Comparison of different Aethalometer correction schemes and a reference multi-wavelength absorption technique for ambient aerosol data

Abstract

Abstract. Deriving absorption coefficients from Aethalometer attenuation data requires different corrections to compensate for artifacts related to filter-loading effects, scattering by filter fibers, and scattering by aerosol particles. In this study, two different correction schemes were applied to seven-wavelength Aethalometer data, using multi-angle absorption photometer (MAAP) data as a reference absorption measurement at 637 nm. The compensation algorithms were compared to five-wavelength offline absorption measurements obtained with a multi-wavelength absorbance analyzer (MWAA), which serves as a multiple-wavelength reference measurement. The online measurements took place in the Amazon rainforest, from the wet-to-dry transition season to the dry season (June-September 2014). The mean absorption coefficient (at 637 nm) during this period was 1.8 ± 2.1 Mm −1 , with a maximum of 15.9 Mm −1 . Under these conditions, the filter-loading compensation was negligible. One of the correction schemes was found to artificially increase the short-wavelength absorption coefficients. It was found that accounting for the aerosol optical properties in the scattering compensation significantly affects the absorption Ångström exponent (å ABS ) retrievals. Proper Aethalometer data compensation schemes are crucial to retrieve the correct å ABS , which is commonly implemented in brown carbon contribution calculations. Additionally, we found that the wavelength dependence of uncompensated Aethalometer attenuation data significantly correlates with the å ABS retrieved from offline MWAA measurements.

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 2: Variability and characteristic differences under near-pristine, biomass burning, and long-range transport conditions

“…2c) reveals equally strong Aiken and accumulation modes as well as a 'patchy' appearance, due to frequent 25 rainfall causing (local) aerosol scavenging. As outlined in our part 1 study, the aerosol abundance in the particle size range >40 nm predominantly defined the measured CCN population (M. Pöhlker et al, 2016). Accordingly, the NCCN(S) and NCCN(S)/NCN time series directly track the SMPS-derived patchy pattern.…”

“…A detailed description of the operation of the CCN counter (CCNC) and the subsequent data analysis can be 35 found in the companion paper (M. Pöhlker et al, 2016), which is the basis for the present study. For further CCN-relevant information, we refer the reader to Rose et al (2008) and Krüger et al (2014).…”

“…In summary, the overall purpose of this study is to link The present study is mostly based on in situ measurements at the remote ATTO site, which has been described in detail by Andreae et al (2015). Further relevant information regarding the site, the measurement period, and the aerosol and trace gas instrumentation can be found in the part 1 paper by M. Pöhlker et al (2016). Note that the 5 time frame of the present analysis including the four in-depth case studies overlapped with the two intensive observation periods (IOPs) of international Green Ocean Amazon 2014/5 (GoAmazon2014/5) campaign (Martin et al, 2016a;.…”

“…Therefore, we conducted a systematic characterization of the trends and properties of the central Amazonian CCN pop-30 ulation at the Amazon tall tower observatory (ATTO) site. The first half of this study has been published recently as part 1 (M. Pöhlker et al, 2016). The present manuscript represents part 2 of this endeavor and focuses on the variability and properties of periods that are characteristic for the Amazonian atmosphere.…”

“…The part 1 paper (M. Pöhlker et al, 2016) focuses on the multi-month trends in the Amazonian CCN population by presenting data from a full seasonal cycle. In particular, it presents annually averages of the key CCN parameters, a detailed analysis of the specific seasonal as well as diurnal trends and a systematic analysis of different CCN parametrization schemes to represent the Amazonian CCN cycling in modeling studies.…”