Potential risk of exposure to heavy metals from co-processing of secondary wastes in the Republic of Korea

The co-processing of secondary wastes during ordinary Portland cement (OPC) can result in high heavy metal concentrations in OPC products. However, earlier studies have not evaluated the concentrations of heavy metals (HMs) in OPC as a function of secondary input materials. Further, the health risk assessment (HRA) model has, thus far, has not been employed to assess the potential health risks associated with secondary raw materials and secondary fuels in OPC. Hence, to address these knowledge gaps, herein, monthly data for six HMs in the input materials and fuels from seven OPC manufacturers in the Republic of Korea were analyzed and modeled. Pb and Cu concentrations were found to be approximately 10-200 and 4-200 times higher than those of the other HMs, respectively. Furthermore, maximum Pb and Cu concentrations were 2-3 and 2-5 times higher than those reported in other countries, respectively. The quantity of input material had a significant influence on the observed patterns, and secondary raw materials, secondary additives, and secondary fuels were also determined to be important. Based on HRA assessment, although the risk levels were within permissible ranges, carcinogenic hazards attributable to Cr and Pb were not negligible. The results can aid in informed decision making and in implementing effective measures for managing risks associated with HMs in the OPC industry, thereby ameliorating threats to human health and environment.

Assessment of physiochemical properties and concentration of heavy metals in agricultural soils fertilized with chemical fertilizers

The present study aim to assess the effect of phosphate and urea fertilizers on the physicochemical properties, pH and electrical conductivity (EC) of the soil. The effect of these fertilizers on cation exchange capacity (CEC), organic matter (OM), and the possibility of contamination with heavy metals (HM) (Cr, Cu, Cd, Mn, Zn, Ni, Fe, and Pb) were studied on the soils of Alshati agricultural project at different seasons after forty years of fertilization. Uncultivated soil samples were also analyzed for comparison and considered as reference. Mean values of soil pH, EC, CEC, and OM ranged between 6.88-7.32, 0.14–0.26 μS/cm, 2.95–4.19 Cmol/kg and 0.49–0.53%, respectively, in all seasons. Concentrations of HMs were 9.50–38.38, 0.0–2.05, 0.0–0.47, 0.0–29.81, 0.0–13.85, 2.83–25.95 and 104–512.20 mg/kg respectively, for Cr, Cu, Cd, Mn, Zn, Ni and Fe. The concentrations of the HMs in the soil were found to be vary significantly with the seasons (winter, spring, summer, and autumn). However, no traces of Pb was found in the soil samples. The result showed a significant correlation between, pH, EC, CEC, OM and HM content of the soil. The geochemical index of contamination shows that there was no contamination with Cu, Cd, Zn, Pb, Cr, Mn, Ni, and Fe.

Quantification of heavy metal pollution for environmental assessment of soil condition

The aim of this study was to quantify heavy metal pollution for environmental assessment of soil quality using a flexible approach based on multivariate analysis. The study was conducted using 241 soil samples collected from agricultural, urban and rangeland areas in northwestern Iran. The heavy metals causing soil pollution (SP) in the study area were determined. The efficiency of principal component analysis (PCA) and discriminate analysis (DA) were compared to identify the critical heavy metals causing SP. Fourteen soil pollution indices were developed using non-linear and linear scoring equations and different integration methods. The indices were validated using the integrated pollution and potential ecological risk indices and by comparing their ability to detect soil pollution risk levels. Chromium (Cr), lead (Pb), Zinc (Zn) and copper (Cu) were identified as the significant pollutant elements using PCA, and the main pollutant elements identified using DA comprised cadmium (Cd), Zn and Pb. DA yielded a better data set for indexing SP and indicated high pollution risks for Cd > Pb > Zn. Sources of heavy metals were reliably identified using PCA, variation assessment and interrelationship evaluation of soil variables. Cr, nickel (Ni) and cobalt (Co) were found to have geogenic sources, and anthropogenic sources controlled the accumulation of Pb, Zn, Cd and Cu in soil. Linear function and additive integration were the best scoring and integrating methods for indexing HMP. The multivariate analysis provided a reliable and rapid method for indexing and mapping soil HMP.

Human nail usage as a Bio-indicator in contamination monitoring of heavy metals in Dizajabaad, Zanjan province-Iran

BACKGROUND

Due to pedogeochemical background and anthropogenic sources, heavy metal contamination of soil is a widespread problem in some parts of Zanjan province located in North West Iran. In this study an affected area located near National Iranian Lead and Zinc Company (NILZ) was selected for detailed study.

METHODOLOGY

Thirty soil samples and eighteen leaf samples were collected and analyzed for heavy metal contamination by Inductively Coupled Plasma-Optical Emission Spectroscopy (ICP-OES). Both soil and plant samples were found to be basically polluted by Pb (72.60 and 97.11), Zn (546.47 and 166.61), and Cd (1.80 and 1.55) mg. kg(-1) respectively. High concentrations of these elements in soil and plant species signifies possible health risks to humans. The distribution maps drawn using Arc GIS (10) show high concentrations of these toxic metals around Dizajabaad village. To assess vulnerability and health risks of metal concentrations in human bodies' twenty nine fingernail samples were also collected from people living in this village.

RESULTS AND DISCUSSION

Analysis for different heavy metal contents of nail samples reveals very high levels of the same toxic elements (Pb = 15.15, Cd = 1.18, As = 15.47, Zn = 68.46 and Ni = 18.22 mg. kg(-1)) compared with samples collected from an unaffected area and available values indicated in the literature. Further, high concentration of heavy metals in the nail samples suggests long term exposure of inhabitants to these toxic metals.

Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area.