Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas

Almeida, Susana Marta; Manousakas, M.; Diapouli, Evangelia; Kertész, Zs.; Samek, Lucyna; Hristova, Elena; Šega, Krešimir; Álvarez, R.; Belis, Claudio A.; Eleftheriadis, K.

doi:10.1016/j.envpol.2020.115199

Cited by 84 publications

(62 citation statements)

References 48 publications

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“…shows that these three components explain 97.4 % of the variability of the data. Almeida et al (2020) and Owoade et al (2015). The K, Cl and MGF corresponding to the Metallurgy source agree with that reported by Owoade et al (2015) in Nigeria.…”

Section: Determination Of Emission Sourcessupporting

confidence: 87%

“…Cu and MGF were associated with the Vehicular source and is in agreement with Banerjee et al (2015). Almeida et al (2020) andSDA (2009). THE source assigned as Vehicular (Cr, Mn, K, S) agrees…”

Section: Determination Of Emission Sourcessupporting

confidence: 87%

“…The source associated with Soil Dust with the elements Fe, V, Ca, S, Cr and Ti, coincides with that related by Almeida et al (2020) and Owoade et al (2015). The elements Cl, Mn, K and Zn being associated with the Metallurgy source, agrees with Owoade et al (2015).…”

Section: Determination Of Emission Sourcessupporting

confidence: 74%

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Sources of Risk to the Health of the Population, by Inhalation of PM2.5 in the Toluca Valley, Mexico

Godoy¹,

Ortiz²,

Monroy³

et al. 2021

Preprint

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Introduction: PM2.5 air pollution causes death and morbidity in populations, 4.2 million premature deaths have been reported worldwide per year and can cause cardiovascular, respiratory, cancer, among other diseases. As a result, it is important to know the sources that produce them.Objective: Determine the possible Sources of Risk (SR) to health, by inhalation of Elemental Chemical Composition (EQC) obtained from PM2.5 samples in the Toluca Valley (TV).Method: Sampling was carried out (26/11/16-14/03/18) in San Mateo Atenco, Ceboruco, Nueva Oxtotitlán, San Lorenzo Tepaltitlán, Zinacantepec and San Cristóbal Huichochitlán, using medium volume equipment every six days for 24 hours. It was calculated: gravimetry, analysis by atomic technique PIXE (Proton Induced X-Ray Emission) to obtain the EQC. The emission sources were determined with multivariate analysis, the elemental risk for three sensitive classes of the population and their possible sources of risk. Results: The SRs determined: Dust-Soil, Industry, Hydrocarbons, Vehicle, Burn-Fuels, Fine Gravimetric Mass, Coal burning, Metallurgy and Sulphates. Discussion: The SRs with the highest values, for sensitive populations, were Industry and Dust-Soil, this as a consequence of the large number of existing industries that produce EQC. Conclusion: The risks of inhalation of EQC present in PM2.5 for sampling sites were high, because of this there is a high probability of contracting some diseases that can be caused by EQC. The risk determined for sources in the ZMTV, to date, does not exist in similar research in the literature.

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Section: Determination Of Emission Sourcessupporting

confidence: 87%

Section: Determination Of Emission Sourcessupporting

confidence: 87%

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Sources of Risk to the Health of the Population, by Inhalation of PM2.5 in the Toluca Valley, Mexico

Godoy¹,

Ortiz²,

Monroy³

et al. 2021

Preprint

View full text Add to dashboard Cite

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“…PMF has been successfully applied in areas with many different characteristics in regions all around the world. Information about several components of PM such as the elements, ions, organic and elemental carbon are usually included in such studies (Almeida et al 2020;Banerjee et al 2015;Pateraki et al 2019). The most commonly identified sources include soil, secondary aerosols, vehicular emissions, fossil fuel burning, biomass burning, sea salt and industrial emissions (Pant and Harrison 2012;Sharma et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Source identification of fine and coarse aerosol during smog episodes in Debrecen, Hungary

Angyal

Ferenczi

Manousakas

et al. 2021

Air Qual Atmos Health

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In this study, the identification of PM sources during smog episodes in Debrecen is presented. The smog episodes were characterized by the high concentration of PM10, and were linked to a thermal inversion period in November 2011 in Hungary, when an anticyclone occurred across Europe. The sources of PM2.5 and PMcoarse were identified by positive matrix factorization (PMF). Additionally, the source locations were explored by using the conditional probability function (CPF). A numerical weather prediction model (WRF) was also applied to evaluate the air pollution situation. In order to meet the goals of the study, the elemental composition with high (2-h) time resolution, the elemental size distribution, and the planetary boundary layer were examined in an urban background site of downtown Debrecen, Hungary. Our results highlight the importance of biomass burning (39%) and traffic (31%) as the major contributors to PM2.5. The main tracers of these sources (K, Cl, Pb, Zn) appeared mainly in droplet mode (0.5–1 μm). The major sources of PMcoarse fraction were soil (32%), and dust attributed to tramline construction (30%). The combination of PMF and CPF results revealed that the PM10 concentrations were affected by sources within the urban agglomeration of Debrecen (city centre and suburban areas) under the given meteorological conditions. This conclusion is further validated by the fact that the diurnal variation of the identified source contributions presented a distinct pattern that depended strongly on the daily activities of the city’s residents (compared to the usually unstructured diurnals of transported sources).

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“…PMF displays enhanced features with respect to the FA and PCA methods, namely the use of the experimental uncertainty in order to weigh the data values and non-negativity constraints for the obtained factors [33]. It is one of the most popular source apportionment techniques for atmospheric aerosol and is extensively used in the framework of air quality management [34][35][36]. PMF is a receptor modeling tool that attributes the observed elemental concentrations to their major emission sources without "a priori" information on source chemical profiles [36][37][38].…”

Section: Introductionmentioning

confidence: 99%

First-Time Source Apportionment Analysis of Deposited Particulate Matter from a Moss Biomonitoring Study in Northern Greece

et al. 2021

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Moss biomonitoring is a widely used technique for monitoring the accumulation of trace elements in airborne pollution. A total of one hundred and five samples, mainly of the Hypnum cupressiforme Hedw. moss species, were collected from the Northern Greece during the 2015/2016 European ICP Vegetation (International Cooperative Program on Effects of Air Pollution on Natural Vegetation and Crops) moss survey, which also included samples from the metalipherous area of Skouries. They were analyzed by means of neutron activation analysis, and the elemental concentrations were determined. A positive matrix factorization (PMF) model was applied to the results obtained for source apportionment. According to the PMF model, five sources were identified: soil dust, aged sea salt, road dust, lignite power plants, and a Mn-rich source. The soil dust source contributed the most to almost all samples (46% of elemental concentrations, on average). Two areas with significant impact from anthropogenic activities were identified. In West Macedonia, the emissions from a lignite power plant complex located in the area have caused high concentrations of Ni, V, Cr, and Co. The second most impacted area was Skouries, where mining activities and vehicular traffic (probably related to the mining operations) led to high concentrations of Mn, Ni, V, Co, Sb, and Cr.

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Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas

Cited by 84 publications

References 48 publications

Sources of Risk to the Health of the Population, by Inhalation of PM2.5 in the Toluca Valley, Mexico

Sources of Risk to the Health of the Population, by Inhalation of PM2.5 in the Toluca Valley, Mexico

Source identification of fine and coarse aerosol during smog episodes in Debrecen, Hungary

First-Time Source Apportionment Analysis of Deposited Particulate Matter from a Moss Biomonitoring Study in Northern Greece

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