Proximate composition and mineral contents in the body wall of two species of sea cucumber from Oman Sea

The proximate composition and mineral contents of Stichopus horrens and Holothuria arenicola from Chabahar Bay were analyzed and investigated. During the present study, we aimed to demonstrate the nutritive value. The approximate percent composition of moisture, protein, fat, and ash were 92.8, 3.47, 0.4, and 3.33% in S. horrens and 93, 4.4, 0.6, and 2% in H. arenicola, respectively. Atomic absorption spectrophotometry of the ashes indicated the body wall of two species of sea cucumbers contained higher amounts of both macro minerals (92.5 mg/100 g Mg in S. horrens and 115 mg/100 g Mg in H. arenicola; 106.25 mg/100 g Ca in S. horrens and 83.25 mg/100 g Ca in H. arenicola) and trace elements (521.781 mg/100 g Fe in S. horrens; 60.354 mg/100 g Fe in H. arenicola, and 0.096 mg/100 g Zn in S. horrens; 0.04 mg/100 g Zn in H. arenicola). For both species, there were high content of protein and essential mineral. Also, they have low content of fat in the body wall of two species in the experiment.     

Re-construction of the shut-down PM10 monitoring stations for the reliable assessment of PM10 in Berlin using fuzzy modelling and data transformation

A dense monitoring network is vital for the reliable assessment of PM10 in different parts of an urban area. In this study, a new idea is employed for the re-construction of the 20 shut-down PM10 monitoring stations of Berlin. It endeavours to find the non-linear relationship between the hourly PM10 concentration of both the still operating and the shut-down PM10 monitoring stations by using a fuzzy modelling technique, called modified active learning method (MALM). In addition, the simulations were performed by using not only raw PM10 databases but also log-transformed PM10 databases for skewness reduction. According to the results of hourly PM10 simulation (root mean square error about 13.0 μg/m³, correlation coefficient 0.88), the shut-down stations have been appropriately simulated and the idea of dense monitoring network development by the re-construction of the shut-down stations was realised. The results of simulations using raw and log-transformed databases showed that data transformation has no significant effect on the performance of MALM in the simulation of shut-down PM10 stations. By the combination of the 11 still operating stations and the 20 re-constructed stations, a dense monitoring network was generated for Berlin and was utilised for the calculation of the reliable monthly and mean annual PM10 concentration for five different PM10 zones in Berlin (the suburban-background, urban-background, urban-traffic, rural-background and suburban-traffic areas). The results showed that the mean annual concentration of PM10 at the five zones increased by about 13.0% in 2014 (26.3 μg/m³) in comparison with 2013 (23.3 μg/m³). Furthermore, the mean annual concentration of PM10 in the traffic lanes of the suburban (2013 25.0 μg/m³, 2014 26.9 μg/m³) and urban (2013 27.7 μg/m³, 2014 31.3 μg/m³) areas is about 14 and 20% higher than the PM10 concentration of suburban-background (2013 21.3 μg/m³, 2014 24.5 μg/m³) and urban-background (2013 23.0 μg/m³, 2014 26.1 μg/m³) areas, respectively.     

Integrating multi-criteria decision analysis for a GIS-based hazardous waste landfill sitting in Kurdistan Province, western Iran

The evaluation of a hazardous waste disposal site is a complicated process because it requires data from diverse social and environmental fields. These data often involve processing of a significant amount of spatial information which can be used by GIS as an important tool for land use suitability analysis. This paper presents a multi-criteria decision analysis alongside with a geospatial analysis for the selection of hazardous waste landfill sites in Kurdistan Province, western Iran. The study employs a two-stage analysis to provide a spatial decision support system for hazardous waste management in a typically under developed region. The purpose of GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of a multi-criteria decision analysis (MCDA) to identify the most suitable sites using the information provided by the regional experts with reference to new chosen criteria. Using 21 exclusionary criteria, as input layers, masked maps were prepared. Creating various intermediate or analysis map layers a final overlay map was obtained representing areas for hazardous waste landfill sites. In order to evaluate different landfill sites produced by the overlaying a landfill suitability index system was developed representing cumulative effects of relative importance (weights) and suitability values of 14 non-exclusionary criteria including several criteria resulting from field observation. Using this suitability index 15 different sites were visited and based on the numerical evaluation provided by MCDA most suitable sites were determined.     

Mathematical Modeling of SO2 Absorption in a Venturi Scrubber

Abstract

A three-dimensional mathematical model was used to predict the removal efficiency of a venturi scrubber for SO₂ absorption into a water and alkaline solution. In order to obtain better results, nonuniform droplet concentration distribution was considered. The results of the model with nonuniform droplet concentration distribution are compared with several sets of experimental data, as well as with prediction data of a mathematical model with uniform droplet concentration distribution. Without exception, all comparisons indicated that including nonuniformity of droplet concentration distribution in the model will significantly improve the agreement between the experimental data and predicted values.     

A Model for Uptake of Pollutants by Vegetation

A mass transfer approach is used in developing a practical mathematical model of gaseous pollutant uptake by leaves in which a series of resistances is summed across a concentration difference. The body of information presented in this paper is directed to plant pathologists or physiologists in the field of vegetal-pollutant effects and to people interested in the natural removal of air pollutants by vegetation. Correlations are given to calculate the aerodynamic and the stomatal resistances to uptake, while both a qualitative investigation and quantitative estimates are made of the mesophyllic resistance. The factors which control the aerodynamic resistance, r_a, are leaf size and wind speed, while the leaf physiology is the determinant of the stomatal resistance, r_s . It is noted that the chemical reaction rate and pollutant diffusivity in the mesophyll control the mesophyllic resistance, r_m, though the overall gas phase mesophyllic resistance, Hr_m, is strongly a function of pollutant solubility in water. Finally, the overall model is compared to earlier experimental work on vegetal uptake of SO₂.     

Health risk assessment of potentially toxic elements intake via food crops consumption: Monte Carlo simulation-based probabilistic and heavy metal pollution index

Environmental Science and Pollution Research - The aim of this study is to assess the content of heavy metals and their potential health risk in consumed food crops. To this end, the samples from...     

Evaluation of a novel hollow fiber membrane technique for collection of 1,1-dimethylhydrazine in air

The purpose of this study was to develop a novel one-step method for the time-weighted average determination of 1,1-dimethylhydrazine (UDMH) in the air followed by spectrophotometric detection. For this reason, 0.1% hydrochloric acid as the absorbent was used in hollow fiber (HF) membrane for sampling of UDMH from an atmospheric standard chamber. Response surface methodology (RSM) with central composite design (CCD) was used to optimize the sampling parameters, such as flow rate and sampling time. Moreover, several analytical parameters including breakthrough (BT) volume, storage time, and carryover effect of the proposed HF were investigated. The results showed that optimal sampling rate was 9.90 mL/min. In order to validate the proposed method, it was compared with the National Institute for Occupational Safety and Health (NIOSH) 3515 method, which showed good compatibility between the two methods. Intra- and inter-day repeatability values of the HF method were in the range 0.082–0.1 and 0.091–0.12, respectively, and the limits of detection (LODs) and limits of quantitation (LOQs) were 0.002 and 0.006 ng/mL, respectively. The storage time of the proposed HF was 7 days at 2 °C. These results demonstrated that the one-step HF membrane offered a high sensitivity for sampling of UDMH in air.     

A heuristic optimization approach for Air Quality Monitoring Network design with the simultaneous consideration of multiple pollutants

An interactive optimization methodology for allocating the number and configuration of an Air Quality Monitoring Network (AQMN) in a vast area to identify the impact of multiple pollutants is described. A mathematical model based on the multiple cell approach (MCA) was used to create monthly spatial distributions for the concentrations of the pollutants emitted from different emission sources. These spatial temporal patterns were subject to a heuristic optimization algorithm to identify the optimal configuration of a monitoring network. The objective of the optimization is to provide maximum information about multi-pollutants (i.e., CO, NO(x) and SO(2)) emitted from each source within a given area. The model was applied to a network of existing refinery stacks and the results indicate that three stations can provide a total coverage of more than 70%. In addition, the effect of the spatial correlation coefficient (R(C)) on total area coverage was analyzed. The modeling results show that as the cutoff correlation coefficient R(C) is increased from 0.75 to 0.95, the number of monitoring stations required for total coverage is increased. A high R(C) based network may not necessarily cover the entire region, but the covered region will be well represented. A low R(C) based network, on the other hand, would offer more coverage of the region, but the covered region may not be satisfactorily represented.     

Bioremediation of DSO contaminated soil

Seven strains isolated from DSO (disulfide oil) contaminated soils. Among them, two strains had high potential to remove DSO from contaminated soils. These strains identified as Paenibacillus (a gram positive, nitrogen fixing spore, spore forming bacillus) and Rhodococcus (a gram positive, catalase positive, acid fast forming bacteria), by preliminary tests. The optimal conditions for DSO removal from contaminated soils were determined. The biotic depletion for Paenibacillus pre-grown in nutrient broth was 24.3% and for Rhodococcus was 19.3%. Bioremediation of DSO in soil was investigated by gas chromatography and UV–vis absorption spectroscopy techniques. The results showed that addition of water (20 μl/g soil) to soil is necessary for DSO removal by both strains and none of the strains could remove DSO in concentrations more than 30 μg/g soil. The results also showed that none of these strains could degrade DSO under anaerobic condition.     

The Effect of Scale-Up on the Performance of High Energy Scrubbers

An experimental investigation has been carried out to examine the effect of scale-up on the performance of scrubbers for a wide range of operating conditions. A pilot plant with a maximum air flow rate of 400 cfm and a water flow rate of 4 gpm was used for this study. For the same operating conditions, the performance of 1.5 in. orifice type scrubber was found better than that of 1.0 in. size. The results were categorized according to the size of the particles, classed as large (1.5 to 3.5μ diam), medium (0.6 to 1.5μ diam) and small (less than O.6μ diam). Although the magnitude of improvement of the collection efficiency was dependent on the operating conditions, differences to the extent of 20% were obtained. The improvement of the collection efficiency for the larger scrubber was found to be due to the influence of the main stream turbulence.