on network design for the detection of urban greenhouse gas emissions: results from the indianapolis...
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![Page 1: On network design for the detection of urban greenhouse gas emissions: Results from the Indianapolis Flux Experiment (INFLUX) Natasha Miles 1, Marie Obiminda](https://reader035.vdocuments.mx/reader035/viewer/2022062714/56649d025503460f949d58dc/html5/thumbnails/1.jpg)
On network design for the detection of urban greenhouse gas emissions: Results from the
Indianapolis Flux Experiment (INFLUX)
Natasha Miles1, Marie Obiminda Cambaliza2, Kenneth Davis1, Michael Hardesty3, Laura Iraci4, Kevin Gurney5, Anna Karion3, Thomas Lauvaux1, Laura McGowan1, Scott Richardson1, Daniel Sarmiento1, Paul Shepson2,
Colm Sweeney3, Jocelyn Turnbull6, James Whetstone7
1. The Pennsylvania State University, 2. Purdue University, 3. NOAA/ESRL4. NASA/JPL, 5. Arizona State University, 6. GNS Science, 7. NIST
ICDC9 Beijing 7 June 2013
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INFLUX motivation
• Emissions mitigation will happen at local and regional scales.
• Validation of emissions mitigation will(?) require (independent) measurements
• Atmospheric GHG measurements have the potential to provide such independent emissions estimates.
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• Develop improved methods for determination of urban area-wide emissions, and spatially and temporally-resolved fluxes of greenhouse gases, specifically, CO2 and CH4.
• Determine and minimize the uncertainty in the emissions estimate methods.
INFLUX objectives
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• Inventory estimates of sector-by-sector emissions at high spatial resolution
• Periodic aircraft flights with CO2, CH4, and flask samples - Whole city flux estimates
• Periodic automobile surveys of CO2 and CH4 – Emissions from strong point sources (power plants, landfill, gas leaks)
• 12 surface towers measuring CO2, 5 with CH4, and 5 with CO & Mesoscale atmospheric inversion - Spatially and temporally resolve GHG emissions
• 5 automated flask samplers from NOAA – Identify sectoral emissions• TCCON-FTS for 4 months (Sept-Dec 2012)• 4 eddy-flux towers from natural to dense urban landscapes – Model
assessment (June 2013)• Doppler lidar (installed late April 2013)• Tracer release experiment (planned August 2013)
INFLUX methodology: Simultaneous application of multiple methods
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Vulcan and Hestia Emission Inventories / Models
Vulcan – hourly, 10km resolution for USA
Hestia: high resolution emission data for the residential, commercial, industrial, transportation and electricity production sectors. http://hestia.project.asu.edu/
250m res - Indy
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INFLUX observational results to date:Aircraft and automobiles
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Aircraft mass balance approach: 1 June 2011 Flight path
Cambaliza et al, in prep
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22,000 moles s-1 203 moles s-1
1 June 2011 Results Cambaliza et al, in prep
8 ppm CO2 50 ppb CH4
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Cambaliza et al, in prep
• Aircraft mass balance: uncertainty based on measurements of plume at different distances from source: 40%
• More day-to-day variability in mass balance results
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CO2 Emissions: Aircraft mass balance vs Hestia inventory
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WWTP
Landfill
Drive-arounds: Separation/quantification of CH4 sources
Instrumentedsurface vehicles toidentify and quantify individual sources.
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INFLUX observational results to date:Ground-based measurements
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INFLUX ground-based instrumentationP
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A a
utom
ated
fla
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ampl
ers;
C
omm
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atio
ns t
ower
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100
m A
GL
10 km
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• NOAA 1 hour integrated flask samples• Mean value in-situ - flask:
CO2: 0.09 ppm CH4: 0.6 ppb CO: -4.1 ppb
• Within WMO recommendations (urban)
In-situ – flask comparisonat 5 INFLUX sites
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Flask results: C14
ICDC9 Poster 224: Turnbull et al.
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Tower in-situ results / Mesoscale atmospheric inversion system
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Mesoscale modeling system
• WRF-Chem running with:– 3 nested domains (9/3/1 km resolution),
inner domain: 87x87 km2
– Meteorological data assimilation– Hestia anthropogenic fluxes for the inner domain– Vulcan anthropogenic fluxes for the outer domains– Carbon Tracker posterior biogenic fluxes– Carbon Tracker boundary conditions
• Lagrangian Particle Dispersion Model • Bayesian matrix inversion
T. Lauvaux
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Gain – relative improvement prior vs. posterior
Very good system performance within the tower array.
Very idealized case, but encouraging nonetheless.
1 = perfect correction to prior fluxes
Flux units: gC m-2 hr-1.
Inversion system test
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Influence functions: INFLUX• “Influence
function” – the areas that contribute to GHG concentrations at measurement points
• 12 towers in 87 x 87 km2 domain
• Strategy: oversampling (?)
Contour: Hestia residential sector
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Sectoral atmospheric mole fractions, tower by tower
Winter mean mole fractions6 of 12 tower sites
Mid
day
AB
L m
ixin
g ra
tio (
ppm
)
mobileindustcommer resid powerplant
Site 1: backgroundSite 2: downwindSite 10: powerplant!
Some structure across towers by sector
Site 1
Site 10
25
79
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Comparison of [CO2] at INFLUX sites
• Afternoon [CO2] with 21-day smoothing
• Site 03 (downtown): high [CO2]
• Site 09 (rural site to the east of the city): low [CO2]
• Seasonal and synoptic cycles are evident
* Note: Tower heights range from 40 m AGL to 136 m AGL
2012
Site 03: downtown
Site 09: rural
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Observed range of CO2 amongst INFLUX sites
< 3 ppm on 29% of days
> 10 ppm on 10% of days
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Observed range of CO2 amongst INFLUX sites
< 3 ppm on 29% of days
> 10 ppm on 10% of days
29% of ranges are < 3 ppm10% of ranges are > 10 ppm
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CO2 range as a function of wind speed
Observations: CO2 range amongst INFLUX sites
Increased residence time (at low winds) tends to increase the CO2 range
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CO2 range as a function of wind speed
Observations: CO2 range amongst INFLUX sites
Model: Difference along domain-averaged wind direction
Increased residence time (at low winds) tends to increase the CO2 range
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Average [CO2] above background site
• Compared to Site 01 (background)
• Site 03 (downtown site) measures larger [CO2] by 3 ppm
• Site 09 measures only 0.3 ppm larger than Site 01
Afternoon hours
Ave
rag
e C
O2
(pp
m)
01 02 03 04 05 07 09 10 12
Bac
kgro
un
d s
ite
ObservationsD
ow
nto
wn
sit
e
Eas
t o
f ci
ty
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Average CO2 compared to background site
• Forward model results: using Hestia 2002 fluxes
• Average: obs 25% higher than predictedA
vera
ge
CO
2 (p
pm
)
01 02 03 04 05 07 09 10 12
Bac
kgro
und
site
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Average CO2 compared to background site
• Forward model results: using Hestia 2002 fluxes
• Average: obs 25% higher than predicted
Ave
rag
e C
O2
(pp
m)
01 02 03 04 05 07 09 10 12
Bac
kgro
und
site
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Conclusions• Whole city flux estimates achieved via aircraft mass
balance. ~40% uncertainty• Winter, CO2 = CO2ff. Summer, not so.• Tower observations detect a clear urban signal in both
CO2 and CH4 (buried amid lots of synoptic “noise”).• Differences vary greatly with weather conditions• Inversion system with 6 towers performs very well under
idealized conditions.• “Real data” forward results encouraging.
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Vertical profiles of CO2
Rural siteOctober 2012
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Vertical profiles of CO2
Downtown siteOctober 2012
Rural siteOctober 2012
• Downtown site, compared to the top level (54 m):• 40 m level is 0.3 ppm higher, averaged over 1 month• 20 m level is 1.7 ppm higher• 10 m level is 4.3 ppm higher
• INFLUX tower heights range from 40 m AGL to 136 m AGL
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Sensitivity test: Average [CO2] above background site
• Check sensitivity of results to small errors in modeled winds
• Hestia fluxes shifted by 1 grid point in each direction
• Which sites are more useful for reducing uncertainty?
Bac
kgro
un
d s
ite
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Sensitivity test: Average [CO2] above background site
• Check sensitivity of results to small errors in modeled winds
• Hestia fluxes shifted by 1 grid point in each direction
• Which sites are more useful for reducing uncertainty?
• Differences of 0.5 – 1 ppm at sites 03, 07, and 10
• Lower at other sites
Bac
kgro
un
d s
ite