Spatial and seasonal variability of carbonaceous aerosol across Italy

Sandrini, Silvia; Fuzzi, S.; Piazzalunga, A.; Prati, P.; Bonasoni, Paolo; Cavalli, F.; Bove, Maria Chiara; Calvello, Mariarosaria; Cappelletti, David; Colombi, Cristina; Contini, Daniele; Gennaro, Gianluigi de; Gilio, Alessia Di; Fermo, P.; Ferrero, Luca; Gianelle, V.; Giugliano, Michèle; Ielpo, Pierina; Lonati, Giovanni; Marinoni, Angela; Massabò, Dario; Molteni, Ugo; Moroni, Beatrice; Pavese, G.; Perrino, Cinzia; Perrone, Maria Grazia; Perrone, Maria Rita; Putaud, Jean Philippe; Sargolini, Tiziana; Vecchi, R.; Gilardoni, Stefania

doi:10.1016/j.atmosenv.2014.10.032

Cited by 146 publications

(88 citation statements)

References 61 publications

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“…The two sites present very different characteristics regarding the magnitude, the distribution and the composition of the aerosol fraction and the climatic characteristics. In particular, Oga San Colombano shows a higher relative contribution of organic aerosol, likely of secondary origin, as suggested by a higher organic to elemental carbon ratio (Sandrini et al, 2014). Milan shows a higher nitrate to sulfate ratio, in agreement with a stronger impact from combustion sources such as traffic and industrial emissions (Perrone, 2012).…”

Section: Datasets and Instrumentationsupporting

confidence: 50%

On the functional form of particle number size distributions: influence of particle source and meteorological variables

et al. 2018

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Abstract. Particle number size distributions (PNSDs) have been collected periodically in the urban area of Milan, Italy, during 2011 and 2012 in winter and summer months. Moreover, comparable PNSD measurements were carried out in the rural mountain site of Oga-San Colombano (2250 m a.s.l.), Italy, during February 2005 and August 2011. The aerosol data have been measured through the use of optical particle counters in the size range 0.3-25 µm, with a time resolution of 1 min. The comparison of the PNSDs collected in the two sites has been done in terms of total number concentration, showing higher numbers in Milan (often exceeding 10 3 cm −3 in winter season) compared to Oga-San Colombano (not greater than 2×10 2 cm −3 ), as expected. The skewness-kurtosis plane has been used in order to provide a synoptic view, and select the best distribution family describing the empirical PNSD pattern. The four-parameter Johnson system-bounded distribution (called Johnson SB or JSB) has been tested for this aim, due to its great flexibility and ability to assume different shapes. The PNSD pattern has been found to be generally invariant under site and season changes. Nevertheless, several PNSDs belonging to the Milan winter season (generally more than 30 %) clearly deviate from the standard empirical pattern. The seasonal increase in the concentration of primary aerosols due to combustion processes in winter and the influence of weather variables throughout the year, such as precipitation and wind speed, could be considered plausible explanations of PNSD dynamics.

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Section: Datasets and Instrumentationsupporting

confidence: 50%

On the functional form of particle number size distributions: influence of particle source and meteorological variables

et al. 2018

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“…PM 2.5 중 탄소성 입자는 크게 원소탄소(elemental carbon, EC)와 유기탄소(organic carbon, OC)로 구분 된다 (Chow et al, 2009;Szidat et al, 2009) 소 오염원에서 대부분 대기 중으로 직접 방출되는 1 차 오염물질이다 (Sandrini et al, 2014). OC는 형성과 정에 따라 인위적 또는 자연적 배출원에서 직접 발생 되는 1차 유기탄소(primary organic carbon, POC)와 이 러한 POC가 산화와 노화과정을 거쳐 변환되는 2차 유기탄소(secondary organic carbon, SOC)가 있다 (Gentner et al, 2012).…”

Section: 서 론unclassified

Potential Source of PM₁₀, PM_2.5, and OC and EC in Seoul During Spring 2016

Ham¹,

Lee²,

Wan³

et al. 2017

Atmosphere

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Organic carbon (OC) and elemental carbon (EC) in PM 2.5 were measured using Sunset OC/EC Field Analyzer at Seoul Hwangsa Monitoring Center from March to April, 2016. The mean concentrations of OC and EC during the entire period were 4.4 ± 2.0 μgC m −3 and 1.4 ± 0.6 μgC m −3 , respectively. OC/EC ratio was 3.4 ± 1.0. The average concentrations of PM 10 and PM 2.5 were 57.4 ± 25.9 and 39.7 ± 19.8 μg m , respectively, which were detected by an optical particle counter. The OC and EC peaks were observed in the morning, which were impacted by vehicle emission, however, their diurnal variations were not noticeable. This is determined to be contributed by the long-range transported OC or secondary formation via photochemical reaction by volatile organic compounds at afternoon. A conditional probability function (CPF) model was used to identify the local source of pollution. High concentrations of PM 10 and PM 2.5 were observed from the westerly wind, regardless of wind speed. When wind velocity was high, a mixing plume of dust and pollution during long-range transport from China in spring was observed. In contrast, pollution in low wind velocity was from local source, regardless of direction. To know the effect of long-range transport on pollution, a concentration weighted trajectory (CWT) model was analyzed based on a potential source contribution function (PSCF) model in which 75 percentiles high concentration was picked out for CWT analysis. PM 10 , PM 2.5 , OC, and EC were dominantly contributed from China in spring, and EC results were similar in both PSCF and CWT. In conclusion, Seoul air quality in spring was mainly affected by a mixture of local pollution and anthropogenic pollutants originated in China than the Asian dust.

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“…Aitana was organic matter (OM, 3.1 µg m -3 ), accounting for more than 60% of the total mass. The organic content was calculated by multiplying OC concentrations by a factor of 1.8, as suggested in the literature for high altitude sites Sandrini et al, 2014). The second most abundant component was ammonium sulfate (1.20 µg m -3 ), which contributed 26% to the average PM 1 concentration.…”

Section: Pm 1 Average Levels and Compositionmentioning

confidence: 99%

Chemical Characterization of PM1 at a Regional Background Site in the Western Mediterranean

Galindo

Yubero

Nicolás

et al. 2016

Aerosol Air Qual. Res.

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From February 2011 to September 2012, PM 1 samples were collected at the regional background station of Mt. Aitana, located near the eastern coast of the Iberian Peninsula at 1558 m a.s.l. Samples were subsequently analyzed to determine the major chemical composition (elemental and organic carbon, secondary inorganic ions and oxalate). The seasonal patterns of the concentrations of PM 1 and its main components and the influence of long-range transport of dust from the Sahara desert were studied in this work. PM 1 was mainly composed of organic matter and ammonium sulfate, while EC and nitrate were minor components. Concentrations ranged from 3.4 µg m -3 in winter to 5.8 µg m -3 during summer. This seasonal cycle is typical of high mountain sites, which are generally above the planetary boundary layer during winter time. All the analyzed components exhibited the same seasonal pattern except nitrate, which showed minimum values in summer. This is most likely the result of the decomposition of NH 4 NO 3 favored by the higher summer temperatures. Due to the close proximity to the African continent, PM 1 levels significantly increased during Saharan dust intrusions. The concentrations of sulfate were 35% higher during dust events since the formation of secondary ammonium sulfate is favored by heterogeneous reactions on the surface of mineral particles.

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Spatial and seasonal variability of carbonaceous aerosol across Italy

Cited by 146 publications

References 61 publications

On the functional form of particle number size distributions: influence of particle source and meteorological variables

On the functional form of particle number size distributions: influence of particle source and meteorological variables

Potential Source of PM₁₀, PM_2.5, and OC and EC in Seoul During Spring 2016

Chemical Characterization of PM1 at a Regional Background Site in the Western Mediterranean

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Spatial and seasonal variability of carbonaceous aerosol across Italy

Cited by 146 publications

References 61 publications

On the functional form of particle number size distributions: influence of particle source and meteorological variables

On the functional form of particle number size distributions: influence of particle source and meteorological variables

Potential Source of PM10, PM2.5, and OC and EC in Seoul During Spring 2016

Chemical Characterization of PM1 at a Regional Background Site in the Western Mediterranean

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Potential Source of PM₁₀, PM_2.5, and OC and EC in Seoul During Spring 2016