Spatial distribution of pollution characteristics and human health risk assessment of exposure to heavy elements in road dust from different functional areas of Zhengzhou, China

Abstract

Road dust from different sources directly contacts the human body and has potential effects on public health. In this study, a total number of 87 road dust samples were collected at 29 sampling sites from five different functional areas (commercial area (CA), residential area (RA), educational area (EA), industrial area (IA), and park area (PA)) in Zhengzhou to study the contamination status, distribution, source identification, ecological risk assessment, and spatial distribution of human health risks due to eight heavy elements. The geo-accumulation index (I geo) and pollution index (PI) revealed that there was very high contamination with Cd and Hg caused by atmospheric deposition, which should be paid special attention. Additionally, the source identification indicated that Cr, Ni, Cu, Zn, Cd, and Pb originate from anthropogenic activities related to traffic, and Hg can originate from medical equipment and agricultural chemicals, while the extremely low level of pollution with As could be explained by geographic sources. Moreover, the calculated ecological risk index values were increased in the order of CA > RA > EA > IA > PA in different functional areas. According to the human health risks of the whole city, children exposed to Pb have the highest health risk, especially for CA and IA, as calculated by the noncarcinogenic hazard index (HI). For adults and children, health risks caused by Cu, Zn, and Pb were higher in the CA, RA, and PA of the downtown area, whereas Cr and Ni had the highest noncarcinogenic exposure risk in northwestern Zhengzhou due to point source pollution. Calculations of the carcinogenic risk (CR) values for Cr, Ni, As, and Cd indicate that the value of Cr is highest (1.17 × 10 −7), especially inside the industrial area (8.55 × 10 −7), which is close to the lower limit of the threshold values (10 −6 to 10 −4). These results can provide a theoretical basis and data support for air treatment, pollution control, and the implementation of public prevention in different functional areas of Zhengzhou.

Potentially Toxic Elements (PTEs) Composition and Human Health Risk Assessment of PM10 on the Roadways of Industrial Complexes in South Korea

“…The average concentration ranged widely from 1-3 times the background (Be, Co, Sr, Tl, V) to 350-420 times the background (Sb, Ag). This observed PTEs order is also commonly reported in other previous research [52,54,58]. Zn, Mn, Pb, Cu, Cr and Ni are mainly the significant contributors to the wear of the natural soil and asphalt, and Zn, Pb, Cu, Sb and Cd are found most predominantly in road [54].…”

“…Pearson's correlation analysis was used to correlate the data with confirmed normality, and Kendall's tau-b method was used to correlate the data without normality. Principal component analysis (PCA) was used to identify PM sources [58,[89][90][91][92]. For factor analysis, factors with a minimum eigenvalue greater than 1 (initial eigenvalue > 1) were selected, and the Varimax rotation component value was used to clarify the relationships among various factors.…”

Concentration, sources, potential ecological and human health risks assessment of trace elements in roadside soil in Hamedan metropolitan, west of Iran

“…Factors used to calculate the average daily dose (ADD) of the heavy metals by children and adults (mg kg -1 day -1 ). a, b a: [5] b: [6] c: [7] d: [8] e: [9] Table S3. The reference doses (RfD) and carcinogenic slope factors (CSF) for each element used in health risk assessment.…”

Source apportionment and risk assessment of heavy metals in urban soils from a central China city by using positive matrix factorization model coupled with Monte Carlo simulation

“…In the past decades, the predominant geological location, policies, cultural conditions played key roles in attracting more people to visit or settle in the city. While the huge population drives economic development, and it also contributes directly or indirectly to the formation of massive amounts of pollutants (Wang et al 2020a).…”