Assessment of heavy metal contamination levels of street dust in the city of Lublin, E Poland

Abstract

Heavy metals are constantly emitted into the environment and pose a major threat to human health, particularly in urban areas. The threat is linked to the presence of Cd, Cr, Cu, Ni, Pb, and Zn in street dust, which consists of mineral and organic particles originating from the soil, industrial emitters, motor vehicles, and fuel consumption. The study objective was to determine the level of street dust contamination with trace metals in Lublin and to indicate their potential sources of origin. The analyses were carried out with an energy-dispersive X-ray fluorescence spectrometer. The sampling sites (49) were located within the city streets characterised by varying intensity of motor traffic. The following mean content values and their variation (SD) were determined:

Concentration of heavy metals in street dust: an implication of using different geochemical background data in estimating the level of heavy metal pollution

“…In contrast, the concentration of Ni in Warsaw's street dust is relatively low and comparable with those obtained from the streets of Lahore (in Pakistan) and Nanjing (in China). The concentration of Cd, Cr, Ni, Pb, and Zn in Warsaw differ from those obtained for another Polish city (Lublin) (Zgłobicki et al, 2018). For street dust from Lublin was obtained significantly higher values of mean content of Cd, significantly lower for Cu and similar concentrations of Ni.…”

“…Previous studies (Cheng et al 2018;Men et al 2018;Soltani et al 2015;Zgłobicki et al 2018) have presented an extensive database of absolute concentrations of heavy metals in urban and industrial dust. However, using absolute concentrations to assess the level of pollution requires using the geochemical background, which depends on geological conditions.…”

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)

“…This method makes it possible to reduce the number of variables (usually dependent between themselves) affecting the particulate concentration and to determine which components, now independent, largely explain the variation of the PM 10 concentration. Reducing the number of variables also simplifies the interpretation of the results [28,30,31,35,36]. In the PCA method, the variance is calculated in relation to all variables taken into account.…”

“…Principal component analysis (PCA) is such a method. It has been used in many studies to isolate independent factors (principal components) that significantly explain the variation of a dependent variable [26,[28][29][30][31]. The aim of this study was to determine which factors and by what degree PM 10 concentrations increased in the air of the Sącz Basin in calendar seasons (spring, summer, autumn and winter).…”

Harmful Chemicals in the Work Environment

“…PCA's approach to data reduction is to create one or more index variables (components) from a set of measured variables. The relationships between data are mathematical, but they allow for several practical conclusions (Zgłobicki et al, 2018). Distribution of sample scores in PCA can indicate the infl uencing factors for the comprehensive variation of variables (Rivetti et al 2017).…”