Influence of stratospheric air masses on radiotracers and ozone over the central Mediterranean

Abstract

This work aims at determining the characteristics and the preferred source regions of stratospheric air masses at the Mt. Cimone World Meteorological Organization‐Global Atmosphere Watch station located in the Italian northern Apennines (44°11′N, 10°42′E, 2165 m above sea level) , a site which is considered representative of Southern Europe‐Mediterranean free troposphere. Source regions of high concentrations of 7Be, 7Be/210Pb, and O3 and regions originating high potential vorticity values are analyzed by means of trajectory statistical methods applied over the time series collected in the period of 1998–2011 to this aim. Our analysis points out the frequent occurrence of stratosphere‐to‐troposphere exchange in the North America and northern Atlantic region, which can be linked to the usual location of the polar‐front and subtropical jet streams in these two regions, but also to the tropopause discontinuity and to the high cyclogenetic activity in the Atlantic region. High 7Be concentrations associated with trajectories of high‐latitude origin descend from high altitudes to the study site, while at midlatitudes trajectories arrive from relatively lower levels. The geographical distribution of the tropopause crossing of air masses before arriving the study site points out particularly to Greenland. Our results also suggest the importance of the interaction between upper level disturbances and the Alps mountain range as a driver for stratosphere‐to‐troposphere exchange. In this case, the time between the tropopause crossing and the arrival at the elevated study site is less than 24 h and frequently below 6 h. The Atlas range in northern Africa plays a similar role though with lower influence.

Spatio-temporal variations and factors of a provincial PM2.5 pollution in eastern China during 2013–2017 by geostatistics

“…The spatial patterns were similar, and the source areas with higher contribution rate were mainly distributed in neighboring provinces such as Anhui, Shandong, Zhejiang provinces, etc., indicating the significance of pollution in the nearby area 37 . In addition, due to the long-range air mass transport, the contribution values of Inner Mongolia, Hebei, Gansu, Ningxia, Guangdong and Fujian provinces reached 0.5–0.8, which increased the pollutant concentrations in the study area 40 . It should be noted that the PSCF analysis did not estimate the spatial distribution of all sources.…”

“…PSCF was a trajectory-based gridded statistical analysis method that can obtain the spatial distribution of pollution sources in a semi-quantitative manner 40 . The basic concept of PSCF was to combine the air mass trajectory with the atmospheric component data to generate a conditional probability in a given region which was divided into i*j small grids.…”

Year-round record of near-surface ozone and O<sub>3</sub> enhancement events (OEEs) at Dome A, East Antarctica

“…Then, in the same way, the residence time over each i, j grid cell corresponding to a measurement period under an OEE was calculated (mij). The PSCF for grid cell i, j was then computed according to Brattich et al (2017): 305 The results are shown in Figure 6, which clearly highlights the connection between the occurrence of OEEs at DA and air masses travelling over the eastern Antarctic Plateau. The PSCF values ranged from 40% to 80% in the DA region, while air masses advected from the East Antarctic Plateau were characterized by high PSCF values.…”

“…Drawing on the algorithm suggested in previous studies (e.g., Brattich et al, 2017), the potential 345 vorticity and ozone mixing ratio of different pressure altitudes (hPa) at 0:00, 6:00, 12:00, and 18:00 every day were analysed during polar night (May, Jun, July, August) at DA. If the potential vorticity of 550 hPa height over DA was greater than 2 PVU, it was considered an STT event.…”

“…To investigate the possible influence of synoptic-scale air mass circulation on the occurrence of OEEs at DA, 5-day HYSPLIT back trajectories were applied (Figure 6). In particular, we used the PSCF to calculate the conditional probabilities and identify the geographical regions related to the occurrence of OEEs atDA (e.g., Hopke et al, 1995;Brattich et al, 2017). The residence time over each i, j grid cell of the back-trajectory spatial domain (discretized into square grid cells of 0.5°× 0.5°) 300…”