Simultaneous derivatization and extraction of nitrophenols in soil and rain samples using modified hollow-fiber liquid-phase microextraction followed by gas chromatography–mass spectrometry

A simple and sensitive method based on a modified hollow-fiber liquid-phase microextraction followed by gas chromatography–mass spectrometry has been successfully developed for the extraction and simultaneous derivatization of some nitrophenols (NPs) in soil and rain samples. Microwave-assisted solvent extraction was used for the extraction of NPs from the soil, while the rain sample was directly applied to the previously mentioned method. Briefly, in this method, the analytes were extracted from aqueous samples into a thin layer of organic solvent (dodecane?+?10 % tri-n-octylphosphine oxide) sustained in the pores of a porous hollow fiber. Then, they were back-extracted using a small volume of organic acceptor solution (25 μl; 10 mg/L N-methyl-N-(trimethylsilyl)trifluoroacetamide, as derivatization reagent, in acetonitrile) that was located inside the lumen of the hollow fiber. Under the optimized extraction conditions, enrichment factors of 255 to 280 and limits of detection of 0.1 to 0.2 μg/L (S/N?=?3) with dynamic linear ranges of 1–100 μg/L were obtained for the analytes. The accuracy of the approach was tested by the relative recovery experiments on spiked samples, with results ranging from 93 to 113 %. The method was shown to be rapid, cost-effective, and potentially interesting for screening purposes.     

Dose-response modeling for developmental neurotoxicity data

The fact that maternal exposures to some chemicals during pregnancy can adversely affect the structure and function of the nervous system in the offspring is well established. Government agencies have for a long time been concerned with regulation of developmental neurotoxicants and safe perinatal exposures. However, despite this concern, current guidelines provide only broad and nonspecific recommendations and lack clear directions for a model based approach to risk estimation. In this paper we propose a dose-response model for the nonquantal data obtained from developmental neurotoxicological experiments. To account for the critical issue of the correlation among responses from pups in the same litter, the so called intralitter correlation, a hierarchical distributional structure is used to derive the underlying unconditional distribution of responses. The maximum likelihood method is used to estimate model parameters and the covariance matrix of the estimates is derived. An example is used to illustrate the results.     

Effect of different biochars amendment on soil biological indicators in a calcareous soil

Environmental Science and Pollution Research - Previous studies suggest that biochar has potential to benefit soil when used as an amendment, but only few studies have investigated how the...     

Mercury accumulation in selected tissues of shrimp Penaeus merguiensis from Musa estuary,Persian Gulf: variations related to sex,size, and season

The levels of mercury in tissues of Penaeus merguiensis from Musa estuary, northwest of the Persian Gulf, were investigated. This study assessed the relationship between mercury levels in hepatopancrea, gill, and muscle with sex, size, and season. The order of mercury concentrations in tissues of the shrimp P. merguiensis was as follows: hepatopancreas > gill > muscle. There was a positive correlation between mercury concentrations in shrimp species with sex and size of its food items. We expected to see higher mercury levels in tissues of female species because they are larger and can eat larger food items. Also, there was a positive correlation between mercury concentrations in shrimp species with its food source. Therefore, female species feed more on shrimp and plant and are contaminated with high levels of mercury. There was significant difference (p?<?0.05) in mercury levels between different seasons; higher mercury levels were found in July (summer season).     

Heavy metal bioaccumulation and risk assessment for wild and farmed beluga sturgeon caviar

Because of over-exploitation of sturgeon for caviar production, they have been listed worldwide in annex II of the Convention on International Trade in Endangered Species regulations; so caviar production using aquaculture is increasingly seen as a feasible way to reduce overfishing. The accumulation of the nonessential metals As, Ba, Cd, Hg, Pb, and Sn was determined in the caviar of farmed and wild Beluga sturgeon (Huso huso). The levels of As in both and Cd in wild samples were less than 0.01 mg kg^?1 wet weight, and the comparison for all of the metals studied did not show large fluctuations in metal concentrations between farmed and wild caviar samples. The average for each toxic metal was below the permissible limits proposed by the UK’s Ministry of Agriculture, Fisheries and Foods (2000). The maximum allowable daily consumption rate of caviar was calculated; however, the health risks from caviar consumption are uncertain because the amount of caviar consumed by heavy users is not known.     

Re-examining the water affordability: A comparison of alternative measures

Water affordability is determined by the percentage of income households that must allocate to municipal water services, while factoring in essential or basic needs water use. With the rise in water prices reported in most areas of the country along with somewhat stagnant income growth—a combination that suggests ceteris paribus—more of a household's disposable income is being spent on water services. This paper adds to the discussion in three ways. First, given the lack of a consistent definition for “affordability” and the subjective connotation associated with such a term, we develop and compare five different water expenditure ratios, including two different measures of water for essential needs, as well as measures for indoor, efficient, and actual water use. Second, because of the granularity of our data, we illustrate how such “affordability” measures can vary significantly within a water district and thus highlight how using district- or county-level income measures can mask the degree to which affordability is an issue for households living in low-income block groups. Our results indicate that the choice of income measure and type of water service use can influence affordability measures substantially.     

How renewable energy and service growth influence environmental quality: Evidence from a sustainable development perspective

The present study inspects the relationships between the carbon dioxide (CO₂) emissions, real GDP, renewable and non-renewable energy consumption, as well as the service growth for top ten countries (TTC) in service activities. The empirical modeling used in the study involves the procedures of cointegration and tests of Granger causality to inspect the dynamic interaction between the variables during the period from 1980 to 2018. The results of the present study suggest that the variables are cross-sectionally dependent. In addition, the variables appear to be cointegrated based on several tests. The long-run outcomes revealed an inversed U-shaped form between emissions-GDP proving the validity of the environmental Kuznets curve assumption. The fully modified ordinary least squares and dynamic OLS estimates show that the non-renewable energy and economic growth contribute to the increase of CO₂ emissions, while service value-added leads to decrease emissions. Furthermore, the renewable energy coefficient comes through as negative but insignificant for the selected panel. The TTC in service should stimulate the usage of renewable energy in various service events for following the path of sustainable development. Devising the investment plans associated with the use of renewable energies is quite essential for the advancement of the service sector leading to mitigating emissions portion.     

Analytical solution to evaluate salt precipitation during CO2 injection in saline aquifers

Carbon dioxide sequestration in deep saline aquifers is a means of reducing anthropogenic atmospheric emissions of CO₂. Among various mechanisms, CO₂ can be trapped in saline aquifers by dissolution in the formation water. Vaporization of water occurs along with the dissolution of CO₂. Vaporization can cause salt precipitation, which reduces porosity and impairs permeability of the reservoir in the vicinity of the wellbore, and can lead to reduction in injectivity. The amount of salt precipitation and the region in which it occurs may be important in CO₂ storage operations if salt precipitation significantly reduces injectivity. Here we develop an analytical model, as a simple and efficient tool to predict the amount of salt precipitation over time and space. This model is particularly useful at high injection velocities, when viscous forces dominate.First, we develop a model which treats the vaporization of water and dissolution of CO₂ in radial geometry. Next, the model is used to predict salt precipitation. The combined model is then extended to evaluate the effect of salt precipitation on permeability in terms of a time-dependent skin factor. Finally, the analytical model is corroborated by application to a specific problem with an available numerical solution, where a close agreement between the solutions is observed. We use the results to examine the effect of assumptions and approximations made in the development of the analytical solution. For cases studied, salt saturation was a few percent. The loss in injectivity depends on the degree of reduction of formation permeability with increased salt saturation. For permeability-reduction models considered in this work, the loss in injectivity was not severe. However, one limitation of the model is that it neglects capillary and gravity forces, and these forces might increase salt precipitation at the bottom of formation particularly when injection rate is low.     

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.     

Effect of oil pollution on function of sandy soils in protected deserts and investigation of their improvement guidelines (case study: Kalmand area,Iran)

Soil pollution is one of the most dangerous sorts of environmental pollutions because of waste materials, fossil fuels, etc. Unfortunately in developing countries, there are very few arrangements to prevent soil pollution due to the fossil fuels and to improve polluted soil. In this research, influences of gas oil on properties of Kalmand protected area’s sandy soil near Yazd, Iran, were studied. It was found that gas oil constituted 5.25% of soil weight in the refueling station in the region. Therefore, cleaning and strengthening of the soil by adding cement rather than expensive and complicated methods were the most important goals of this research. First, the influence of gas oil on soil properties was studied, and to improve the soil, different percentages of ordinary portland cement were added to the polluted sand to study the improved soil properties using laboratory tests. It was found that unconfined compressive strength, cohesion, and angle of internal friction of sample with 16% cement and 8% gas oil after 28 days of curing were higher than those of the specimen of 6% cement and 14% gas oil, at 4.6, 5.4, and 1.3 times, respectively. Moreover, based on falling head tests it was observed that permeability of the stabilized specimens decreased substantially. From SEM tests, fewer voids were observed in the stabilized samples, which led to less pollutant penetration into the soil. According to EDX, although dangerous elements in the contaminated specimen made up 3.99% of the specimen total weight, addition of cement introduced considerable amounts of elements that are vital for pozzolanic reactions. Therefore, it can be concluded that addition of cement to the gas oil-polluted soil not only can improve geotechnical properties of the soil and reduce its permeability, but also is very efficient for environmental issues.