Carbon Monoxide Lecture
AOSC 637
Atmospheric Chemistry
Russell R. Dickerson
Finlayson-Pitts Chapt. 16
Seinfeld Chapt. 2 & 6
Wallace & Hobbs Chapt. 5
EPA 2000 Criteria Document: http://www.epa.gov/NCEA/pdfs/coaqcd.pdf
EPA 2010 ISA: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=218686
OUTLINE
Importance
Detection Techniques
Sources and Sinks
Global Chemistry & Trends
Remaining Challenges
References
Copyright © 2010 R.R. Dickerson
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Carbon Monoxide
Importance
• Primary Air Pollutant
• Major sink for OH (greenhouse forcing, esp. short term!)
Thompson et al. (1989); Shindell et al. (2009); Hoor et al. (2009)
• Source/Sink of O3 depending on NOx
• Toxic air pollutant
Esp. for individuals with Coronary Artery Disease (EPA 2010)
• Excellent tracer for combustion and dynamics.
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In the remote atmosphere there is often insufficient NOx to drive this
reaction to two O3; the process reduces OH. Globally, Thompson et
al. (1989) predict that increased CO increases H2O2 and the ratio of
HO2 to OH, but reduces OH. Reduced OH means a longer lifetime
for CH4 and O3 which contribute to global warming, e.g., Shindell et
al., (2009); EPA (2010)
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Chemistry
Carbon monoxide oxidation in a clean environment:
(1) O3 + h  O2 + O(1D)
(2)
O(1D) + H2O  2OH
(3) OH + O3  HO2 + O2
(4) HO2 + O3  2O2 + OH
----------------------------------------(3+4)
2O3  3O2
NET
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Chemistry, continued
Carbon monoxide oxidation in a dirty (polluted)
environment:
(3')
OH + CO  H + CO2
(4') H + O2 + M  HO2 + M
(5') HO2 + NO  NO2 + OH
(6')
NO2 + h  NO + O
(7')
O + O2 + M  O3 + M
------------------------------------------------Dickerson+ O
(3'-7') CO Copyright
+ 2 O©22010R.R.CO
2
3
NET
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Detection Methods
• GC-FID
• Hg Liberation (CO + HgO → CO2 + Hg↑)
• Gas Filter Correlation NDIR
• FTIR
• Fluorescence
• Tunable Diode Laser Spectroscopy
• Remote sensing NDIR
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Non-Dispersive Gas-Filter Correlation
Detection of Carbon Monoxide
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Tunable Diode Laser Spectroscopy: Schematic Diagram
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A TDL can be finely tuned to the
precise wavelength that
characterizes whatever chemical
its users wish to detect. By
measuring how much light has
been absorbed, the TDL-based
detector can determine how
much carbon monoxide is
present. The laser is tuned on
and off a single rotational line
around 4.6 mm to generate an
AC signal. The signal is most
easily seen as the second
derivative.
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MOPITT (Measurement of Pollution in the Troposphere):
MOPITT is the first satellite
sensor to use gas
correlation spectroscopy.
GCS is a non-dispersive
technique to increase the
sensitivity of the instrument
to the gas of interest by
separating out the regions
of the spectrum where the
gas has absorption lines
and integrating the signal
from just those regions.
The specific wavelengths
are located using a sample
of the gas as a reference
for the spectrum. By using
correlation cells of differing
pressures, some height
resolution can be obtained.
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MOPITT (Measurement of Pollution in the Troposphere)
http://terra.nasa.gov/
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MOPITT CO image
from EPA ISA.
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Geostationary Remote Infrared Pollution Sounder
[GRIPS]
Science Overview
GRIPS will measure columns of CO2, CH4, and CO with high accuracy and
sensitivity down to the surface. From geostationary orbit over Asia where no
wide-scale monitoring of these key pollutants and greenhouse gases currently
exists we will determine sources and fluxes. Asia is a large but uncertain source
CO as seen from Geo at 120oE
of these gases.
CO: Toxic. Emissions of pollutants such as NOx, SO2, and aerosols can be estimated from ratios
to CO. Plumes from Asia travel across the Pacific and have large-scale adverse impacts.
CH4: A major greenhouse gas that affects the oxidizing capacity of the atmosphere and
tropospheric ozone
CO2: The key greenhouse gas; Asian sources large and changing rapidly.
Key to understanding fluxes will the the ratios of trace gas species which provide unique fingerprints. GRIPS
can distinguish sources of pollution
using ratios of CO2/CO and
Power Generation
Biomass
Vehicles
CO2/CH4. Industrial and
burning
residential sources can be further
distinguished using data from a
GRIPS
UV/Vis spectrometer such as
alone
Estimated CO2 Source Regions
GEMS that measures SO2, NO2,
CO/BC*
and Black Carbon.
CO/NO2
E+02
E+01
E+00
CO2/CO
E+03
CO2/CH4
E+04
CO2/CO
CO2/CH4
for
Power GeneraFingerprints
on
Vehicles
Major
Chinese
Emission Sources
Biomass
Burning
E+03
E+02
CO/SO2
0E+01
E+00
SO2/NO2
0E-01
0E-02
Power Genera
on
Industry
Industry
Residential
Residen
al
Vehicles
Biomass Burning
GRIPS
+
GEMS
* Black Carbon
Total
PI: Prof. Russell Dickerson
U of MD
russ@atmos.umd.edu
Geostationary Remote Infrared Pollution Sounder
[GRIPS]
Instrument Overview
GRIPS uses the well-understood gas filter correlation radiometry (GFCR) technique. GFCR, used by a
number of satellite instruments including HALOE and MOPITT, employs tubular cells containing the target
gas as a filter. These eliminate the need for a dispersive element, while providing outstanding spectral
resolution, resulting in column concentrations of CO2, CH4, CO with sensitivity down to the surface and
some altitude resolution in the troposphere. Our GFCR will use reflected solar IR for CO2 and CH4 and both
solar and thermal IR for CO. Nadir pixel size is ~4x4 km.
Species
Instrument
30 cm
Bundle
20 cm
Wavelength (µm)
CO2
2.05
-
CH4
2.28
-
CO
2.33
4.64
The GRIPS Instrument
Mass: 13 kg
Power: 15W
Data Rate: 6.5 Gbits/day
Volume: 0.012 m3
Nadir pixel: 8 km2
Continental scan: 1 hour
Disk scan: 2 hours
20 cm
To measure each species, light is brought through a 4 telescope bundle hosting gas cells at different pressures. Light is then concentrated to a
4 partition cooled MerCadTel detector using a pyramidal mirror. In the instrument configuration shown, one bundle is for CH 4, one for CO2
CO/NOX
CO2/CO
CO2/CH4
CO/SO2
Sources
Natural: Methane oxidation. Biogenic hydrocarbon (esp. isoprene) oxidation.
Direct emission from plants and oceans, although plants may absorb CO as well
as emit it. In any case, only direct emission is small relative to HC oxidation.
Anthropogenic: Internal combustion engines emit CO, especially when they run
rich. Even at a stoichiometric air/fuel mixture, CO is produced because of hightemperature dissociation of CO2.
CO2 → CO + ½O2
CO + ½O2 → CO2
H = -67.6
Coal combustion does not generate much CO because the power plants run
lean in order to extract as much energy from the coal as possible. Biomass
burning is a major source, as is oxidation of anthropogenic hydrocarbons in the
presence of NOx.
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American CO Emissions 2008
MISCELLANEOUS
17%
c
OFF-HIGHWAY
26%
HIGHWAY VEHICLES
57%
Direct anthropogenic emissions only, based on the
Copyright © 2010 R.R. Dickerson
Mobile6 model.
(EPA, 2009)
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Trend in American CO Emissions
Thousands of tons per year
250000
200000
150000
100000
50000
0
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
Year
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Comparison of observed (jagged red line) and modeled morning CO vertical
profiles paired in time and space over Mid Atlantic region. The solid lines
are the medians, and the shaded areas represent the 25th and 75th
quartiles of the data. The blue line corresponds to modeled CO with the
deposition velocity calculated in MCIP v3.4.1, and the green line
corresponds to modeled CO with the deposition velocity set to zero. The
total CO column below 1000 m is closer to observations when the CO
deposition velocity is set to zero, but the shape of the vertical profile does
not change substantially (Castellanos et al., 2010).
Copyright © 2010 R.R. Dickerson
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Copyright © 2010
. Same as previous figure
except comparison of
observed and modeled
afternoon CO vertical
profiles. The top graph
corresponds to
observations of poorly
mixed air near the surface
(51 profiles). The bottom
graph corresponds to
observations of well mixed
air near the surface (21
profiles). The local
maximum observed around
2000 m cannot be produced
by diffusive processes, but
may be generated by smallscale convective processes
such as those associated
with fair weather cumulus
clouds.
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Model Performance of CO in CMAQ
Turbulent transport is modeled with an
eddy diffusion coefficient (Kz, m2/s)
ci
t
VDIFF
ci


Kz
z
z
Analogous to molecular diffusivity
K
Turbulent
z may be
overestimated
mixing
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Model Performance of CO in CMAQ
Convective Transport
Afternoon Well Mixed
Asymmetric
Convective
Model
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Model Performance of CO in CMAQ
Convective Transport
Underestimated
Afternoon Poorly Mixed
Fast turbulent
mixing near
the surface
Copyright © 2010 R.R. Dickerson
High resolution WRF-UCM and
CMAQ modeling
Christopher P. Loughner1, Dale J. Allen1, Russell R. Dickerson1,
Kenneth E. Pickering1,2 Yi-Xuan Shou3, and Da-Lin Zhang1
1Department
of Atmospheric and Oceanic Science, University of
Maryland, College Park, MD
2NASA Goddard Space Flight Center, Greenbelt, MD
3National Satellite Meteorological Center, China Meteorological
Administration, Beijing, China
MDE Quarterly Meeting
April 25, 2011
Introduction
• Investigate the influence of grid resolution on the
Chesapeake Bay breeze, the dispersion of
pollutants, and ozone formation.
• The Chesapeake Bay breeze influences:
–
–
–
–
Horizontal advection;
Convergence;
Stagnation; and
Vertical transport
WRF-UCM 2-m temperature and 10-m wind speed
at 1200 UTC (7 am EST) July 9, 2007. Westerly
winds in the 13.5 and 0.5 km simulations
transporting near surface pollutants over the
Chesapeake Bay.
WRF-UCM 2-m temperature and 10-m wind speed
at 1400 UTC (9 am EST) July 9, 2007. Stagnation
in northern end of Chesapeake Bay in the 0.5 km
simulation causes pollutants to accumulate.
WRF-UCM 2-m temperature and 10-m wind speed
at 1900 UTC (2 pm EST) July 9, 2007. A stronger
temperature gradient along the coastline of the
Chesapeake Bay in the 0.5km domain results in a
stronger Bay breeze.
Ozone
concentrations
at 1900 UTC (2
pm EST) July 9,
2007. Early
morning
stagnation over
the Chesapeake
Bay allowed high
ozone
concentrations
to be transported
northward in the
higher resolution
simulations.
Cross-section of CO between Washington, DC and
Baltimore, MD for the 13.5 and 0.5km simulations.
The stronger bay breeze in the 0.5km simulation
causes higher pollutant concentrations at the bay
breeze convergence zone where they are lofted and
then transported downwind.
coastline
13.5km
coastline
0.5km
Profiles near western shore
coastline
CO
O3
Edgewood profiles
Edgewood profiles
Edgewood profiles
Edgewood profiles
Edgewood profiles
Edgewood profiles
Edgewood profiles
Conclusions
• The Chesapeake Bay breeze causes:
– Stagnation and accumulation of pollutants in
the bay;
– Convergence of pollutants at the bay breeze
convergence zone; and
– Lofting of pollutants at the bay breeze
convergence zone.
The global distribution
of CO reflects the
dominance of
emissions in the
Northern Hemisphere,
the seasonal cycle of
OH, and the short
lifetime relative to
transport across the
ITCZ.
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From the NOAA CMDL Trends Network Available almost real time.
http://www.esrl.noaa.gov/gmd/ccgg/iadv/
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Remaining Challenges related to CO in the atmosphere
How accurate are the emissions from Mobile6?
Finlayson-Pitts, in Ch. 16 of her 2000 book, pointed out that
emissions were a problem. Things do not seem much better today.
Parrish (2006) “Mobile6 too high by factor of 2”
Castellanos et al., (2010) “About right (+/-10%)”
Yu et al., 2007, 2009 “20-30% low bias except NYC high bias”
Marmur et al., (2009) “a 36% low bias”
Kuhns et al. (2004) “factor of ~2 too high for gasoline-powered
vehicles”
Bishop and Stedman [2008] “deterioration rate of control technology in
motor vehicles was overestimated by a factor of five”
Hudman et al. [2008] and Warneke et al. [2006] “modeled CO
anthropogenic emissions are 50-60% too high.”
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CO/NOx ratio from observations indicates a ratio of ~6:1 (Luke et al., 2010).
Emissions inventories (http://www.epa.gov/ttnchie1/trends/) indicate a ratio of
12:1.
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References
Bishop, G. A. and D. H. Stedman (2008), A decade of on-road emissions measurements, Environmental Science & Technology,
42, 1651-1656.
Castellanos, P., L. T. Marufu, B. G. Doddridge, B. F. Taubman, S. H. Ehrman, and R. R. Dickerson (2010), Evaluation of Vertical
Mixing and Emissions in the CMAQ Model Using Measured Vertical Profiles of CO and O3, J. Geophys. Res., in preparation.
Hoor, P., J. Borken-Kleefeld, D. Caro, O. Dessens, O. Endresen, M. Gauss, V. Grewe, D. Hauglustaine, I. S. A. Isaksen, P. Jockel,
J. Lelieveld, G. Myhre, E. Meijer, D. Olivie, M. Prather, C. S. Poberaj, K. P. Shine, J. Staehelin, Q. Tang, J. van Aardenne, P.
van Velthoven, and R. Sausen (2009), The impact of traffic emissions on atmospheric ozone and OH: results from
QUANTIFY, Atmospheric Chemistry and Physics, 9, 3113-3136.
Hudman, R. C., L. T. Murray, D. J. Jacob, D. B. Millet, S. Turquety, S. Wu, D. R. Blake, A. H. Goldstein, J. Holloway, and G. W.
Sachse (2008), Biogenic versus anthropogenic sources of CO in the United States, Geophysical Research Letters, 35.
Hudman, R. C., L. T. Murray, D. J. Jacob, S. Turquety, S. Wu, D. B. Millet, M. Avery, A. H. Goldstein, and J. Holloway (2009),
North American influence on tropospheric ozone and the effects of recent emission reductions: Constraints from ICARTT
observations, Journal of Geophysical Research-Atmospheres, 114, DOI: 10.1029/2008JD010126
Kuhns, H. D., C. Mazzoleni, H. Moosmuller, D. Nikolic, R. E. Keislar, P. W. Barber, Z. Li, V. Etyemezian, and J. G. Watson (2004),
Remote sensing of PM, NO, CO and HC emission factors for on-road gasoline and diesel engine vehicles in Las Vegas, NV,
Science of the Total Environment, 322, 123-137, DOI: 10.1016/j.scitotenv.2003.09.013
Luke, W. T., P. Kelley, B. L. Lefer, and M. Buhr (2010), Measurements of primary trace gases and NOy composition in Houston,
Texas, Atmospheric Environment, in press, DOI: 10.1016/j.atmosenv.2009.08.014.
Marmur, A., W. Liu, Y. Wang, A. G. Russell, and E. S. Edgerton (2009), Evaluation of model simulated atmospheric constituents
with observations in the factor projected space: CMAQ simulations of SEARCH measurements, Atmospheric Environment,
43, 1839-1849, DOI: 10.1016/j.atmosenv.2008.12.027.
Novelli, P. C., K. A. Masarie, P. M. Lang, B. D. Hall, R. C. Myers, and J. W. Elkins (2003), Reanalysis of tropospheric CO trends:
Effects of the 1997-1998 wildfires, Journal of Geophysical Research-Atmospheres, 108.
Parrish, D. D. (2006), Critical evaluation of US on-road vehicle emission inventories, Atmospheric Environment, 40, 2288-2300.
Shindell, D. T., G. Faluvegi, D. M. Koch, G. A. Schmidt, N. Unger, and S. E. Bauer (2009), Improved Attribution of Climate Forcing
to Emissions, Science, 326, 716-718.
Thompson, A. M., R. W. Steward, M. A. Owens, and J. A. Herwehe (1989), Sensitivity of tropospheric oxidants to global chemical
and climate change, Atmos. Environ., 23, 519-532.
Warneke, C., J. A. de Gouw, A. Stohl, O. R. Cooper, P. D. Goldan, W. C. Kuster, J. S. Holloway, E. J. Williams, B. M. Lerner, S. A.
McKeen, M. Trainer, F. C. Fehsenfeld, E. L. Atlas, S. G. Donnelly, V. Stroud, A. Lueb, and S. Kato (2006), Biomass burning
and anthropogenic sources of CO over New England in the summer 2004, Journal of Geophysical Research-Atmospheres,
111, DOI: 10.1029/2005JD006878.
Yu, S. C., R. Mathur, D. W. Kang, K. Schere, and D. Tong (2009), A study of the ozone formation by ensemble back trajectoryprocess analysis using the Eta-CMAQ forecast model over the northeastern US during the 2004 ICARTT period,
Atmospheric Environment, 43, 355-363.
Yu, S. C., R. Mathur, K. Schere, D. W. Kang, J. Pleim, and T. L. Otte (2007), A detailed evaluation of the Eta-CMAQ forecast
model performance for O-3, its related precursors, and meteorological parameters during the 2004 ICARTT study, Journal of
Geophysical Research-Atmospheres, Copyright
112.
© 2010 R.R. Dickerson
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Take Home Messages
• Carbon Monoxide is a relatively well understood
trace gas with important roles in human health,
the oxidizing capacity of the atmosphere and in
global climate.
• CO is a useful tracer for dynamical processed in
the atmosphere such as convective mixing.
• The uncertainty in the emissions is larger than
can be explained by measurement uncertainty.
Copyright © 2010 R.R. Dickerson
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