Mass absorption cross-section and absorption enhancement from long term black and elemental carbon measurements: A rural background station in Central Europe

Abstract

Black carbon (BC) is a dominant aerosol light absorber, and its brown carbon (BrC) coating can enhance absorption and lead to uncertainties concerning the radiative forcing estimation. This study investigates the mass absorption cross-section of equivalent BC (MAC eBC ) during a long-term field measurement (2013–2017) at a rural Central European site. The MAC enhancement factor (E abs ) and the contribution of BrC coatings to the absorption coefficient (B abs ) were estimated by combining different approaches. The annual mean B abs and MAC eBC values decreased slightly over the measurement period associated with change in the submicron aerosol size distribution. Regardless of the wavelength, B abs exhibited clear seasonal and diurnal variations, with higher values in winter when a higher absorption Ångström exponent (1.4) was observed due to the local biomass burning (BB). In contrast, MAC eBC did not have a distinct temporal trend at 600 nm (7.84 ± 2.79 m 2 g −1 ), while it showed a seasonal trend at 370 nm with higher values in winter (15.64 ± 4.77 m 2 g −1 ). During this season, E abs_660 was 1.18 ± 0.27 and did not exhibit any clear wavelength dependence, despite the influence of BB. During the study period, BrC-attributed absorption was observed in 31% of the samples, with a contribution of up to 40% of total B abs . In summer, the E abs_660 increased to 1.59 ± 0.60, when a larger BC coating could be formed by secondary aerosol fractions. During this season, MAC eBC_660 and E abs_660 showed comparable source profiles that were mainly associated with aged air masses over central Europe, thereby supporting the fact that characteristics of coating materials formed during atmospheric aging are a major factor driving the MAC eBC_660 measured at the regional background site. Further field investigations of the composition of BC coatings would help to better understand and estimate uncertainties related to the radiative effect of aerosols.

Different approaches to explore the impact of COVID-19 lockdowns on carbonaceous aerosols at a European rural background site

“…S6) and the concomitant influence of traffic and domestic activities, e.g. local residential biomass burning, particularly in winter ( Mbengue et al, 2018 , Mbengue et al, 2020 , Mbengue et al, 2021 ). EC and OC reached minima in the noon/afternoon when the MLH and VC are at their maximum height (Fig.…”

“…One of the main Czech highways (40,756 cars/day, CSD, 2016 ) is approximately 6 km north and northeast. NAOK is affected by regional and long-distance transported air masses, mainly associated with western and southeastern winds ( Dvorská et al, 2015 ; Mbengue et al, 2018 , Mbengue et al, 2020 , Mbengue et al, 2021 ; Schwarz et al, 2016 ; Vodička et al, 2015 ).

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“…2 ). Part of this work has previously been published ( Mbengue et al, 2018 , Mbengue et al, 2020 , Mbengue et al, 2021 ; Schwarz et al, 2016 ; Vodička et al, 2015 ). In late 2019, a second OCEC analyzer was placed in a sampling container on top of the tower (230 m a.g.l) and measurements were performed simultaneously with ground measurements from December 2019 to June 2021.…”

“…The AMBTs were calculated every 6 h using the HYSPLIT_4 model and meteorological data from the Global Data Assimilation System (GDAS) archive information with a resolution of 1° × 1° ( Rolph et al, 2017 ; Stein et al, 2015 ). Details regarding the CBPF and PSCF can be found in our previous studies ( Mbengue et al, 2020 , Mbengue et al, 2021 ; Zíková et al, 2016 ).…”

AERO-MAP: A data compilation and modelling approach to understand spatial variability in fine and coarse mode aerosol composition

“…In addition to particulate matter in the PM10 and PM2.5 size fractions, we also compile the following observations to compare to the model: black carbon (BC), elemental carbon (EC), organic carbon (OC) (or particulate organic material, OM, that is here considered to be 1.8 x OC in mass), sulfate, nitrate, aluminum, sodium and chloride. To include both BC (based on light absorption measurements) and EC (based on thermal oxidation induced combustion measurements) data are also a source of uncertainty, both are proxies of the soot combustion particles since they are based on different measurements techniques, and there is no accepted equivalence between them (Mbengue et al, 2021). Details on how the model is compared to data for different elements is in section 3.2.…”