Evaluating emissions from top-down observations

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Evaluating emissions from top-down
observations T. Ryerson NOAA Chemical Sciences
Division Motivation Most inventories compiled
from bottom-up estimates, where reported data
from many individual sources are summed an
enormous undertaking regulatory / legal
baggage independent assessments are needed to
evaluate accuracy Emissions routinely change
over all time scales hours - power plant loads -
30 days - urban mobile fleet mix - 50 years -
response to control strategies - up to 80
Accurate inventory input is critical for models
(AQ, Carbon Cycle, Climate).

difficult, and slow, to update
Evaluation methods and selected examples Power
plant NOx, petrochemical VOCs, ship BC, oil gas
CH4 (biogenics covered in other presentations
today)
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Top-down methods for inventory assessment power
plant NOx, SO2, CO, CO2 Emission ratios derived
from field data snapshots agree with continuous
emission monitoring systems (CEMS) at power plants
W.A. Parish power plant plume 1-Hz aircraft data
Method accuracy ratios are within 5 of
CEMS Peischl et al., JGR (submitted) absolute
emissions within 30 Ryerson et al., JGR
(1998), Science (2001) - apply top-down
approach to wider variety of sources with
reasonable confidence
W.A. Parish emission estimates compared
NOx/CO2
SO2/CO2 observed slope 0.24 0.03 1.9
0.3 CEMS inventory 0.20 1.9
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Top-down methods for inventory assessment urban
CO Urban CO emissions overestimated in US
national inventory
NOAA WP-3D aircraft data flight track scaled by
measured CO
NOAA Tall Tower Network data 457m level, KWKT
tower, Waco, TX
Additional data, analysis A. Andrews, NOAA
GMD Flexpart model A. Stohl, NILU
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Top-down methods for inventory assessment urban
CO Urban CO emissions overestimated in US
national inventory
NOAA WP-3D aircraft data flight track scaled by
measured CO
NOAA Tall Tower Network data 457m level, KWKT
tower, Waco, TX
Additional data, analysis A. Andrews, NOAA
GMD Flexpart model A. Stohl, NILU
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Top-down methods for inventory assessment urban
CO Urban CO emissions overestimated in US
national inventory
NOAA WP-3D aircraft data flight track scaled by
measured CO
NOAA Tall Tower Network data 457m level, KWKT
tower, Waco, TX
field project inventory snapshots very
similar to data from longer-term monitoring
top-down assessments are critical for both
carbon cycle - determining biospheric CO2
uptake using tall-tower data requires accurate
knowledge of urban CO/CO2 signatures
Additional data, analysis A. Andrews, NOAA
GMD Flexpart model A. Stohl, NILU
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Top-down methods for inventory assessment
petrochemical industry Errors in petrochemical
VOC inventories persist in Houston
Ethene flux from the Freeport petrochemical
complex
Measurement TCEQ inventory
Top-down methods point to large (factor of 30)
underestimates of alkene emissions from
petrochemical industries in Houston, TX in 2000
and 2006
Ryerson et al., JGR (2003) de Gouw et al., EST
(2009) Washenfelder et al., JGR (submitted).
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Top-down methods for inventory assessment
petrochemical industry Errors in petrochemical
VOC inventories persist in Houston
Ethene flux from the Freeport petrochemical
complex
Measurement TCEQ inventory
Top-down methods point to large (factor of 30)
underestimates of alkene emissions from
petrochemical industries in Houston, TX in 2000
and 2006
These alkenes dominate the most extreme (gt150
ppbv) ozone exceedances
Ryerson et al., JGR (2003) de Gouw et al., EST
(2009) Washenfelder et al., JGR (submitted).
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Top-down methods for inventory assessment
petrochemical industry Errors in petrochemical
VOC inventories persist in Houston
Gaussian plume model
WRF-Chem 3D model
70
Sweeny
Freeport
Reported VOC emissions Increased
alkene emissions
60
Ozone (ppbv)
50
40
30
3D model and analysis Grell, Bao, McKeen - NOAA
GSD and CSD
-96.0
-95.8
-95.6
-95.4
longitude (deg)
Gaussian model and analysis M. Trainer - NOAA CSD
Models realistically simulate observations of
ozone and other photoproducts only after
reactive VOC emissions are made consistent with
top-down assessments State of Texas changed
its emissions control strategy as a result of
these findings
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Top-down methods for inventory assessment -
shipping
Soot emission factors vary by a factor of
3 between marine engine types Soot emission
dependencies on engine load and fuel quality are
not well established
Observed variability suggests using a single
value in large-scale models will hamper
the understanding of regionality of soot
forcings and exposure
Lack et al., GRL (2008).
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Top-down methods for inventory assessment oil
gas extraction
NASA DC-8 data from ARCTAS April 2008
EDGAR 3.2 (2000 reporting year) US/Canadian
Arctic total 0.4 Tg CH4/year
32 million cubic feet per day 0.3 Tg CH4 per
year)
Prudhoe Bay plume
Prudhoe Bay includes the worlds largest
gas-handling facility, and is the single largest
CH4 source in the EDGAR oil production sector
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Top-down methods for inventory assessment oil
gas extraction
2000
EDGAR inventories for 2000 and 2005 show
1000-fold differences for Prudhoe Bay
Emissions unlikely did not not
change substantially between these two
years Working with EDGAR inventory teams to
resolve these issues a direct comparison is on
hold
2005
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Top-down methods for inventory assessment Conclusi
ons
Tabulated inventories can be substantially in
error, by factors of 2 to 10 or more, for many
important chemical species from many of the
largest source types. - continuing need for
top-down, independent assessment of
inventories Bottom-up inventories appear to
be accurate to 25 or better only if directly
measured monitoring data are routinely available
(e.g., point source CEMS) Errors are
sufficiently large to confound development of
scientifically sound control strategies based
on anthropogenic emissions reductions. -
relevant to air quality, carbon cycle, and
climate issues