Measuring megacity air
Miikka Dal Maso1, Anssi Järvinen1, Antti Rosted1, Jian
Gao2, Topi Rönkkö1
1Tampere University of Technology, Tampere, Finland
2CRAES, Beijing, China
Improving urban air quality – a challenge
on many fronts
2015 - Miikka Dal Maso
Understanding and improving urban air quality requires a holistic approach in
which all critical aspects are taken into account.
At TUT, our focus is measuring emissions and concentrations and
modeling transformation at high scientific quality.
6/10/2015
TUT FOCUS TUT FOCUS
Roadmap to Beautiful Beijing/Beautiful China
2
Challenges of measuring aerosol in
(mega)cities
Particle Diameter (nm)
1 10 100 1000
107
105
103
101
10000
Sulfuric Acid
Organic
Nitrate
Carbonaceous
Sulfate
Sea Sal
Mineral
2015 - Miikka Dal Maso
Urban PM, with multiple source components, also
exhibits high physical and chemical complexity
6/10/2015
Example of urban aerosol complexity:
Beijing size distribution data shows six
different typical size distributions.
Half the time, more than 50% of
particles are <50 nm.
Beijing
Particle size
Particlenumber(norm.)
Gao, Dal Maso et al, in prep.
3
TUT researches city aerosol on several
fronts
6/10/20152015 - Miikka Dal Maso
1. Targeted urban measurements 2. Instrument development
4. Process studies - modeling3. Fresh and aged emission
measurements
4
MMEA (Measurement, Monitoring and
Environmental Efficiency Assessment) aerosol
reseach environment
5
• Measurement methods, instrument
development
• Calibrations, field tests
• Emission studies
• Data intercomparisons
• Air quality studies
6/10/20152015 - Miikka Dal Maso
What is needed for urban aersol
measurement?
2015 - Miikka Dal Maso
Requirements for urban aerosol
physical characterization:
• small and large particles,
number and volume (mass)
• high time resolution
• high spatial density of
measurement sites – low price
• low maintenance
Understanding of physics and
chemistry, and sources
Gathering and analysis of
heterogeneous urban-scale
data
6/10/2015
Image: ENFUSER example
In urban areas, pollutants are not
distributed evenly, and concentrations
depend on source proximity
6
China Testbed instrument: Pegasor PPS-
M sensor
6/10/20152015 - Miikka Dal Maso
Diffusion charger based aerosol
sensors (e.g. Pegasor PPS-M) are
good fit for presented requirements:
• Affordable, small, robust,
repeatable, easy to use
• potential for extracting size-
dependency information
• number and mass
• can cover wide size range
7
• Overview
– Diffusion charging
+ electrical detection
– Non-collective instrument
– Applications: Emissions,
air quality, portable systems...
• Components
– Pre-cut cyclone
– Ion source
– Charging region
– Ejector pump
– Mobility analyser
8
PPS-M sensor
Sample inlet
Sensor exhaust
Pressurized
air inlet
6/10/20152015 - Miikka Dal Maso
Calibration of PPS-M at TUT
2015 - Miikka Dal Maso 9
Aim of calibration is to find response function by particle size and
mobility analyser voltage
CPC is the reference
instrument which
has been calibrated
electrically
CPC is used
because neutral
particles are
preferred in charger
calibrations
Rostedt et al. 2014
Electrically neutral
particles
6/10/2015
Developed PPS-M response function
6/10/20152015 - Miikka Dal Maso
Overall response Polydisperse test
   Out p p pS R d N d dd 
Rostedt et al., 2014
Optimal size response for combustion
originating particles
Charging efficiency, mobility analyzer,
diffusion, inertial losses
         , , ,p ma ch p ma ma p ma d p i pR d V E d V P d V P d P d
10
Field measurements with PPS-M in
Finland
6/10/20152015 - Miikka Dal Maso
Number
concentration
PPS-M shows good correlations with PM2.5 in residential area and roadside,
and also good number correlations.
China testbed research question: Can we get more information?
Järvinen et al, 2014
PM2.5 Mass
concentration
11
Field measurements with PPS-M in China
6/10/20152015 - Miikka Dal Maso
Server in
China
Server in
Finland
Pressurized airDroplet separation
PPS
internal
heating
Insulation
Inlet heating
• PPS-M sensor installed at the CRAES
measurement station
• Continuous measurements from Feb-
Nov 2014
• Comparisons with long-term
observations of performed at CRAES
• Data logged locally and transferred via
network
• Data covers many different situations of
polluted urban air
Gao, Dal Maso et al.,
2015 (in prep)
PPS-M Number and Mass response in
highly polluted air
6/10/20152015 - Miikka Dal Maso
PPS-M response dependency on
mobility analyser voltage can be used
to gain information on the mass-
number relationship.
We have used measurements in
Beijing to test the mobility analyser in
real polluted megacity air.
Signal ratio
Mass/Numberratio
Reference
PPS-M fit w/
mobility analyser
voltage cycling
VolumeNumber
Gao, Dal Maso et al., 2015 (in prep)
Summary
• We need good concentration
measurements covering urban city
environment
• Diffusion charging based sensors such as
PPS-M fulfill many requirements for
sensors
• We have developed a sensor response
model for size and mobility analyzer
dependence which has been verified by
laboratory measurements
• In outdoor measurements in Finland and
China we could get both mass and number
information. Mobility analysis was added
for measurements in China
6/10/20152015 - Miikka Dal Maso 14
Thank you for your attention
6/10/20152015 - Miikka Dal Maso
1. Rostedt, A., Arffman, A., Janka, K., Yli-Ojanperä, J. &
Keskinen, J. (2014) Characterization and Response
Model of the PPS-M Aerosol Sensor, Aerosol Science and
Technology, 48(10), p. 1022-1030, DOI:
10.1080/02786826.2014.951023
2. Järvinen A., Kuuluvainen H., Niemi J.V., Saari S., Dal Maso
M., Pirjola L., Hillamo R., Janka K., Keskinen J., Rönkkö T.
(2014). Monitoring urban air quality with a diffusion charger
based electrical particle sensor, Urban Climate 10,
doi:10.1016/j.uclim.2014.10.002
3. Gao, J,., Järvinen, A., Hui, L., Luo, D., Rönkkö, T., and Dal
Maso, M. (2015): Urban air quality measurements in
Beijing using a diffusion charger based electrical particle
sensor, in preparation
References
15

Measuring megacity air by Miikka Dal Maso and Craes

  • 1.
    Measuring megacity air MiikkaDal Maso1, Anssi Järvinen1, Antti Rosted1, Jian Gao2, Topi Rönkkö1 1Tampere University of Technology, Tampere, Finland 2CRAES, Beijing, China
  • 2.
    Improving urban airquality – a challenge on many fronts 2015 - Miikka Dal Maso Understanding and improving urban air quality requires a holistic approach in which all critical aspects are taken into account. At TUT, our focus is measuring emissions and concentrations and modeling transformation at high scientific quality. 6/10/2015 TUT FOCUS TUT FOCUS Roadmap to Beautiful Beijing/Beautiful China 2
  • 3.
    Challenges of measuringaerosol in (mega)cities Particle Diameter (nm) 1 10 100 1000 107 105 103 101 10000 Sulfuric Acid Organic Nitrate Carbonaceous Sulfate Sea Sal Mineral 2015 - Miikka Dal Maso Urban PM, with multiple source components, also exhibits high physical and chemical complexity 6/10/2015 Example of urban aerosol complexity: Beijing size distribution data shows six different typical size distributions. Half the time, more than 50% of particles are <50 nm. Beijing Particle size Particlenumber(norm.) Gao, Dal Maso et al, in prep. 3
  • 4.
    TUT researches cityaerosol on several fronts 6/10/20152015 - Miikka Dal Maso 1. Targeted urban measurements 2. Instrument development 4. Process studies - modeling3. Fresh and aged emission measurements 4
  • 5.
    MMEA (Measurement, Monitoringand Environmental Efficiency Assessment) aerosol reseach environment 5 • Measurement methods, instrument development • Calibrations, field tests • Emission studies • Data intercomparisons • Air quality studies 6/10/20152015 - Miikka Dal Maso
  • 6.
    What is neededfor urban aersol measurement? 2015 - Miikka Dal Maso Requirements for urban aerosol physical characterization: • small and large particles, number and volume (mass) • high time resolution • high spatial density of measurement sites – low price • low maintenance Understanding of physics and chemistry, and sources Gathering and analysis of heterogeneous urban-scale data 6/10/2015 Image: ENFUSER example In urban areas, pollutants are not distributed evenly, and concentrations depend on source proximity 6
  • 7.
    China Testbed instrument:Pegasor PPS- M sensor 6/10/20152015 - Miikka Dal Maso Diffusion charger based aerosol sensors (e.g. Pegasor PPS-M) are good fit for presented requirements: • Affordable, small, robust, repeatable, easy to use • potential for extracting size- dependency information • number and mass • can cover wide size range 7
  • 8.
    • Overview – Diffusioncharging + electrical detection – Non-collective instrument – Applications: Emissions, air quality, portable systems... • Components – Pre-cut cyclone – Ion source – Charging region – Ejector pump – Mobility analyser 8 PPS-M sensor Sample inlet Sensor exhaust Pressurized air inlet 6/10/20152015 - Miikka Dal Maso
  • 9.
    Calibration of PPS-Mat TUT 2015 - Miikka Dal Maso 9 Aim of calibration is to find response function by particle size and mobility analyser voltage CPC is the reference instrument which has been calibrated electrically CPC is used because neutral particles are preferred in charger calibrations Rostedt et al. 2014 Electrically neutral particles 6/10/2015
  • 10.
    Developed PPS-M responsefunction 6/10/20152015 - Miikka Dal Maso Overall response Polydisperse test    Out p p pS R d N d dd  Rostedt et al., 2014 Optimal size response for combustion originating particles Charging efficiency, mobility analyzer, diffusion, inertial losses          , , ,p ma ch p ma ma p ma d p i pR d V E d V P d V P d P d 10
  • 11.
    Field measurements withPPS-M in Finland 6/10/20152015 - Miikka Dal Maso Number concentration PPS-M shows good correlations with PM2.5 in residential area and roadside, and also good number correlations. China testbed research question: Can we get more information? Järvinen et al, 2014 PM2.5 Mass concentration 11
  • 12.
    Field measurements withPPS-M in China 6/10/20152015 - Miikka Dal Maso Server in China Server in Finland Pressurized airDroplet separation PPS internal heating Insulation Inlet heating • PPS-M sensor installed at the CRAES measurement station • Continuous measurements from Feb- Nov 2014 • Comparisons with long-term observations of performed at CRAES • Data logged locally and transferred via network • Data covers many different situations of polluted urban air Gao, Dal Maso et al., 2015 (in prep)
  • 13.
    PPS-M Number andMass response in highly polluted air 6/10/20152015 - Miikka Dal Maso PPS-M response dependency on mobility analyser voltage can be used to gain information on the mass- number relationship. We have used measurements in Beijing to test the mobility analyser in real polluted megacity air. Signal ratio Mass/Numberratio Reference PPS-M fit w/ mobility analyser voltage cycling VolumeNumber Gao, Dal Maso et al., 2015 (in prep)
  • 14.
    Summary • We needgood concentration measurements covering urban city environment • Diffusion charging based sensors such as PPS-M fulfill many requirements for sensors • We have developed a sensor response model for size and mobility analyzer dependence which has been verified by laboratory measurements • In outdoor measurements in Finland and China we could get both mass and number information. Mobility analysis was added for measurements in China 6/10/20152015 - Miikka Dal Maso 14
  • 15.
    Thank you foryour attention 6/10/20152015 - Miikka Dal Maso 1. Rostedt, A., Arffman, A., Janka, K., Yli-Ojanperä, J. & Keskinen, J. (2014) Characterization and Response Model of the PPS-M Aerosol Sensor, Aerosol Science and Technology, 48(10), p. 1022-1030, DOI: 10.1080/02786826.2014.951023 2. Järvinen A., Kuuluvainen H., Niemi J.V., Saari S., Dal Maso M., Pirjola L., Hillamo R., Janka K., Keskinen J., Rönkkö T. (2014). Monitoring urban air quality with a diffusion charger based electrical particle sensor, Urban Climate 10, doi:10.1016/j.uclim.2014.10.002 3. Gao, J,., Järvinen, A., Hui, L., Luo, D., Rönkkö, T., and Dal Maso, M. (2015): Urban air quality measurements in Beijing using a diffusion charger based electrical particle sensor, in preparation References 15

Editor's Notes

  • #3 Places with cars have more particles than places with no cars. Here’s an example, if we look at typical