Comparison of different static methods for assessment of AMD generation potential in mining waste dumps in the Muteh Gold Mines,Iran

Acid mine drainage (AMD) gives rise to several problems in sulfide-bearing mineral deposits whether in an ore body or in the mining wastes and tailings. Hence, several methods and parameters have been proposed to evaluate the acid-producing and acid-neutralizing potential of a material. This research compares common static methods for evaluation of acid-production potential of mining wastes in the Muteh gold mines by using 62 samples taken from six waste dumps around Senjedeh and Chah-Khatoun mines. According to a detailed mineralogical study, the waste materials are composed of mica-schist and quartz veins with a high amount of pyrite and are supposed to be susceptible to acid production, and upon a rainfall, they release acid drainage. All parameters introduced in different methods were calculated and compared in this research in order to predict the acid-generating and neutralization potential, including APP, NNP, MPA, NPR, and NAGpH. Based on the analytical results and calculation of different parameters, all methods are in a general consensus that DWS-02 and DWS-03 waste dumps are acid-forming which is clearly attributed to high content of pyrite in samples. DWS-04 is considered as non-acid forming in all methods except method 8 which is uncertain about its acid-forming potential and method 7 which considers a low potential for it. DWC-01 is acid-forming based on all methods except 8, 9, 10, and 11 which are also uncertain about its potential. The methods used are not reached to a compromise on DWS-01 and DWC-02 waste dumps. It is supposed that method 7 gives the conservationist results in all cases. Method 8 is unable to decide on some cases. It is recommended to use and rely on results provided by methods 1, 2, 3, and 12 for taking decisions for further studies. Therefore, according to the static tests used, the aforementioned criteria in selected methods can be used with much confidence as a rule of thumb estimation.     

Monitoring and assessment of seasonal land cover changes using remote sensing: a 30-year (1987–2016) case study of Hamoun Wetland,Iran

The availability of Landsat data allows improving the monitoring and assessment of large-scale areas with land cover changes in rapid developing regions. Thus, we pretend to show a combined methodology to assess land cover changes (LCCs) in the Hamoun Wetland region (Iran) over a period of 30-year (1987–2016) and to quantify seasonal and decadal landscape and land use variabilities. Using the pixel-based change detection (PBCD) and the post-classification comparison (PCC), four land cover classes were compared among spring, summer, and fall seasons. Our findings showed for the water class a higher correlation between spring and summer (R²?=?0.94) than fall and spring (R²?=?0.58) seasons. Before 2000, ~?50% of the total area was covered by bare soil and 40% by water. However, after 2000, more than 70% of wetland was transformed into bare soils. The results of the long-term monitoring period showed that fall season was the most representative time to show the inter-annual variability of LCCs monitoring and the least affected by seasonal-scale climatic variations. In the Hamoun Wetland region, land cover was highly controlled by changes in surface water, which in turn responded to both climatic and anthropogenic impacts. We were able to divide the water budget monitoring into three different ecological regimes: (1) a period of high water level, which sustained healthy extensive plant life, and approximately 40% of the total surface water was retained until the end of the hydrological year; (2) a period of drought during high evaporation rates was observed, and a mean wetland surface of about 85% was characterized by bare land; and (3) a recovery period in which water levels were overall rising, but they are not maintained from year to year. After a spring flood, in 2006 and 2013, grassland reached the highest extensions, covering till more than 20% of the region, and the dynamics of the ecosystem were affected by the differences in moisture. The Hamoun wetland region served as an important example and demonstration of the feedbacks between land cover and land uses, particularly as pertaining to water resources available to a rapidly expanding population.     

Effects of water shortage in Kabul River network on the plain areas of Khyber Pakhtunkhwa,Pakistan

Kabul River is a shared resource of Pakistan and Afghanistan and is a major source of economy for both countries. It is used for irrigation, power generation, fishery, hunting, and recreation. This study explored human-induced impact on Kabul River and its associated wetlands. For an in-depth study, the area situated between the two tributaries of Kabul River, i.e., Shalam and Naguman Rivers, was selected. The focus of the study was to find out reduction in the wetland areas, its causes, and associated impacts. For this purpose, a survey was conducted in 10 villages selected randomly in 10 union councils. The study revealed that anthropogenic activities, such as wetland farming, grazing residential encroachment, and industrial development, have caused severe alteration in the wetland of the study areas. The results revealed that before the 1990s, 33.55% area of the study area was wetland. Due to regular decrease in the flow of the Kabul River System and human encroachment, it has engulfed 68.40% of the total wetland leaving behind only 10.60% wetland. This can be termed as a big ecological disturbance. In the long run, this will have negative effects on both the countries. It is therefore recommended to give proper attention to this important wetland, positioning between Shalam and Naguman Rivers and to conserve it. One of the solutions is to regulate the natural flow of Kabul River.     

Determination of nickel, copper, zinc and lead in human scalp hair in Syrian occupationally exposed workers by total reflection X-ray fluorescence

In this study, an attempt has been made to study methane flux and quantification of heavy metals from Municipal Solid Waste (MSW) landfill areas of selected cities in India. During the period of study, the average value of methane flux was estimated from these landfill areas varied from 146–454 mg/m2/h. Methane emission from landfill is of serious environmental global concern as it accounts for approximately 15 percentages of current Greenhouse gas emissions. It has been estimated that methane emission, from landfill areas in the world, in next two decades would be same as that what is emitted from paddy fields presently. Besides, the estimation of methane flux, quantification of some heavy metals was conducted to analyse the suitability of using MSW as compost. The average values for metals were observed to be both within the range of USEPA and Indian standards for MSW disposal in landfill areas and to be used as compost respectively.     

Assessment of elemental concentrations in the urban air (case study: Tehran city)

Tehran is one of the megacities of the world with a population of over eight million. Its air is highly polluted mainly due to the suspended particulate matters, which encompasses a wide spectrum of chemical elements. These elements based on their type, size, and impact on the life cycle have various environmental and heath risks. In this research, the neutron activation method is used to determine the concentration levels of Al, Ba, Fe, Mg, and V in the urban air. Thus, two districts of Tehran with different characteristics are selected. District 21 includes much of the industries located in Tehran metropolitan and is considered as an industrial area. In contrast, district 22 lacks any significant industrial activity. It is a newly established and expanding district adjacent to district 21 with a great deal of constructional activities. For the measurement of the suspended particulate matters in the air, the various sections of the aforesaid districts with industrial, residential, heavily congested traffic, residential/commercial, residential/heavily congested traffic, and residential/industrial classifications were identified. Subsequently, 24 sampling stations were selected. The sampling of the suspended particulate matters was conducted with the aid of a high volume pump containing 125 mm cellulose filters in two different time intervals. After completion of the sampling process, the samples were prepared and sent to the research reactor of the Iran Nuclear Energy Organization for Neutron Activation. During the next steps, the radiations emitted from the samples were registered, the radiation curves were plotted, and the amounts of the trace elements were determined. As a result, the average concentration levels of Al, Ba, Fe, Mg, and V were identified to be 3.301140, 2.273658 × 10, 4.0681696 × 10^???1, 3.5525475 × 10^???1, and 3.04075 × 10^???2 μg/m³, respectively. Moreover, the emission sources of the aforesaid elements into the air were identified. The concentration levels of these elements in the industrial and heavily congested traffic sections were higher. Finally, it was concluded that the statistical analysis of these elements presents a meaningful correlation among them.     

A mobile monitoring system to understand the processes controlling episodic events in Corpus Christi Bay

Corpus Christi Bay (TX, USA) is a shallow wind-driven bay and thereby, can be characterized as a highly pulsed system. It cycles through various episodic events such as hypoxia, water column stratification, sediment resuspension, flooding, etc. Understanding of the processes that control these events requires an efficient observation system that can measure various hydrodynamic and water quality parameters at the multitude of spatial and temporal scales of interest. As part of our effort to implement an efficient observation system for Corpus Christi Bay, a mobile monitoring system was developed that can acquire and visualize data measured by various submersible sensors on an undulating tow-body deployed behind a research vessel. Along with this system, we have installed a downward-looking Acoustic Doppler Current Profiler to measure the vertical profile of water currents. Real-time display of each measured parameter intensity (measured value relative to a pre-set peak value) guides in selecting the transect route to capture the event of interest. In addition, large synchronized datasets measured by this system provide an opportunity to understand the processes that control various episodic events in the bay. To illustrate the capability of this system, datasets from two research cruises are presented in this paper that help to clarify processes inducing an inverse estuary condition at the mouth of the ship channel and hypoxia at the bottom of the bay. These measured datasets can also be used to drive numerical models to understand various environmental phenomena that control the water quality of the bay.     

Mercury speciation in the Persian Gulf sediments

The concentrations of total mercury (Hg) and methyl mercury (MMHg) were determined in 78 marine sediments in the Iranian coastal waters of the Persian Gulf along nine transects perpendicular to the coastline. Total Hg ranged from 10 to 56 ng g( - 1)d.w. and MMHg from 0.1 to 0.4 ng g( - 1) d.w. The fraction of methyl mercury accounted from 0.3% to 1.1% of the total mercury amount. The organic carbon (OC) content ranged from 0.4% to 1.8%. The present study indicates that the levels of Hg in the sediments of the Iranian coast of the Persian Gulf were all in the concentration range of unpolluted areas regarding Hg (<100 ng g( - 1)). The concentrations of total Hg, methyl mercury and organic carbon were generally higher in the deeper stations. Total Hg and MMHg were significantly correlated, but no significant correlations could be found between the Hg and OC levels.     

The effectiveness of digital soil mapping to predict soil properties over low-relief areas

This study investigates the ability of different digital soil mapping (DSM) approaches to predict some of physical and chemical topsoil properties in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province, Iran. According to a semi-detailed soil survey, 120 soil samples were collected from 0 to 30 cm depth with approximate distance of 750 m. Particle size distribution, coarse fragments (CFs), electrical conductivity (EC), pH, organic carbon (OC), and calcium carbonate equivalent (CCE) were determined. Four machine learning techniques, namely, artificial neural networks (ANNs), boosted regression tree (BRT), generalized linear model (GLM), and multiple linear regression (MLR), were used to identify the relationship between soil properties and auxiliary information (terrain attributes, remote sensing indices, geology map, existing soil map, and geomorphology map). Root-mean-square error (RMSE) and mean error (ME) were considered to determine the performance of the models. Among the studied models, GLM showed the highest performance to predict pH, EC, clay, silt, sand, and CCE, whereas the best model is not necessarily able to make accurate estimation. According to RMSE%, DSM has a good efficiency to predict soil properties with low and moderate variabilities. Terrain attributes were the main predictors among different studied auxiliary information. The accuracy of the estimations with more observations is recommended to give a better understanding about the performance of DSM approach over low-relief areas.