Journal
ATMOSPHERIC MEASUREMENT TECHNIQUES
Volume 4, Issue 6, Pages 1027-1044Publisher
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/amt-4-1027-2011
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Funding
- ESA [22202/09/I-EC]
- EU [GOCE-CT-2004-505337, FP6-2005-Global-4-036677]
- Ministry of Education, Culture, Sports, Science and Technology (MEXT) [20710021, 22710026]
- Ministry of the Environment, Japan [S-7]
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We attempt for the first time to retrieve lower-tropospheric vertical profile information for 8 quantities from ground-based Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations. The components retrieved are the aerosol extinction coefficients at two wavelengths, 357 and 476 nm, and NO2, HCHO, CHOCHO, H2O, SO2, and O-3 volume mixing ratios. A Japanese MAX-DOAS profile retrieval algorithm, version 1 (JM1), is applied to observations performed at Cabauw, the Netherlands (51.97 degrees N, 4.93 degrees E), in June-July 2009 during the Cabauw Intercomparison campaign of Nitrogen Dioxide measuring Instruments (CINDI). Of the retrieved profiles, we focus here on the lowest-layer data (mean values at altitudes 0-1 km), where the sensitivity is usually highest owing to the longest light path. In support of the capability of the multi-component retrievals, we find reasonable overall agreement with independent data sets, including a regional chemical transport model (CHIMERE) and in situ observations performed near the surface (2-3 m) and at the 200-m height level of the tall tower in Cabauw. Plumes of enhanced HCHO and SO2 were likely affected by biogenic and ship emissions, respectively, and an improvement in their emission strengths is suggested for better agreement between CHIMERE simulations and MAX-DOAS observations. Analysis of air mass factors indicates that the horizontal spatial representativeness of MAX-DOAS observations is about 3-15 km (depending mainly on aerosol extinction), comparable to or better than the spatial resolution of current UV-visible satellite observations and model calculations. These demonstrate that MAX-DOAS provides multi-component data useful for the evaluation of satellite observations and model calculations and can play an important role in bridging different data sets having different spatial resolutions.
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