Influence of aggregated particles on biodegradation activities for dimethylarsinic acid (DMA) in Lake Kahokugata

Aquatic arsenic cycles mainly depend on microbial activities that change the arsenic chemical forms and influence human health and organism activities. The microbial aggregates degrading organic matter are significantly related to the turnover between inorganic arsenic and organoarsenic compounds. We investigated the effects of microbial aggregates on organoarsenic mineralization in Lake Kahokugata using lake water samples spiked with dimethylarsinic acid (DMA). The lake water samples converted 1 μmol L⁻¹ of DMA to inorganic arsenic for 28 d only under anaerobic and dark conditions in the presence of microbial activities. During the DMA mineralization process, organic aggregates >5.0 μm with bacterial colonization increased the densities. When the organic aggregates >5.0 μm were eliminated from the lake water samples using filters, the degradation activities were reduced. DMA in the lake water would be mineralized by the microbial aggregates under anaerobic and dark conditions. Moreover, DMA amendment enhanced the degradation activities in the lake water samples, which mineralized 50 μmol L⁻¹ of DMA. The DMA-amended aggregates >5.0 μm completely degraded 1 μmol L⁻¹ of DMA with a shorter incubation time of 7 d. The supplement of KNO₃ and NaHCO₃ to lake water samples also shortened the DMA-degradation period. Presumably, the bacterial aggregates involved in the chemical heterotrophic process would contribute to the DMA-biodegradation process in Lake Kahokugata, which is induced by the DMA amendment.     

Cytotoxicity estimation of ionic liquids based on their effective structural features

Cytotoxicity of a diverse set of 227 ionic liquids (taken from UFT/Merck Ionic Liquids Biological Effects Database) containing 94 imidazolium, 53 pyridinium, 23 pyrrolidinium, 22 ammonium, 15 piperidinium, 10 morpholinium, 5 phosphanium, and 5 quinolinium cations in combination with 25 different types of anions to Leukemia Rat Cell Line (IPC-81) was estimated from their structural parameters using quantitative structure - toxicity relationship “QSTR” methodology. Linear and nonlinear models were developed using genetic algorithm (GA), multiple linear regressions (MLR) and multilayer perceptron neural network (MLP NN) approaches. Robustness and reliability of the constructed models were evaluated through internal and external validation methods. Furthermore, chemical applicability domain was determined via leverage approach. In this work, it was revealed that the cationic moieties make the major contribution to cytotoxicity and the anionic parts play a secondary role in cytotoxicity of the ionic liquids studied here. Structural information represented in this work, can be used for a rational design of safer ILs.     

The use of artificial neural networks and multiple linear regression to predict rate of medical waste generation

Prediction of the amount of hospital waste production will be helpful in the storage, transportation and disposal of hospital waste management. Based on this fact, two predictor models including artificial neural networks (ANNs) and multiple linear regression (MLR) were applied to predict the rate of medical waste generation totally and in different types of sharp, infectious and general. In this study, a 5-fold cross-validation procedure on a database containing total of 50 hospitals of Fars province (Iran) were used to verify the performance of the models. Three performance measures including MAR, RMSE and R² were used to evaluate performance of models. The MLR as a conventional model obtained poor prediction performance measure values. However, MLR distinguished hospital capacity and bed occupancy as more significant parameters. On the other hand, ANNs as a more powerful model, which has not been introduced in predicting rate of medical waste generation, showed high performance measure values, especially 0.99 value of R² confirming the good fit of the data. Such satisfactory results could be attributed to the non-linear nature of ANNs in problem solving which provides the opportunity for relating independent variables to dependent ones non-linearly. In conclusion, the obtained results showed that our ANN-based model approach is very promising and may play a useful role in developing a better cost-effective strategy for waste management in future.     

Determination of nickel, copper, zinc and lead in human scalp hair in Syrian occupationally exposed workers by total reflection X-ray fluorescence

In this study, an attempt has been made to study methane flux and quantification of heavy metals from Municipal Solid Waste (MSW) landfill areas of selected cities in India. During the period of study, the average value of methane flux was estimated from these landfill areas varied from 146–454 mg/m2/h. Methane emission from landfill is of serious environmental global concern as it accounts for approximately 15 percentages of current Greenhouse gas emissions. It has been estimated that methane emission, from landfill areas in the world, in next two decades would be same as that what is emitted from paddy fields presently. Besides, the estimation of methane flux, quantification of some heavy metals was conducted to analyse the suitability of using MSW as compost. The average values for metals were observed to be both within the range of USEPA and Indian standards for MSW disposal in landfill areas and to be used as compost respectively.     

Evaluation of Pb, Cu, Zn, Cd, Ni and Fe levels in Rosmarinus officinalis labaiatae (Rosemary) medicinal plant and soils in selected zones in Jordan

The concentration of heavy metals including Pb, Cu, Zn, Cd, Ni and Fe in different parts of Rosmarinus officinalis medicinal plant grown in Jordan were evaluated. Medicinal plant samples and soil samples were collected from three different zones in Jordan (Irbid, Al-Mafraq and Ma’an). Samples were analyzed by atomic absorption spectrometry (AAS) after chemical treatments using acid digestion procedures. Heavy metal levels in washed and unwashed in each part of R. officinalis were analyzed and compared statistically. Results show that concentrations of investigated heavy metals were varied from plant part to another part of R. officinalis. For example, Pb, Zn, Cu and Cd in most parts of R. officinalis in the three zones were concentrated in the following order: flowers, leaves, stems, whereas Pb, Ni and Fe were concentrated in order as follows: leaves, flowers and stems. Heavy metal concentrations in soil samples was evaluated and correlated with their levels in R. officinalis. Two standard reference materials of plant (SRM 1790a; spinach leaves and CRM 281; rye grass) and one standard reference materials of soil (GBW 07406) were examined to validate the method used. Results show that high recoveries were obtained.     

Assessment of elemental concentrations in the urban air (case study: Tehran city)

Tehran is one of the megacities of the world with a population of over eight million. Its air is highly polluted mainly due to the suspended particulate matters, which encompasses a wide spectrum of chemical elements. These elements based on their type, size, and impact on the life cycle have various environmental and heath risks. In this research, the neutron activation method is used to determine the concentration levels of Al, Ba, Fe, Mg, and V in the urban air. Thus, two districts of Tehran with different characteristics are selected. District 21 includes much of the industries located in Tehran metropolitan and is considered as an industrial area. In contrast, district 22 lacks any significant industrial activity. It is a newly established and expanding district adjacent to district 21 with a great deal of constructional activities. For the measurement of the suspended particulate matters in the air, the various sections of the aforesaid districts with industrial, residential, heavily congested traffic, residential/commercial, residential/heavily congested traffic, and residential/industrial classifications were identified. Subsequently, 24 sampling stations were selected. The sampling of the suspended particulate matters was conducted with the aid of a high volume pump containing 125 mm cellulose filters in two different time intervals. After completion of the sampling process, the samples were prepared and sent to the research reactor of the Iran Nuclear Energy Organization for Neutron Activation. During the next steps, the radiations emitted from the samples were registered, the radiation curves were plotted, and the amounts of the trace elements were determined. As a result, the average concentration levels of Al, Ba, Fe, Mg, and V were identified to be 3.301140, 2.273658 × 10, 4.0681696 × 10^???1, 3.5525475 × 10^???1, and 3.04075 × 10^???2 μg/m³, respectively. Moreover, the emission sources of the aforesaid elements into the air were identified. The concentration levels of these elements in the industrial and heavily congested traffic sections were higher. Finally, it was concluded that the statistical analysis of these elements presents a meaningful correlation among them.     

Monitoring results for organochlorine pesticides in soil and water from selected obsolete pesticide stores in Pakistan

Seasonal changes in micromineral and macromineral concentrations in tissues of shrimp (Parapenaus longirostris) from Marmara Sea were measured for a 1-year period by using inductively coupled plasma mass spectrometer. The contents of investigated minerals in shrimp were found to be in the range of 0.374–0.716 mg/kg for Hg, 0.526–1.286 mg/kg for Se, 0.007–0.098 mg/kg for Cd, 0.197–0.230 mg/kg for Pb, 5.194–7.600 mg/kg for Cu, 11.090–17.707 mg/kg for Zn, 22.128–38.850 mg/kg for Al, 61.769–88.437 mg/kg for Fe, 0.262–0.368 mg/kg for As, 0.081–0.249 mg/kg for Co, 0.850–1.459 mg/kg for Mn, 0.316–0.507 mg/kg for Ni, 0.032–0.107 mg/kg for Sn, 1.262–1.502 mg/kg for Cr, 2,813.770–3,317.819 mg/kg for Na, 3,702.230–4,479.648 mg/kg for K, 495.782–650.280 mg/kg for Mg, 790.407–1,016.112 mg/kg for Ca, 2,685.873–3,657.658 mg/kg for P, and 0.454–0.942 mg/kg for I. The levels of Hg found in autumn were higher than maximum levels proposed by the European legislation.     

Hydrogeochemistry and water quality assessment of the Kor–Sivand Basin, Fars province, Iran

In order to assess the quality and suitability of waters in the Kor-Sivand river basin, 60 water samples from the Kor river and 90 water samples from wells in the basin were studied. Assessments were based on Piper's and Gibbs' diagrams for water quality, Food and Agricultural Organization's (FAO) guidelines, and US Salinity Laboratory diagram for water suitability. The results showed that the river water is of Ca-HCO(3) type, while well water is of Ca-Cl and Na-Cl type. Based on Gibbs' diagram, the source of soluble ions in the river water samples is the weathering of stones over which water flows, while evaporation was found to be the dominant process in the ion concentration of the well samples. According to the FAO Guidelines, the salinity of surface water for irrigation did not cause great restrictions; however, many of these waters could create potential permeability problems. In the groundwater samples, a high salt concentration is more important than the infiltration problem. Mg hazard values at some sites limit its use for agricultural purposes. One third of the river water samples and two thirds of well waters had more than 50% magnesium. Saturation indices showed that 94% of the analyzed water samples are supersaturated with calcite, aragonite, and dolomite. Based on the US Salinity Laboratory diagram, river water samples were classified as C(2)S(1) and C(3)S(1), while C(4)S(3), C(4)S(4), C(2)S(1), and C(3)S(1) were the most dominant classes in well samples. Some management practices necessary for sustainable development of water resources in the study area were discussed briefly, including appropriate selection of crops, adequate drainage, leaching, blending and cyclic use of saline water, proper irrigation method, and addition of soil amendment.     

Climatology of atmospheric circulation patterns of Arabian dust in western Iran

Being in vicinity of vast deserts, the west and southwest of Iran are characterized by high levels of dust events, which have adverse consequences on human health, ecosystems, and environment. Using ground based dataset of dust events in western Iran and NCEP/NCAR reanalysis data, the atmospheric circulation patterns of dust events in the Arabian region and west of Iran are identified. The atmospheric circulation patterns which lead to dust events in the Arabian region and western Iran were classified into two main categories: the Shamal dust events that occurs in warm period of year and the frontal dust events as cold period pattern. In frontal dust events, the western trough or blocking pattern at mid-level leads to frontogenesis, instability, and air uplift at lower levels of troposphere in the southwest of Asia. Non-frontal is other pattern of dust event in the cold period and dust generation are due to the regional circulation systems at the lower level of troposphere. In Shamal wind pattern, the Saudi Arabian anticyclone, Turkmenistan anticyclone, and Zagros thermal low play the key roles in formation of this pattern. Summer and transitional patterns are two sub-categories of summer Shamal wind pattern. In summer trough pattern, the mid-tropospheric trough leads to intensify the surface thermal systems in the Middle East and causes instability and rising of wind speed in the region. In synthetic pattern of Shamal wind and summer trough, dust is created by the impact of a trough in mid-levels of troposphere as well as existing the mentioned regional systems which are contributed in formation of summer Shamal wind pattern.