SPME-based air sampling method for inhalation exposure assessment studies: case study on perchlorethylene exposure in dry cleaning

Exposure to perchlorethylene, especially for dry cleaning workers and for people living near dry cleaning shops, could lead to several diseases and disorders. This study examines the value of solid-phase microextraction (SPME) for sampling perchlorethylene in the atmosphere of dry cleaning shops. Carboxen/polydimethylsiloxane (CAR/PDMS) in 0.5-cm retracted mode was selected. There were no significant differences between sampling rates at different temperatures (range of 20 to 30 °C) and air velocities (2 to 50 cm/s). On the opposite, relative humidity (RH) had a significant effect on sampling rates. Method reproducibility was realized in the laboratory and field conditions and was 6.2 % and 7 to 11 %, respectively. Repeatability was also determined as 8.9 %. Comparison of the results according to the American Industrial Hygiene Association exposure assessment strategy showed the SPME sampler yields more conservative results in comparison with traditional standard method.     

Characterization of ionic composition of TSP and PM10 during the Middle Eastern Dust (MED) storms in Ahvaz, Iran

Because of the recent frequent observations of major dust storms in southwestern cities in Iran such as Ahvaz, and the importance of the ionic composition of particulate matters regarding their health effects, source apportionment, etc., the present work was conducted aiming at characterizing the ionic composition of total suspended particles (TSP) and particles on the order of ～10?μm or less (PM(10)) during dust storms in Ahvaz in April-September 2010. TSP and PM(10) samples were collected and their ionic compositions were determined using an ion chromatography. Mean concentrations of TSP and PM(10) were 1,481.5 and 1,072.9?μg/m(3), respectively. Particle concentrations during the Middle Eastern Dust (MED) days were up to four times higher than those in normal days. Ionic components contributed to only 9.5% and 11.3% of the total mass of TSP and PM(10), respectively. Crustal ions were most abundant during dust days, while secondary ions were dominant during non-dust days. Ca(2+)/Na(+) and Cl(-)/Na(+) ratios can be considered as the indicators for identification of the MED occurrence. It was found that possible chemical forms of NaCl, (NH(4))(2)SO(4), KCl, K(2)SO(4), CaCl(2), Ca(NO(3))(2), and CaSO(4) may exist in TSP. Correlation between the anionic and cationic components suggests slight anion and cation deficiencies in TSP and PM(10) samples, though the deficiencies were negligible.     

Effect of fertilizer application on soil heavy metal concentration

A large amount of chemicals is annually applied at the agricultural soils as fertilizers and pesticides. Such applications may result in the increase of heavy metals particularly Cd, Pb, and As. The objective of this study was to investigate the variability of chemical applications on Cd, Pb, and As concentrations of wheat-cultivated soils. Consequently, a study area was designed and was divided into four subareas (A, B, C, and D). The soil sampling was carried out in 40 points of cultivated durum wheat during the 2006–2007 periods. The samples were taken to the laboratory to measure their heavy metal concentration, soil texture, pH, electrical conductivity, cationic exchange capacity, organic matter, and carbonate contents. The result indicated that Cd, Pb, and As concentrations were increased in the cultivated soils due to fertilizer application. Although the statistical analysis indicates that these heavy metals increased significantly (P value < 0.05), the lead and arsenic concentrations were increased dramatically compared to Cd concentration. This can be related to overapplication of fertilizers as well as the pesticides that are used to replant plant pests, herbs, and rats.     

GIS-based statistical model for the prediction of flood hazard susceptibility

At present, flood is the most significant environmental problem in the entire world. In this work, flood susceptibility (FS) analysis has been done in the Dwarkeswar River basin of Bengal basin, India. Fourteen flood causative factors extracted from different datasets like DEM, satellite images, geology, soil and rainfall data have been considered to predict FS. Three heuristic models and one statistical model fuzzy Logic (FL), frequency ratio (FR), multi-criteria decision analysis (MCDA) and logistic regression (LR) have been used. The validating datasets are used to validate these models. The result shows that 68.71%, 68.7%, 60.56% and 48.51% area of the basin is under the moderate to very high FS by the MCDA, FR, FL and LR, respectively. The ROC curve with AUC analysis has shown that the accuracy level of the LR model (AUC?=?0.916) is very much successful to predict the flood. The rest of the models like FL, MCDA and FR (AUC?=?0.893, 0.857 and 0.835, respectively) have lesser accuracy than the LR model. The elevation was the most dominating factor with coefficient value of 19.078 in preparation of the FS according to the LR model. The outcome of this study can be implemented by local and state authority to minimize the flood hazard.

     

Estimating Population Size and Detection Probability of the Lorestan Newt,Neurergus kaiseri (Schmidt, 1952) using an Integrated Method

Russian Journal of Ecology - Robust estimates of species population abundance are necessary for the success of conservation plans and species management strategies. In the present study, our main...     

Differential growth,nutrition, physiology,and gene expression in Melissa officinalis mediated by zinc oxide and elemental selenium nanoparticles

Environmental Science and Pollution Research - Regarding the rapid progress in the production and consumption of nanobased products, this research considered the behavior of Melissa officinalis...     

Source apportionment of PAHs and n-alkanes in respirable particles in Tehran,Iran by wind sector and vertical profile

The vertical concentration profiles and source contributions of polycyclic aromatic hydrocarbons (PAHs) and n-alkanes in respirable particle samples (PM₄) collected at 10, 100, 200 and 300-m altitude from the Milad Tower of Tehran, Iran during fall and winter were investigated. The average concentrations of total PAHs and total n-alkanes were 16.7 and 591 ng/m³, respectively. The positive matrix factorization (PMF) model was applied to the chemical composition and wind data to apportion the contributing sources. The five PAH source factors identified were: ‘diesel’ (56.3 % of total PAHs on average), ‘gasoline’ (15.5 %), ‘wood combustion, and incineration’ (13 %), ‘industry’ (9.2 %), and ‘road soil particle’ (6.0 %). The four n-alkane source factors identified were: ‘petrogenic’ (65 % of total n-alkanes on average), ‘mixture of petrogenic and biomass burning’ (15 %), ‘mixture of biogenic and fossil fuel’ (11.5 %), and ‘biogenic’ (8.5 %). Source contributions by wind sector were also estimated based on the wind sector factor loadings from PMF analysis. Directional dependence of sources was investigated using the conditional probability function (CPF) and directional relative strength (DRS) methods. The calm wind period was found to contribute to 4.4 % of total PAHs and 5.0 % of total n-alkanes on average. Highest average concentrations of PAHs and n-alkanes were found in the 10 and 100 m samples, reflecting the importance of contributions from local sources. Higher average concentrations in the 300 m samples compared to those in the 200 m samples may indicate contributions from long-range transport. The vertical profiles of source factors indicate the gasoline and road soil particle-associated PAHs, and the mixture from biogenic and fossil fuel source-associated n-alkanes were mostly from local emissions. The smaller average contribution of diesel-associated PAHs in the lower altitude samples also indicates that the restriction of diesel-fueled vehicle use in the central area of Tehran has been effective in reducing the PAHs concentration.     

Assessment of land cover changes & water quality changes in the Zayandehroud River Basin between 1997–2008

Water quality of rivers is strongly influenced by landscape characteristics of their watershed, including land use /cover types, and their spatial configuration. This research evaluates the effects of land cover changes on the water quality of the Zayandehroud River, which is the most important river in the center of Iran. The main goal of this study was to quantify the change in rangelands, forests, and bare lands in the Zayandehroud river basin, which suffered intense human interference, in a period of 11 years (1997–2008), and to evaluate how landscape patterns (including the number of patches, edge density, percentage of rangelands, forests, and bare lands) influence on the 14 water quality indices (including BOD5, EC, NO3, P, and TDS) measured in 10 stations along the river. Results showed that from 1997 to 2008, bare lands increased from 5.8 to 20 %, while rangelands decreased from 70 to 55 % in the whole basin. The results indicated that water quality was significantly correlated with both the proportions and configuration of rangeland and bare land areas. The total edge (TE) of rangeland area had positive effects on water quality, especially on BOD5 and EC. Percentage of landscape (PLAND) and largest patch index (LPI) metrics of rangeland had positive effect on decreasing nutrient (NO₃, PO₄). The results showed that water quality was more likely degraded when there was high edge density (ED) of bare lands. Results of this study also revealed that degradation of rangeland lead to the degradation of water quality. Finding of this study highlights the importance of rangeland conservation in water quality management at landscape scale.     

Heavy metals fractionation in surface sediments of Gowatr bay-Iran

Establishing the effectiveness of habitat features to act as surrogate measures of diversity and abundance of juvenile reef fish provides information that is critical to coral reef management. When accurately set on a broader spatial context, microhabitat information becomes more meaningful and its management application becomes more explicit. The goal of the study is to identify coral reef areas potentially important to juvenile fishes in Ngederrak Reef, Republic of Palau, across different spatial scales. To achieve this, the study requires the accomplishment of the following tasks: (1) structurally differentiate the general microhabitat types using acoustics; (2) quantify microhabitat association with juvenile reef fish community structure; and (3) conduct spatial analysis of the reef-wide data and locate areas optimal for juvenile reef fish settlement. The results strongly suggest the importance of branching structures in determining species count and abundance of juvenile reef fish at the outer reef slope of Ngederrak Reef. In the acoustic map, the accurate delineation of these features allowed us to identify reef areas with the highest potential to harbor a rich aggregation of juvenile reef fish. Using a developed spatial analysis tool that ranks pixel groups based on user-defined parameters, the reef area near the Western channel of Ngederrak is predicted to have the most robust aggregation of juvenile reef fish. The results have important implications not only in management, but also in modeling the impacts of habitat loss on reef fish community. At least for Ngederrak Reef, the results advanced the utility of acoustic systems in predicting spatial distribution of juvenile fish.