Urban background levels of particle number concentration and sources in Vilnius, Lithuania

Byčenkienė, Steigvilė; Plauškaitė, Kristina; Dudoitis, Vadimas; Ulevičius, Vidmantas

doi:10.1016/j.atmosres.2014.02.019

Cited by 39 publications

(17 citation statements)

References 70 publications

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“…This is due to anthropogenic activities; a higher concentration of aerosols is reported when the sources are in Russia, Central Europe, and Eastern Europe [87]. Heavily industrialized areas in Germany, the Czech Republic, and Poland are also sources of high particle number concentrations [88]. Consequently, for the study area, the high water content and low CCN in western and southern circulation forces water particles to condensate on a smaller number of nuclei and makes rain drops comparatively large.…”

Section: Rain Microstructurementioning

confidence: 99%

Rain Microstructure Parameters Vary with Large-Scale Weather Conditions in Lausanne, Switzerland

et al. 2018

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Rain properties vary spatially and temporally for several reasons. In particular, rain types (convective and stratiform) affect the rain drop size distribution (DSD). It has also been established that local weather conditions are influenced by large-scale circulations. However, the effect of these circulations on rain microstructures has not been sufficiently addressed. Based on DSD measurements from 16 disdrometers located in Lausanne, Switzerland, we present evidence that rain DSD differs among general weather patterns (GWLs). GWLs were successfully linked to significant variations in the rain microstructure characterized by the most important rain properties: rain intensity (R), mass weighted rain drop diameter (D m ), and rain drop concentration (N), as well as Z = AR b parameters. Our results highlight the potential to improve radar-based estimations of rain intensity, which is crucial for several hydrological and environmental applications.

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Section: Rain Microstructurementioning

confidence: 99%

Rain Microstructure Parameters Vary with Large-Scale Weather Conditions in Lausanne, Switzerland

et al. 2018

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“…As can be seen, the differences in ambient BC levels may be caused by different sampling location and season as well as different emission sources. It was concluded that annual mean BC aerosol mass concentrations in Vilnius were significantly higher than those measured at coastal/marine and rural environments as domestic biofuel use, transportation and industry sectors are important emission sources in Vilnius [26]. ) in urban background environment [32].…”

Section: Seasonal and Diurnal Variationsmentioning

confidence: 99%

“…However, the sources of OC still cannot be estimated accurately. In Lithuania, few studies have been carried out on BC measurements with a view to assess their pollution events and annual variation of BC mass concentration [26,27]. There have not been previous long-term OC measurements.…”

Section: Introductionmentioning

confidence: 99%

Spatial and Temporal Analysis of Organic and Black Carbon Mass Concentrations in Lithuania

et al. 2015

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Both organic carbon (OC) and black carbon (BC) mass concentrations were measured in Lithuania at coastal/marine (Preila), rural (Rūgšteliškis), and urban background (Vilnius) environments have been analyzed to infer the spatial and temporal distributions of the OC/BC ratios from May 2013 to October 2014. OC/BC ratios reflected the location of the different sites, as well as possible different sources influencing air quality. The results from an industrialized and populated urban background area indicated that biomass combustion for heating contributed to BC and OC mass concentration. Typically, BC mean concentrations (±st.deviation) were higher in urban areas (1.72(±1.22 μg·m )) during warm periods. The air mass backward trajectory analysis indicated influence of local sources in urban environment and strong influence of long-range transport in rural environment. A clear seasonal dependence of OC/BC ratios was observed at rural and urban environments. The highest OC/BC ratios were calculated in coastal/marine (6.3) and rural (9.5) environments in summer.

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“…The PSCF was the conditional probability that a parcel with a certain level of pollutant concentrations arrived at a receptor site after having passed through a specific upwind source area (Hwang and Hopke, 2007;Byčenkienė et al, 2014). The zone of concern was divided into i × j small equal grid cells.…”

Section: The Weight Potential Source Contribution Function (Wpscf) Anmentioning

confidence: 99%

Analysis of Long-Range Transport Effects on PM2.5 during a Short Severe Haze in Beijing, China

Yang

Guochen

2017

Aerosol Air Qual. Res.

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Comprehensively using Inverse Distance Weighted (IDW) analysis, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, three-dimensional (3D) cluster analysis, Weight Potential Source Concentration Function (WPSCF) analysis and other statistic methods, we mainly studied about the spatio-temporal variation, long-range transport and potential source regions of PM 2.5 in Beijing during a short severe haze from Dec05 to Dec11, 2015. The results showed that the concentration of PM 2.5 decreased from south to north of Beijing. PM 2.5 accumulation in the short-severe haze had high correlation with calm and steady meteorological condition (high relative humidity (RH), low wind speed (WS), low boundary-layer temperature (BLT) and surface air pressure (SAP)). In addition, air-flow in different heights (500 m, 1500 m and 3000 m) had different effects on the haze episode and the air flows at 500 m had the greatest contribution of the air pollution. The potential sources were mainly from the desert in northwest of Beijing and the built-up areas in Jing-Jin-Ji zone. Higher WPSCF values (> 0.7) were mainly distributed in Hebei, west Shandong province (around 0.5) and south Tianjin (around 0.5).

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Urban background levels of particle number concentration and sources in Vilnius, Lithuania

Cited by 39 publications

References 70 publications

Rain Microstructure Parameters Vary with Large-Scale Weather Conditions in Lausanne, Switzerland

Rain Microstructure Parameters Vary with Large-Scale Weather Conditions in Lausanne, Switzerland

Spatial and Temporal Analysis of Organic and Black Carbon Mass Concentrations in Lithuania

Analysis of Long-Range Transport Effects on PM2.5 during a Short Severe Haze in Beijing, China

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