1. NACP Synthesis Project: Spatial and Temporal Distributions of Sources for non-CO 2 Greenhouse Gases (CH 4, CO, N 2 O) over North America Bottom-up Inventories Patrick Crill Boulder, CO 22 October 2008

2. Harvey AugenbraunHarvey Augenbraun, Elaine Matthews, and David SarmaElaine Matthews

3. Consilience and Caricature

4. A Season of CO 2 and CH 4 Fluxes across a Wetland Trophic Gradient in the BOREAS NSA Fen site, Thompson, Manitoba, Canada Patrick Crill 1 and Jill Bubier 2 1 Complex Systems Research Center, Institute for the Study of Earth, Oceans and Space, University of New Hampshire, Durham, NH, USA 03824 2 Environmental Studies Program, Mount Holyoke College, South Hadley, MA, USA 01075 Poor fen Bog Intermediate fen Rich fen CO 2 FluxCH 4 Flux

10. 01/01/200601/02/200601/03/200601/04/200601/05/200601/06/200601/07/200601/08/200601/09/200601/10/200601/11/200601/12/200601/01/2007 -5 0 5 10 15 20 25 30 13260911211521822132442743053351 DOY CH 4 flux, mg m -2 h EC data from Marcin Jackowicz-Korczyński

11. Stordalen Mire 68º22’ N, 19º03’ E

12. From Bäckstrand et al., JGR-B,2008

13. Vegetation change Stordalen 1970-2000 From T Johansson,2002

14. Vegetation change Stordalen 1970-2000 From T Johansson,2002

15. Methane emission change Stordalen 1972-2000 From T Johansson,2002

20. Images showing the Aerodyne, UNH and Washington State mobile instrumented vans parked at the stationary sampling location in Cambridge, MA, on May 27-29, 1999. The second image depicts some of the instrumentation housed in the Aerodyne van. This same instrument package was used during both the mobile and stationary sampling campaigns.

21. Concentration of fine particles along the street pathway sampled by the Aerodyne instrumented van in metropolitan Boston area on May 23, 1999. Shown are the concentrations of total fine particles (unheated) and non-volatile fine particles (heated). Note that these two measurements alternated in 2 minute intervals. Thus, there are non-measurement time periods (lightest blue color) in-between the actual measurements. These GPS-GIS based maps were generated by the Ferreira group at MIT.

22. Unpublished Data from Aerodyne Corp. and UNH

25. SectorSource% ContributionEmission (TgCH 4 ) Agriculture enteric fermentation195.6 Manure61.7 Rice10.4 burning of agricultural residues0.10.04 Sector Total26.17.7 [mmk1] [mmk1] Waste Landfills339.9 wastewater treatment41.3 Sector Total3711.2 Energy natural gas206 Coal113 Petroleum41.1 Sector Total3510.1 Other industrial processes, stationary and mobile combustion 20.7 Anthropogenic Total 29.0 [mmk1] Removed the final digit for consistency in significant figures.[mmk1]

27. Inventory -magnitude -temporal dynamics Mapping -source identification -location Flux Measurement -direct measurements -aerodynamic/meteorological -tracers A Generalized Case Study Scheme Modelling Efforts Integration Extrapolation Interpolation Spatial/Temporal Scale larger smaller

28. Ed Dlugokencky, 2008

30. 1. Quantification and assembly of the emissions databases Role of local to regional scale measurements Extrapolation and consilience with ancillary information 2. Refinement of emissions factors 3. Uncertainties definitions and quantifications – how well can we resolve emissions 4. Definition of temporal dynamics 5. Consilience of functions and controls 6. Caricature of the emissions – decisions about the utility of the cloud of nuance NACP Synthesis Project: "Spatial and Temporal Distributions of Sources for non-CO 2 Greenhouse Gases (CH 4, CO, N 2 O) over North America"

31. 1. Develop in situ sensors and sampling protocols. 1.1. calibration standards (for CH 4 ) 1.2. sampling/measurement protocols 1.3. Identify differences needed in CH 4 sampling protocols compared to CO 2, N 2 O, CO, F-gases and aerosols 2. Perform model studies of measurement strategy design and model-data fusion. 2.1. Perform model-data fusion exercises to design measurement strategies. accuracy needed and detectable additional species to be measured 2.2. Improve process modeling of (CH 4 ) emissions modeling and field measurement activities at scales that capture locally unresolved flux variations in space and time. improve process-based model capabilities to predict sensitivities (particularly nonlinearities)

32. 3. Optimize national inventories for accounting. 3.1. Continually evaluate and update national (e.g. wetlands) inventories (Canada, US, Mexico). 3.2. Develop a current estimate North American surface (CH 4 ) flux maps (e.g., 0.5° grid or higher resolution, monthly at least) by emission sector. Quantify or estimate the uncertainty in the magnitude, location, and seasonality of the (CH 4 ) sources. 4. Strengthen current observational networks. 4.1. Identify and support continuous (CH 4 ) concentration and/or comprehensiv flux measurement programs, maintaining long-term datasets. 4.2. Establish continuous, high-frequency atmospheric (CH 4 ) concentration measurement sites dependent upon source uncertainties and required data. 4.3. Particular attention to continuous (CH4) flux and ancillary measurements Flux mapping, network design studies, and analysis and modeling of extant data should guide deployment of future measurements. 4.4. Characterize the chemical meteorology. Ensure that additional species (e.g., CO, HCFCs) and isotopes ( 13 C, 14 C, D) are measured to better characterize CH4 source regions 4.5. Evaluate the adequacy of the existing measurement networks, E.g. of floodplain wells, wetland water table monitoring, and stream gages (geographic distribution, sampling frequencies).

33. 5. Improve databases of fossil fuel use, land cover, and industrial emissions dynamics. 5.1. Evaluate the energy sector data for (CH 4 ) emission analysis. 5.2. More subtle economic analyses of emissions 6. Develop remote sensing technology. 6.1. Support analysis of satellite products for usefulness to NACP-NCGHGs. 6.2. Radar data would be particularly useful for wetland distribution, inundation, and hydrologic studies. 6.3. Identify other potentially useful sensors for urban sources.