Investigations of Metal Pollution in Road Dust of Steel Industrial Area and Application of Magnetic Separation

Pollution characteristics and ecological risks for metals in non-magnetic and magnetic road dust from steel industrial areas were investigated by applying a magnetic separation method. Metal (except for Al, Li, Ti, As, and Sb) concentrations in the magnetic road dust were 1.2 (Sn) to 7.8 (Fe) times higher than those in the non-magnetic road dust. For the magnetic road dust, the geo-accumulation index revealed a strongly to extremely polluted status for Cr, Zn, Cd, and Sb, a strongly polluted status for Mn, Cu, and Pb, and a moderately to strongly polluted status for Fe, Ni, Mo, and Hg. This result indicates that the dominant metal pollution sources of road dust in industrial areas were the traffic activities of heavy-duty vehicles. The mean content of magnetic particles accounted for 44.7% of the total road dust. The metal loadings in the magnetic road dust were 86% (Fe), 77% (Cr), 67% (Mn), 86% (Ni), 76% (Cu), 72% (Zn), 64% (Mo), and 62% (Cd), respectively. Removal of the magnetic fraction from road dust using magnetic separation techniques not only reduces metal contamination but can also improve effective road cleaning strategies or reduce waste generation.

Air pollution from gas refinery through contamination with various elements disrupts semiarid Zagros oak (Quercus brantii Lindl.) forests, Iran

Soils and oak trees (Quercus brantii Lindl.) in Zagros forests are suffering from the air pollution caused by the Ilam Gas Refinery. Thus, for the first time, we investigated the contamination level of sulfur and trace elements in these ecosystems. Sampling of soil and tree leaves was carried out in different seasons of 2019 and at different distances from the gas refinery. The results showed that soils and leaves at the various distances compared with control distance (10,000 m) were more affected by the gas refinery. Distance from the pollution source and physicochemical properties of soils were the main factors affecting contamination of soil elements contents. The soils with pollution load indices (PLI) of 4.54 were in the highly polluted category. Sulfur was at highly polluted category in soils and were highly enriched in trees. The trees mainly absorbed studied elements via their aerial organs. Our findings indicated that oak trees with the highest value of metal accumulation index are influence tools for monitoring various elements in the polluted air produced by the gas refinery. It is recommended that the ecosystem components near the refinery be studied to accurately evaluate disorders in the food chain.

Distribution and contamination assessment of heavy metals in soils and sediments from the Fildes Peninsula and Ardley Island in King George Island, Antarctica

Concentrations of heavy metals (Cu, Pb, Zn, Cd and Cr) in surface soils and sediments collected in 2008 from 37 sampling sites in the Fildes Peninsula and Ardley Island were detected by atomic absorption spectrometry. The total contents of Cu, Pb, Zn, Cd and Cr ranged, respectively, from 61.36 to 562.2 mg/kg, 0.52 to 1.95 mg/kg, 54.61 to 577.9 mg/kg, 0.04 to 3.76 mg/kg and 6.83 to 25.9 mg/kg in soils and from 58.55 to 498.3 mg/kg, 0.60 to 2.51 mg/kg, 56.22 to 345.9 mg/kg, 0.07 to 5.77 mg/kg and 7.76 to 39.5 mg/kg in sediments. The geo-accumulation index and the pollution load index were calculated to evaluate the environmental effects of heavy metal pollutants, Cu, Zn and Cd, in the study area. Soils and sediments from Ardley Island were found to be moderately polluted with the studied metals. Pearson’s correlation analysis and principal component analysis were applied to assess the distribution pattern and potential source of heavy metals. The results suggest that Cu, Zn and Cd in the study area originated from both the lithogenic sources and penguin guano, while Pb and Cr were probably derived from lithogenic sources.

Evaluation of Groundwater Quality for Heavy Metals by Using Chemical Indices Approach in Karachi, Pakistan

Freshwater consumption has been increased because of population growth and economic development. At the same time, depletion and contamination of groundwater is subject of great concern. Karachi is the industrial hub and serves as the economic backbone of Pakistan. The research aims to investigate the heavy metal pollution in the groundwater of Korangi Industrial Area, one of the largest industrial estates in Karachi. Eighteen representative locations were selected to collect groundwater samples and study the concentrations of heavy metals Cr, Fe, Ni, Cu, Zn, and Pb. Pollution load index, Nemerow's pollution index, and geo accumulation index approaches were used to interpret the basic data. The average concentrations of the measured heavy metals were 354.67 µg.L-1 , 694.33 µg.L-1 , 39.2 µg.L-1 , 12.89 µg.L-1 , 9.5 µg.L-1 , and 6.17 µg.L-1 for Fe, Zn, Cu, Pb, Cr, and Ni, respectively. The results showed that groundwater quality in the study area is poor and mainly contaminated by Pb and Fe.

Snowpack Distribution Using Topographical, Climatological and Winter Season Index Inputs

A majority of the annual precipitation in many mountains falls as snow, and obtaining accurate estimates of the amount of water stored within the snowpack is important for water supply forecasting. Mountain topography can produce complex patterns of snow distribution, accumulation, and ablation, yet the interaction of topography and meteorological patterns tends to generate similar inter-annual snow depth distribution patterns. Here, we question whether snow depth patterns at or near peak accumulation are repeatable for a 10-year time frame and whether years with limited snow depth measurement can still be used to accurately represent snow depth and mean snow depth. We used snow depth measurements from the West Glacier Lake watershed, Wyoming, U.S.A., to investigate the distribution of snow depth. West Glacier Lake is a small (0.61 km2) windswept (mean of 8 m/s) watershed that ranges between 3277 m and 3493 m. Three interpolation methods were compared: (1) a binary regression tree, (2) multiple linear regression, and (3) generalized additive models. Generalized additive models using topographic parameters with measured snow depth presented the best estimates of the snow depth distribution and the basin mean amounts. The snow depth patterns near peak accumulation were found to be consistent inter-annually with an average annual correlation coefficient (r2) of 0.83, and scalable based on a winter season accumulation index (r2 = 0.75) based on the correlation between mean snow depth measurements to Brooklyn Lake snow telemetry (SNOTEL) snow depth data.

Determination and risk assessment of heavy metals in air dust fall particles

Background: Urban and industrial development has increased the concentration of heavy metals in various environments, and also, increased their amount in dust fall particles. The aim of this study was to determine and assess the risk of heavy metals in air dust fall particles. Methods: Sampling of air dust fall particles was performed using the British model Dust Fall Jar devices. Heavy metals concentrations in the samples were determined using an atomic absorption spectrometer device. Then, the risk assessment of heavy metals in air dust fall was calculated by three indicators including enrichment factor (EF), geo-accumulation index (Igeo), and integrated pollution index (IPI). Data were analyzed using descriptive statistics and Excel 2016 software. Results: Zn was the most abundant heavy metal. The results of EF index showed that the highest degree of enrichment of dust fall particles with heavy metals is related to Ag and the lowest one is related to Cr. Also, the changes of Mean of both Igeo and IP indicators were as Ag > Pb > Zn > Cd > Cu > Co > Cr. Conclusion: According to the results, it can be concluded that Cr metal is originated from the earth and other metals are of man-made origin and are mainly due to the emissions of vehicles and industries. Also, on average, the samples had very low pollution in relation to all metals. Although the amount of pollution caused by heavy metals has not exceeded the allowable limits, but considering industrial development programs in the region, continuous measures to control air pollution caused by industries, are absolutely necessary.

Can a Data-Driven Measure of Neuroanatomic Dementia Risk be Considered a Measure of Brain Aging?

There is an increasing interest in identifying aging-related factors which may be permissive of Alzheimer’s Disease (AD) emergence. We previously used machine learning to derive an index of neuroanatomic risk of dementia called AD pattern similarity (AD-PS) score using MRIs obtained in the Atherosclerosis Risk in Communities (ARIC) study. Here, we investigate the potential of the AD-PS scores as a brain-focused measure of biologic age. Among 1970 ARIC participants with MRI collected at ARIC Visit 5, we related AD-PS scores to three measures of aging: mortality (n=356) over 8 years of follow-up; an a priori panel of 32 proteins related to aging (N=1647); and a deficit accumulation index (DAI) based on 38 health-related measures. We found lower AD-PS scores associated with significantly lower mortality (HR=0.58, CI-95%, [0.45 - 0.75], p < 0.001) after adjusting for age, race, smoking and hypertension. Among the 32 proteins, nine were significantly associated to AD-PS scores (p < 0.05) with 4 remaining significant adjusting for multiple comparisons (Growth/differentiation factor 15, Tumor necrosis factor receptor superfamily member 1A and 1B and Collagen alpha-1(XVIII) chain). Finally, in a linear regression model after adjusting for age, race, sex, hypertension and smoking, AD-PS scores were associated with the DAI (p < 0.001). The consistent patterns of associations suggest that a data-driven measure of AD neuroanatomic risk may be capturing aspects of biologic age in older adults.

Effects of Human Activities on the Spatial Distribution, Ecological Risk and Sources of PTEs in Coastal Sediments

Potentially toxic elements (PTEs) have attracted substantial attention because of their widespread sources, long residue time and easy accumulation. PTEs in the surface sediments of inshore waters are strongly affected by human activities because these waters are a zone of interaction between the ocean and land. In the present study, to explore the environmental geochemical behaviour and source of PTEs in the surface sediments of coastal waters, the contents and spatial distributions of copper (Cu), lead (Pb), zinc (Zn), cadmium (Cd), chromium (Cr), mercury (Hg) and arsenic (As) in different regions of Xiamen Bay were investigated. The data were processed by multivariate statistical methods, and the distribution characteristics of PTEs in the surface sediments of Xiamen Bay were analysed. In addition, the pollution load index (PLI), geo-accumulation index (Igeo) and potential ecological index(RI) were used to evaluate the pollution degree and potential risk in the surface sediments of Xiamen Bay, and the positive matrix factorisation (PMF) model was used to analyse the source. The results show that Zn had the highest mean concentration, followed by Pb, Cr, Cu, As, Cd and Hg, among the seven PTEs. The mean contents of Pb, Zn, Cd, Cu and Hg, and especially Hg and Cd, were higher than the corresponding environmental background values. The average PLI value indicated that the Xiamen Bay sediment was moderately contaminated by PTEs. The Igeo results showed that Xiamen Bay was moderately to strongly polluted by Cd and Hg. The proportions of samples with low, medium and strong risk levels were 11.63%, 74.42%, and 13.95% in surface sediments, respectively. PMF models showed that the input of chemical fertilizer and medication, anthropogenic atmospheric components and terrestrial detritus were the main sources of PTEs in the surface sediment of Xiamen Bay.

Characteristics and Risk Assessment of 16 Metals in Street Dust Collected from a Highway in a Densely Populated Metropolitan Area of Vietnam

The present study focused on investigating the contamination and risk assessment for 16 metals in street dust from Ha Noi highway, Ho Chi Minh City. The results indicated that the concentrations of metals (mg/kg) were found, in decreasing order, to be Ti (676.3 ± 155.4) > Zn (519.2 ± 318.9) > Mn (426.6 ±113.1) > Cu (144.7 ± 61.5) > Cr (81.4 ± 22.6) > Pb (52.2 ± 22.9) > V (35.5 ± 5.6) > Ni (30.9 ± 9.5) > Co (8.3 ± 1.2) > As (8.3 ± 2.5) > Sn (7.0 ± 3.6) > B (5.7 ± 0.9) > Mo (4.1 ± 1.7) > Sb (0.8 ± 0.3) > Cd (0.6 ± 0.2) > Se (0.4 ± 0.1). The geo-accumulation index (Igeo) showed moderate contamination levels for Pb, Cd, Cu, Sn, Mo, and Zn. The enrichment factor (EF) values revealed moderate levels for Cd, Cu, Mo, and Sn but moderate–severe levels for Zn. The pollution load index of the heavy metals was moderate. The potential ecological risk (207.43) showed a high potential. Notably, 40.7% and 33.5% of the ecological risks were contributed by Zn and Mn, respectively. These findings are expected to provide useful information to decision-makers about environmental quality control strategies.

Elucidating the effect and mechanism of the brown coal-based amendment on plant availability of zinc, lead and cadmium in a Haplic Luvisols

Plants are a key link in the trophic chain and therefore may determine the global circulation of pollutants, including heavy metals (HMs). In the context of sustaining soil functions associated with food safety, the bioavailability of HMs should be reduced to a minimum needed for adequate plant nutrition. The objective of the study was to analyse the bioavailability of zinc, lead and cadmium in phacelia (Phacelia tanacetifolia Benth.) under conditions of varied soil pH and doses of brown coal-based organo-mineral amendment so-called the Rekulter. The experiment was carried out on Haplic Luvisols in field stone pots that sank into the ground, with the following HM content (in mg kg−1 of soil): 90.0 (Zn), 60.4 (Pb) and 0.80 (Cd). The Rekulter was applied to the soil in the amounts of 180, 360 and 720 g per pot. The bio-accumulation index (BI) was calculated as a ratio of a HM content in a plant to its total content in a soil sample, and it was used to evaluate bioavailability. The application of the Rekulter reduced the bioavailability of the studied heavy metals: the lowest BI values were found in the case of Pb. The uptake of HMs by phacelia was the smallest for the highest applied Rekulter dose at a soil pH of approximately 6.0. The bioavailability of Zn, Pb and Cd was influenced by soil pH and organic matter content, reducing their mobility and possible environmental risks. The Rekulter reduced HM bioavailability: the lowest bio-accumulation index (BI) values were found in the case of Pb. The application of the Rekulter into soil improved the physical, chemical and biological properties of soil, including the reduction of contaminant bioavailability.