Wednesday, 15 January 2020: 9:45 AM
206B (Boston Convention and Exhibition Center)
Quantifying the anthropogenic sources of CO2 and CH4 is imperative yet challenging. We introduce a tractable multi-species data analysis framework that aims to enhance CO2 and CH4 signatures from anthropogenic activities through the synergistic use of satellite-derived measurements of combustion-related trace gases (CO and NO2, CO2 and CH4) and global chemistry transport modeling. This is anchored upon the utility of NO2 data to identify combustion activity (for CO2) and CO to track corresponding plumes and to provide information on combustion efficiency (CE). These constituents (CO, NO2, CH4) are also strongly coupled chemically via OH (i.e., CO is a sink of OH while NO2 is a source of OH within the tropospheric O3 chemistry). Here, we present initial results on our joint analysis of CO2 and CO data in constraining regional fossil-fuel CO2 from Asia and Korea/Japan (ffCO2) using simulated CO2 and CO (including regional tags of ffCO2 and ffCO) in the Community Atmosphere Model with Chemistry (CAM-chem) and 14CO2, CO2, and CO data taken during KORUS-AQ field campaign in May 2016. We use an ensemble of posterior CO2 fluxes from available CO2 inversion systems (e.g., CarbonTracker) and best emission scenarios based on the HTAPv2 inventory for CO to provide a modeling platform that best simulate the abundance of these species, enabling us to explore these synergies more effectively. Our CAM-chem simulations show reasonable agreement across observation platforms including NOAA CCGG, TCCON, OCO-2, and MOPITTv8. We find that ffCO2 derived from 14CO2 and simulated ffCO2 tags show strong correlation (r=0.82). We also find that ffCO2 from East Asia and rest of the world need to be scaled up (1.61 and 1.28, respectively), while ffCO2 from Korea and Japan needs to be scaled down (0.84). This is supported by a complementary analysis on CO abundance (and ffCO tags) which reveals clearer signatures of modeled ffCO2 plume transport, sectoral emissions, and CE. We find that dCO/dCO2 can be better use in diagnosing inconsistencies in CE using ffCO and ffCO2 tags. The observed and modeled dCO/dCO2 (~13 ppb/ppm) over Korea is largely influenced by dffCO/dffCO2 from Korea (6.7 ppb/ppm) with modest influence from middle and northern East Asia (~52-55 ppb/ppm), suggesting a higher CE over Korea than East Asia despite recent decreases in CO. To further support our findings, we also conduct a suite of Bayesian synthesis inversions with KORUS-AQ and OCO-2/MOPITT data. We augment the ffCO2 emission (state) and observation vectors with ffCO emission and CO, respectively. We took advantage of CO2:CO error correlations derived from KORUS-AQ data to incorporate off-diagonal elements in the a priori and observation error covariances. These correlations simply serve to transfer CO information from the CO data to ffCO2. Our results show that there is a reduction in a posteriori error in ffCO2 emissions when these correlations are incorporated. However, the a posteriori ffCO2emissions are fairly sensitive to the magnitudes of these correlations relative to inversions using only ffCO2 data as constraints, suggesting that such correlations need to be further accurately quantified. Our results have implications on the design of current multi-species inversion systems, especially those that have planned on using satellite column retrievals of CO (and/or NO2) with CO2 (and/or CH4).
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