9:00 AM - 10:30 AM
[AAS07-P10] Improving MAX-DOAS tropospheric NO2 profile retrievals using ground-based in-situ and direct-sun observations
Keywords:nitrogen dioxide, NO2, remote sensing
Nitrogen dioxide (NO2) is one of the air pollutants and a precursor of nitric acid and tropospheric ozone. Additionally, NO2 emissions are potentially a tracer of CO2 emissions1,2. Satellite observations of NO2 have provided important information on the sources of NOx and their time evolutions. Spatial-resolution of recent NO2 satellite observations has been significantly improved, such as TROPOMI developed by ESA and the Korean geostationary environmental satellite (GEMS). A Japanese satellite (TANSO-3 onboard GOSAT-GW) will also be launched in 2024. The satellite-observed NO2 vertical column density and assumed concentration profile are compared and validated with ground-based observations. In particular, ground-based observation by Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS), which uses scattered sunlight, can obtain the vertical column density and the vertical profile of tropospheric NO2. Therefore, the satellite-observed NO2 vertical column densities and the assumed vertical profiles are generally compared with those with MAX-DOAS observations. However, it is known that the satellite-observed NO2 vertical column densities are systematically smaller than those with the ground-based MAX-DOAS observations3. The bias is more distinct in polluted urban areas, up to ~50%, than in remote areas3. Several candidates for the cause have been pointed out but are still debated .
Here, we revisit the retrieval of NO2 vertical profiles with the ground-based MAX-DOAS observations. Observations of MAX-DOAS installed at JAMSTEC Yokosuka Headquarters in an urban area (Yokosuka, Kanagawa) indicate that the retrieved NO2 vertical column density depends significantly (up to ~18%) on the ‘a priori’ vertical profile required for the MAX-DOAS retrieval. When a priori vertical profiles assuming higher fractions of NO2 present in the lower atmosphere (0–1 km altitude range) are used, the NO2 column densities tend to be small, implying that the aforementioned bias between satellite and ground-based observations may be partly remedied. The shifts in the NO2 vertical column densities and the NO2 surface concentrations retrieved with such an improved MAX-DOAS algorithm were supported by the independent direct-sun Pandora spectrometer observations, and in-situ measurements of cavity attenuated phase shift spectroscopy (CAPS), respectively. These comparisons result in more plausible a priori vertical profiles and, finally, the NO2 vertical profile retrievals with MAX-DOAS measurements are to be improved.
References
1. Lindenmaier et al. (2014) PNAS 111(23), 8386−8391.
2. Fujinawa et al. (2021) Geophys. Res. Lett. 48(14), e2021GL092685.
3. Kanaya et al. (2014) Atmos. Chem. Phys. 14(15), 7909−7927.
Here, we revisit the retrieval of NO2 vertical profiles with the ground-based MAX-DOAS observations. Observations of MAX-DOAS installed at JAMSTEC Yokosuka Headquarters in an urban area (Yokosuka, Kanagawa) indicate that the retrieved NO2 vertical column density depends significantly (up to ~18%) on the ‘a priori’ vertical profile required for the MAX-DOAS retrieval. When a priori vertical profiles assuming higher fractions of NO2 present in the lower atmosphere (0–1 km altitude range) are used, the NO2 column densities tend to be small, implying that the aforementioned bias between satellite and ground-based observations may be partly remedied. The shifts in the NO2 vertical column densities and the NO2 surface concentrations retrieved with such an improved MAX-DOAS algorithm were supported by the independent direct-sun Pandora spectrometer observations, and in-situ measurements of cavity attenuated phase shift spectroscopy (CAPS), respectively. These comparisons result in more plausible a priori vertical profiles and, finally, the NO2 vertical profile retrievals with MAX-DOAS measurements are to be improved.
References
1. Lindenmaier et al. (2014) PNAS 111(23), 8386−8391.
2. Fujinawa et al. (2021) Geophys. Res. Lett. 48(14), e2021GL092685.
3. Kanaya et al. (2014) Atmos. Chem. Phys. 14(15), 7909−7927.