Meteorological dependence of size-fractionated number concentrations of urban aerosol particles

Hussein, Tareq; Karppinen, Ari; Kukkonen, Jaakko; Härkönen, Jari; Aalto, Pasi; Hämeri, Kaarle; Kerminen, Veli‐Matti; Kulmala, Markku

doi:10.1016/j.atmosenv.2005.10.061

Cited by 166 publications

(93 citation statements)

References 27 publications

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“…5a). It is also well known that temperatures directly affect the force of vertical air convection, causing a negative correlation with concentration of TSP (Hussein et al 2006). In this study, however, this effect was not particularly clear during the whole period of sampling.…”

Section: Black Crustscontrasting

confidence: 51%

Natural and anthropogenic sources of total suspended particulate and their contribution to the formation of black crusts on building stone materials of Catania (Sicily)

2012

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Blackening and disaggregation of exposed surfaces of stone monuments are well-known effects of stone decay taking place in polluted urban environments all over the world. This paper aims to assess the contribution of natural and anthropogenic sources of total suspended particulate (TSP) causing permanent damage (black crusts) to the stone monuments of Catania (Sicily), one of the most popular ''cities of art'' of southern Italy. Atmospheric pollution of Catania, a typical Mediterranean coastal town, is mainly contributed by vehicle exhaust emissions rather than industrial ones. Episodically, the city also suffers gaseous and ash emissions (plumes) from the nearby Mount Etna volcano. Thus, to discriminate between natural and anthropogenic contributions to stone decay on Catania monuments, black crusts and TSP were sampled within the urban area and subjected to specific analytical procedures (optical microscopy, X-ray powder diffraction, Fourier transformed infrared spectroscopy, scanning electron microscopy equipped with energy dispersive spectrometry, ionic chromatography and dual inlet mass spectrometry). Mineralogical, chemical and isotopic characterization of black crusts and TSP provided new insights concerning the partition of sulfate sources in this particular urban context. The influence of Mount Etna emissions on both TSP and black crusts compositions was shown. Nevertheless, the key role of anthropogenic sources in the total sulfate budget was confirmed, while sea spray and volcanic emissions were found to make subordinate contributions. Quantitative data useful for the identification of the threshold pollution levels for preventive conservation of Catania monuments were obtained.

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Section: Black Crustscontrasting

confidence: 51%

Natural and anthropogenic sources of total suspended particulate and their contribution to the formation of black crusts on building stone materials of Catania (Sicily)

2012

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“…• As opposed to the previous works (Mølgaard et al, 2012;Clifford et al, 2011;Hussein et al, 2006;Sabaliauskas et al, 2012), we have used simultaneous measurements of NO, NO 2 , CO and O 3 (covariates of the model) and UFP number concentrations (target variable) at three different locations, obtaining a similar model performance at all three locations.…”

Section: Introductionmentioning

confidence: 99%

“…• The previous works (Mølgaard et al, 2012;Clifford et al, 2011;Hussein et al, 2006) have used data from an urban background, while the 8 data from our study were gathered at or near the roadside where the variability of the UFP is likely to be higher.…”

Section: Introductionmentioning

confidence: 99%

“…• Compared to the work presented by Mølgaard et al (2012), Clifford et al (2011 and Hussein et al (2006), we have used NO, NO 2 , CO and O 3 as covariates. These data are usually available from the governmental monitoring stations in urban environments.…”

Section: Introductionmentioning

confidence: 99%

“…have been used (Clifford et al, 2011) to model the UFP number concentrations using a generalized additive model and meteorological data, time, solar radiation and rainfall as covariates, reporting an R 2 of 0.836 for their fitted model. Hussein et al (2006) use the data from a background monitoring station. They found that the covariates that contained the most information are the ambient temperature and local wind conditions.…”

Section: Introductionmentioning

confidence: 99%

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