Low cost gas sensors

19/09/2014
State-of-the-art van gassensoren voor het
meten van omgevingscondities
VSL Themadag Gasanalyse – Gassen en Gezondheid
Delft, 18/09/2014
VITO – VIsion on TechnOlogy
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Air quality monitoring
MRG
Exposure modelling
Environmental
Risk & Health
Rudi Torfs
Exposure and health
monitoring
73 staff (research + lab)
20 PhD & post-doc
Luchtkwaliteitsmetingen
(Eco-)Toxicology
Gert Otten
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Referentielabo – organisatie van ringtesten
» Flemish reference laboratory for environmental analyses and
measurements is VITO a link between the Flemish Government and the
environmental laboratories
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Sensor Evaluation Lab
For VOC sensor tests
Freezer
Heater
IMEC NL NO2
sensors
AppliedSensor
NO2 sensors
VOC generation
Custom built controlled
gas humidifier
Heat exchanger
Testo T and RH
logger
From NO2/VOC
gas generation
NO2 gas bottle
Voice 200 SIFT-MS made
by Syft technologies
to exhaust
Log computers
3 way valve
Sample point for
reference monitors
Wide tube to
exhaust
Thermo 42C chemiluminescence NO –
NO2 – NOx analyzer
Humidified air gas
inlet
Air is compressed,
dried and filtered with
active charcoal
Bronkhorst controlled
evaporator mixer
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gassensoren voor
het meten van
omgevingscondities
?
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• Spatial variability
• Health relevance
• Traffic related
• BC, UFP >> PM10/2.5
• NO2/(NO) >> O3, CO
Novel Air Quality Monitoring Methods
Objectives
High-resolution mapping
• Spatio-temporal dynamics of air pollutants
• Potential users: authorities, urban planners, air pollution modellers
Hot-spot identification
• Fast and reliable method for hot spot detection
• Targeted measurements to potential hot-spots
• Potential users: city authorities, environmental agencies
Exposure monitoring
• Validity for confined area and period : extrapolation?
• Combine with activity patterns for exposure assessment
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Novel Air Quality Monitoring Methods
Strategies
» health-relevance versus regulation
» exposure in different micro-environments
» detailed data – high spatio-temporal resolution
» Portable monitors in mobile applications
» Low cost sensors in dense networks
Participatory sensing
» Low cost sensors in mobile applications
» Challenges: sensor quality, data quality, mobile data,
intelligent data processing
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Gas sensors – what ?
Basic sensors
- Electrochemical
Sensor head
- Semiconductor metaloxide - temperature control
- calibration curve
- 5 – 80 €
- correcting for T, RH
- 200 - 300 €
Not designed for / little
experience in ppb range
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© 2014, VITO NV
Measuring device
- 1000 - 2000 €
cross-interference, drift,
T and Hum effects
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Low cost gas sensors : lab performance
» e.g. Mead et al. 2013 :
Alphasense – electrochemical
sensors
Mead, M. I., Popoola, O. A. M., Stewart, G. B.,
Landshoff, P., Calleja, M., Hayes, M., … Jones, R. L.
(2013). The use of electrochemical sensors for
monitoring urban air quality in low-cost, high-density
networks. Atmospheric Environment, 70(0), 186–203.
doi:10.1016/j.atmosenv.2012.11.060
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Low cost gas sensors : lab performance
» e.g. Brunet et al 2008 : phtalocyanine sensor
»
Brunet, J., Garcia, V. P., Pauly, A., Varenne, C., & Lauron, B. (2008). An optimised gas sensor microsystem for accurate and
real-time measurement of nitrogen dioxide at ppb level. Sensors and Actuators B: Chemical, 134(2), 632–639.
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Low cost gas sensors :
lab performance
Project No: 611887
» Objective :
» develop highly competitive production technologies enabling flexible
integration of nanotechnology based multi-sensor systems with
conventional electronic chips
» Integration of array of gas sensors
» Metaloxide (nanowire) sensors (NO2, O3, CO, VOC, CO2)
» GaN sensor (NO2)
» Graphene sensors (VOC, NO2 (??))
» Lab and field tests of
» individual sensing components
» MSP demonstrator devices
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IMEC GaN NO2 sensor
Project No: 611887
Low NO2 concentrations (10 ppb) are well detected
Faster sensor response and recovery with sensors on higher
temperature: heater power 5 Watt -> 6,7 Watt
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AppliedSensor NO2 sensor
Project No: 611887
The sensors react rather fast on changes in
NO2. The response (T90) and recovery time
(T10) are both 4 minutes.
Low NO2 concentrations (10 ppb) are well
detected
large influence of T on the sensor
signal might be present
(further investigation needed)
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NO2 sensors - Linearity
Project No: 611887
Good linear response on NO2 (R² = 99%)
Very good linear response on NO2: R² = 99,8%
Quite a large difference between the
responses of identical sensors.
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NO2 sensors – RH test
Project No: 611887
Sensor is not sensitive to changes in humidity!
Possibly due to high power usage of sensor
heater (5 Watt).
In MSP membranes and micro hot plates will
be developed to minimize power consumption.
Large influence of changes in RH
on the sensor signal
Good linear relationship between
sensor response and presence of RH:
R² = 98% without NO2 present
R² = 93% with NO2 present
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Low cost gas sensors : field comparison
» EveryAware : SensorBox for use in participatory monitoring
» Comparison of sensor measurements made with 4 EveryAware sensor
boxes and reference gas measurements from station 42R801 of the
official Flemish air quality monitoring network. Averages of 4 sensor boxes
are shown together with the standard deviations between brackets
Bart Elen, Jan Theunis, Stefano Ingarra, Andrea Molino, Joris Van den Bossche,
Matteo Reggente and Vittorio Loreto (2012) The EveryAware SensorBox: a tool for
community-based air quality monitoring, paper presented at the Workshop Sensing a
Changing World, May 9-11, 2012, Wageningen, The Netherlands. (http://www.geoinformatie.nl/workshops/scw2/papers/Elen_etal_EveryAware_SensorBox.pdf )
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Low cost gas sensors : issues
» sensitive to changes in temperature and humidity
» marked cross-sensitivity towards other gases
» cross-sensitivity towards ozone is a major issue for both metal oxide
sensors and electrochemical NO2 sensors (Afzal et al. 2012, Mead et
al. 2013).
» response times to gas concentrations in the ppb range can also be
significantly longer than specified for gas concentrations in the ppm range
» long term sensor baseline drift
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Low cost gas sensors : developments
Alphasense Air Sensor for Air Quality Networks
» electrochemical O3, NO2 , NO, and CO sensors that specifically target
ambient air monitoring, making use of a second sensing electrode to
compensate temperature or humidity induced baseline drift.
» low noise electronics to be used to attain the specified detection limit
» But :
» Technical specification sheets still indicate possible baseline shifts up
to 50 ppb
» lack of selectivity of NO2 and O3 sensors towards each other.
» specifications have to be verified in real ambient conditions.
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Low cost gas sensors : developments
» use of nanomaterials (nanowires, carbon nanotubes, graphene) and
nano-electronics to reach better gas sensing performances and lower
power consumption.
» nanostructured materials
» high sensitivity,
» but lack of selectivity and stability remain major issues.
» most results acquired in laboratory conditions, and have not yet made
their way to field applications.
» Recent overviews of the state of the art and future developments :
»
»
»
Afzal, A., Cioffi, N., Sabbatini, L., & Torsi, L. (2012). NOx sensors based on semiconducting metal oxide nanostructures:
Progress and perspectives. Sensors and Actuators B: Chemical, 171-172, 25–42. doi:10.1016/j.snb.2012.05.026
Llobet, E. (2013). Gas sensors using carbon nanomaterials: A review. Sensors and Actuators B: Chemical, 179, 32–45.
doi:10.1016/j.snb.2012.11.014
Basu, S., & Bhattacharyya, P. (2012). Recent developments on graphene and graphene oxide based solid state gas sensors.
Sensors and Actuators B: Chemical, 173, 1–21. doi:10.1016/j.snb.2012.07.092
»
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Low cost gas sensors : developments
» Use of semiconducting polymers
» e.g. Brunet et al, 2008 phthalocyanine gas sensor to measure ppb
levels of NO2
» Additional use of sensitizing or filtering layers
» e.g. Dubois et al, 2013 use carbonaceous filter to remove ozone
»
»
Brunet, J., Garcia, V. P., Pauly, A., Varenne, C., & Lauron, B. (2008). An optimised gas sensor microsystem for accurate and
real-time measurement of nitrogen dioxide at ppb level. Sensors and Actuators B: Chemical, 134(2), 632–639.
doi:10.1016/j.snb.2008.06.010
Dubois, M., Brunet, J., Pauly, A., Spinelle, L., Ndiaye, A., Guérin, K., … Vinogradov, A. S. (2013). A carbonaceous chemical
filter for the selective detection of NO2 in the environment. Carbon, 52, 17–29. doi:10.1016/j.carbon.2012.08.067
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Sensing devices based on low cost gas sensors
» strategies to improve the sensitivity or selectivity of gas sensors or to
compensate for drift
» modulation of temperature regimes (e.g. Bur et al. 2013)
» modulation of the flow over the sensor (e.g. Williams et al, 2009;
Aeroqual)
» removal of interfering gases through scrubbers and filters (e.g.
Williams et al, 2009; Aeroqual)
» Delgado-Saborit (2012) compared an Aeroqual handheld NO2 monitor to a
reference monitor at 1 h temporal resolution  correlation is rather poor
(R2 = 0.63).
»
»
»
Bur, C., Bastuck, M., Lloyd Spetz, A., Andersson, M., & Schütze, A. (2014). Selectivity enhancement of SiC-FET gas sensors by
combining temperature and gate bias cycled operation using multivariate statistics. Sensors and Actuators B: Chemical, 193,
931–940.
Williams, D. E., Salmond, J., Yung, Y. F., Akaji, J., Wright, B., Wilson, J., … Laing, G. (2009). Development Of Low-Cost Ozone
and Nitrogen Dioxide Measurement Instruments Suitable For Use In An Air Quality Monitoring Network. In The 8th Annual
IEEE Conference on Sensors.
Delgado-Saborit, J. M. (2012). Use of real-time sensors to characterise human exposures to combustion related pollutants.
Journal of Environmental Monitoring, 14(7), 1824–1837.
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Sensing devices based on low cost gas sensors
» strategies to improve the sensitivity or selectivity of gas sensors or to
compensate for drift
» e.g. Mead et al. 2013
» commercially available electrochemical NO, NO2 and CO sensors
(Alphasense,UK) optimised for use at ppb level through improved
techniques for electrode and sensor manufacture as well as careful
design of a low-noise conditioning circuitry.
» intrinsic detection limit, sensitivity, noise characteristics and response
time of electrochemical sensors compatible with their use in ambient
air quality studies
» data post-processing procedures to correct for baseline sensitivity to
temperature and humidity and to correct for O3 interference.
» Implemented in AQ Mesh : results ??
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Sensing devices based on low cost gas sensors
» e.g. Mead et al. 2013 – correcting NO2 sensor results for ozone
Mead, M. I., Popoola, O. A. M., Stewart, G. B., Landshoff, P., Calleja, M., Hayes, M., … Jones, R. L. (2013). The use of
electrochemical sensors for monitoring urban air quality in low-cost, high-density networks. Atmospheric Environment, 70(0),
186–203. doi:10.1016/j.atmosenv.2012.11.060
19/09/2014
© 2014, VITO NV
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Sensing devices based on low cost gas sensors
» strategies to improve the sensitivity or selectivity of gas sensors or to
compensate for drift
» data post-processing procedures to correct for baseline sensitivity to
temperature and humidity.
Poor outdoor correlation of electrochemical CO sensor to
½ hour reference values due to temperature dependency
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Sensing devices based on low cost gas sensors
» correcting interference of environmental factors
» Test set-up: sensors collocated with reference CO monitor
» Develop statistical model
Two weeks
Two weeks
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Sensing devices based on low cost gas sensors
» Gerboles and Buzica (2009; 2011) evaluated 4 commercially available
ozone measurement devices.
» Lab tests : sensitivity to humidity in particular, but also to temperature
and in some cases wind speed
» Reasonable measurement results were possible after a field
calibration using O3 reference measurements.
» calibration is specific for sites or for different periods over the year
»
Gerboles, M., & Buzica, D. (2009). Evaluation of micro-sensors to monitor ozone in ambient air. JRC-Ispra. Research Report.
Retrieved from http://publications.jrc.ec.europa.eu/repository/bitstream/111111111/10477/1/eur23676.pdf
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Sensor arrays – multivariate calibration
» electronic nose (e-nose) (Gardner & Bartlett 1994)
Individual low-cost sensors
Sensor array (e-nose)
 Exploit partial selectivity towards different gas components using machine
learning tools to achieve multivariate calibration
» De Vito et al. (2009)
» low cost multi-sensor device based on seven solid-state sensors (5 gas
sensors, one temperature and one humidity sensor) and a neural
network for on field calibration to estimate benzene, CO and NO2.
» Two weeks of training for their neural network was enough to have
acceptable results for CO and NO2 estimation for 6 months.
» (The encountered concentrations are quite high. NO2 levels were not
below 50 µg/m3 with daytime concentrations roughly between 80 160 µg/m3.)
»
De Vito, S., Piga, M., Martinotto, L., & Di Francia, G. (2009). CO, NO2 and NOx urban pollution monitoring with on-field
calibrated electronic nose by automatic bayesian regularization. Sensors and Actuators B: Chemical, 143(1), 182–191.
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Sensor arrays – multivariate calibration
» EveryAware SensorBox.
» Calibration models using machine learning techniques
(SupportVectorMachines)
6 metal oxide
sensors
1 electrochemical
7 sensors which react on traffic pollution
Ozone, Temperature and Relative humidity
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500 hours
1350 hours
Input : NO2
sensors; O3
sensor, T
NO2
training:
R2= 0.718, RMSE = 10.111
SB –
Stationary
Estimation
models
evaluation:
R2= 0.389, RMSE = 19.507
750 hours
1100 hours
Input : NO2
sensors; O3
sensor, T
NO2
training:
R2= 0.788, RMSE = 11.064
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© 2014, VITO NV
evaluation:
R2= 0.676, RMSE = 13.559
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Conclusions
» No low-cost mass produced gas sensors exist that can directly measure
crucial parameters such as NO2 or O3 in ambient environments. Their
possible availability will be a matter of several years.
» The main issues are the inherent lack of sensitivity, sensitivity to changes
in temperature and humidity, lack of selectivity towards other gases,
stability and baseline drift.
» Strategies to improve the performance of these sensors lead to a higher
complexity and significantly higher cost of the sensing device, complex
field calibration procedures and extensive data post-processing.
» Some encouraging examples show that the use of low-cost sensors has
potential but requires know-how on sensing principles, careful electronics
design, laboratory and field testing, and complex data post-processing or
field calibration procedures, requiring serious interdisciplinary
development efforts.
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