Ca’ Foscari University of Venice, Dept. Environmental Sciences, Informatics and Statistics, via Torino, 155 – 8 30172 Venice-Mestre, Italy
Università degli Studi di Perugia, Dipartimento di Chimica, Biologia e Biotecnologie, Perugia, Italy
Abstract. Black Carbon (BC) is a major forcing agent in the Arctic but substantial uncertainty remains to quantify its climate effects due to the complexity of mechanisms involved. In this study, we provide unique information on processes driving the variability of BC mass concentration in surface snow in the Arctic. Two different snow-sampling strategies were adopted during spring 2014 and 2015, focusing on the refractory BC (rBC) mass Ny-Ålesund concentration daily/hourly variability on a seasonal/daily time scale (referred to as 80-days and 3-days experiments). Despite the low rBC mass concentrations (never exceeding 22 ng g−1), a daily variability of up to 4.5 ng g−1 was observed. Atmospheric, meteorological and snow-related physico-chemical parameters were considered in multiple statistical models to understand the factors behind the observed variation of rBC mass concentrations. Results indicate that the main drivers of the variation of rBC are the precipitations events, snow metamorphism (melting-refreezing cycles, surface hoar formation and sublimation) and the activation of local sources (wind resuspension) during the snow melting periods. The rBC in the snow seems de-coupled with the atmospheric BC load. Our results highlighted a common association of snow rBC with coarse mode particles number concentration and with snow precipitation events.
This preprint has been withdrawn.
How to cite. Bertò, M., Cappelletti, D., Barbaro, E., Varin, C., Gallet, J.-C., Markowicz, K., Rozwadowska, A., Mazzola, M., Crocchianti, S., Poto, L., Laj, P., Barbante, C., and Spolaor, A.: Black Carbon Seasonal and Diurnal Variation in surface
snow in Svalbard and its
Connections to Atmospheric Variables, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-574, 2020.
Received: 09 Jun 2020 – Discussion started: 08 Jul 2020
We present the daily and seasonal variability of Black carbon inferred from two specific experiment based on the hourly and daily time resolution sampling strategy. These unique datasets give us for the first time the opportunity to evaluate the associations between the observed surface snow rBC mass concentration and a set of predictors corresponding to the considered meteorological and snow physico-chemical parameters, via a multiple linear regression approach.
We present the daily and seasonal variability of Black carbon inferred from two specific...