

_K_ - _(_ _a_ + _a_ _b_ _)_ 2 + _εL_



 _,_ (3)

_C_ = _(n_ - 1 _)_ - _L_ - _ε_ 0 ·

- _(_ _εL_ + _εS_ _)_
2

_h_

_a_

where _a,b,h,L_ and _n_ are electrode distance, width, height,
length and number, respectively, _εL_ and _εS_ are the relative
permittivities of air and substrate material and _K(x)_ is the
elliptic integral of the first kind (Endres and Drost, 1991; Endres and Bock, 2006). Taking average values of the used IDE
( _a_ = 27.5 µm, _b_ = 27.5 µm, _h_ = 5 µm, _L_ = 1400 µm, _n_ = 34,
_εL_ = 1.000059, _εS_ = 9.5), Eq. (3) yields a capacitance of
2.9 pF, which is in good agreement with our results. In principle, electrode distances will not affect the results in resistive measurements (assuming a homogeneous coverage with
sufficiently small particles). In a capacitive approach, it will
influence the base capacitance ( _C_ 0 _)_ as well as the sensitivity. Therefore, an adjustment of the electrode structure can
be utilized as an optimization parameter in further investigations.

The capacitance shows only small fluctuations between
measurements from day to day (0.04 %) in the laboratory
setup. Signal changes of 0.1 % can be clearly separated from
the noise. The cross-sensitivity to humidity is quite low. The
capacitance of the fresh IDE structure at 16.3 kHz changes
by only 0.03 %, when the relative humidity is varied from
0 to 30 % at room temperature. Figure 3 shows examples
of three IDE structures with different levels of soot loading
from a wood-driven SHS. As can be seen, even hardly visible loadings lead to clearly measurable results (middle). The
response will reach very high values for loads in excess of
the percolation threshold (right).

4.2 Thermal regeneration

Besides IDE, the substrate possesses a platinum resistance
wire (PT10) that is arranged in a U shape around the IDE
in a sublayer and that serves as a resistance thermometer
and heating. It allows an exact temperature control as well
as thermal regeneration at temperatures up to 800 ◦ C. The
organic part of the dust deposits can be burned directly on
the IDE structure. Optical investigations reveal that 650 ◦ C

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42 A. Weiss et al.: Impedance spectroscopy characterization of an interdigital structure

Figure 4. Single soot particle left between the platinum electrodes
after a first regeneration step. The particle was removed by a second
regeneration (electrode width 27.5 µm).

are sufficient to relieve the surface of all black deposits. The
required time depends on the amount of dust and varies between a few seconds for light loading and up to 5 min for
heavy loading. Higher temperatures are able to fasten this
procedure. In a series of ten regeneration tests, only one sensor showed a single residual soot particle after a first regeneration step (see Fig. 4). A second regeneration was sufficient
to remove the particle. The complete cleaning of the sensor
surface is verified by further IS measurements. It is shown
that the capacitance returned to its former basic value of _C_ 0.

The dissipated heating power during temperaturecontrolled regeneration can serve as a further measurand. As
indicated in Fig. 5, higher dust loadings require an elevated
amount of heat. This optional analysis step may deliver additional information about the dust loading and will be the
object of further investigations, as well as the detailed temperature dependence of the IDE structure.

4.3 Results from the test grid

Series of measurements were performed with IDE structures
loaded in different SHS (Buderus Blueline stove, Buderus
Logano S231-25 wood gasifier) and with different kinds of
wood-based fuels. In each case, the IDE structures are placed
in the exhaust tube directly behind the SHS with the surface
facing upstream in the direction of the combustion chamber. Because it is not possible to generate completely reproducible combustion situations (see Sect. 2), reference systems are necessary. The only feasible ones are the instruments according to 1st BImSchV and in accordance with
VDI guideline 2066-1 from which two with different measurement principles are used. Due to the fact that they are
not designed for continuous operation, they enforce 15 min
measurements with corresponding high loading levels for the
IDE sensor.

Figure 5. Dissipated heating power during thermal regeneration
of a heavily loaded IDE structure (line) and a fresh IDE structure
(dashed line).

First results indicated that there is an acceptable correlation between the IDE sensor and references despite the fact
that the capacitance signal is not volume weighted like the
references (Weiss et al., 2014).

Further results from a series with four different woodbased fuels using the Buderus Blueline stove are shown in
Fig. 6. The measurement numbers indicate eight separate
fires. To evaluate the relative accuracy of the IDE sensors,
each measurement is carried out using two of them in parallel. As can be seen, the relative deviations are small, with
only 6 % of the response on average and some points so close
to one another that they can hardly be differentiated on this
scale. A distinguishable correlation between IDE sensor response and the reference values is achieved over all measurements, despite various fuels. The remarkable deviations of
the two reference instruments (Fig. 6: nos. 5 to 8) may be
caused by a saturation effect of reference instrument 1 due to
the high dust concentrations ( _>_ 150 mg m −3 ).

Measurement no. 8 exhibits an overestimation of the dust
content by the IDE sensor. Detailed inspection of the trends
of temperature, dust, CO and O2 reveals that the fire has
come to the final combustion phase during the measurement.
This has a strong influence on the pressure inside the systems and therefore on the exhaust velocity. In contrast to the
IDE sensor, the volume-weighted values of the reference instruments compensate for that effect, which may explain the
deviation.

5 Conclusions

The continuous in situ measurement of particles under firing conditions is an important task to reduce wood fire emissions, especially during the initial and ceasing states. This paper presents a first step in that direction, showing that cheap
interdigital structures generate useful signals for an economical device. Further on, it could be shown that these devices
can be used repeatedly in a cyclic manner. That opens the

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A. Weiss et al.: Impedance spectroscopy characterization of an interdigital structure 43

Acknowledgements. The authors thank Bernd Vollmer and
Hans-Eberhard Kopp of the North Rhine-Westphalia chimney
sweep academy (Schornsteinfegerakademie Dülmen) as well as
Ulrich Strohal and Jochen Fey of the Strohal enterprise (Strohal
Anlagenbau, Staufenberg) for their technical support and preparation of the test combustion systems. Further gratitude goes to
the German Federal Environment Foundation for supporting the
project.

Edited by: A. Schütze
Reviewed by: two anonymous referees

References

Bari, M. A., Baumbach, G., Kuch, B., and Scheffknecht, G.: Air

Figure 6. Comparison of the response ( _C/C_ 0 _)_ of two IDE sensors
at a frequency of 16.3 kHz with values from two reference instruments. The response of both IDE sensors overlap at several points
due to their small deviation. The fuels are HTC char (no. 1, no. 2),
beech briquette (no. 3, no. 4), Pini&Kay briquette beech (no. 5, no.
6), Pini&Kay briquette spruce (no. 7, no. 8). The deposition time is
15 min according to the 1st BImSchV requirements of the reference
instruments.

possibility of applying them in an online control system for
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At this early stage of research, the sensors already show a
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The influence of humidity on the capacitance of loaded
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First tests of capacitive sensor readout with simpler electronics are conducted under lab conditions with promising
results. As mentioned above, the dissipated heating power as
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