1. Using atmospheric radiocarbon ( 14 CO 2 ) to constrain North American fossil and biogenic CO 2 fluxes John B. Miller Scott Lehman, Arlyn Andrews, Colm Sweeney, Pieter Tans, Chad Wolak, Jocelyn Turnbull, Marc Fischer, Brian LaFranchi, Tom Guilderson, John Southon

2. Fossil Fuel are the biggest annual global and N. American fluxes… 1.…but, at many time scales NEE is bigger, which makes FF hard to identify (see Yoichi Shiga poster) 2.Inventories are good; why check them? a.They have spatio-temporal biases at the state/monthly and smaller scales. b.Generally, for up to date inversions, we need to extrapolate inventories. Global USA

3. Biases in FF will manifest themselves as biases in NEE in inversions, when using only CO 2 1.So, with a limited set of 14 C observations, we’ll soon focus on relaxing the assumption of FF_error = 0. 2.Eventually, with more 14 C observations, we’ll move towards direct emissions verification. 3.Here, I’ll describe our data and our modeling framework (and some examples of constraints of NEE and fossil fluxes).

4. 14 C is a theoretically robust tracer for fossil fuel fluxes. Total  14 C looks just like fossil CO 2. C atm* d  atm /dt = (  fos -  atm )F fos +  dis F surf_gross + isoF nuc + isoF cosmo dC atm /dt = F fos + F net _ surf + F fire  14 C ff = -1000 per mil (i.e. zero 14 C) Scaling: -2.7 per mil  14 C = 1 ppm CO2-fossil  14 C C ff

5. Results of simulated 14 CO 2 inversions show Fossil Fuel emissions can be retrieved with low uncertainty 5000 measurements per year over the US (currently ~ 750)  Monthly, state-sized fluxes at ~ 10% uncertainty.  NRC Recommendation of large increase in 14 CO 2 measurements to verify reductions

6. Current network of sites samples a large fraction of N. American fossil fuel emissions.  Dense enough to relax assumption of perfectly known fossil fuel emissions. (without sacrificing precision in NEE)

7. US PBL data show expected depletions of 14 C (… AND enhancements of other anthropogenic gases: see Steve Montzka’s poster) NWR Downwind PBL ~ 2-3 samples/week 10 ppm Cff

8. CO 2 PBL enhancements (or depletions) can be partitioned into NEE and Fossil fractions.  Fossil Fuel masks Bio signal  C bio large even in winter (~60% of total winter- time enhancement) despite urban/industrial observational footprint  CO 2 -only methods (tower, satellite, etc.) can not assume enhancements are due just to C ff (see Miller et al, JGR-D 2012) US East Coast 300 m asl PBL enhancement

9. How well can we model our observations? (using TM5 with full 14 CO 2 and CO 2 budget) TM5 Land (CASA model) Ocean (GLODAP/WOCE) Fossil (CDIAC/CT) Cosmogenic (50/50 Strat/trop) Nuclear Power (Graven)

10. The global trend and background for N. America are modeled very well. Bias = 0.8 per mil Stdev = 2.3 per mil

11. …And depletions relative to the trend fairly well. R 2 = 0.50 1:1

12. At polluted tower sites, seasonally varying depletion is captured. NWR Seasonal cycles probably driven by wind direction co- varying with flux (not PBL height or flux seasonality)

13. Downwind of mid-Atlantic East Coast, there are significant differences in vertical gradients

14. CMA (Original fossil fuel emissions)

15. CMA (Vulcan fossil fuel emissions)

16. Vulcan’s emissions match data better because of lower urban emissions. Standard CT-FFVulcan FF Vulcan minus CT

17. CMA (Vulcan fossil fuel emissions)  But, Vulcan may still have too much FF fuel emission near the coast in urban areas.

18. Summary 1. 14 CO 2 can partition NEE and FF fluxes – AND CO2 ≠ Cff 2.Increasingly dense set of 14 CO 2 observations that will allow us to soon relax the assumption of fixed FF in inversions. 3.A reliable modeling framework. 4.Some ability already to distinguish fossil fuel patterns.

20. Detection Sensitivity allows for < 1ppm recently added Fossil Fuel CO 2 NWT3 by measurement order: manual = 43.25 ± 1.60 Crex = 43.26 ± 1.65 Sigma-Cff = sqrt(2) * 1.8 per mil / 2.7 per mil/ppm = 0.9 ppm Determination of background is always important!

21. use of 14 C + CO 2 in CT to improve NEE F ff prior (given 0 uncertainty)NEE posterior retrieval deviation F ff prior from actuals will lead directly to bias in retrieved F bio (NEE) from inversion of C obs dC obs /dt = F ff + F bio + F fire F ff is large w.r.t net annual F bio, and.. extrapolation of F ff inventories will not capture F ff anomalies associated with sustained heat and cold waves CT 2000-10