Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Atmos. Chem. Phys., 14, 5969-5987, 2014
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
18 Jun 2014
Estimation of aerosol water and chemical composition from AERONET Sun–sky radiometer measurements at Cabauw, the Netherlands
A. J. van Beelen1, G. J. H. Roelofs1, O. P. Hasekamp2, J. S. Henzing3, and T. Röckmann1 1Institute for Marine and Atmospheric research Utrecht (IMAU), P.O. Box 80005, Utrecht University, Utrecht, the Netherlands
2Netherlands Institute for Space Research (SRON), Sorbonnelaan 2, 3584 CA Utrecht, the Netherlands
3Netherlands Organisation for Applied Scientific Research, TNO, P.O. Box 80015, Utrecht, the Netherlands
Abstract. Remote sensing of aerosols provides important information on atmospheric aerosol abundance. However, due to the hygroscopic nature of aerosol particles observed aerosol optical properties are influenced by atmospheric humidity, and the measurements do not unambiguously characterize the aerosol dry mass and composition, which complicates the comparison with aerosol models. In this study we derive aerosol water and chemical composition by a modeling approach that combines individual measurements of remotely sensed aerosol properties (e.g., optical thickness, single-scattering albedo, refractive index and size distribution) from an AERONET (Aerosol Robotic Network) Sun–sky radiometer with radiosonde measurements of relative humidity. The model simulates water uptake by aerosols based on the chemical composition (e.g., sulfates, ammonium, nitrate, organic matter and black carbon) and size distribution. A minimization method is used to calculate aerosol composition and concentration, which are then compared to in situ measurements from the Intensive Measurement Campaign At the Cabauw Tower (IMPACT, May 2008, the Netherlands). Computed concentrations show good agreement with campaign-average (i.e., 1–14 May) surface observations (mean bias is 3% for PM10 and 4–25% for the individual compounds). They follow the day-to-day (synoptic) variability in the observations and are in reasonable agreement for daily average concentrations (i.e., mean bias is 5% for PM10 and black carbon, 10% for the inorganic salts and 18% for organic matter; root-mean-squared deviations are 26% for PM10 and 35–45% for the individual compounds). The modeled water volume fraction is highly variable and strongly dependent on composition. During this campaign we find that it is >0.5 at approximately 80% relative humidity (RH) when the aerosol composition is dominated by hygroscopic inorganic salts, and <0.1 when RH is below 40%, especially when the composition is dominated by less hygroscopic compounds such as organic matter. The scattering enhancement factor (f(RH), the ratio of the scattering coefficient at 85% RH and its dry value at 676 nm) during 1–14 May is 2.6 ± 0.5. The uncertainty in AERONET (real) refractive index (0.025–0.05) is the largest source of uncertainty in the modeled aerosol composition and leads to an uncertainty of 0.1–0.25 (50–100%) in aerosol water volume fraction. Our methodology performs relatively well at Cabauw, but a better performance may be expected for regions with higher aerosol loading where the uncertainties in the AERONET inversions are smaller.

Citation: van Beelen, A. J., Roelofs, G. J. H., Hasekamp, O. P., Henzing, J. S., and Röckmann, T.: Estimation of aerosol water and chemical composition from AERONET Sun–sky radiometer measurements at Cabauw, the Netherlands, Atmos. Chem. Phys., 14, 5969-5987, doi:10.5194/acp-14-5969-2014, 2014.
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