The sensing characteristics and long-term stability of different
kinds of CO
Small-scale furnaces operated in domestic households, especially wood-log-fuelled heating systems and also wood-chip- or
pellet-fuelled central heaters, are
well known to contribute considerably to air pollution with toxic emissions of
uncombusted and/or partly combusted exhaust gas components (CO
There have been several attempts to reduce these toxic emissions, e.g. by
improving the construction of the fireplaces and/or by introducing automatic
combustion airstream control systems, based on continuous measurement of
combustion temperature (
In addition, there is a high demand to monitor the combustion quality of
automatically fed wood-chip-fuelled furnaces. The gaseous emissions of these
furnaces are comparably low as long as the system is operated under optimized
conditions. However, the continuous deposition of combustion residuals (ashes,
soot, etc.) on the walls of the combustion chambers and heat exchanger tubes
is known to have a negative influence on the combustion process during long-term
operation and can correspondingly seriously reduce combustion quality
(completeness of combustion) and efficiency (quotient of heat output to fuel
heat input). This results in increased toxic gas and PM emissions. In this
context, appropriate and reliable CO
In this paper both aspects, improved process control of
Firing experiments have been conducted with a wood-log-fuelled furnace
(SF10SK; Brunner GmbH, Eggenfelden, Germany) and two different wood-chip-fuelled central heaters (Multifuel Central Heater; A.P. Bioenergietechnik,
Hirschau, Germany). One of the latter (heating power: 49 kW) was operated in
the lab, and the other (heating power: 88 kW) was used to provide a small
settlement of several houses with heat energy in field test experiments over
nearly 4 months during the winter season 2016–2017. All furnaces were
complemented by a sensor (LSU 4.9; Bosch) for measurement of ROC and
different types of CO
Schematic drawing of a wood-log-fuelled fireplace with indication of the primary and secondary combustion airstreams controlled by mass flow sensor–shutter systems (blue). The various sensor elements and their positions are depicted.
For comparative evaluation of the CO
For the evaluation of the sensors in the exhaust gas of the wood-chip-fuelled
firing system, the standard operation and control unit of the producer were
used. In addition, a monitoring system with software was developed, which
enabled continuous calculation of the QC under practical conditions of
operation (field test experiments). The software algorithm recorded and
assessed the data from the furnace control unit, the actual heat output
measured with a heat meter (Sharky 773; Diehl Metering GmbH) and the sensor
signals for
The main focus of this work was to investigate the sensitivity and signal
stability of different kinds of CO
Commercially available high-temperature (HT) gas sensors of the non-Nernstian
mixed potential (MP) type have been investigated: CarboSen (CS) 1K and 10K (Lamtec GmbH & Co.
KG, Walldorf) and a prototype sensor for CO
The sensors are designed for in situ flue gas operation and are protected
from particulate matter contamination by filters. Generally, they are in
contact with a multitude of gas components (majorly CO, CH
The CO
The CO
Typical sequence of
Except for an offset, the progression of the signals of CS1K and CS10K is
rather similar (Fig. 2). They mainly follow the CO signal of the HT-FTIR
system, but the values are clearly enhanced beyond 225 min when the
concentration of the hydrocarbons contribute significantly to the MP. In
contrast, the signals of the HCS are very low as long as the concentrations
of the hydrocarbons are less than 5 ppm. Even to the stepwise rise in c(CO)
after the change from 70 to 50 % NP, the sensor reacts only with a small but
significant signal increase. This indicates that the signal of this type of
MP gas sensor depends less on c(CO) and seems to be more estimated by
the concentration of methane (c(CH
Significantly higher emissions are observed when the heater is continuously
operated in a mode for heating of a settlement (field test) over months and
NP is repeatedly changed in small time intervals according to the heat demand
and without any routine maintenance. Now emission peaks even higher than
1000 ppm CO (Fig. 3) are observed. The CO
Representative cut-out of the CO
The sensor signals of another set of CO
Course of
Regarding the course of the two signals of a CS10K and an HCS (Fig. 4), the
response to different flue gas compositions is clearly different due to
different sensitivities. In good agreement with the observations described
above (Fig. 3), the HCS signal is generally lower and seems to depend mainly
on c(CH
The sensor signal stability was evaluated by repeated sensor signal
measurements under exposure to CO
Evaluation of long-term stability by repeated sensor signal
measurements.
In addition to the necessity of an optimal control of the combustion process, the
continuous monitoring of the QC is the second essential reason for
the introduction of sensor-based CO
If a malfunction, a failure or a shutdown of the furnace is recorded by the
monitor system, the debug indicator (DI) is set to 1. Because DI
Example of the calculated quality of combustion (QC) in a wood-chip combustion unit with 88 kW of nominal heat output in field operation over a whole day in the winter season.
In Fig. 6 three segments with DI
Between the segments with DI
All CO
Further comparative studies will give more insight into the long-term stability of the different types of sensors and their individual behaviours when operated in the flue gas. As a highlight, one of the sensor elements (HCS) showed no signal loss even after a 4-month field test operation in the flue gas of a wood-chip combustion heater.
The use of the HCS CO
A dataset supplementing Figs. 2, 3, 4, 5 and 6 is provided at
The authors declare that they have no conflict of interest.
This article is part of the special issue “Sensor/IRS2 2017”. It is a result of the AMA Conferences, Nuremberg, Germany, 30 May–1 June 2017.
This project was funded by the Bundesministerium für Ernährung und Landwirtschaft (BMEL) and executed by the Fachagentur für Nachwachsende Rohstoffe (FNR), Gülzow. Edited by: Jens Zosel Reviewed by: two anonymous referees