The interaction of aerosol with atmospheric water affects the processing and wet removal of atmospheric particles. Understanding such interaction is mandatory to improve model description of aerosol lifetime and ageing. We analyzed the aerosol–water interaction at high relative humidity during fog events in the Po Valley within the framework of the Agenzia Regionale per la Prevenzione e l'Ambiente (ARPA) – Emilia Romagna supersite project. For the first time in this area, the changes in particle chemical composition caused by fog are discussed along with changes in particle microphysics. During the experiment, 14 fog events were observed. The average mass scavenging efficiency was 70% for nitrate, 68% for ammonium, 61% for sulfate, 50% for organics, and 39% for black carbon. After fog formation, the interstitial aerosol was dominated by particles smaller than 200 nm Dva (vacuum aerodynamic diameter) and enriched in carbonaceous aerosol, mainly black carbon and water-insoluble organic aerosol. For each fog event, the size-segregated scavenging efficiency of nitrate and organic aerosol (OA) was calculated by comparing chemical species size distribution before and after fog formation. For both nitrate and OA, the size-segregated scavenging efficiency followed a sigmoidal curve, with values close to zero below 100 nm Dva and close to 1 above 700 nm Dva. OA was able to affect scavenging efficiency of nitrate in particles smaller than 300 nm Dva. A linear correlation between nitrate scavenging and particle hygroscopicity (κ) was observed, indicating that 44–51% of the variability of nitrate scavenging in smaller particles (below 300 nm Dva) was explained by changes in particle chemical composition. The size-segregated scavenging curves of OA followed those of nitrate, suggesting that organic scavenging was controlled by mixing with water-soluble species. In particular, functional group composition and OA elemental analysis indicated that more oxidized OA was scavenged more efficiently than less oxidized OA. Nevertheless, the small variability of organic functional group composition during the experiment did not allow us to discriminate the effect of different organic functionalities on OA scavenging.

We present results from a systematic study of vertical profiles of aerosol number size distribution and black carbon (BC) concentrations conducted in the Arctic, over Ny-Ålesund (Svalbard). The campaign lasted 2 years (2011–2012) and resulted in 200 vertical profiles measured by means of a tethered balloon (up to 1200 m a.g.l.) during the spring and summer seasons. In addition, chemical analysis of filter samples, aerosol size distribution and a full set of meteorological parameters were determined at ground. The collected experimental data allowed a classification of the vertical profiles into different typologies, which allowed us to describe the seasonal phenomenology of vertical aerosol properties in the Arctic. During spring, four main types of profiles were found and their behavior was related to the main aerosol and atmospheric dynamics occurring at the measuring site. Background conditions generated homogenous profiles. Transport events caused an increase of aerosol concentration with altitude. High Arctic haze pollution trapped below thermal inversions promoted a decrease of aerosol concentration with altitude. Finally, ground-based plumes of locally formed secondary aerosol determined profiles with decreasing aerosol concentration located at different altitude as a function of size. During the summer season, the impact from shipping caused aerosol and BC pollution plumes to be constrained close to the ground, indicating that increasing shipping emissions in the Arctic could bring anthropogenic aerosol and BC in the Arctic summer, affecting the climate.

Moderate-Resolution Imaging spectroradiometer (MODIS) land surface temperatures in Antarctica were processed in order to produce a gridded data set at 25 km resolution, spanning the period 2000–2011 at an hourly time step. The Aqua and Terra orbits and MODIS swath width, combined with frequent clear-sky conditions, lead to very high availability of quality-controlled observations: on average, hourly data are available 14 h per day at the grid points around the South Pole and more than 9 h over a large area of the Antarctic Plateau. Processed MODIS land surface temperatures, referred to hereinafter as MODIS Ts values, were compared with in situ hourly measurements of surface temperature collected over the entirety of the year 2009 by seven stations from the Baseline Surface Radiation Network (BSRN) and automatic weather stations (AWSs). In spite of an occasional failure in the detection of clouds, MODIS Ts values exhibit a good performance, with a bias ranging from −1.8 to 0.1 °C and errors ranging from 2.2 to 4.8 °C root mean square at the five stations located on the plateau. These results show that MODIS Ts values can be used as a precise and accurate reference to test other surface temperature data sets. Here, we evaluate the performance of surface temperature in the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis known as ERA-Interim reanalysis. During conditions detected as cloud free by MODIS, ERA-Interim shows a widespread warm bias in Antarctica in every season, ranging from +3 to +6 °C on the plateau. This confirms a recent study which showed that the largest discrepancies in 2 m air temperature between ERA-Interim and the global temperature data set HadCRUT4 compiled by the Met Office Hadley Centre and the University of East Anglia's Climatic Research Unit occur in Antarctica. A comparison with in situ surface temperature shows that this bias is not strictly limited to clear-sky conditions. A detailed comparison with stand-alone simulations by the Crocus snowpack model, forced by ERA-Interim, and with the ERA-Interim/land simulations, shows that the warm bias may be due primarily to an overestimation of the surface turbulent fluxes in very stable conditions. Numerical experiments with Crocus show that a small change in the parameterization of the effects of stability on the surface exchange coefficients can significantly impact the snow surface temperature. The ERA-Interim warm bias appears to be likely due to an overestimation of the surface exchange coefficients under very stable conditions.