scholarly journals Statistical evaluation and predicting the possible sources of particulate matter in a Mediterranean metropolitan city

2017 ◽  
Vol 20 (2) ◽  
pp. 173-180 ◽  
Keyword(s):  
Particulate Matter ◽  
Inductively Coupled Plasma ◽  
Heavy Traffic ◽  
Gravimetric Method ◽  
Principal Component ◽  
Sampling Period ◽  
Ambient Air ◽  
Research Field ◽  
Elemental Concentrations ◽  
Pm2.5 And Pm10

In Mega-cities, such as Istanbul, urbanization causes heavy traffic. Air pollution, which originated from heavy traffic and industrialization, is one of the most important problems for the people who live in the populated cities. Due to both environmental and health effects, particulate matter problem always remains popular and serves an important research field. For this purpose, PM2.5 and PM10 measurements were taken in the megacity of Istanbul, close to Besiktas district by a low volume sampler at 5 different sampling stations. A total of 150 samples, 75 samples of PM2.5 and 75 samples of PM10 were collected from these sampling stations. Sampling period was between March 2009 and March 2010. Determination of particulate matter concentration was performed by the gravimetric method and elemental concentrations were analyzed with Inductively Coupled Plasma (ICP-OES). Principal Component Analysis (PCA) and Enrichment Factor (EF) analysis were applied to obtained elemental concentrations in order to identify the possible sources associated with the particulate matter. Four factors for PM2.5 and five factors for PM10 were determined by PCA method, which had variance contributions of 82.3% for PM2.5 and 83.5% for PM10. Acquired data showed that Istanbul ambient air was dominated by traffic emissions and crustal originated elements.

scholarly journals Physicochemical properties of particulate matter (PM2.5) from the steel industry in Indonesia

2022 ◽  
Vol 951 (1) ◽  
pp. 012032
Author(s):  
R Ermawati ◽  
I Setiawati ◽  
Irwinanita ◽  
A Ariani
Keyword(s):  
Particle Size ◽  
Particulate Matter ◽  
Physicochemical Properties ◽  
Steel Industry ◽  
Inductively Coupled Plasma ◽  
Fine Particles ◽  
Average Particle Size ◽  
Sampling Period ◽  
Hot Strip Mill ◽  
Average Particle

Abstract Particulate matter (PM) as one of the pollutants in the atmosphere needs to be studied. PM has physical and chemical characteristics and is called physicochemical properties. These properties vary depending on the source of the PM. PM samplers are used for air sampling to characterize some fine particles (PM2.5). The PM2.5 samples have collected from four sampling sites in the steel industry in Cilegon, Indonesia. The sampling sites are the main gate, the hot strip mill, the billet post, and the hot blast plant. The sampling period was four months. The physicochemical properties analysed are morphology, elements content, heavy metals, and particle size. The instruments used to analyse were Scanning Electron Microscopy (SEM) and Energy Dispersive Spectrometry (EDS), Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES), and Particle Size Analyzer (PSA). The morphology of PM2.5 detected varied, but the elements and the most elements found were F and C particles. The metals concentration was below the Indonesia Regulation. While the average particle size analysed was below 2,500 nm. The physicochemical properties of PM2.5 are affected by the type of production process in the industry.

scholarly journals Spatio-Temporal Variation in the Concentration of Inhalable Particulate Matter (PM10) in Uganda

2019 ◽  
Vol 16 (10) ◽  
pp. 1752 ◽  
Author(s):  
Silver Onyango ◽  
Beth Parks ◽  
Simon Anguma ◽  
Qingyu Meng
Keyword(s):  
Particulate Matter ◽  
Sampling Period ◽  
Ambient Air ◽  
Average Density ◽  
Diurnal Variations ◽  
Time Data ◽  
Seasonal Differences ◽  
Wide Range ◽  
The Impact

Long-term particulate matter (PM10) measurements were conducted during the period January 2016 to September 2017 at three sites in Uganda (Mbarara, Kyebando, and Rubindi) representing a wide range of urbanization. Spatial, temporal and diurnal variations are assessed in this paper. Particulate matter (PM10) samples were collected for 24-h periods on PTFE filters using a calibrated pump and analyzed gravimetrically to determine the average density. Particulate levels were monitored simultaneously using a light scattering instrument to acquire real time data from which diurnal variations were assessed. The PM10 levels averaged over the sampling period at Mbarara, Kyebando, and Rubindi were 5.8, 8.4, and 6.5 times higher than the WHO annual air quality guideline of 20 µg·m−3, and values exceeded the 24-h mean PM10 guideline of 50 µg·m−3 on 83, 100, and 86% of the sampling days. Higher concentrations were observed during dry seasons at all sites. Seasonal differences were statistically significant at Rubindi and Kyebando. Bimodal peaks were observed in the diurnal analysis with higher morning peaks at Mbarara and Kyebando, which points to the impact of traffic sources, while the higher evening peak at Rubindi points to the influence of dust suspension, roadside cooking and open-air waste burning. Long-term measurement showed unhealthy ambient air in all three locations tested in Uganda, with significant spatial and seasonal differences.

scholarly journals Characteristics of Locally Occurring High PM2.5 Concentration Episodes in a Small City in South Korea

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 86
Author(s):  
Su-Yeon Choi ◽  
Sung-Won Park ◽  
Jin-Yeo Byun ◽  
Young-Ji Han
Keyword(s):  
Biomass Burning ◽  
Principal Component ◽  
Sampling Period ◽  
Ambient Air ◽  
Quality Standard ◽  
Water Soluble ◽  
Strongly Correlated ◽  
Secondary Formation ◽  
Ambient Air Quality Standard ◽  
Pm2.5 Concentration

In this study, the ionic and carbonaceous compounds in PM2.5 were analysed in the small residential city of Chuncheon, Korea. To identify the local sources that substantially influence PM2.5 concentrations, the samples were divided into two groups: samples with PM2.5 concentrations higher than those in the upwind metropolitan area (Seoul) and samples with lower PM2.5 concentrations. During the sampling period (December 2016–August 2018), the average PM2.5 was 23.2 μg m−3, which exceeds the annual national ambient air quality standard (15 μg m−3). When the PM2.5 concentrations were higher in Chuncheon than in Seoul, the organic carbon (OC) and elemental carbon (EC) concentrations increased the most among all the PM2.5 components measured in this study. This is attributable to secondary formation and biomass burning, because secondary OC was enhanced and water soluble OC was strongly correlated with K+, EC, and OC. A principal component analysis identified four factors contributing to PM2.5: fossil-fuel combustion, secondary inorganic and organic reactions in biomass burning plumes, crustal dust, and secondary NH4+ formation.

scholarly journals Assessment of the Accuracy of Analyzers for Automatic Determination of PM10 and PM2.5 Particulate Matter in Ambient Air

2020 ◽  
Vol 71 (1) ◽  
pp. 83-87
Author(s):  
Elena Bucur ◽  
Radu Motisan ◽  
Andrei Vasile ◽  
Gheorghita Tanase ◽  
Luoana Florentina Pascu ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Pearson Correlation ◽  
Reference Method ◽  
Ambient Air ◽  
Data Series ◽  
Test Results ◽  
Particulate Matter Concentration ◽  
Pm2.5 And Pm10 ◽  
Matter Concentration

The paper presents the test results regarding the evaluation of the accuracy of the PM2.5 and PM10 particulate matter concentration measurement performed with the uRADMonitor A3 fixed air quality monitoring station produced by SC MAGNASCI SRL. The procedure involves the calculation of the accuracy elements: trueness and precision, based on the experimental data obtained by measuring the concentration of particulate matter using the tested analysers in parallel with the reference method, SR EN 12341: 2014, and analysis of data series by Pearson correlation and linear regression.

scholarly journals Identification of emission sources of particle-bound polycyclic aromatic hydrocarbons in the vicinity of the industrial zone of the city of Novi Sad

2013 ◽  
Vol 67 (2) ◽  
pp. 337-348 ◽  
Author(s):  
Natasa Jovcic ◽  
Jelena Radonic ◽  
Maja Turk-Sekulic ◽  
Mirjana Vojinovic-Miloradov ◽  
Srdjan Popov
Keyword(s):  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Heavy Traffic ◽  
Principal Component ◽  
Ambient Air ◽  
Emission Sources ◽  
Industrial Zone ◽  
Polycyclic Aromatic ◽  
Novi Sad ◽  
The City

Data on polycyclic aromatic hydrocarbons (PAHs) in ambient air accessed at selected locations in the vicinity of the industrial zone of the city of Novi Sad, Serbia, have been presented and analyzed in order to determine seasonal and spatial variations and to identify emission sources of particle-bound PAHs. Previous studies have demonstrated that the major contributors of PAHs in urban areas are the emissions from vehicle exhaust, and emissions releases from industrial processes like aluminium production, creosote and wood preservation, waste incineration, cement manufacture, petrochemical and related industries, commercial heat/power production etc. The sampling campaigns have been conducted at three sampling sites, during the two 14-day periods. The first site was situated near industrial area, with a refinery, power plant and heavy-traffic road in the vicinity. The second site was located nearby the heavy traffic area, especially busy during the rush hour. The third site was residential district. Summer sampling period lasted from June 26th to July 10th 2008, while sampling of ambient air during the winter was undertaken from January 22nd to February 5th 2009. Eighty-four (84) air samples were collected using a high volume air sampler TCR Tecora H0649010/ECHO. 16 US EPA polycyclic aromatic hydrocarbons were determined in all samples using a gas chromatographer with a mass spectrometer as a detector (Shimatzu MDGC/GCMS-2010). The total average concentrations of PAHs ranged from 1.21 to 1.77 ng/m3 during the summer period and from 6.31 to 7.25 ng/m3 in the winter. Various techniques, including diagnostic ratio (DR) and principal component analysis (PCA), have been used to define and evaluate potential emission sources of PAHs. Diagnostic ratio analysis indicated that vehicles, diesel or/and gasoline, industrial and combustion emissions were sources of PAHs in the vicinity of the industrial zone. Additionally, principal component analysis was used to constrain the potential sources. The results showed that vehicles are the predominant source of particle-bound PAHs during the whole year, and stationary sources (thermal power and heating plant, oil refinery, individual furnaces) during the winter period.

scholarly journals Preliminary PM2.5 and PM10 fractions source apportionment complemented by statistical accuracy determination

Nukleonika ◽  
2016 ◽  
Vol 61 (1) ◽  
pp. 75-83 ◽  
Author(s):  
Lucyna Samek ◽  
Zdzislaw Stegowski ◽  
Leszek Furman
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Biomass Burning ◽  
Airborne Particulate Matter ◽  
Principal Component ◽  
Simulation Method ◽  
Statistical Simulation ◽  
Pollution Sources ◽  
Pm10 And Pm2.5 ◽  
Pm2.5 And Pm10

Abstract Samples of PM10 and PM2.5 fractions were collected between the years 2010 and 2013 at the urban area of Krakow, Poland. Numerous types of air pollution sources are present at the site; these include steel and cement industries, traffic, municipal emission sources and biomass burning. Energy dispersive X-ray fluorescence was used to determine the concentrations of the following elements: Cl, K, Ca, Ti, Mn, Fe, Ni, Cu, Zn, Br, Rb, Sr, As and Pb within the collected samples. Defining the elements as indicators, airborne particulate matter (APM) source profiles were prepared by applying principal component analysis (PCA), factor analysis (FA) and multiple linear regression (MLR). Four different factors identifying possible air pollution sources for both PM10 and PM2.5 fractions were attributed to municipal emissions, biomass burning, steel industry, traffic, cement and metal industry, Zn and Pb industry and secondary aerosols. The uncertainty associated with each loading was determined by a statistical simulation method that took into account the individual elemental concentrations and their corresponding uncertainties. It will be possible to identify two or more sources of air particulate matter pollution for a single factor in case it is extremely difficult to separate the sources.

scholarly journals Simulation of the Impact of Urban Forest Scale on PM2.5 and PM10 based on System Dynamics

2019 ◽  
Vol 11 (21) ◽  
pp. 5998
Author(s):  
Zhou ◽  
Liu ◽  
Zhou ◽  
Xia
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
System Dynamics ◽  
Forest Cover ◽  
Urban Forest ◽  
Ambient Air ◽  
Atmospheric Environment ◽  
Pm2.5 And Pm10 ◽  
The Impact

In the context of ecological civil construction in China, afforestation is highly valued. Planting trees can improve air quality in China's large cities. However, there is a lack of scientific analysis quantifying the impact urban forest scale has on the air quality, and what scale is advisable. The problem still exists of subjective decision-making in afforestation. Similar studies have rarely analyzed the long-term effect research of urban forests on air improvement. Using as an example, the city of Wuhan, this paper identifies the regularity between particulate matter concentration and adsorption of sample leaves, and establishes a system dynamics model of "economy, energy and atmospheric environment.” By combining this regularity with the model, the long-term impact of forest scale on particulate matter and atmospheric environment was simulated. The results show that if the forest coverage rate reaches at least 30%, the annual average concentrations of inhalable particulate matter (PM10) and fine particulate matter (PM2.5) can both reach the Grade I limit of national Ambient Air Quality Standard by 2050. The current forest cover is 22.9% of the administrative area. Increasing the forest cover by 600 km2 would increase this percentage to 30% of the total area. In the long run (by the year 2050), however, we showed that this increase would only reduce the annual concentration of PM2.5 and PM10 by 1–2%. Therefore, about 90% of the concentration reduction would still rely on the traditional emission reduction measures. More other ecological functions of forests should be considered in afforestation plan.

scholarly journals Characterization of Urban Particulate Matter by Diffusive Gradients in Thin Film Technique

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Michaela Dufka ◽  
Bohumil Dočekal
Keyword(s):  
Particulate Matter ◽  
Inductively Coupled Plasma ◽  
Heavy Traffic ◽  
Total Content ◽  
Insoluble Fraction ◽  
Inductively Coupled ◽  
Significant Difference ◽  
Thickness Of Diffusion Layer ◽  
Plasma Mass Spectrometry

A diffusive gradient in thin films (DGT) technique was employed in characterization of the particulate matter related to the urban area suffering from heavy traffic. Kinetics of mobilization metals fluxes from the metal-contaminated particulate matter was investigated. To monitor responses of the particulate matter sample, DGT probes of various thickness of diffusion layer were deployed in aqueous model suspensions of the particulate matter for different time periods. Particulate matter samples and exposed DGT resin gels were decomposed in a mixture of nitric and hydrochloric acid in a microwave pressurized PTFE-lined system. Total content of some traffic-related elements (Cd, Co, Cu, Mo, Ni, Pb, Pd, Pt, Rh, Sb, and V) was determined by inductively coupled plasma mass spectrometry. DGT measurements revealed that two metals pools associated with particles could be recognized, which can be characterized as high soluble fraction and almost insoluble fraction. DGT-measured metal fluxes from the labile pool showed significant difference in mobilization and resupply fluxes of individual selected elements, which might reflect the origin of selected metals and their speciation in particulate matter. The DGT technique can be applied as a useful tool for characterization of metals mobilization from the particulate matter.

scholarly journals Relationship between airborne microbial and particulate matter concentrations in the ambient air at a mediterranean site

2013 ◽  
Vol 12 (1) ◽  
pp. 84-91
Keyword(s):  
Particulate Matter ◽  
Size Distribution ◽  
Heterotrophic Bacteria ◽  
Sampling Period ◽  
Ambient Air ◽  
Airborne Bacteria ◽  
Ambient Conditions ◽  
The Mean ◽  
Bacteria And Fungi ◽  
Respirable Particulate

The relationship between the viable airborne bacterial and fungal concentrations and the respirable particulate matter with aerodynamic diameter less than 10 μm (PM10), 2.5 μm (PM2.5), and 1 μm (PM1) in the ambient air was studied. An Andersen six stage viable particle sampler and a MAS 100 sampler were used for microbial measurements. Duplicates of samples were collected at each sampling period (20 campaigns in total) at a residential site in the city of Chania (Crete, Greece) during April, May and June 2008. Mean concentration of the total sum of the six size fractions was 79 + 41 CFU m-3 for mesophilic heterotrophic bacteria, whereas for mesophilic fungi it was five times higher (395 + 338 CFU m-3). Particulate matter measurements at the same time period at the same site revealed that the mean concentrations of PM10, PM2.5, and PM1 were 46 + 14, 35 + 14, and 28 + 12 μg m-3, respectively, whereas the mean cumulate counts of PM1 particles was 5,059 + 1,973 particles cm-3. The mean arithmetic concentration of the size distribution of the airborne fungi had a maximum at aerodynamic diameters between 2.1 and 3.3 μm. However, a maximum was not observed for the mean arithmetic concentration of the size distribution of the airborne heterotrophic bacteria. It was also observed that concentrations of airborne bacteria and fungi outdoors were highly variable and do not correlate with the particle number (PM1) or mass concentration of PM10, PM2.5 and PM1. Thereby, the R2-values in all correlations were less than 0.3. However, the concentrations of airborne bacteria and fungi were decreased with increasing mass concentrations of PM10, PM2.5, or PM1 while were increased with increasing number concentration of PM1. In addition, the concentrations of airborne bacteria were increased with increasing concentrations of airborne fungi. Finally, the microbial or the particulate matter data did not correlate with meteorological parameters, such as temperature, relative humidity, wind speed and UV radiation in ambient conditions.

scholarly journals Seasonal Variation, Chemical Composition, and PMF-Derived Sources Identification of Traffic-Related PM1, PM2.5, and PM2.5–10 in the Air Quality Management Region of Žilina, Slovakia

2021 ◽  
Vol 18 (19) ◽  
pp. 10191
Author(s):  
Dusan Jandacka ◽  
Daniela Durcanska
Keyword(s):  
Seasonal Variation ◽  
Urban Environment ◽  
Maximum Concentration ◽  
Inductively Coupled Plasma ◽  
Road Traffic ◽  
Fine Fraction ◽  
Gravimetric Method ◽  
Principal Component ◽  
Coarse Fraction ◽  
Over Time

Particulate matter (PM) air pollution in the urban environment is mainly related to the presence of potential sources throughout the year. Road transport is one of the most important sources of PM in the urban environment, because it directly affects pedestrians. PM measurements were performed in the city of Žilina, Slovakia, at various road-traffic-related measurement stations over the course of several years. This paper evaluates changes in the concentration of the fine fraction (PM2.5), the ultrafine fraction (PM1), and the coarse fraction (PM2.5–10) over time. PM concentrations were measured by reference gravimetric method. Significant changes in PM concentrations over time due to the diversification of pollution sources and other, secondary factors can be observed from the analysis of the measured data. PM samples were subjected to chemical analysis inductively coupled plasma mass spectrometry (ICP-MS) to determine the concentrations of elements (Mg, Al, Ca, Cr, Cu, Fe, Cd, Sb, Ba, Pb, Ni, and Zn). The seasonal variation of elements was evaluated, and the sources of PM2.5, PM1, and PM2.5–10 were estimated using principal component analysis (PCA) and positive matrix factorization (PMF). PM2.5 (maximum concentration of 148.95 µg/m3 over 24 h) and PM1 (maximum concentration of 110.51 µg/m3 over 24 h) showed the highest concentrations during the heating season, together with the elements Cd, Pb, and Zn, which showed a significant presence in these fractions. On the other hand, PM2.5–10 (maximum concentration of 38.17 µg/m3 over 24 h) was significantly related to the elements Cu, Sb, Ba, Ca, Cr, Fe, Mg, and Al. High correlation coefficients (r ≥ 0.8) were found for the elements Mg, Ca, Fe, Al, Cd, Pb, and Zn in the PM1 fraction, Cd, Pb, and Zn in PM2.5, and Ba, Sb, Fe, Cu, Cr, Mg, Al, and Ca in PM2.5–10. Using PMF analysis, three major sources of PM (abrasion from tires and brakes, road dust resuspension/winter salting, and combustion processes) were identified for the PM2.5 and PM1 fractions, as well as for the coarse PM2.5–10 fraction. This study reveals the importance of non-exhaust PM emissions in the urban environment.

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