Pollution characteristics, spatial distribution, and source identification of heavy metals in road dust in a central eastern city in China: a comprehensive survey.

Road dust enriched with heavy metals (HMs) is detrimental to ecosystems and human health in urban environments. In this study, it is to explore the concentrations, spatial distribution, contaminated levels, and source identification of six HMs (lead (Pb), zinc (Zn), copper (Cu), cobalt (Co), chromium (Cr), and nickel (Ni)) based on 130 road dusts in Xinyang urban area. The results indicated that the contents of Pb, Zn, Cu, and Co were higher than the background values in more than 99% of the samples, and their average concentrations were 15.2, 9.2, 8.6, and 6.3 times the background value, respectively. The spatial distribution of high-value areas for Pb, Zn, Cu, Cr, and Ni was more similar, which was associated with traffic density near major roads and population and settlement patterns. Co was relatively different from the five elements, which was distributed in the areas of residence, commerce, and industry. Furthermore, the investigated HMs were clearly polluted, with Pb, Zn, Cu, and Co indicating high levels of contamination, while Cr and Ni were moderately polluted. The comprehensive pollution of the six HMs was mostly moderate to heavy in this study. Moreover, three sources of HMs designated by correlation analysis (CA) and principal component analysis (PCA) were mixed traffic emissions and industrial waste for Cu and Cr; automotive emissions for Pb, Ni, and Zn; and mixed domestic waste and industrial activities for Co, with contributions of 42.3%, 46.4%, and 11.3% via the principal component analysis-multiple linear regression (PCA-MLR) model. The multi-factor index for pollution assessment combined with source identification is extremely effective and practical for providing reliable data support and a theoretical reference for pollution monitoring and governance.

Identifying environmental pollution recorded in street dust using the magnetic method: a case study from central eastern China.

Urban street dust constitutes important intermediate products for the transmission of solid organic and inorganic pollutants in the urban environment. In this study, 133 street dust samples were collected from Xinyang to explore their magnetic characteristics, spatial distribution, and environmental implications using magnetic measurements. The results are as follows. (1) There were ferrimagnetic, antiferrimagnetic, and paramagnetic (e.g., lepidocrocite) minerals in the dust. Among these, the dominant magnetic carriers were ferrimagnetic minerals. Furthermore, magnetite was a first-order ferrimagnetic carrier. (2) The magnetic domains of the dust were pseudo single-domain to multi-domain. (3) The magnetic concentration (χ and SIRM) of dust were 2.6 and 4.1 times higher than those of background samples that were not polluted by urban and anthropogenic activities, respectively. Therefore, we conclude that the dust consisted of high concentration of ferrimagnetic minerals and coarse magnetic particles. (4) The magnetic distribution was spatially different. The industrial area, which was the most polluted sampling area, had the highest magnetic concentration and the coarsest magnetic particles. This was attributable to industrial emissions, fossil fuel combustion, and exhaust emissions from heavy-laden trucks. Residential and commercial areas, which were the second most polluted areas, had higher concentration and coarser particles. This was primarily due to the high population density and traffic activities of mini-cars (i.e., high flux and exhaust emissions). Hence, the conclusion is that the magnetic characteristics, spatial distribution, and the sources of dust are dictated by anthropogenic activities. Our results indicate that the magnetic method is a highly effective tool to monitor urban environmental pollution.