Quantification of uncertainty associated with United States high resolution fossil fuel CO2 emissions: updates, challenges

and future plans Kevin Gurney, Vandhana Chandrasekaran*, Daniel

Mendoza*, Sarath Geethakumar

Arizona State University*Department of Earth and Atmospheric Sciences

Purdue University

With thanks to current collaborators/funders:Yuyu Zhou, Daniel Mendoza, Vandhana Chandrasekaran, Sarath Geethakumar, Igor Razlivanov, Bedrich Benes, Nathan Andrysco, Chris Miller, Kathy Corbin, Scott Denning, Marc Fischer, Stephane de la Rue du Can, Simon Ilyushchenko, Paul Shepson, Advait Godbole, Knauf Insulation, Showalter Trust, NASA, NSF CAREER, NIST, CO2FFEE group, INFLUX group, PCCRC, Rose Filley, …….

See poster by Mendoza & Gurney

Vulcan

Gurney et al., Env. Sci & Tech, 2009

Version 2.0 now available(please use latest documentation)

www.purdue.edu/eas/carbon/vulcan

Multiple datastreams transformed to CO2

Vulcan is a “data product” – it uses mostly “regulatory data”

n, fCO 2E n, f

gEn, fgEF

fHC n, fCO 2EF Ox%

Estimation process

3 fundamental processes

1.CO2 direct (95% of electricity production emit)Bias and uncertainty on CEMs!

2.CO to fuel to CO2 (Res, Comm, Ind, airport)

(g is CO, f is fuel, n is process)

3.VMT/fuel efficiency to CO2 (onroad, nonroad)

CV ,XC C

V ,XVMT VCF

VCF C

Y

V

YV

Y 1

N

Eff

Ox%

Uncertainty – our approach

CO emission factor range from databasesreported CO2 (power plants: Ackerman & Sundquist, 2008)*carbon content by fuel from DOE dataheat content by fuel from DOE dataVMT uncertainty from FHWAFleet age distribution variation from sample dataClinker production & EF

In the form of “sensitivity” – hi and lo SD

reported CO emission value*Vehicular fuel efficiency (SE & SD)Nonroad uncertainties (3%)No spatial (impact to area sources, transportation)No temporal (impact res, comm, ind)

Not yet incorporated

Not consideredreported fuel typereported timeframereported deviceomission errors

National-level

2002 Vulcan / DOE comparison (MtC/year)

DOE/EIA -- “Emissions of Greenhouse Gases in the United States” [2009].

• Data sources are ~90% independent• Fugitive and bunker represent ~3%• Vulcan greater than DOE/EIA in onroad primarily

Context for this level of uncertainty

10% uncertainty is ~160 MtC/year (0.16 GtC/yr)

1.8 X proposed 7% Kyoto target for the US

1.5 X 2007 Australia fossil fuel CO2 emissions

~ entire bottom-up estimated US forest sink

~ entire 2007 UK fossil fuel CO2 emissions

What sectors, error sources dominate?

Sectors

Error sources

What sector responsible for EF uncertainty?

Uncertainty at county/annual level

Cumulative weighted uncertainty

Evaluation

THE TOP TEN (19% of ERROR!)

1. Cuyahoga, OH (Cleveland)……... ±50%2. Harris, TX (Houston) ……………. ±35%3. Porter, IN (steel industry)……….. ±40%4. Los Angeles, CA (LA)……………. ±15%5. Hennepin, MN (Minneapolis)6. Hutchinson, TX (oil/gas industry)7. Monterey, CA8. Cook, IL (Chicago)9. San Diego, CA (commercial)10.Wayne, MI (Detroit)

Indianapolis (INFLUX/Hestia fame) is 87th

Challenges & next steps:

• Still not a complete uncertainty assessment

1. Incoming CO emissions uncertainty

2. Variations in fuel efficiency (estimate of the mean; driving patterns, start/stop, etc)

3. Powerplant by powerplant examination (CEMs v fuel stats)

• Spatial analysis of uncertainty (at 10 km scale)

• Monte Carlo approach

Conclusions:

• Central estimate is consistent with DOE fuel (within 2%)

• National-level uncertainty: ~10%. Average county uncertainty: ~ ±8% (will likely increase)

• Driven by VMT uncertainty, Industrial CO EF & CO2 EF, Electricity Production fuel stat/CEMs uncertainty

• County distribution of error is highly lognormal

• ~20% of uncertainty in 10 counties (cities and large industrial concentrations), 50% in top 5% of counties

• How can we really progress?

1. Measure atmosphere – of course

2. Improve the measurements of fuel, driving, CEMs

Concrete suggestion: bring science to 5% of large powerplants and industrial point sources!!

Hestia flythrough……. Click here for link to movie (135 M)

Thanks to Bedrich Benes & Yuyu Zhou

Evaluation: EIA SEDS

EIA “consumption”