Developing a fuzzy neural network-based support vector regression (FNN-SVR) for regionalizing nitrate concentration in groundwater

The aim of this study is to develop a fuzzy neural network-based support vector regression model (FNN-SVR) for mapping crisp-input and fuzzy-output variables. In this model, an artificial neural network (ANN) estimator based on multilayer perceptron (MLP) is considered as the kernel function of the SVR, whereas asymmetric triangular fuzzy H-level sets are assumed for model parameters including weight and biases of the ANN model. A genetic algorithm (GA) with real coding is implemented to optimize the model parameters during the training phase. To evaluate the efficiency and applicability of the proposed model, it is applied for simulating and regionalizing nitrate concentration in Karaj Aquifer in Iran. The goodness-of-fit criteria indicate a better performance of the FNN-SVR compared to some benchmark models such as geostatistic techniques as well as traditional SVR models with linear, quadratic, polynomial, and Gaussian kernel functions for modeling nitrate concentrations in groundwater.     

The effects of using reprocessable material on the durability and mechanical properties of landfill leachate collection HDPE pipes

This paper investigated the durability and mechanical properties of landfill leachate collection HDPE pipes which had been made of different weight percent amounts of virgin and reprocessable HDPE compounds (VC and RC). Durability is reported base on the chemical properties, obtained through oxidative induction time (OIT) and melt flow index (MFI) measurements, at the temperature of 50 °C and over a period of 12 months immersion in a synthetic leachate. Mechanical properties are also described according to tensile and pressure tests which had been conducted on the pipes samples. All of the factors were examined had been affected by the addition of RC, but for the special combination the antioxidant depletion was significantly affected by the experimental aging condition and no important changes had been observed in the other pipe properties. The results from OIT tests indicate that the rate of antioxidant depletion is reduced by an increase in the weight percent amounts of RC, during the experimental aging condition. This reduction is probably attributed to the extraction of antioxidants from RC in their recovery process. Finally, although these results are related to the particular HDPE compound, antioxidant formulation and condition examined, but it can be said that the use of clean own reprocessable material for the production of landfill leachate pipes shall be permitted without limitations.     

Uncertainties in vegetated buffer strip function in controlling phosphorus export from agricultural land in the Canadian prairies

Environmental Science and Pollution Research - Vegetated buffer strips (VBSs) are widely encouraged as a cost-effective strategy to address phosphorus (P) pollution associated with agricultural...     

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.     

Assessment of heavy metal enrichment in the offshore fine-grained sediments of the Caspian Sea

Sampling of the offshore seabed sediments of southwestern part of the Caspian Sea was carried out by gravity corer in order to study heavy metal concentration and the physicochemical factors controlling their distribution in the fine-grained fraction. The grain size distribution, amount, and type of clay minerals, total organic carbon (TOC) content, and Eh–pH of the sediments were determined. The average concentrations of the heavy metals in ppm are Mn (563), Cu (207.5), Sr (187), Zn (94), Pb (26.3), Ni (14.5), Co (11.5), Cd (2.56), and Ag (1.04) in their order of abundances. Co and Zn mostly indicate increase in silt-size fraction of the sediments suggesting their probable detrital provenance but the Mn, Ni, Cu, Sr, Pb, Cd, and Ag concentrations show a similar trend to distribution of the clay-size fraction. The concentrations of Mn, Co, and Cd increase with increase in the TOC content but the Cu, Pb, Ni, Ag, and Sr concentrations decrease with increase of the TOC content. The amounts of Zn, Cu, Sr, Pb, Cd, and Ag increase with increase in the CaCO₃ content. The calculated enrichment factor indicates that the sediments are very strong to extremely enriched in Ag, significantly enriched in Cu and Cd, and depleted to mineral for Pb, Sr, Co, Ni, and Zn. Variations of the Cu, Sr, Cd, Ag, and Pb concentrations are similar to the clay and CaCO₃ distributions.     

Soil-plant nitrogen isotope composition and nitrogen cycling after biochar applications

Environmental Science and Pollution Research - Biochar has strong potential to improve nitrogen (N) use efficiency in both agricultural and horticultural systems. Biochar is usually co-applied with...     

Effect of virtual water trade on freshwater pollution in trading partners: a systematic literature review

Environmental Science and Pollution Research - Systematic reviews are a more complete, repeatable, and less biased form of literature reviews leading to evidence-based conclusions. A systematic...     

Sustainable biofuels from algae

There is currently great interest in microalgae as sources of renewable energy and biofuels. Many algae species have a high lipid content and can be grown on non-arable land using alternate water sources such as seawater. This paper discusses in detail the issue of sustainability of commercial-scale microalgae production of biofuels with particular focus on land, water, nutrients (N and P) and CO₂ requirements and highlights some of the key issues in the very large scale culture of microalgae which is required for biofuels. The use of genetically modified algae is also considered.