1. On network design for the detection of urban greenhouse gas emissions: Results from the Indianapolis Flux Experiment (INFLUX) Natasha Miles 1, Marie Obiminda Cambaliza 2, Kenneth Davis 1, Michael Hardesty 3, Laura Iraci 4, Kevin Gurney 5, Anna Karion 3, Thomas Lauvaux 1, Laura McGowan 1, Scott Richardson 1, Daniel Sarmiento 1, Paul Shepson 2, Colm Sweeney 3, Jocelyn Turnbull 6, James Whetstone 7 1. The Pennsylvania State University, 2. Purdue University, 3. NOAA/ESRL 4. NASA/JPL, 5. Arizona State University, 6. GNS Science, 7. NIST ICDC9 Beijing 7 June 2013

2. 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.

3. Develop improved methods for determination of urban area- wide emissions, and spatially and temporally-resolved fluxes of greenhouse gases, specifically, CO 2 and CH 4. Determine and minimize the uncertainty in the emissions estimate methods. INFLUX objectives

4. 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

5. 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

6. INFLUX observational results to date: Aircraft and automobiles

7. Aircraft mass balance approach: 1 June 2011 Flight path Cambaliza et al, in prep

8. 22,000 moles s -1 203 moles s -1 1 June 2011 Results Cambaliza et al, in prep 8 ppm CO2 50 ppb CH4

9. 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 CO2 Emissions: Aircraft mass balance vs Hestia inventory

10. WWTP Landfill Drive-arounds: Separation/quantification of CH 4 sources Instrumented surface vehicles to identify and quantify individual sources.

11. INFLUX observational results to date: Ground-based measurements

12. INFLUX ground-based instrumentation Picarro, CRDS sensors; NOAA automated flask samplers; Communications towers ~ 100 m AGL 10 km

13. 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 comparison at 5 INFLUX sites

14. Flask results: C14 ICDC9 Poster 224: Turnbull et al.

15. Tower in-situ results / Mesoscale atmospheric inversion system

16. Mesoscale modeling system WRF-Chem running with: –3 nested domains (9/3/1 km resolution), inner domain: 87x87 km 2 –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

17. 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

18. Influence functions: INFLUX “Influence function” – the areas that contribute to GHG concentrations at measurement points 12 towers in 87 x 87 km 2 domain Strategy: oversampling (?) Contour: Hestia residential sector

19. Sectoral atmospheric mole fractions, tower by tower Winter mean mole fractions 6 of 12 tower sites Midday ABL mixing ratio (ppm) mobileindustcommerresidpowerplant Site 1: background Site 2: downwind Site 10: powerplant! Some structure across towers by sector Site 1 Site 10 2 5 7 9

20. 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

21. Observed range of CO2 amongst INFLUX sites < 3 ppm on 29% of days > 10 ppm on 10% of days

22. Observed range of CO2 amongst INFLUX sites < 3 ppm on 29% of days > 10 ppm on 10% of days 29% of ranges are < 3 ppm 10% of ranges are > 10 ppm

23. 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

24. 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

25. 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 Average CO2 (ppm) 01 02 03 04 05 07 09 10 12 Background site Observations Downtown site East of city

26. Average CO2 compared to background site Forward model results: using Hestia 2002 fluxes Average: obs 25% higher than predicted Average CO2 (ppm) 01 02 03 04 05 07 09 10 12 Background site

27. Average CO2 compared to background site Forward model results: using Hestia 2002 fluxes Average: obs 25% higher than predicted Average CO2 (ppm) 01 02 03 04 05 07 09 10 12 Background site

28. 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.

29. Vertical profiles of CO2 Rural site October 2012

30. Vertical profiles of CO2 Downtown site October 2012 Rural site October 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

31. 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? Background site

32. 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 Background site