Variability of Atmospheric Radon-222 and Secondary Aerosol Components in Accordance with Air Mass Transport Pathways at Jeju Island, Korea, during 2011-2014

2016 ◽  
Vol 37 (6) ◽  
pp. 841-846
Author(s):  
Jun-Oh Bu ◽  
Jung-Min Song ◽  
Won-Hyung Kim ◽  
Chang-Hee Kang ◽  
Scott D. Chambers ◽  
...  
2006 ◽  
Vol 37 (12) ◽  
pp. 1809-1825 ◽  
Author(s):  
Ki-Hyun Kim ◽  
Chang-Hee Kang ◽  
Jin-Hong Lee ◽  
Kum-Chan Choi ◽  
Yong-Hoon Youn ◽  
...  

2017 ◽  
Author(s):  
Bin Chen ◽  
Bärbel Vogel ◽  
Xiangde Xu ◽  
Shuai Yang

Abstract. The Asian summer monsoon (ASM) is associated with an upper-level anticyclone and acts as a well-recognized conduit for troposphere-to-stratosphere transport. The Lagrangian dispersion and transport model FLEXPART forced by ERA-Interim data from 2001–2013 was used to perform climatological modeling of the summer season (May–July). This study examines the properties of the air mass transport from the atmospheric boundary layer (BL) to the tropopause layer (TL), with particular focus on the sub-seasonal variability in the tracer-independent BL sources and the potential controlling mechanisms. The results show that, climatologically, the three most impactful BL source regions are northern India, the Tibetan Plateau, and the southern slope of the Himalayas. These regions are consistent with the locations of sources identified in previous studies. However, upon closer inspection, the different source regions to the BL-to-TL air mass transport are not constant in location or shape and are strongly affected by sub-seasonal variability. The contributions from the Tibetan Plateau are most significant in early May but decrease slightly in mid-May to mid-June. In contrast, the contributions from India and the southern slope of the Himalayas increase dramatically, with peak values occurring in mid-July. Empirical Orthogonal Function (EOF) analysis provides further evidence that the BL sources in the ASM region vary across a wide range of spatiotemporal scales. The sub-seasonal behavior of these BL sources is closely related to the strength of persistent deep convection activity over the northern Bay of Bengal and its neighboring areas.


2011 ◽  
Vol 11 (12) ◽  
pp. 33465-33509 ◽  
Author(s):  
J. P. Zhang ◽  
T. Zhu ◽  
Q. H. Zhang ◽  
C. C. Li ◽  
H. L. Shu ◽  
...  

Abstract. This study investigated the air pollution characteristics of synoptic-scale circulation in the Beijing megacity, and provided holistic evaluation of the impacts of circulation patterns on air quality during the 2008 Beijing Summer Olympics. Nine weather circulation types (CTs) were objectively identified over the North China region during 2000–2009, using obliquely rotated T-mode principal component analysis (PCA). The resulting CTs were examined in relation to the local meteorology, regional transport pathways, and air quality parameters, respectively. The FLEXPART-WRF model was used to calculate 48-h backward plume trajectories for each CT. Nine CTs were characterized, with distinct local meteorology and air mass origins. CT 1 (high to the west with a strong pressure gradient) was characterized by a northwestern origin, with the smallest local and southeasterly air mass sources, and CT 6 (high to the northwest) had air mass sources mostly from the north and east. In contrast, CTs 5, 8, and 9 (unique, high to the east, and low to the northwest, respectively) were characterized by southern and southeastern trajectories, which indicated a greater influence of high pollutant emission sources. In turn, poor air quality in Beijing (high loadings of PM10, BC, SO2, NO2, O3, AOD, and low visibility) was associated with these CTs. Good air quality in Beijing was associated with CTs 1 and 6. The average visibilities (with ±1 σ) in Beijing for CTs 1 and 6 during 2000–2009 were 18.5 ± 8.3 km and 14.3 ± 8.5 km, respectively. In contrast, poor visibility values of 6.0 ± 3.5 km, 6.6 ± 3.7 km, and 6.7 ± 3.6 km were found in CTs 5, 8, and 9, respectively. The mean concentrations of PM10 for CTs 1, 6, 5, 8, and 9 during 2005–2009 were 90.3 ± 76.3 μg m−3, 111.7 ± 89.6 μg m−3, 173.4 ± 105.8 μg m−3, 158.4 ± 90.0 μg m−3, and 151.2 ± 93.1 μg m−3, respectively. Analysis of the relationship between circulation pattern and air quality during the emission control period suggests that CTs are the primary drivers of day-to-day variations in pollutant concentrations over Beijing and its vicinity. During the Olympics period, the frequency of CT 6 was twice that of the mean in August from 2000 to 2009. This CT had northerly transport pathways and favorable meteorological conditions (e.g. frequent precipitation) for clean air during the Olympics. Assuming that relationships between CTs and air quality parameters in the same season (month) were constant in different years, the relative contributions of synoptic circulation to decreases in PM10, BC, SO2, NO2, CO, AOD, and horizontal light extinction during the Olympics were estimated as 19 ± 14%, 18 ± 13%, 41 ± 36%, 12 ± 7%, 19 ± 11%, 25 ± 28%, and 50 ± 46%, respectively.


2021 ◽  
Author(s):  
Meike Rotermund ◽  
Vera Bense ◽  
Martyn Chipperfield ◽  
Andreas Engel ◽  
Jens-Uwe Grooß ◽  
...  

<p>We report on measurements of total bromine (Br<sup>tot</sup>) in the upper troposphere and lower stratosphere (UTLS) taken from the German High Altitude and LOng range research aircraft (HALO) over the North Atlantic, Norwegian Sea and north-western Europe in September/ October 2017 during the WISE (Wave-driven ISentropic Exchange) research campaign. Br<sup>tot</sup> is calculated from measured total organic bromine (Br<sup>org</sup>) (i.e., the sum of bromine contained in CH<sub>3</sub>Br, the halons and the major very short-lived brominated substances) added to inorganic bromine (Br<sub>y</sub><sup>inorg</sup>), evaluated from measured BrO and photochemical modelling. Combining these data, the weighted mean [Br<sup>tot</sup>] is 19.2 ± 1.2 ppt in the extratropical lower stratosphere (Ex-LS) of the northern hemisphere. The inferred average Br<sup>tot</sup> for the Ex-LS is slightly smaller than expected for the middle stratosphere in 2016 (~19.6 ppt (ranging from 19-20 ppt) as reported by the WMO/UNEP Assessment (2018)). However, it reflects the expected variability in Br<sup>tot</sup> in the Ex-LS due to influxes of shorter lived brominated source and product gases from different regions of entry. A closer look into Br<sup>org</sup> and Br<sub>y</sub><sup>inorg</sup> as well as simultaneously measured transport tracers (CO, N<sub>2</sub>O, ...) and an air mass lag-time tracer (SF<sub>6</sub>), suggests that a filament of air with elevated Br<sup>tot</sup> protruded into the extratropical lowermost stratosphere (Ex-LMS) from 350-385 K and between equivalent latitudes of 55-80˚N (high bromine filament – HBrF). Lagrangian transport modelling shows the multi-pathway contributions to Ex-LMS bromine. According to CLaMS air mass origin simulations, contributions to the HBrF consist of predominantly isentropic transport from the tropical troposphere (also with elevated [Br<sup>tot</sup>] = 21.6 ± 0.7 ppt) as well as a smaller contribution from an exchange across the extratropical tropopause which are mixed into the stratospheric background air. In contrast, the surrounding LS above and below the HBrF has less tropical tropospheric air, but instead additional stratospheric background air. Of the tropical tropospheric air in the HBrF, the majority is from the outflow of the Asian monsoon anticyclone and the adjacent tropical regions, which greatly influences concentrations of trace gases transported into the Ex-LMS in boreal summer and fall. The resulting increase of Br<sup>tot</sup> in the Ex-LMS and its consequences for ozone is investigated through the TOMCAT/SLIMCAT model simulations. However, more extensive monitoring of total stratospheric bromine in more aged air (i.e., in the middle stratosphere) as well as globally and seasonally is required in addition to model simulations to fully understand its impact on Ex-LMS ozone and the radiative forcing of climate.</p>


2019 ◽  
Vol 40 (2) ◽  
pp. 782-794 ◽  
Author(s):  
Yafei Li ◽  
Rongcai Ren ◽  
Ming Cai ◽  
Yueyue Yu
Keyword(s):  

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