Sources of high PM2.5 concentrations in Milan, Northern Italy: Molecular marker data and CMB modelling

Perrone, Maria Grazia; Larsen, B.; Ferrero, Luca; Sangiorgi, G; Gennaro, Gianluigi de; Udisti, Roberto; Zangrando, Roberta; Gambaro, Andrea; Bolzacchini, Ezio

doi:10.1016/j.scitotenv.2011.11.026

Cited by 172 publications

(119 citation statements)

References 59 publications

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“…1). The high level of air pollution in the city has already been well documented (see Baltensperger et al, 2002;Vecchi et al, 2004), and it derives from both anthropogenic activities (mainly traffic and heating; Perrone et al, 2012) and weak atmospheric dispersal conditions (i.e., a short mixing layer), especially during the wintertime (Ferrero et al, 2011a(Ferrero et al, , 2011bSangiorgi et al, 2011). The result is the presence of high emissions of air pollutants in a troposphere characterized by low dispersive movements.…”

Section: The Sampling Sitesmentioning

confidence: 98%

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Indoor airborne particle sources and semi-volatile partitioning effect of outdoor fine PM in offices

Sangiorgi

Ferrero

Ferrini

et al. 2013

Atmospheric Environment

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118

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To date, few studies have focused on PM air quality in offices, despite the fact that a lot of people spend\ud many working hours a day in such offices. The aim of the present study is to investigate PM1 and PM2.5\ud in offices in Milan (Northern Italy) and in the air outside those offices. The PM samples were analyzed to\ud determine the entity of certain compounds with possible direct or indirect adverse effects on human\ud health: PAHs, BpA, and water soluble inorganic ions.\ud A good correlation between outdoor and indoor PM mass concentrations emerged (R2 w0.87). The\ud maximum I/O concentration ratiowas 0.92, suggesting that the indoor PM levelwas always lower than the\ud outdoor level. The average infiltration factor, FINF,was 0.55, showing that about a half of the outdoor PMhad\ud come indoors. The indoor-generated particles, Cig, had values ranging from 0 to 4.4 mg m3 (<25% of the\ud indoor PM), showing that PM indoor sources had only made a limited contribution to total indoor PM.\ud The results of the indoor-to-outdoor comparisons for the aforementioned chemical compounds\ud demonstrate that the offices were characterized by the absence of effective indoor sources of particulatebound\ud PAHs and inorganic ions, whereas Cig was around 58% of the indoor concentration for BpA. Our\ud analysis of the FINF data pointed to the presence of a volatilization effect from PM for semi-volatile\ud compounds like ammonium nitrate and 4- or 5-ring PAHs, which affected the measurement of their\ud FINF. We propose the introduction of a new and simple parameter, called volatilization correction, to take\ud account of this effect

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Section: The Sampling Sitesmentioning

confidence: 98%

“…Only those figures above dl were admitted as valid. The following is a brief description of the analytical procedures (details are in Perrone et al, 2010Perrone et al, , 2012. For sample processing and analysis to determine BpA, see the Supplementary Material (Section B).…”

Section: Pm Chemical Characterizationmentioning

confidence: 99%

Indoor airborne particle sources and semi-volatile partitioning effect of outdoor fine PM in offices

Sangiorgi

Ferrero

Ferrini

et al. 2013

Atmospheric Environment

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118

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“…As illustrated in Table 2, the average total PAH concentration at NAEO was similar to the background site Mountain (MT). Waliguan (the Global Climate Observing System of the World Meteorological Organization in tropical zone) (Cheng, 2006) and rural site in Italy (Perrone et al, 2012), and also higher than the high mountain regions in Europe (Fernandez et al, 2002), MT Taishan (Li et al, 2010), while lower than those found in other urban or suburban sites such as Guangzhou (Li et al, 2006), Shanghai (Chen et al, 2011), Beijing (Zhou et al, 2005), Hong Kong , Seoul in Korea (Park et al, 2002). Eastern China is a significant source of atmospheric PAHs (Zhang et al, 2011).…”

Section: Concentrations Of Pahsmentioning

confidence: 99%

Atmospheric polycyclic aromatic hydrocarbons in rural and urban areas of northern China

Wang

et al. 2014

Environmental Pollution

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Thirty six pairs of gas and particle (PM 2.5 . Seasonal trends of PAH concentrations were observed with high concentrations in winter and low in summer, mainly due to regional sources and meteorological conditions. The association with other airborne pollutants and diagnostic ratio analysis indicated that PAHs in Eastern China background were predominantly from coal/biomass combustion. Coal combustion controlled atmospheric PAHs in winter, whilst biomass burning became important in summer and autumn. Located at eastern coastal areas, Ningbo site was chosen to estimate the atmospheric outflow of PAHs. Transport fluxes were characterized by elevated values in spring and winter. Southward transport fluxes dominated during the sampling period, presenting the transport from northern to southern China.

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“…Mass concentrations of aerosol species (PM components) such as sulphate (SO 4 2-), nitrate (NO 3 -), ammonium (NH 4 + ), organic (OC) and elemental carbon (EC) in the fine fraction (PM 2.5 ) were examined against literature data from Perrone et al (2012) and Carbone et al (2010) and against data from the EMEP database for the stations Ispra and Montelibretti. Mass concentrations of carbonaceous aerosol and contribution of primary and secondary sources to organic aerosol were compared to the data shown in Larsen et al (2012).…”

Section: Chemical Composition Of Aerosolmentioning

confidence: 99%

“…Mass concentrations of carbonaceous aerosol and contribution of primary and secondary sources to organic aerosol were compared to the data shown in Larsen et al (2012). The grid resolution effect on chemical composition is shown using Perrone et al (2012) and EMEP data for different seasons, using Carbone et al (2012) data for day and night during summer, and using Larsen et al (2012) data for primary and secondary OC sources during winter. (Table S2) compares the chemical composition of the aerosol fine fraction for simulations with low and high spatial resolution using the data shown in Fig.…”

Section: Chemical Composition Of Aerosolmentioning

confidence: 99%

Impact of Grid Resolution on Aerosol Predictions: A Case Study over Italy

Mircea

Grigoraș

D’Isidoro

et al. 2016

Aerosol Air Qual. Res.

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This study investigates the effect of grid resolution on the particulate matter (PM 10 , PM 2.5 ) mass concentrations and its chemical composition simulated with the AMS-MINNI modelling system. The air pollution was simulated over Italy with grid resolutions of 20 and 4 km, for a whole year. The gridded emissions were produced performing speciation and spacetime disaggregation of aggregated inventory data, using both land use information and anthropogenic activity-based profiles. Often, the fine grid simulations, based on high resolution gridded emissions, improved the agreement between model and measurements. In particular, the use of a fine grid improved predictions of primary species such as elemental carbon (EC), PM 10 and PM 2.5 mainly at urban stations. An improvement of predicted PM components and mass concentration at high altitudes sites was also observed, especially during winter. However, a general overestimation of nitrate (NO 3 -) and of secondary inorganic species, more evident at night than during the day, was increased by employing a finer grid. Organic carbon (OC) was more affected by the grid resolution than the other species. At urban and kerbside stations, the use of a finer grid resulted in an overestimation of primary organic carbon aerosol (POC) but had a negligible effect on secondary organic carbon aerosol (SOC). The overestimation of carbonaceous aerosol (defined as the sum of EC, POC and SOC), at an urban station, opposite to general underestimation of this component by air quality (AQ) models, indicates that the anthropogenic emissions can contribute as much as organic model formulation at the success of simulation in reproducing experimental data.The modelling results obtained under stable meteorological conditions characterised by weak winds, which are often encountered in the Po Valley, did not improve substantially by the increase of the modelling system resolution.

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Sources of high PM2.5 concentrations in Milan, Northern Italy: Molecular marker data and CMB modelling

Cited by 172 publications

References 59 publications

Indoor airborne particle sources and semi-volatile partitioning effect of outdoor fine PM in offices

Indoor airborne particle sources and semi-volatile partitioning effect of outdoor fine PM in offices

Atmospheric polycyclic aromatic hydrocarbons in rural and urban areas of northern China

Impact of Grid Resolution on Aerosol Predictions: A Case Study over Italy

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