Analysis of Particulate Matter Concentration Variability and Origin in Selected Urban Areas in Poland

Sówka, Izabela; Chlebowska-Styś, Anna; Pachurka, Łukasz; Rogula–Kozłowska, Wioletta; Mathews, Barbara

doi:10.3390/su11205735

Cited by 26 publications

(21 citation statements)

References 43 publications

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“…In general, Wrocław seems to be significantly less polluted than Katowice, according to a PLI. Probably the presence of abandoned industrial companies and coal-fired houses contributed significantly to the highest values of PLI obtained for Katowice agglomeration [11,38,84]. Even the contaminants deriving from former, abandoned industries could influence the URD composition.…”

Section: Pollution Load Index (Pli)mentioning

confidence: 99%

Selected Metals in Urban Road Dust: Upper and Lower Silesia Case Study

et al. 2020

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In this study, urban road dust (URD) samples were collected in two populated agglomerations of Wrocław and Katowice (Lower and Upper Silesia) in Poland. Both the total concentrations of URD-bound Mn, Ni, Cu, Zn, As, Rb, Ba, Cr, Mg, and Al and concentrations of their water-soluble fraction were determined. The contamination characteristics and health risk related to these elements were assessed. Contamination level assessment was done by Pollution Load Index (PLI), which indicated much higher pollution of Katowice agglomeration than Wrocław. The enrichment factor values (EF) showed that the most elements in both Katowice and Wrocław orginated from anthropogenic sources. The calculations of geo-accumulation index (Igeo) showed that Zn and As are the key pollutants in Katowice; and in the Wrocław region, Cu, Zn, Cr, and Ni are. The principle component analysis (PCA) and correlation analysis provide information about the potential sources of metals. Additionally, a positive matrix factorization (PMF) was performed and four factors in PMF analysis were found and then interpreted by comparing to the source profiles. Three contamination sources were revealed: fossil fuel combustion, road traffic and industrial emissions. Although the main source of studied metals in Lower Silesia is road traffic, in Upper Silesia, domestic heating with the use of hard and brawn coal and industrial activity predominates. Human exposure to individual toxic metals through road dust was assessed for both children and adults. By calculating the average daily dose (ADD) via ingestion, inhalation, and dermal contact, it was found that ingestion and then dermal contact were the greatest exposure pathways for humans in Katowice and Wrocław. Children had greater health risks than adults. According to the health risk assessment, the overall non-carcinogenic risks in both urban areas was rather low. The only exception was As bound to urban road dust in Katowice agglomeration, which indicates risk for children when ingested. The total excess cancer risk (ECR) was also lower than the acceptable level (10−6–10−4) for both adults and children, although ECR for Katowice was closer to this limit.

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Section: Pollution Load Index (Pli)mentioning

confidence: 99%

Selected Metals in Urban Road Dust: Upper and Lower Silesia Case Study

et al. 2020

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“…Annual particulate concentrations monitored in urban and suburban areas significantly exceed the acceptable level [2,5,6]. The adverse effects of increased particulate concentrations on the environment have been discussed in numerous studies [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Hence, we need a method to answer these questions. One way to determine the dependence of particulate concentrations on the values of meteorological elements is to plot a multiple regression curve [6,18,22,27]. Unfortunately, this method does not yield reliable results for all data used.…”

Section: Introductionmentioning

confidence: 99%

Application of the Principal Component Analysis (PCA) Method to Assess the Impact of Meteorological Elements on Concentrations of Particulate Matter (PM10): A Case Study of the Mountain Valley (the Sącz Basin, Poland)

et al. 2019

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The aim of this study was to determine, by use PCA analysis, the impact of meteorological elements on the PM10 concentration on the example of the mountain valley. Daily values of selected meteorological elements, measured during a ten-year period in the spring, summer, autumn and winter, obtained from the meteorological station in Nowy Sącz, were adopted as variables explaining PM10 concentration. The level of PM10 was significantly affected by the maximum, minimum and average temperature in autumn, winter and spring. In summer the average and maximum temperature was significant. In winter, the first principle component mainly consisted of the combination of the average and maximum wind speed. The second principal component in spring, summer and autumn was the combination of the wind speed (average and maximum), but in winter humidity and atmospheric pressure seemed to be significant. The third principal component, in terms of strength of impact, was humidity in spring, the combination of humidity and minimum temperature in summer, and precipitation in autumn. In winter, the highest PM10 concentrations were observed during the non-directional, anticyclonic wedge conditions. Three principal components were distinguished in this situation: temperature (average, maximum and minimum); the combination of humidity and wind speed and precipitation.

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“…Events of air quality deterioration occur usually in the autumn-winter season and the biggest threat is related to emission of fine particulate matter (i.e. PM2.5) [9]. That fraction of PM deposits throughout the respiratory tract, penetrate to the lower parts and alveoli and has a serious negative impact on health [2].…”

Section: Introductionmentioning

confidence: 99%

Sensor network for PM_2.5 measurements on an academic campus area

Badura

Sówka

Batog³

et al. 2019

E3S Web Conf.

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Fine particulate matter (PM2.5) pose a serious threat to health. Therefore it should be monitored to assess its health impacts and to take actions to reduce its pollution. However, the traditional regulatory measuring stations are not able to capture the spatial and temporal variability of PM2.5 concentrations. The opportunity to improve the resolution of PM2.5 data is based on dense networks of miniaturized low-cost sensors. The article presents the sensor network for campus area of Wrocław University of Science and Technology. This system consists of 20 sensor nodes, distributed both on a narrow scale (14 devices on the main campus area) and on a wide scale (devices on campuses in distant parts of the city). Sensor devices have been equipped with optical sensors A003 from Plantower company and with heated inlets. Dedicated website with a map is used to present the up-to-date information about air quality to the public. Messages on air quality are based on air quality index, calculated every 15 minutes. The article demonstrates also few results of preliminary measurements, when episodes of elevated PM2.5 concentrations were observed. Sensor nodes proved to be an useful tool to monitor the changes of air pollution during such events.

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Analysis of Particulate Matter Concentration Variability and Origin in Selected Urban Areas in Poland

Cited by 26 publications

References 43 publications

Selected Metals in Urban Road Dust: Upper and Lower Silesia Case Study

Selected Metals in Urban Road Dust: Upper and Lower Silesia Case Study

Application of the Principal Component Analysis (PCA) Method to Assess the Impact of Meteorological Elements on Concentrations of Particulate Matter (PM10): A Case Study of the Mountain Valley (the Sącz Basin, Poland)

Sensor network for PM_2.5 measurements on an academic campus area

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Analysis of Particulate Matter Concentration Variability and Origin in Selected Urban Areas in Poland

Cited by 26 publications

References 43 publications

Selected Metals in Urban Road Dust: Upper and Lower Silesia Case Study

Selected Metals in Urban Road Dust: Upper and Lower Silesia Case Study

Application of the Principal Component Analysis (PCA) Method to Assess the Impact of Meteorological Elements on Concentrations of Particulate Matter (PM10): A Case Study of the Mountain Valley (the Sącz Basin, Poland)

Sensor network for PM2.5 measurements on an academic campus area

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Sensor network for PM_2.5 measurements on an academic campus area