TOP-DOWN CONSTRAINTS ON REGIONAL CARBON FLUXES USING CO 2 :CO CORRELATIONS FROM AIRCRAFT DATA P. Suntharalingam, D. J. Jacob, Q. Li, P. Palmer, J. A. Logan,

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Presentation transcript:

TOP-DOWN CONSTRAINTS ON REGIONAL CARBON FLUXES USING CO 2 :CO CORRELATIONS FROM AIRCRAFT DATA P. Suntharalingam, D. J. Jacob, Q. Li, P. Palmer, J. A. Logan, C. Gerbig, R. Yantosca Harvard University S. A. Vay, G. Sachse NASA Langley D. Streets Argonne National Laboratory TRACE-P March-April, 2001 COBRA-2000 August 2000

Regional CO 2 /CO Emissions Ratios March 2001 (from a priori inventories) Observed CO 2 :CO Correlations (TRACE-P Flight DC8 #16, March 29, 2001) CO 2 (mol) CO (mol) ATMOSPHERIC MEASUREMENTS OF CO 2 :CO CORRELATIONS CAN PROVIDE UNIQUE INFORMATION ON SOURCE REGION AND SOURCE TYPE CHINA JAPAN - The emissions ratio varies with combustion efficiency - Range in regional emissions ratios reflects mix of sources and variation in fossil fuel combustion ratio Boundary layer, off China (slope = 12) Ascent out of Japan (slope = 65) Measurements above 500hPa (slope = 60)

The NASA/GTE TRACE-P Aircraft Mission Sampled Asian outflow over the Western Pacific in the spring of 2001 (Feb. 28 th – April 10, 2001) CO 2 measurements : S. Vay; CO measurements: G. Sachse NASA, Langley GEOS-CHEM CO 2 Simulation Boundary Layer, March 10-20, 2001

MOTIVATION To identify constraints on CO 2 sources using analysis of observed CO 2 /CO correlations Combine analysis of aircraft data with model simulations to evaluate bottom-up inventories GEOS-CHEM Model Bottom-up Inventories APPROACH Aircraft Data Improved CO 2 Fluxes

ASIAN EMISSIONS INVENTORIES FOSSIL FUEL MODEL GEOS-CHEM (global) 2 o x2.5 o ; 48 levels BIOFUEL BIOMASS BURNING BIOSPHERE Heald et al. (2003) Duncan et al. (2003) Streets et al. (2003) CASA, Randerson et al.(1997) Streets et al. (2003) Consistent combustion inventories for CO 2 and CO Shown: March, 2001

ASIAN CO 2 SOURCES Seasonal Cycle : CO 2 TRACE-P TRACE-P at seasonal CO 2 maximum Biospheric emissions are 65% of Chinese total, according to bottom-up inventories Average over TRACE-P period

REGIONAL ANALYSIS OF TRACE-P MEASUREMENTS Offshore China Over Japan Slope (> 840 mb) = 51 R 2 = 0.76 Slope (> 840 mb) = 22 R 2 = 0.45 Analysis conducted on a regional basis Factor of 2 difference in boundary layer CO 2 :CO correlations between the two regions Japan China

CO 2 Simulation Based on A Priori Inventories Model overestimate of CO 2 in boundary layer Discrepancy greatest off China JAPANALL FLIGHTS MODEL GEOS-CHEM CO 2 simulation sampled along TRACE-P flight tracks OBSERVATIONS CHINA

CO 2 :CO Correlations Region : Offshore China Simulation : Bottom-up inventories for CO 2 and CO Modeled BL slope close to bottom-up emissions ratio for China (58) Modeled boundary layer CO 2 :CO slope higher than observations. This is due to underestimate of CO and overestimate of CO 2 in the boundary layer CO CO 2 MODEL OBS CO simulation : Palmer et al. [2003] TRACE-P Observations GEOS-CHEM Model Slope = 22 Slope = 57

Which CO 2 Emissions Source is too High ? Modeled CO 2 :CO ratios higher than observations Modeled boundary layer CO 2 is higher than observations Reconciliation of modeled CO 2 with observed CO 2 and CO 2 :CO ratios requires a reduction in a source with a high CO 2 :CO emissions ratio Region : Offshore China Mean BL slope = 22 MODEL OBS Mean BL slope = 57 GEOS-CHEM Model TRACE-P ObservationsGEOS-CHEM Model

IMPROVED CO 2 and CO SIMULATION S Better match to observed boundary layer concentrations and correlations Obtaining CO 2 fuel emission changes consistent with CO depends on cause of a priori CO underestimate (activity rate vs. emissions factor error) CO 2 : 45% reduction in Chinese biospheric flux CO : 54% increase in Chinese fuel emissions (Palmer et al ) Slope = 18 R 2 = 0.52 Slope = 55 R 2 = 0.66 Slope = 29 R 2 = 0.67 Mean Vertical Profiles in Chinese Outflow Region COCO 2 Observations A Priori Best-case TRACE-P A Priori Best-Case

The COBRA-2000 Aircraft Mission Tropospheric measurements over North America in August CO 2 and CO Measurements : C. Gerbig, S. Wofsy, B. Daube, J. Lin, A. Andrews, Harvard University Measurements sampled summer CO 2 drawdown and intense biomass burning SEASONAL CYCLE CO 2 CO COBRA-2000 CO 2 /CO Emissions ratio (mol/mol) CO 2 :CO Correlations Selected Flights (2-8 km) CO 2 (ppmv) CO (ppbv) Positive : mix of combustion and biospheric respiration Negative : Biospheric uptake FLIGHT TRACKS

A PRIORI EMISSIONS : North America CO 2 and CO INVENTORIES Fossil : Marland et al. 2001, Logan et al. Biomass Burning : Duncan et al Biosphere : CASA (Olsen and Randerson. 2003) FOSSIL BIOMASS BURN BIOSPHERE (CASA) 31% 12% 57% 37% 63% CO 2 CO Fossil Biosphere Biomass Burning Fossil (43) Biomass Burning (12) Shown : August 2000 TOTAL (-27) Biosphere CO CO 2 Regional CO 2 /CO Flux Ratio

IDAHAO-MONTANA FOREST FIRES (August 2000) Biomass Burning Plumes from COBRA-2000 Aug 19 Aug 24 Alt (km) -Forest fire emissions had significant impact on tropospheric CO over North America -Estimated contribution : 9 Tg CO for August, 2000 (Lamarque et al. 2003) GEOS-CHEM CO Simulation August, 2000; Alt : 2.8 km MOPITT CO Column shows enhancements downwind of fire location

COMPARISON OF GEOS-CHEM SIMULATION WITH COBRA-2000 MEASUREMENTS GEOS-CHEM CO 2 and CO simulations sampled along COBRA-2000 flight tracks CO 2 Altitude Profiles : All Flights - Modeled CO and CO 2 overestimate observations - Diurnal cycle in CO 2 fluxes improves model simulation in boundary layer - To use CO 2 :CO correlations as constraints on CO 2 fluxes, we must first identify source of CO overestimate CO All Flights MODEL OBS MODEL without diurnal cycle in biospheric fluxes

COMPARISON OF GEOSCHEM CO WITH MOPITT COLUMNS Modeled CO columns higher than MOPITT especially in and downstream of high fire regions GEOS-CHEM CO Simulation Li et al. [2003] MOPITT CO Column, August 2000 GEOS-CHEM CO Column, August 2000

CO 2 :CO CORRELATION ANALYSIS OF BIOMASS BURNING SIGNAL IN COBRA-2000 MEASUREMENTS - Modeled correlations underestimate observed slope - Reduction in biomass burning source improves simulation of correlations and absolute concentrations - A likely source of error in biomass burning inventory is from omission of day to day variability in modeled fire emissions CO 2 CO OBS REDUCE BIOMASS BURNING A PRIORI COBRA-2000 GEOS-CHEM S = 36 R 2 = 0.42 S = 14 R 2 = 0.64 S = 25 R 2 = 0.64 Analysis in Depicted Region at 2-4 km

SUMMARY Observed CO 2 :CO correlations from aircraft data display distinct slopes reflecting regional and source type signatures, and provide top-down constraints to evaluate regional emissions inventories Asian outflow : CO 2 :CO constraints indicate an overestimate in bottom-up Chinese biospheric CO 2 emissions for March North America : Success in constraining CO 2 fluxes using CO 2 :CO constraints requires accurate characterization of fire influences. CO and correlation constraints indicate an overestimate in the biomass burning inventory for August An optimal set of emissions adjustments requires a formal inverse analysis of the coupled CO 2 :CO system

POSTERS : Top-down Constraints from Multiple-Species Correlations A52B-0797: P. Palmer et al. Exploiting observed CO:CO 2 correlations in Asian outflow to invert simultaneously for emissions of CO and CO 2 A52B-0796 : Y. Xiao et al. Constraints on Asian and European Sources of Methane from CH 4 - C 2 H 6 - CO Correlations in Asian Outflow ACKNOWLEDGEMENTS NOAA OGP Global Carbon Cycle Program NASA Carbon Cycle Program