Measuring CO2 and CH4 Emissions from Indianapolis: A Test Bed for Urban Greenhouse Gas Emissions MonitoringKenneth Davis1, Maria Cambaliza2, Kevin Gurney3, Michael Hardesty4, Anna Karion5, Thomas Lauvaux1, Natasha Miles1, Kuldeep

Prasad6, Igor Razlivanov3, Scott Richardson1, Daniel Sarmiento1, Paul Shepson2, Colm Sweeney5, Jocelyn Turnbull7, James Whetstone6

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14th National Conference and Global Forum on Science, Policy and the Environment, January, 2014

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Acknowledgments:Field operations were supported by Earth Networks, Inc. Funding is provided by the National Institute for Standards and Technology. INFLUX contributes to the North American Carbon Program. Influx.psu.edu; nacarbon.org

Goals of the Indianapolis Flux Experiment (INFLUX)

Contact: kjd10@psu.edu

1The Pennsylvania State University, 2Purdue University, 3Arizona State University, 4NOAA Earth System Research Laboratory, University of Colorado, 6National Institute of Standards and Technology, 7GNS Science

Develop and assess methods of quantifying greenhouse gas emissions at the urban scale, using Indianapolis as a test bed.

In particular:

Determine whole-city emissions of CO2 and CH4

Measure emissions of CO2 and CH4 at 1 km2 spatial resolution and weekly temporal resolution across the city

Distinguish biogenic vs. anthropogenic sources of CO2

Quantify and reduce uncertainty in urban emissions estimates Determine monitoring system requirements for achieving a given

uncertainty threshold

Aircraft Measurement of GHG EmissionsAircraft Measurement of GHG Emissions

mixing height(ABL)

Measure GHG concentrations upwind and downwind of a source.Measure atmospheric transport (wind, mixing depth).Estimate GHG emissions needed to explain the observed difference in GHG concentrations.

June 1, 2011 flight path. Purdue University flight downwind of the city of Indianapolis measuring CH4 and CO2 in the atmospheric boundary layer (ABL).

Indianapolis Flux Indianapolis Flux Experiment (INFLUX) Experiment (INFLUX)

Tower NetworkTower Network

Spatial Structure of Urban COSpatial Structure of Urban CO22

Average [COAverage [CO22] Above Background Site ] Above Background Site

• Site 09 measures 0.3 ppm larger than Site 01• Site 03 (downtown site) measures larger [CO2]

by 3 ppm • Model results using mesoscale atmospheric

model and a “bottom-up” emissions estimate (Hestia for 2002)

• Observations are 25% higher than modeled values, on average.

• The discrepancy suggests an underestimate in the “bottom-up” emissions estimate.

Miles et al, in prep1 January – 1 April, 2013 afternoon daily data

Lauvaux et al, in prep

BEFORE AFTER DIFFERENCE / CORRECTION

Spatial structure of the model-data difference reveals the spatial pattern of emissions corrections.

Corrections can be computed continuously in time, detecting changes in emissions over time.

Questions:Are these methods viable for policy and management applications?What additional research is needed to make these methods useful for

policy and management applications?

Methods and their characteristics:Atmospheric budgets

All emissions are captured, but identifying individual sources is challenging.

Aircraft measurements

Cover space very well, poor spatial resolution, provide snapshots in time.

Tower-based measurements

Can provide continuous emissions estimates for years, spatial domain and resolution a function of the measurement network.

“Bottom-up” inventoriesEconomic data and emissions factors

Rich source of data regarding types of emissions and spatial distributions of emission. Prone to missing sources. Temporal resolution is limited. Atmospheric measurement of greenhouse gas (GHG)

emissions:

Wind

emissions

Wind

Upwind GHG concentration

Downwind GHG concentration

Emissions within box = (concentration difference) * (wind perpendicular to the surface) integrated over the surface

Results:

June 1, 2011 atmospheric concentrations. CO2 and CH4 concentrations downwind of the city of Indianapolis.

Methane emissions estimates. Estimated CH4 emissions from the city of Indianapolis. Similar results also exist for CO2.

Snapshots in time. Roughly 30% uncertainty with each snapshot.

Cambaliza et al, in reviewCambaliza et al, in prep

June 1, 2011 atmospheric concentrations with kriging to fill in a complete atmospheric “wall” of GHGs.

Tower-Based Measurement of GHG EmissionsTower-Based Measurement of GHG Emissions

Atmospheric inverse flux estimate: