Abstract
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.
Highlights
Remote sensing of greenhouse gases (GHGs) in cities provides abundant datasets for quantifying urban carbon sources and sinks, complementary to in situ ground-based measurements
We developed GFIT3, a full physics algorithm to retrieve trace gases in the presence of aerosols, and demonstrated its performance by retrieving XCO2 and XCH4 from California Laboratory for Atmospheric Remote Sensing (CLARS)-FTS measurements
This algorithm simultaneously retrieves fine- and coarse-mode aerosol properties including aerosol optical depth (AOD) and ALH
Summary
Remote sensing of greenhouse gases (GHGs) in cities provides abundant datasets for quantifying urban carbon sources and sinks, complementary to in situ ground-based measurements. Many different full physics retrieval algorithms, which explicitly account for atmospheric absorption and scattering and surface reflection in the radiative transfer (RT) forward modeling, have been developed for spaceborne instruments for retrieving column-averaged dry air mole fractions of atmospheric carbon dioxide (XCO2) and methane (XCH4). For GHG retrievals based on reflected solar radiation measurements (e.g., CLARS-FTS, GOSAT, and OCO-2), the aerosol scattering effect is important and needs to be accurately modeled. It is very important to have proper aerosol models with accurate optical properties, including phase function and single scattering albedo (SSA), in order to obtain accurate GHG retrievals Another scientifically unique feature of CLARS-FTS, among instruments that measure surface-reflected sunlight, is that it uses the O2 1 band at 1.27 μm instead of the O2 A band at 0.76 μm that is traditionally used by spaceborne instruments to constrain surface pressure and aerosols.
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