Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

Linear and non-linear relationships mapping the Henry’s law parameters of organic pesticides

This work aims to predict the air to water partitioning for 96 organic pesticides by means of the Quantitative Structure–Property Relationships Theory. After performing structural feature selection with Genetics Algorithms and Replacement Method linear approaches, it is found that among the most important molecular features appears the Moriguchi octanol–water partition coefficient, and higher lipophilicities would lead to compounds having higher Henry’s law constants. We also compare the statistical performance achieved by four fully-connected Feed-Forward Multilayer Perceptrons Artificial Neural Networks. The statistical results found reveal that the best performing model uses the Levenberg–Marquardt with Bayesian regularization (BR) weighting function for achieving the most accurate predictions.     

Concentration and characterization of airborne particles in Tehran’s subway system

Particulate matter is an important air pollutant, especially in closed environments like underground subway stations. In this study, a total of 13 elements were determined from PM₁₀ and PM_2.5 samples collected at two subway stations (Imam Khomeini and Sadeghiye) in Tehran’s subway system. Sampling was conducted in April to August 2011 to measure PM concentrations in platform and adjacent outdoor air of the stations. In the Imam Khomeini station, the average concentrations of PM₁₀ and PM_2.5 were 94.4?±?26.3 and 52.3?±?16.5 μg m^?3 in the platform and 81.8?±?22.2 and 35?±?17.6 μg m^?3 in the outdoor air, respectively. In the Sadeghiye station, mean concentrations of PM₁₀ and PM_2.5 were 87.6?±?23 and 41.3?±?20.4 μg m^?3 in the platform and 73.9?±?17.3 and 30?±?15 μg m^?3, in the outdoor air, respectively. The relative contribution of elemental components in each particle fraction were accounted for 43 % (PM₁₀) and 47.7 % (PM_2.5) in platform of Imam Khomeini station and 15.9 % (PM₁₀) and 18.5 % (PM_2.5) in the outdoor air of this station. Also, at the Sadeghiye station, each fraction accounted for 31.6 % (PM₁₀) and 39.8 % (PM_2.5) in platform and was 11.7 % (PM₁₀) and 14.3 % (PM_2.5) in the outdoor. At the Imam Khomeini station, Fe was the predominant element to represent 32.4 and 36 % of the total mass of PM₁₀ and PM_2.5 in the platform and 11.5 and 13.3 % in the outdoor, respectively. At the Sadeghiye station, this element represented 22.7 and 29.8 % of total mass of PM₁₀ and PM_2.5 in the platform and 8.7 and 10.5 % in the outdoor air, respectively. Other major crustal elements were 5.8 % (PM₁₀) and 5.3 % (PM_2.5) in the Imam Khomeini station platform and 2.3 and 2.4 % in the outdoor air, respectively. The proportion of other minor elements was significantly lower, actually less than 7 % in total samples, and V was the minor concentration in total mass of PM₁₀ and PM_2.5 in both platform stations.     

Toward a robust analytical method for separating trace levels of nano-materials in natural waters: cloud point extraction of nano-copper(II) oxide

Cloud point extraction (CPE) factors, namely Triton X-114 (TX-114) concentration, pH, ionic strength, incubation time, and temperature, were optimized for the separation of nano-sized copper(II) oxide (nCuO) in aqueous matrices. The kinetics of phase transfer was studied using UV–visible spectroscopy. From the highest separation rate, the most favorable conditions were observed with 0.2 %?w/v of TX-114, pH?=?9.0, ionic strength of 10 mM NaCl, and incubation at 40 °C for 60 min, yielding an extraction efficiency of 89.2?±?3.9 % and a preconcentration factor of 86. The aggregate size distribution confirmed the formation of very large nCuO–micelle assemblies (11.9 μm) under these conditions. The surface charge of nCuO was also diminished effectively. An extraction efficiency of 91 % was achieved with a mixture of TX-100 and TX-114 containing 30 wt.% of TX-100. Natural organic and particulate matters, represented by humic acid (30 mg/L) and micron-sized silica particles (50 mg/L), respectively, did not significantly reduce the CPE efficiency (<10 %). The recovery of copper(II) ions (20 mg/L) in the presence of humic acid was low (3–10 %). The spiked natural water samples were analyzed either directly or after CPE by inductively coupled plasma mass spectrometry following acid digestion/microwave irradiation. The results indicated the influence of matrix effects and their reduction by CPE. A delay between spiking nCuO and CPE may also influence the recovery of nCuO due to aggregation and dissolution. A detection limit of 0.04 μg Cu/L was achieved for nCuO.     

Simultaneous Removal of Nitrate and Natural Organic Matter from Drinking Water Using a Hybrid Heterotrophic/Autotrophic/Biological Activated Carbon Bioreactor

Simultaneous removal of nitrate ([Formula: see text]) and natural organic matter (NOM) from drinking water using a hybrid heterotrophic/autotrophic/BAC bioreactor (HHABB) was studied in continuous mode. The HHABB consisted of three compartments: ethanol heterotrophic part, sulfur autotrophic part, and biological activated carbon (BAC)-part (including anoxic and aerobic sections). Experiments were performed with [Formula: see text] concentration 30?mg N/L, [Formula: see text] loading rate 0.72?kg N/m(3)/d, C?:?N ratio 0.53, and three concentrations of NOM (0.6, 2.6, and 5.7?mg C/L). Overall denitrification rate and efficiency of the HHABB were not affected by NOM concentration and were in the suitable ranges of 0.69-0.70?kg N/m(3)/d and 96.0%-97.7%, respectively. NOM removal at concentration 0.6?mg C/L was not efficient because of organic carbon replacement as soluble microbial products. At higher NOM concentrations, total NOM removal efficiencies were 55%-65%, 55%-70%, and 55%-65% for dissolved organic carbon, trihalomethane formation potential, and UV absorbance at 254?nm (UV(254)), respectively. The more efficient compartments of the HHABB for the removal of NOM were the ethanol heterotrophic phase and aerobic BAC-phase. The efficiency of the HHABB in the removal of NOM was considerable, and the effluent dissolved organic carbon and trihalomethane formation potential concentrations were relatively low. This study indicated that the HHABB without the anoxic BAC-phase could be a feasible alternative for simultaneous removal of [Formula: see text] and NOM from drinking water at full scale.     

Drivers that help adopting stabilised earth construction to address urban low-cost housing crisis: an understanding by construction professionals

Addressing urban housing crisis is an enormous challenge for most of the countries due to the increasing cost of the building material. Therefore, affordable alternative building material can make a breakthrough to the urban housing crisis. In the light of current success of stabilised earth construction in urban low-cost housing, it is important to find out the potential drivers that can help to adopt this building material. This paper aims to identify and highlight these drivers from the method of literature review and validates through a Delphi technique.     

Statistical analysis and isotherm study of uranium biosorption by <Emphasis Type="Italic">Padina</Emphasis> sp. algae biomass

Introduction  

The application of response surface methodology is presented for optimizing the removal of U ions from aqueous solutions using Padina sp., a brown marine algal biomass.     

Hexachlorocyclohexane (HCH) as new Stockholm Convention POPs��a global perspective on the management of Lindane and its waste isomers

Purpose

Hexachlorocyclohexane (HCH) isomers (??-, ??- and ??- (Lindane)) were recently included as new persistent organic pollutants (POPs) in the Stockholm Convention, and therefore, the legacy of HCH and Lindane production became a contemporary topic of global relevance. This article wants to briefly summarise the outcomes of the Stockholm Convention process and make an estimation of the amount of HCH waste generated and dumped in the former Lindane/HCH-producing countries.

Results

In a preliminary assessment, the countries and the respective amount of HCH residues stored and deposited from Lindane production are estimated. Between 4 and 7 million tonnes of wastes of toxic, persistent and bioaccumulative residues (largely consisting of alpha- (approx. 80%) and beta-HCH) are estimated to have been produced and discarded around the globe during 60 years of Lindane production. For approximately 1.9 million tonnes, information is available regarding deposition. Countries are: Austria, Brazil, China, Czech Republic, France, Germany, Hungary, India, Italy, Japan, Macedonia, Nigeria, Poland, Romania, Slovakia, South Africa, Spain, Switzerland, Turkey, The Netherlands, UK, USA, and former USSR. The paper highlights the environmental relevance of deposited HCH wastes and the related POPs?? contaminated sites and provides suggestions for further steps to address the challenge of the legacy of HCH/Lindane production.

Conclusion

It can be expected that most locations where HCH waste was discarded/stockpiled are not secured and that critical environmental impacts are resulting from leaching and volatilisation. As parties to the Stockholm Convention are legally required to take action to stop further POPs pollution, identification and evaluation of such sites are necessary.     

Removal of antibiotics from aqueous solutions by nanoparticles: a systematic review and meta-analysis

Environmental Science and Pollution Research - Antibiotics, as one of the emerging pollutants, are non-biodegradable compounds and long-term exposure to them may affect endocrine, hormonal, and...