Hematite grains: Size and coercive force from AF demagnetization at high temperatures

The coercivity spectrum of low-field high-temperature partial thermoremanent magnetization (PTRM) of a synthetic hematite powder, extremely high at room temperature, decreases very slowly with increasing temperature up to 500°C then decreases rapidly, especially above 600°C. From the AF demagnetization curves at 600 and 650°C it is calculated, following the Néel's theory of single-domain particles that the grains carrying the PTRM have a mean coercive force of 23 ± 5 kOe and a mean grain size of 0.40 ± 0.15 μm, which is not significantly different from the mean grain size of 0.48 ± 0.03 μm from electron micrograph observations.     

Vertical distribution and source identification of polycyclic aromatic hydrocarbons in anoxic sediment cores of Chini Lake, Malaysia: Perylene as indicator of land plant-derived hydrocarbons

Four anoxic sediment cores were collected from Chini Lake, Malaysia in order to investigate the variability of polycyclic aromatic hydrocarbon (PAH) and perylene concentrations. The study also determined significant differences of perylene concentrations in different sediment layers. Total PAH concentrations ranged from 248 to 8098 ng g⁻¹ in the samples. Diagnostic PAH ratios such as methylphenanthrenes/phenanthrene (MP/P), phenanthrene/anthracene (P/A) and fluoranthene/(fluoranthene + pyrene) (Fl/(Fl + Py) revealed a dominance of pyrogenic influences and partial petrogenic inputs to the top sediment layers. Perylene concentrations were high in the top layers (<12 cm) and increased with increasing depth. There is a significant positive correlation (r = 0.705, p = 0.01) between perylene concentrations and TOC. Analysis of variance (ANOVA) and LSD revealed significant differences (p < 0.05) in TOC-normalized perylene concentrations between the upper (<12 cm) and bottom layers (>12 cm). The average perylene concentrations accounted for 26–50% (0–12 cm) and 50–77% (12–36 cm) of pentacyclic-aromatic hydrocarbon isomers (PAI) present whereas it made up 10–34% (0–12 cm) and 46–66% (12–36 cm) of the total PAH. The average pyrene concentrations decreased with increasing depth and accounted for 62% (0–3 cm), 20–23% (3–12 cm) and 3–1.4% (12–36 cm) of perylene present. The results of hierarchical cluster analysis based on these ratios suggested different input sources for the top and bottom layers. It is concluded that the activity of termites on woody plants produced perylene which is supplied to the lake by run-off from the heavy and frequent rains in this Asian tropical climate. In addition, there was also in situ formation of perylene in the bottom layers due to diagenetic processes.     

Spatiotemporal analysis of dust patterns over Mesopotamia and their impact on Khuzestan province,Iran

Dust storms are yet quite frequent in various parts of the world, particularly ancient Mesopotamia (approximately corresponding to most parts of Iraq as well as certain surrounding regions toward its north). To add to the ongoing difficulty, monitoring dust patterns has been proven to be a rather difficult endeavor given the absence of reliable ground-based monitoring stations in the corresponding area. Additionally, western provinces of Iran, especially Khuzestan in the southwest of Iran, have been severely affected by dust storms carried by the westerly winds, blown through neighboring countries in ancient Mesopotamia. This study proceeds to employ aerosol optical depth (AOD), extracted from the MODerate-resolution Imaging Spectroradiometer onboard the Terra spacecraft, to assess spatial dust variations between 2001 and 2017 over the Khuzestan province and ancient Mesopotamia. The variations were also correlated with the temporal dust changes in the Khuzestan province. Frequency of occurrence for AOD?>?1 was used to identify and categorize major dust sources in the aforementioned regions. The findings were indicative of an increasing trend in the annual AODs of the Khuzestan province, which eventually led to a significant increase from 2008 toward the end of 2012, but decreased again in the following years. Correspondingly, the entire time period (2001–2017) was further divided into three sub-periods: the first time period spanning from 2001 to 2007, followed by the second from 2008 to 2012 and finally a third time period from 2013 to 2017. Dust source identification was speculative of numerous dust spots in Iraq, Syria, Kuwait and also the southern parts of Khuzestan province which have become more active in recent years. Additionally, a large active dust spot was pinpointed between the northwest Iraq and eastern Syria border which has become extremely active during the second time period, possibly due to a severe drought in the Fertile Crescent.

     

Copper(II) Biosorption on Soda Lignin From Oil Palm Empty Fruit Bunches (EFB)

The adsorption of Cu(II) ions from aqueous solutions by soda lignin as an absorbent using a batch adsorption system is presented in this paper. The soda lignin used in this study was extracted from black liquor derived from oil palm empty fruit bunches (EFB) using 20% v/v sulfuric acid. The effects of varying experimental parameters such as pH value, adsorbent dosage, different concentrations of Cu(II) ions, and agitation period were investigated. The results revealed that the optimum adsorption of Cu(II) onto soda lignin was recorded at a pH of 5.0 at an adsorbent dosage of 0.5 g soda lignin and an agitation period of 40 min. The adsorption capacities and rates of Cu(II) ions onto soda lignin was evaluated. The Langmuir and Freundlich adsorption models were applied to calculate the isotherm constants. It was found that the adsorption isothermal data could be well interpreted by the Freundlich model. The kinetic experimental data properly correlated with the pseudo‐second‐order kinetic model, which implies that chemical sorption is the rate‐limiting step.     

Input variable selection for water resources systems using a modified minimum redundancy maximum relevance (mMRMR) algorithm

Input variable selection (IVS) is a necessary step in modeling water resources systems. Neglecting this step may lead to unnecessary model complexity and reduced model accuracy. In this paper, we apply the minimum redundancy maximum relevance (MRMR) algorithm to identifying the most relevant set of inputs in modeling a water resources system. We further introduce two modified versions of the MRMR algorithm (α-MRMR and β-MRMR), where α and β are correction factors that are found to increase and decrease as a power-law function, respectively, with the progress of the input selection algorithms and the increase of the number of selected input variables. We apply the proposed algorithms to 22 reservoirs in California to predict daily releases based on a set from a 121 potential input variables. Results indicate that the two proposed algorithms are good measures of model inputs as reflected in enhanced model performance. The α-MRMR and β-MRMR values exhibit strong negative correlation to model performance as depicted in lower root-mean-square-error (RMSE) values.     

Groundwater Quality Modeling with a Small Data Set

Seventeen groundwater quality variables collected during an 8‐year period (2006 to 2013) in Andimeshk, Iran, were used to implement an artificial neural network (NN) with the purpose of constructing a water quality index (WQI). The method leading to the WQI avoids instabilities and overparameterization, two problems common when working with relatively small data sets. The groundwater quality variables used to construct the WQI were selected based on principal component analysis (PCA) by which the number of variables were decreased to six. To fulfill the goals of this study, the performance of three methods (1) bootstrap aggregation with early stopping; (2) noise injection; and (3) ensemble averaging with early stopping was compared. The criteria used for performance analysis was based on mean squared error (MSE) and coefficient of determination (R²) of the test data set and the correlation coefficients between WQI targets and NN predictions. This study confirmed the importance of PCA for variable selection and dimensionality reduction to reduce the risk of overfitting. Ensemble averaging with early stopping proved to be the best performed method. Owing to its high coefficient of determination (R² = 0.80) and correlation coefficient (r=0.91), we recommended ensemble averaging with early stopping as an accurate NN modeling procedure for water quality prediction in similar studies.     

Application of Tree-Based Predictive Models to Forecast Air Overpressure Induced by Mine Blasting

Natural Resources Research - In surface mines and underground excavations, every blasting operation can have some destructive environmental impacts, among which air overpressure (AOp) is of major...     

Biostratigraphy of the Surgah formation in Kuh-e-Surgah and correlation with Tang-e-Gerab (West of Iran)

In biostratigraphic studies of the Surgah formation in the Kuh-e-Surgah section, 145 samples were collected. The thickness of the Surgah formation is about 175 m, and it consists mainly of limestone and shale. The lower and upper boundaries of the Surgah formation are Sarvak and Ilam formations, respectively, and they are conformable with sharp lithology. Seventeen species which belong to six genera of planktonic foraminifera and four biozones have been identified in this study. Based on foraminifera assemblages and biozone determinations, the age of the Surgah formation is Late Turonian to Early Late Santonian. This section is correlated with the Tang-e-Gerab section.