Abstract. Remote sensing of greenhouse gases (GHGs) in cities,
where high GHG emissions are typically associated with heavy aerosol
loading, is challenging due to retrieval uncertainties caused by the imperfect
characterization of scattering by aerosols. We investigate this problem by
developing GFIT3, a full physics algorithm to retrieve GHGs (CO2 and
CH4) by accounting for aerosol scattering effects in polluted urban
atmospheres. In particular, the algorithm includes coarse- (including sea
salt and dust) and fine- (including organic carbon, black carbon, and
sulfate) mode aerosols in the radiative transfer model. The performance of
GFIT3 is assessed using high-spectral-resolution observations over the Los
Angeles (LA) megacity made by the California Laboratory for Atmospheric
Remote Sensing Fourier transform spectrometer (CLARS-FTS). CLARS-FTS is
located on Mt. Wilson, California, at 1.67 km a.s.l. overlooking the LA
Basin, and it makes observations of reflected sunlight in the near-infrared
spectral range. The first set of evaluations are performed by conducting
retrieval experiments using synthetic spectra. We find that errors in the
retrievals of column-averaged dry air mole fractions of CO2 (XCO2)
and CH4 (XCH4) due to uncertainties in the aerosol optical
properties and atmospheric a priori profiles are less than 1 % on average. This
indicates that atmospheric scattering does not induce a large bias in the
retrievals when the aerosols are properly characterized. The methodology is
then further evaluated by comparing GHG retrievals using GFIT3 with those
obtained from the CLARS-GFIT algorithm (used for currently operational CLARS
retrievals) that does not account for aerosol scattering. We find a
significant correlation between retrieval bias and aerosol optical depth
(AOD). A comparison of GFIT3 AOD retrievals with collocated ground-based
observations from AErosol RObotic NETwork (AERONET) shows that the developed algorithm produces very
accurate results, with biases in AOD estimates of about 0.02. Finally, we
assess the uncertainty in the widely used tracer–tracer ratio method to
obtain CH4 emissions based on CO2 emissions and find that using
the CH4/CO2 ratio effectively cancels out biases due to aerosol
scattering. Overall, this study of applying GFIT3 to CLARS-FTS observations
improves our understanding of the impact of aerosol scattering on the remote
sensing of GHGs in polluted urban atmospheric environments. GHG retrievals
from CLARS-FTS are potentially complementary to existing ground-based and
spaceborne observations to monitor anthropogenic GHG fluxes in megacities.
Reevaluating the Use of O
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