Facile green synthesis of zero-valent iron nanoparticles using barberry leaf extract (GnZVI@BLE) for photocatalytic reduction of hexavalent chromium.

In this study, zero-valent iron (GnZVI) was synthesized using barberry leaf extract (GnZVI@BLE). The physicochemical properties of the final products were characterized by FT-IR, SEM, TEM, and EDS techniques. The results of TEM analysis showed that the obtained iron zero-valent nanoparticles with a diameter between 20 and 40 nm and shell-core structures were successfully synthesized. The results of FT-IR confirmed the presence of various functional groups. The photocatalytic activity of synthesized nanoparticles was investigated by reduction of hexavalent chromium. Laboratory data showed that the presence of GnZVI@BLE as a nanocatalyst in the photocatalytic process could be reduction the hexavalent chromium (Cr (VI)). Photocatalytic data revealed that, when the dosage of nanoparticles was 0.675 g/L, the reduction efficiency of hexavalent chromium was 100%. The kinetics of the reaction follows a pseudo-second-order equation. The constant of reaction rate was 0.4 at pH 2 and 0.5 g/L concentration of GnZVI@BLE.

Kinetics of biogas production and chemical oxygen demand removal from compost leachate in an anaerobic migrating blanket reactor.

In this study, laboratory anaerobic migrating blanket reactor (AMBR) with four units was used to reduce and remove COD leachate of composting process; it was also used to determine the kinetic coefficients of COD removal and biogas and methane gas production in several different OLRs. The maximum concentration of organic matter entering the reactor was 100,000 mg/L and the reactor was under operation for 319 days. The results showed that the COD removal efficiency of AMBR in all concentrations of substrate entering the reactor was above 80%. First-order model and Stover-Kincannon were used to investigate the kinetics of COD removal via AMBR biological process; in addition, the two models of Modified Stover-Kincannon and Van der Meer and Heertjes were used to check the kinetic constants of biogas and methane gas production. The results obtained from the models showed that the experimental data on COD removal were more consistent with the results obtained from Stover-Kincannon model (R2 = 0.999) rather than with the First-order model (R2 = 0.926). Kinetic constants calculated via Stover-Kincannon model were as follows: saturation value constant (KB) and maximum utilization rate constants (Umax), respectively, were 208,600 mg/L d and 172,400 mg/L d. We investigated the linear relationship between the experimental data and the values predicted by the models; as compared with the values predicted by the First-order model, the values predicted by Stover-Kincannon model were closer to the values measured via experiments. Based on the results of the evaluation of kinetic coefficients of Stover-Kincannon model, with the migration of the leachate flow from unit 1 to unit 4, Umax value has fallen significantly. The values of maximum specific biogas production rate (Gmax) and proportionality constant (GB) obtained from the Stover-Kincannon model, respectively, were 35,714 ml/L d and 42.85 (dimensionless) and value of kinetic constant of Van der Meer and Heertjes (ksg) was 0.0473 ml CH4/mg COD.

Species on the move: Impacts of climate change on the spatial range of endemic fishes of the eco-sensitive semi-arid area of the Arabian Peninsula.

Climate change is one of the most significant challenges worldwide in the Anthropocene, and it is predicted to importantly affect biological diversity, especially in freshwaters. Freshwater fishes are facing considerable global threats, particularly in eco-sensitive semi-arid to arid areas such as the Arabian Peninsula, which is considered a highly stressed region in the Middle East. Endemic species are believed to display a narrow range of traits, with rarity reflecting adaptation to specific environmental regimes, and they are thus highly sensitive to environmental disturbances. This study is the first attempt to map the occurrence of endemic freshwater fish species and predict the impact of climate change on their spatial range in the semi-arid area of the Arabian Peninsula using Species Distribution Modeling (SDM). We compared the present and future (2041-2060 and 2061-2080) climate niche for the species under various climatic scenarios. All global circulation models (GCMs) performed well in predicting the species' climatic niche (AUC ranging between 0.72 and 0.92). For certain species (Cyprinion acinaces, Garra buettikeri, Carasobarbus exulatus, Arabibarbus arabicus, and Cyprinion mhalense), variables associated with precipitation were more important than those related to temperature, while for others (Carasobarbus apoensis, G. sahilia, G tibanica, and Aphaniops kruppi), temperature-related variables were most important. Precipitation in the coldest quarter and in the driest quarter was the most sensitive variable for the predictions. The species showed distinct responses to climate change; seven were predicted to lose their climatically suitable habitats (losers) and are thus threatened and highly vulnerable to the effects of climate change, while two species were predicted to expand their range (winners). Regular monitoring of fish in the Arabian Peninsula is recommended to conserve endemic species and their ecosystems.

Detecting hybridization between Iranian wild wolf (Canis lupus pallipes) and free-ranging domestic dog (Canis familiaris) by analysis of microsatellite markers.

The genetic threat due to hybridization with free-ranging dogs is one major concern in wolf conservation. The identification of hybrids and extent of hybridization is important in the conservation and management of wolf populations. Genetic variation was analyzed at 15 unlinked loci in 28 dogs, 28 wolves, four known hybrids, two black wolves, and one dog with abnormal traits in Iran. Pritchard's model, multivariate ordination by principal component analysis and neighbor joining clustering were used for population clustering and individual assignment. Analysis of genetic variation showed that genetic variability is high in both wolf and dog populations in Iran. Values of H(E) in dog and wolf samples ranged from 0.75-0.92 and 0.77-0.92, respectively. The results of AMOVA showed that the two groups of dog and wolf were significantly different (F(ST) = 0.05 and R(ST) = 0.36; P < 0.001). In each of the three methods, wolf and dog samples were separated into two distinct clusters. Two dark wolves were assigned to the wolf cluster. Also these models detected D32 (dog with abnormal traits) and some other samples, which were assigned to more than one cluster and could be a hybrid. This study is the beginning of a genetic study in wolf populations in Iran, and our results reveal that as in other countries, hybridization between wolves and dogs is sporadic in Iran and can be a threat to wolf populations if human perturbations increase.

Combining multiscale niche modeling, landscape connectivity, and gap analysis to prioritize habitats for conservation of striped hyaena (Hyaena hyaena).

Identifying spatial gaps in conservation networks requires information on species-environment relationships, and prioritization of habitats and corridors. We combined multi-extent niche modeling, landscape connectivity, and gap analysis to investigate scale-dependent environmental relationships, and identify core habitats and corridors for a little-known carnivore in Iran, the striped hyaena (Hyaena hyaena). This species is threatened in Iran by road vehicle collisions and direct killing. Therefore, understanding the factors that affect its habitat suitability, spatial pattern of distribution, and connectivity among them are prerequisite steps to delineate strategies aiming at human-striped hyaena co-existence. The results showed that the highest predictive power and extent of habitats was obtained at the extent sizes of 4 and 2 km, respectively. Also, connectivity analysis revealed that the extent and number of core habitats and corridors changed with increasing dispersal distance, and approximately 21% of the landscape was found to support corridors. The results of gap analysis showed that 15-17% of the core habitats overlapped with conservation areas. Given the body size of the species, its mobility, and lack of significant habitat specialization we conclude that this species would be more strongly influenced by changes in habitat amount rather than landscape configuration. Our approach showed that the scale of variables and dispersal ability must be accounted for in conservation efforts to prioritize habitats and corridors, and designing conservation areas. Our results could facilitate the conservation of striped hyaena through the identification and prioritization of habitats, establishment of conservation areas, and mitigating conflicts in corridors.

Modeling climate change impacts on the distribution of an endangered brown bear population in its critical habitat in Iran.

Climate change is one of the major challenges to the current conservation of biodiversity. Here, by using the brown bear, Ursus arctos, in the southernmost limit of its global distribution as a model species, we assessed the impact of climate change on the species distribution in western Iran. The mountainous forests of Iran are inhabited by small and isolated populations of brown bears that are prone to extinction in the near future. We modeled the potential impact of climate change on brown bear distribution and habitat connectivity by the years 2050 and 2070 under four representative concentration pathways (RCPs) of two general circulation models (GCMs): BCC-CSM1-1 and MRI-CGCM3. Our projections revealed that the current species' range, which encompasses 6749.8 km2 (40.8%) of the landscape, will decline by 10% (2050: RCP2.6, MRI-CGCM3) to 45% (2070: RCP8.5, BCC-CSM1-1). About 1850 km2 (27.4%) of the current range is covered by a network of conservation (CAs) and no-hunting (NHAs) areas which are predicted to decline by 0.64% (2050: RCP2.6, MRI-CGCM3) to 15.56% (2070: RCP8.5, BCC-CSM1-1) due to climate change. The loss of suitable habitats falling within the network of CAs and NHAs is a conservation challenge for brown bears because it may lead to bears moving outside the CAs and NHAs and result in subsequent increases in the levels of bear-human conflict. Thus, re-evaluation of the network of CAs and NHAs, establishing more protected areas in suitable landscapes, and conserving vital linkages between habitat patches under future climate change scenarios are crucial strategies to conserve and manage endangered populations of the brown bear.

Genetic structure and ecological niche segregation of Indian gray mongoose (Urva edwardsii) in Iran.

Combining genetic data with ecological niche models is an effective approach for exploring climatic and nonclimatic environmental variables affecting spatial patterns of intraspecific genetic variation. Here, we adopted this combined approach to evaluate genetic structure and ecological niche of the Indian gray mongoose (Urva edwardsii) in Iran, as the most western part of the species range. Using mtDNA, we confirmed the presence of two highly differentiated clades. Then, we incorporated ensemble of small models (ESMs) using climatic and nonclimatic variables with genetic data to assess whether genetic differentiation among clades was coupled with their ecological niche. Climate niche divergence was also examined based on a principal component analysis on climatic factors only. The relative habitat suitability values predicted by the ESMs for both clades revealed their niche separation. Between-clade climate only niche comparison revealed that climate space occupied by clades is similar to some extent, but the niches that they utilize differ between the distribution ranges of clades. We found that in the absence of evidence for recent genetic exchanges, distribution models suggest the species occurs in different niches and that there are apparent areas of disconnection across the species range. The estimated divergence time between the two Iranian clades (4.9 Mya) coincides with the uplifting of the Zagros Mountains during the Early Pliocene. The Zagros mountain-building event seems to have prevented the distribution of U. edwardsii populations between the western and eastern parts of the mountains as a result of vicariance events. Our findings indicated that the two U. edwardsii genetic clades in Iran can be considered as two conservation units and can be utilized to develop habitat-specific and climate change-integrated management strategies.

Effect of UVC and UVA Photocatalytic Processes on Tetracycline Removal Using CuS-Coated Magnetic Activated Carbon Nanocomposite: A Comparative Study.

In this study, we synthesized a novel MAC nanocomposite using almond's green hull coated with CuS. The whole set of experiments have been conducted inside a batch (discontinuous reactor system) at room temperature. The effectiveness of different parameters in tetracycline removal pH (3, 5, 7, and 9), pollutant concentration (5-100 mg/L), nanocomposite dosage (0.025-1 g/L), and contact time (5-60 min) using newly synthesized nanocomposite were investigated. Based on the results, in the optimal conditions of pH = 9, nanocomposite dosage of 1 g/L, pollutant concentration of 20 mg/L, contact time of 60 min, and room temperature, 95% removal efficiency was obtained. In MAC/CuS/UVC process, the removal of COD and TOC were 76.89% and 566.84% respectively meanwhile, these values in MAC/CuS/UVA process were 74.19% and 62.11%, respectively. The results of nanocomposite stability and magnetic recovery illustrated that the removal efficiency was reduced by 1.5% in the presence of UVC and 5% in the presence of UVA lights during all six cycles. Therefore, this nanocomposite was highly capable of recycling and reuse. It can be concluded that considering the high potential of the synthesized nanocomposite, the photocatalytic efficiency of the MAC/CuS/UVC process in tetracycline synthesis was higher than MAC/CuS/UVA process.

Ventilation Prediction for an Industrial Cement Raw Ball Mill by BNN-A "Conscious Lab" Approach.

In cement mills, ventilation is a critical key for maintaining temperature and material transportation. However, relationships between operational variables and ventilation factors for an industrial cement ball mill were not addressed until today. This investigation is going to fill this gap based on a newly developed concept named "conscious laboratory (CL)". For constructing the CL, a boosted neural network (BNN), as a recently developed comprehensive artificial intelligence model, was applied through over 35 different variables, with more than 2000 records monitored for an industrial cement ball mill. BNN could assess multivariable nonlinear relationships among this vast dataset, and indicated mill outlet pressure and the ampere of the separator fan had the highest rank for the ventilation prediction. BNN could accurately model ventilation factors based on the operational variables with a root mean square error (RMSE) of 0.6. BNN showed a lower error than other traditional machine learning models (RMSE: random forest 0.71, support vector regression: 0.76). Since improving the milling efficiency has an essential role in machine development and energy utilization, these results can open a new window to the optimal designing of comminution units for the material technologies.

Assessing the origin, genetic structure and demographic history of the common pheasant (Phasianus colchicus) in the introduced European range.

The common pheasant, a game species widely introduced throughout the world, can be considered as an ideal model to study the effects of introduction events on local adaptations, biogeographic patterns, and genetic divergence processes. We aimed to assess the origin, spatial patterns of genetic variation, and demographic history of the introduced populations in the contact zone of Central and Southeast Europe, using mitochondrial DNA control region sequences and microsatellite loci. Both types of molecular markers indicated relatively low to moderate levels of genetic variation. The mtDNA analyses revealed that common pheasants across the study area are divided into two distinct clades: B (mongolicus group) and F (colchicus group). Analyses of the microsatellite data consistently suggested a differentiation between Hungary and Serbia, with the pheasant population in Hungary being much more genetically homogeneous, while that of Serbia has much more genetic mixture and admixture. This cryptic differentiation was not detected using a non-spatial Bayesian clustering model. The analyses also provided strong evidence for a recent population expansion. This fundamental information is essential for adequate and effective conservation management of populations of a game species of great economic and ecological importance in the studied geographical region.

Morphological diversity and ecological niche divergence in goitered and sand gazelles.

The phylogeny and species boundaries of Gazella subgutturosa and G. marica have been long debated. The achievements of past conservation efforts have been compromised by a lack of knowledge about the phylogeny and taxonomic status of different populations. We integrated the recent genetic findings by previous studies with morphometric analyses and ecological niche modeling (ENM) to assess discreteness among populations of these gazelle species in Asia. Taxonomic diversity of gazelles was investigated by using principal components analysis (PCA) based on 14 cranial measures of male skulls. Ecological niche divergence was examined based on a PCA on climatic factors and a species distribution modeling (SDM) with environmental variables. Morphometric results indicated substantial differentiation in size between skulls of the western Zagros Mountains including west and south-western Iran and Arabian Peninsula from all other samples east of the Zagros Mountains from Iran to China. ENM also revealed that gazelles in the east and west of Zagros Mountains occupy distinct niches and that there are apparent areas of disconnection across the goitered gazelle suitable range. A complete divergent niche occupation was also observed between goitered gazelles of northern Mongolia and other populations of the species, except those in China. Taking the inferences from ENM and morphology together with previous genetics results, we conclude that gazelles in the west and south-west of Iran may represent G. marica. Also, our combined analyses revealed divergence among gazelles of Iran, Central Asia, and Mongolia/China. These results may pave the way for future studies and have conservation implications particularly for reintroduction/supplementation programs.

Genetic Diversity and Structure of Common Carp (Cyprinus carpio L.) in the Centre of Carpathian Basin: Implications for Conservation.

Hungary is one of the largest common carp-production countries in Europe and now, there is a large number of local breeds and strains in the country. For proper maintenance of the animal genetic resources, information on their genetic diversity and structure is essential. At present, few data are available on the genetic purity and variability of the Hungarian common carp. In this study, we genetically analyzed 13 strains in Hungary and, in addition, the Amur wild carp, using 12 microsatellite markers. A total of 117 unique alleles were detected in 630 individuals. Low levels of genetic differentiation (Fst and Cavalli-Sforza and Edwards distance) were estimated among strains. The AMOVA showed the low but significant level of genetic differentiation among strains (3.79%). Bayesian clustering analysis using STRUCTURE classified the strains into 14 different clusters. The assignment test showed that 93.64% of the individuals could be assigned correctly into their original strain. Overall, our findings can be contributed to complementing scientific knowledge for conservation and management of threatened strains of common carp.

Spatial modeling, risk mapping, change detection, and outbreak trend analysis of coronavirus (COVID-19) in Iran (days between February 19 and June 14, 2020).

OBJECTIVES: Coronavirus disease 2019 (COVID-19) represents a major pandemic threat that has spread to more than 212 countries with more than 432,902 recorded deaths and 7,898,442 confirmed cases worldwide so far (on June 14, 2020). It is crucial to investigate the spatial drivers to prevent and control the epidemic of COVID-19. METHODS: This is the first comprehensive study of COVID-19 in Iran; and it carries out spatial modeling, risk mapping, change detection, and outbreak trend analysis of the disease spread. Four main steps were taken: comparison of Iranian coronavirus data with the global trends, prediction of mortality trends using regression modeling, spatial modeling, risk mapping, and change detection using the random forest (RF) machine learning technique (MLT), and validation of the modeled risk map. RESULTS: The results show that from February 19 to June 14, 2020, the average growth rates (GR) of COVID-19 deaths and the total number of COVID-19 cases in Iran were 1.08 and 1.10, respectively. Based on the World Health Organisation (WHO) data, Iran's fatality rate (deaths/0.1M pop) is 10.53. Other countries' fatality rates were, for comparison, Belgium - 83.32, UK - 61.39, Spain - 58.04, Italy - 56.73, Sweden - 48.28, France - 45.04, USA - 35.52, Canada - 21.49, Brazil - 20.10, Peru - 19.70, Chile - 16.20, Mexico- 12.80, and Germany - 10.58. The fatality rate for China is 0.32 (deaths/0.1M pop). Over time, the heatmap of the infected areas identified two critical time intervals for the COVID-19 outbreak in Iran. The provinces were classified in terms of disease and death rates into a large primary group and three provinces that had critical outbreaks were separate from the others. The heatmap of countries of the world shows that China and Italy were distinguished from other countries in terms of nine viral infection-related parameters. The regression models for death cases showed an increasing trend but with some evidence of turning. A polynomial relationship was identified between the coronavirus infection rate and the province population density. Also, a third-degree polynomial regression model for deaths showed an increasing trend recently, indicating that subsequent measures taken to cope with the outbreak have been insufficient and ineffective. The general trend of deaths in Iran is similar to the world's, but Iran's shows lower volatility. Change detection of COVID-19 risk maps with a random forest model for the period from March 11 to March 18 showed an increasing trend of COVID-19 in Iran's provinces. It is worth noting that using the LASSO MLT to evaluate variables' importance, indicated that the most important variables were the distance from bus stations, bakeries, hospitals, mosques, ATMs (automated teller machines), banks, and the minimum temperature of the coldest month. CONCLUSIONS: We believe that this study's risk maps are the primary, fundamental step to take for managing and controlling COVID-19 in Iran and its provinces.

Data on the optimization of the synthesis of green iron nanoparticles using plants indigenous to South Khorasan.

Green synthesis is a novel method for nanoparticle preparation, which is known as an environmentally friendly technique (Wang et al., 2017a, 2017b) [1], [2]. This research was carried out to investigate the use and efficacy of Barberry leaf, Elaeagnus angustifolia leaf, Saffron sepal, and Ziziphus jujube leaf extracts as agents for the synthesis of green iron nanoparticles (GINPs). The studied plants are among the native plants abundantly found in South Khorasan, Iran. The data also show the effect and role of important variables in green synthesis process including Fe to extract ratio, extract heating time, and length of time when Fe-extract solution was mixed under ultrasonic waves. The effects of the mentioned variables were measured by weighing the produced nanoparticle and determining the yield of the prepared nanoparticles. Based on the data, with decreasing Fe to extract ratio, the amount of produced GINPs was increased but the yield of the process decreased. Additionally, extract heating time and ultrasonic mixing time had a significant effect on GINPs yield. Based on the results of transmission electron microscopy (TEM) test, the size of GINPs in all of the plant extracts was about 40 nm and smaller.

Spatial distribution variation and probabilistic risk assessment of exposure to chromium in ground water supplies; a case study in the east of Iran.

A high concentration of chromium (VI) in groundwater can threaten the health of consumers. In this study, the concentration of chromium (VI) in 18 drinking water wells in Birjand, Iran, s was investigated over a period of two yearsNon-carcinogenic risk assessment, sensitivity, and uncertainty analysis as well as the most important variables in determining the non-carcinogenic risk for three age groups including children, teens, and adults, were performed using the Monte Carlo simulations technique. The northern and southern regions of the study area had the highest and lowest chromium concentrations, respectively. The chromium concentrations in 16.66% of the samples in an area of 604.79 km2 were more than World Health Organization (WHO) guideline (0.05 mg/L). The Moran's index analysis showed that the distribution of contamination is a cluster. The Hazard Index (HI) values for the children and teens groups were 1.02 and 2.02, respectively, which was more than 1. A sensitivity analysis indicated that the most important factor in calculating the HQ was the concentration of chromium in the consumed water. HQ values higher than 1 represent a high risk for the children group, which should be controlled by removing the chromium concentration of the drinking water.

Probabilistic risk assessment of exposure to fluoride in most consumed brands of tea in the Middle East.

The aim of this study was to evaluate the fluoride concentration in seven most consumed brands of tea in the Middle East which was imported to Iran through Zabol County. In the present study, the health risk of exposure to fluoride was estimated using a probabilistic approach. Monte Carlo simulation and sensitivity analysis were applied to quantify uncertainties in risk estimation. The highest mean and 95th percentile of chronic daily intake (CDI) was observed for children group. Iranian tea and Kenya tea had maximum CDI and target hazard quotient (THQ) values among studied brands of tea which followed by Green tea, Taksetare tea, Ceylan tea, Red tea, and White tea. These result indicated that there were significant risks of exposure to fluoride in most of studied brands of tea for children (THQ>1). Sensitivity analysis showed that fluoride concentration and daily intake were the most influential variables in three exposed populations. In conclusion, the fluoride concentration in some studied brands of tea is high and it put children at risk risks of exposure to fluoride.

Biodegradation and nutrients removal from greywater by an integrated fixed-film activated sludge (IFAS) in different organic loadings rates.

In this study, the efficiency of Integrated Fixed-film Activated Sludge (IFAS) system in synthetic greywater treatment and nutrients removal was studied in duration of 105 days according to different Organic Loadings Rates (OLRs). The study was operated in pilot-scale and OLRs of 0.11-1.3 gCOD/L.d. Scanning Electron Microscope (SEM) image showed that the biofilm with a proper thickness was formed on IFAS reactor's media. The results indicated that the best removal efficiency of BOD5, COD, and TSS were 85.24, 92.52 and 90.21%, respectively, in an organic loading of 0.44 gCOD/L.d. Then, with the OLR increased, the removal efficiencies of BOD5, COD, and TSS increased as long as the organic loading reached 0.44 gCOD/L.d. But with the OLR increased more, the removal efficiency of these parameters decreased. The ANOVA statistical test results showed that the mean difference of removal efficiency in organic loadings for BOD5 (p ≤ 0.001) and COD (p = 0.003) was significant, while it was insignificant for TSS (p = 0.23). The best removal efficiencies of Total Nitrogen (TN) and Total Phosphorus (TP) were 89.60 and 86.67%, respectively, which were obtained at an OLR of 0.44 gCOD/L.d. By increasing OLR up to 0.44 gCOD/L.d, removal efficiencies of TN and TP increased, while the removal efficiency decreased with the OLR increased more, and this difference was statistically significant (p = 0.021). Finally, the results showed that the IFAS system provided a proper efficiency in treatment of the synthetic greywater and it could be used in a full scale.

A review and investigation of the effect of nanophotocatalytic ozonation process for phenolic compound removal from real effluent of pulp and paper industry.

Phenol and its derivatives are the major environmental pollutants discharged from paper and pulp industries into water bodies. All these compounds and chlorinated phenolic compounds in particular are very toxic to fauna and flora, even at relatively low concentration. This study aimed to investigate the removal rate of phenolic compounds from the effluent of pulp and paper industries using a combination of ozonation and photocatalytic processes. Firstly, a certain volume from the effluent of paper and pulp industries containing certain phenol concentrations was obtained and fed into a prefabricated reactor at laboratory scale. Then, the combined and separate effects of zinc oxide dosage (ZnO), ozone flow rate (O3), and pH under ultra violet radiation for 30 min were evaluated. The concentration of phenolic compounds and the produced ozone gas flow rate were measured by a spectrophotometry and iodometric method, respectively. The results showed that the phenolic removal rate increased at acidic PHs compared with alkaline PHs; it was also decreased with the increase in ZnO dosages. Furthermore, the highest phenolic compound's removal rate was 99% at the optimal condition (pH 5, ZnO dosage of 0.1 g L-1 at the 30 min with UV-C illumination of 125 W). Finally, Daphnia toxicity test showed that treated effluent was safe and met the standards to the extent that it can be discharged into the receiving waters. Graphical abstract ᅟ.

Is black coat color in wolves of Iran an evidence of admixed ancestry with dogs?

Melanism is not considered a typical characteristic in wolves of Iran and dark wolves are believed to have originated from crossbreeding with dogs. Such hybrid individuals can be identified with the combined use of genetic and morphological markers. We analyzed two black wolves using a 544 base pairs (bp) fragment of the mtDNA control region and 15 microsatellite loci in comparison with 28 dogs, 28 wolves, and four known hybrids. The artificial neural networks (ANNs) method was applied to microsatellite data to separate genetically differentiated samples of wolves, dogs, and hybrids, and to determine the correct class for the black specimens. Individual assignments based on ANNs showed that black samples were genetically closer to wolves. Also, in the neighbor-joining network of mtDNA haplotypes, wolves and dogs were separated, with the dark specimens located in the wolf branch as two separate haplotypes. Furthermore, we compared 20 craniometrical characters of the two black individuals with 14 other wolves. The results showed that craniometrical measures of the two black wolves fall within the range of wolf skulls. We found no trace of recent hybridization with free-ranging dogs in the two black wolves. Dark coat color might be the result of a natural combination of alleles in the coat-color-determining gene, mutation in the K locus due to past hybridization with free-ranging dogs, or the effect of ecological factors and adaption to habitat conditions.

Preparation and characterization of a biochar from pistachio hull biomass and its catalytic potential for ozonation of water recalcitrant contaminants.

This work introduces a biochar as novel catalyst prepared from the pistachio hull, and demonstrates its catalytic potential for degrading the reactive red 198 (RR198) dye in catalytic ozonation processes (COPs). The prepared pistachio hull biochar (PHB) was a macroporous, basic material with low specific surface area. PHB had the greatest catalytic potential at an optimal alkaline pH of 10. Significant catalytic potential was observed when PHB was added to the ozonation reactor; a 58.4% catalytic potential was obtained in the decolorization of RR198 in the COP with 0.2g of catalyst after a reaction time of 60 min. A 71% mineralization (TOC reduction) of the dye solution was observed in the COP after a reaction time of 60 min. Overall, it can be concluded from the experimental results that the PHB is a promising and affordable catalyst for use in COPs for treatment of resistant organic compounds.