PREDICTING EROSION AND DEPOSITION ON A STRIPMINED AND RECLAIMED AREA1

ABSTRACT A rill-interrill erosion model was applied to a mined and reclaimed area. Soil loss from the interrill areas was estimated by the Universal Soil Loss Equation (USLE). The model considers the fate and ultimate disposition of the sediment from interrill areas along with the fate and destination of soil materials detached by the rill flow. The net sediment loss was predicted by comparing, for a given flow, the amounts of eroded soil to rill transport capacity. When applied to a selected stripmined and reclaimed site the model displayed the location of contributing areas and the amount of erosion and deposition. The predicted areal distribution of erosion and deposition was compared to measured data. Agreement between the predicted and measured values was within 25 percent.     

Comparative cancer risk assessment of THMs in drinking water from well water sources and surface water sources

This research evaluates the lifetime cancer risks from trihalomethanes in Tehran's drinking water. The Trihalomethanes were measured in seven different water districts. Sixty-three samples were taken from tap water across the city for 7 months. The samples were analyzed for trihalomethanes using US EPA method 524.2. The average concentration of total trihalomethanes in different districts were between 0.81 and 9.0 μg/L, and the highest concentrations were detected in district 2 at 19.5 μg/L. Total lifetime cancer risks assessment from exposure to trihalomethanes in drinking water (ingestion, inhalation, and skin routes) were performed for people living in different districts in Tehran. The lifetime cancer risk was 7.19 × 10(-5) in district 2 (a more affluent neighborhood) where mostly surface water sources is used to supply drinking water and 9.38 × 10(-6) in district 7 (a less affluent neighborhood) which is mainly supplied with well water sources. Based on the population data, the total expected lifetime cancer cases from exposure to trihalomethanes are 104, 108, 81, 81, 41, 27, and three for districts 1 through 7, respectively. The average lifetime cancer risk was 4.33 × 10(-5) which means a total of 606 lifetime cancer cases for the entire province of Tehran. The highest risk from THMs seems to be from the inhalation route followed by ingestion and dermal contacts.     

Randomly selected order statistics in ranked set sampling: A less expensive comparable alternative to simple random sampling

Rank-based sampling designs are powerful alternatives to simple random sampling (SRS) and often provide large improvements in the precision of estimators. In many environmental, ecological, agricultural, industrial and/or medical applications the interest lies in sampling designs that are cheaper than SRS and provide comparable estimates. In this paper, we propose a new variation of ranked set sampling (RSS) for estimating the population mean based on the random selection technique to measure a smaller number of observations than RSS design. We study the properties of the population mean estimator using the proposed design and provide conditions under which the mean estimator performs better than SRS and some existing rank-based sampling designs. Theoretical results are augmented with some numerical studies and a real-life example, where we also study the performance of our proposed design under perfect and imperfect ranking situations.     

Oxidative potential (OP) and mineralogy of iron ore particulate matter at the Gol-E-Gohar Mining and Industrial Facility (Iran)

Concentrations of total suspended particulate matter, particulate matter with aerodynamic diameter <2.5 μm (PM_2.5), particulate matter <10 μm (PM₁₀), and fallout dust were measured at the Iranian Gol-E-Gohar Mining and Industrial Facility. Samples were characterized in terms of mineralogy, morphology, and oxidative potential. Results show that indoor samples exceeded the 24-h PM_2.5 and PM₁₀ mass concentration limits (35 and 150 µg m^?3, respectively) set by the US National Ambient Air Quality Standards. Calcite, magnetite, tremolite, pyrite, talc, and clay minerals such as kaolinite, vermiculite, and illite are the major phases of the iron ore PM. Accessory minerals are quartz, dolomite, hematite, actinolite, biotite, albite, nimite, laumontite, diopside, and muscovite. The scanning electron microscope structure of fibrous-elongated minerals revealed individual fibers in the range of 1.5 nm to 71.65 µm in length and 0.2 nm to 3.7 µm in diameter. The presence of minerals related to respiratory diseases, such as talc, crystalline silica, and needle-shaped minerals like amphibole asbestos (tremolite and actinolite), strongly suggests the need for detailed health-based studies in the region. The particulate samples show low to medium oxidative potential per unit of mass, in relation to an urban road side control, being more reactive with ascorbate than with glutathione or urate. However, the PM oxidative potential per volume of air is exceptionally high, confirming that the workers are exposed to a considerable oxidative environment. PM released by iron ore mining and processing activities should be considered a potential health risk to the mine workers and nearby employees, and strategies to combat the issue are suggested.     

Assessing the effects of dam building on land degradation in central Iran with Landsat LST and LULC time series

This study aimed to analyze the impact of Zayandehrood Dam on desertification using the spatio-temporal dynamics of land use/land cover (LULC) and land surface temperature (LST) in an arid environment in central Iran from 1987 to 2014. The LULC and LST images were calculated from Landsat TM, ETM+, and OLI data, and their accuracies were assessed against reference data using error matrix and linear regression analysis. Results showed that salty and bare lands increased up to 57,302 ha, while agricultural lands declined substantially (28,275.58 ha) in the region. The changes in LULC classes resulted in dramatic variations in LST values. The average temperature showed a 5.03 °C increase, and the minimum temperature increased by 5.66 °C. LST had an increasing trend in bare lands (8.74 °C), poor rangelands (6.8 °C), agricultural lands (9.46 °C), salty lands (9.6 °C), and residential areas (3.18 °C) in this 27-year period. Rainfall and temperature trend analysis revealed that the main cause of these extreme changes in LULC and LST was largely attributed to the drying up of Zayandehrood River due to dam construction and allocating water mainly for industrial sectors. Results indicate that in addition to LULC changes, the spatio-temporal variations of LST can be used as an effective index in desertification assessment and monitoring in arid environments.     

Contaminants of emerging concern: a review of new approach in AOP technologies

The presence of contaminants of emerging concern (CECs) such as pharmaceuticals and personal care products (PPCPs), endocrine-disrupting compounds (EDCs), flame retardants (FRs), pesticides, and artificial sweeteners (ASWs) in the aquatic environments remains a major challenge to the environment and human health. In this review, the classification and occurrence of emerging contaminants in aquatic environments were discussed in detail. It is well documented that CECs are susceptible to poor removal during the conventional wastewater treatment plants, which introduce them back to the environment ranging from nanogram per liter (e.g., carbamazepine) up to milligram per liter (e.g., acesulfame) concentration level. Meanwhile, a deep insight into the application of advanced oxidation processes (AOPs) on mitigation of the CECs from aquatic environment was presented. In this regard, the utilization of various treatment technologies based on AOPs including ozonation, Fenton processes, sonochemical, and TiO₂ heterogeneous photocatalysis was reviewed. Additionally, some innovations (e.g., visible light heterogeneous photocatalysis, electro-Fenton) concerning the AOPs and the combined utilization of AOPs (e.g., sono-Fenton) were documented.     

Developing an environmental water quality monitoring program for Haraz River in Northern Iran

Water quality management plans are an indispensable strategy for conservation and utilization of water resources in a sustainable manner. One common industrial use of water is aquaculture. The present study is an attempt to use statistical analyses in order to prepare an environmental water quality monitoring program for Haraz River, in Northern Iran. For this purpose, the analysis of a total number of 18 physicochemical parameters was performed at 15 stations during a 1-year sampling period. According to the results of the multivariate statistical methods, the optimal monitoring would be possible by only 3 stations and 12 parameters, including NH₃, EC, BOD, TSS, DO, PO₄, NO₃, TDS, temperature, turbidity, coliform, and discharge. In other words, newly designed network, with a total number of 36 measurements (3 stations × 12 parameters = 36 parameters), could achieve exactly the same performance as the former network, designed based on 234 measurements (13 stations × 18 parameters = 234 parameters). Based on the results of cluster, principal component, and factor analyses, the stations were divided into three groups of high pollution (HP), medium pollution (MP), and low pollution (LP). By clustering the stations, it would be possible to track the water quality of Haraz River, only by one station at each cluster, which facilitates rapid assessment of the water quality in the river basin. Emphasizing on three main axes of monitoring program, including measurement parameters, sampling frequency, and spatial pattern of sampling points, the water quality monitoring program was optimized for the river basin based on natural conditions of the study area, monitoring objectives, and required financial resources (a total annual cost of about US $2625, excluding the overhead costs).     

Contamination by organochlorine compounds in the edible tissue of four sturgeon species from the Caspian Sea (Iran)

This study focused on accumulation of organochlorine compounds (OCs), including dichloro-diphenyl-trichloroethanes (DDTs), hexachlorobenzene (HCB), hexachlorocyclohexanes (HCHs), and polychlorinated biphenyls (PCBs) accumulation in the muscle of four sturgeon (Persian sturgeon, Acipenser persicus; Stellate sturgeon, Acipenser stellatus; Ship sturgeon, Acipenser nudiventris and Beluga sturgeon, Huso huso) from the southern Caspian Sea. The DDT group was prominent in all of the sturgeon muscle tested constituting almost half or more of the total organochlorine content. Contaminant concentration generally followed this order: DDTs>PCBs>HCHs>HCB. The OCs concentrations in Beluga sturgeon (H. huso) were the highest and over four times higher than in the next highest species (A. nudiventris). From an ecotoxicological point of view, the concentrations of OCs in experimental fishes do not reflect a comparatively clean and pollution-free environment; however, results from this study shown that the inflow of organic pollutants into the Caspian Sea has been reduced when compared with prior studies. Levels of measured OCs in sturgeon were relatively low, but the level of some OCs in some of the specimens tested exceeded the guidelines for food; therefore, the maximum allowable daily consumption rate for sturgeon from this watershed may be limited by DDTs and PCBs content for high risk populations.     

Optimized processing power and trainability of neural network in numerical modeling of Al Matrix nano composites

In this research, an experimental study of reinforcing alumina nano-particles into the aluminum alloy matrix was implemented to verify the accuracy of modeling results obtained by feed forward neural networks. Artificial neural network combined with numerical technique were used to predict the various parameters of mechanical properties such as hardness, tensile and compressive yield stress, UTS and elongation percentage. Much experimentation were taken to discover a suitable number of hidden neurons, avoid detraction from the trainability and enable feed forward neural networks to solve more complex problems. The predictions were found to be consistent with experimental measurements.