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Emission estimates of carbon dioxide (CO2) and methane (CH4) and the meteorological factors affecting them are investigated over Sacramento, California, using an aircraft equipped with a cavity ring-down greenhouse gas sensor as part of the Alpha Jet Atmospheric eXperiment (AJAX) project. To better constrain the emission fluxes, we designed flights in a cylindrical pattern and computed the emission fluxes from two flights using a kriging method and Gauss's divergence theorem. Differences in wind treatment and assumptions about background concentrations affect the emission estimates by a factor of 1.5 to 7. The uncertainty is also impacted by meteorological conditions and distance from the emission sources. The vertical layer averaging affects the flux estimate, but the choice of raw wind or mass-balanced wind is more important than the thickness of the vertical averaging for mass-balanced wind for both urban and local scales. The importance of vertical mass transfer for flux estimates is examined, and the difference in the total emission estimate with and without vertical mass transfer is found to be small, especially at the local scale. The total flux estimates accounting for the entire circumference are larger than those based solely on measurements made in the downwind region. This indicates that a closed-shape flight profile can better contain total emissions relative to a one-sided curtain flight because most cities have more than one point source and wind direction can change with time and altitude. To reduce the uncertainty of the emission estimate, it is important that the sampling strategy account not only for known source locations but also possible unidentified sources around the city. Our results highlight that aircraft-based measurements using a closed-shape flight pattern are an efficient and useful strategy for identifying emission sources and estimating local- and city-scale greenhouse gas emission fluxes.

We present two new products from near-infrared Greenhouse Gases Observing Satellite (GOSAT) observations: Lowermost tropospheric (LMT, from 0 to 2.5km) and upper tropospheric-stratospheric (U, above 2.5km) carbon dioxide partial column mixing ratios. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial column mixing ratios significantly improve upon the Atmospheric CO2 Observations from Space (ACOS) and GOSAT (ACOS-GOSAT) initial guess and/or a priori, with distinct patterns in the LMT and U seasonal cycles that match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8ppm for retrieved GOSAT LMT, U, and XCO2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5ppm for retrieved GOSAT LMT, U, and XCO2. In the southern hemispheric biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and a CO-CO2 emission factor comparable to published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with a monthly average error of 0.8 (1.4)ppm for ocean (land). LMT is more locally influenced than U, meaning that local fluxes can now be better separated from CO2 transported from far away.