Environmental impact of Gümüşhane City,Turkey, waste area in terms of heavy metal pollution

China has become the biggest CO₂ emitter in the world. In China, economic development in different regions is not the same. Thus, it is necessary to study the regional decoupling relationship between energy-related CO₂ emission and economic development. Considering the regional difference of economic development, energy consumption and CO₂ emission, provincial regions in China are divided into seven economic bands. The Tapio decoupling method is adopted to calculate the decoupling index in the seven regions over the study period 1996–2013. Furthermore, the WCDM is developed to study the driving factors governing the decoupling state. The result showed that decoupling development differed in each economic band; North-East and North-West, showed a better trend and a worse one, respectively, than the others. Economic factor showed a stable trend of negative effect, and energy intensity factor was the crucial factor to accelerate the process of CO₂ emission decoupling. Only in Yangtze River delta, economic band had structural factor shown a positive effect during the research period, and emission efficiency factor was not stable and showed a negative effect in most years in every region.     

Geochemistry and mineral chemistry of pyroxenite xenoliths and host volcanic alkaline rocks from north west of Marand (NW Iran)

Mineralogy and Petrology - The Plio-Quaternary alkaline volcanic rocks from the northwest of Marand (NW Iran) consist of trachy-andesites, trachy-basaltic andesites, leucite-tephrites and...     

GIS-based bivariate statistical techniques for groundwater potential analysis (an example of Iran)

Groundwater potential analysis prepares better comprehension of hydrological settings of different regions. This study shows the potency of two GIS-based data driven bivariate techniques namely statistical index (SI) and Dempster–Shafer theory (DST) to analyze groundwater potential in Broujerd region of Iran. The research was done using 11 groundwater conditioning factors and 496 spring positions. Based on the ground water potential maps (GPMs) of SI and DST methods, 24.22% and 23.74% of the study area is covered by poor zone of groundwater potential, and 43.93% and 36.3% of Broujerd region is covered by good and very good potential zones, respectively. The validation of outcomes displayed that area under the curve (AUC) of SI and DST techniques are 81.23% and 79.41%, respectively, which shows SI method has slightly a better performance than the DST technique. Therefore, SI and DST methods are advantageous to analyze groundwater capacity and scrutinize the complicated relation between groundwater occurrence and groundwater conditioning factors, which permits investigation of both systemic and stochastic uncertainty. Finally, it can be realized that these techniques are very beneficial for groundwater potential analyzing and can be practical for water-resource management experts.     

Hydraulic Conductivity of Compacted Granite Residual Soil Mixed with Palm Oil Fuel Ash in Landfill Application

Laboratory tests were carried out on compacted granite residual soil treated with 0 to 15% Palm Oil Fuel Ash (POFA), with a view to evaluate its hydraulic conductivity for its application in landfilling. The Soil–POFA mixtures were compacted using both Standard and Modified Proctors compactive efforts at 2% dry of Optimum Moulding water Content (?2%), at Optimum Moulding water Content (0%), at 2 and 4% on the wet side of Optimum Moulding water Content (+2 and +4%). The samples were permeated with water and the effect of moulding water content; compactive effort and POFA content were examined. The samples that met the minimum threshold of 1 × 10^?9 m/s were used in plotting the acceptable zones criterion at various POFA mixtures. The results gave indications of reduction in the hydraulic conductivity values, with increase in compactive efforts, moulding water content and POFA content up to about 10%. This was the most suitable soil–POFA mixture for the hydraulic application.     

The Tunisian Jurassic aquifer in the North African Sahara aquifer system: information derived from two-dimensional seismic reflection and well logs

Southern Tunisia is an arid area where socio-economic activities are dependent on groundwater resources. The presented study aims to better characterize the Jurassic aquifer based on geological and geophysical data, with a view to develop a rational exploitation program. Well logs are used to precisely determine the position and composition of the known Jurassic aquifer layers and to identify others able to produce good quality water. The logs show that limestones, sandstones and dolomites of the Krachoua, Techout and Foum Tataouine formations are the main Jurassic aquifers. Sixty-eight seismic-reflection sections are integrated within this study. The interpolation between the interpreted sections leads to the construction of isochronous isopach maps and geoseismic sections, and their analysis finds that compressive and extensive tectonic deformations have influenced the Jurassic aquifer geometry. The Hercynian orogeny phase manifestation is remarkable in that there are several stratigraphic gaps in the Jurassic sequence. The E–W, NW–SE, and NNW–SSE accidents, reactivated in normal faults since the Permian to Lower Cretaceous epochs, have generated the structures found in the Jurassic series, such as subsided and raised blocks. Their syn-sedimentary activity has controlled the thickness and facies of these series. The Cretaceous, Tortonian and Post-Villafranchian compressions are responsible for the Jurassic-deposits folding in some localities. The highlighted tectonic and sedimentary events have an important impact on the Jurassic aquifer function by favoring the Jurassic aquifer interconnections and their connections with the Triassic and Cretaceous permeable series.     

A comparative analysis among computational intelligence techniques for dissolved oxygen prediction in Delaware River

Most of the water quality models previously developed and used in dissolved oxygen (DO) prediction are complex. Moreover, reliable data available to develop/calibrate new DO models is scarce. Therefore, there is a need to study and develop models that can handle easily measurable parameters of a particular site, even with short length. In recent decades, computational intelligence techniques, as effective approaches for predicting complicated and significant indicator of the state of aquatic ecosystems such as DO, have created a great change in predictions. In this study, three different AI methods comprising: (1) two types of artificial neural networks (ANN) namely multi linear perceptron (MLP) and radial based function (RBF); (2) an advancement of genetic programming namely linear genetic programming (LGP); and (3) a support vector machine (SVM) technique were used for DO prediction in Delaware River located at Trenton, USA. For evaluating the performance of the proposed models, root mean square error (RMSE), Nash–Sutcliffe efficiency coefficient (NS), mean absolute relative error (MARE) and, correlation coefficient statistics (R) were used to choose the best predictive model. The comparison of estimation accuracies of various intelligence models illustrated that the SVM was able to develop the most accurate model in DO estimation in comparison to other models. Also, it was found that the LGP model performs better than the both ANNs models. For example, the determination coefficient was 0.99 for the best SVM model, while it was 0.96, 0.91 and 0.81 for the best LGP, MLP and RBF models, respectively. In general, the results indicated that an SVM model could be employed satisfactorily in DO estimation.     

Potential ecological risk assessment,enrichment, geoaccumulation,and source identification of metals in the surface sediments of Choghakhor Wetland,Iran

This study reported the first comprehensive research on identification of metal concentrations (Fe, Mg, Mn, Pb, Cd, Cr) in order to provide baseline data for future studies, identify possible sources, determine degree of pollution, and identify potential ecological risks of metals in surface sediments from Iran’s Choghakhor Wetland. The order of metal concentration was as follows: Fe > Mg > Mn > Pb > Cd > Cr, with mean concentrations of 6140.35, 1647.32, 289.03, 1.10, and 0.45 µg/g of dry weight, respectively. These results reveal that Choghakhor Wetland is not heavily polluted compared to other regions. The results of enrichment factor (EF) and geoaccumulation index (I _geo) showed that Fe, Pb, Mg, Cr, and Mn presented low levels of contamination and probably originated from natural sources. On the other hand, the results of EF and I _geo indices suggested that Cd concentrations in sediments of Choghakhor Wetland originated from anthropogenic sources. Based on the results of three sets of sediment quality guidelines, only Cd concentration in sediments of Choghakhor Wetland is a threat for aquatic organisms of Choghakhor Wetland. The results of multivariate analysis such as principal component analysis and cluster analysis showed that Fe–Mn, Cr–Mg, and Pb groups originated from natural sources, while Cd concentrations in sediments of Choghakhor Wetland originated from both natural and anthropogenic sources (mainly chemical fertilizers). To our knowledge, this is the first study about metal concentrations in sediments of Choghakhor Wetland, and because of low levels of these metals, these concentrations can be considered background levels for future investigation.     

Comparison between inductively coupled plasma and X-ray fluorescence performance for Pb analysis in environmental soil samples

Comparison of two conventional analytical techniques such as X-ray fluorescence (XRF) and inductively coupled plasma mass spectrometry (ICP-MS) for measuring Pb concentrations in soil samples was achieved using field and laboratory work. Seventy-three samples were collected from urban areas surrounding the large lead smelter at South Australia, as an indicator of the environment impact of smelter activity. Soil Pb concentrations were determined using hand-held XRF analyser under laboratory conditions. ICP-MS analysis on digested soils (using a microwave-assisted nitric acid digestion-extraction) was applied to validate p-XRF data. The analysis showed that Pb concentrations determined by XRF correlated with high linearity with Pb concentrations determined by ICP-MS measurements (R ² = 0.89). Statistical test (t test) was applied to the data of both methods applied without any significant difference between the two techniques. These results indicated that ICP-MS corroborated XRF for Pb soil measurements and suggests that XRF was a reliable and quick alternative to traditional analytical methods in studies of environmental health risk assessment, allowing for much larger sampling regimes in relatively shorter times and could be applied in the field.     

Groundwater potential recharge estimation in bare soil using three soil moisture accounting models: field evaluation for a semi-arid foothill region

Performances of conventional and improved soil moisture balance as well as locally calibrated empirical models were evaluated in simulating potential recharge (R) and soil moisture content for a semi-arid foothill region. Models comparison with observed values using lysimeter data during [(2011–2012), (2012–2013)] reveal poor performance of conventional soil moisture balance model, underestimating annual R values. Improved soil moisture balance model provided acceptable estimation of annual R for 2011–2012 by considering the wetting of the near surface soil storage. However, it produced the worst simulation for daily soil moisture content once rainy season was over. Sensitivity analysis revealed that the precision degree of initial soil moisture deficit value would strongly influence estimation of R by improved soil moisture balance model, which can be viewed as a limiting factor. Additionally, locally calibrated model produced the best estimation of annual R and daily soil moisture content, which is suggested for the study region.