Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran)

Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.     

The effect of EDDS and citrate on the uptake of lead in hydroponically grown Matthiola flavida

Root and shoot lead concentrations and the impact of chelating agents on these were investigated in two populations of the novel metallophyte Matthiola flavida. Plants were exposed in hydroponics to Pb(NO₃)₂, supplied alone, or in combination with citric acid, or EDDS. When supplied at concentrations expected to bind about 95% of the Pb in a solution containing 1-μM Pb (1000 μM citrate or 3.1 μM EDDS, respectively), the root and shoot Pb concentrations were dramatically lowered, in comparison with a 1-μM free ionic Pb control exposure. A 1-mM EDDS + 1-μM Pb treatment decreased the plants’ Pb concentrations further, even to undetectable levels in one population. At 100 μM Pb in a 1-mM EDDS-amended solution the Pb concentration increased strongly in shoots, but barely in roots, in comparison with the 1-μM Pb + 1-mM EDDS treatment, without causing toxicity symptoms. Further increments of the Pb concentration in the 1-mM EDDS-amended solution, i.e. to 800 and 990 μM, caused Pb hyperaccumulation, both in roots and in shoots, associated with a complete arrest of root growth and foliar necrosis. M. flavida seemed to be devoid of constitutive mechanisms for uptake of Pb-citrate or Pb-EDDS complexes. Hyperaccumulation of Pb-EDDS occurred only at high exposure levels. Pb-EDDS was toxic, but is much less so than free Pb. Free EDDS did not seem to be toxic at the concentrations tested.     

Groundwater depth and elevation interpolation by kriging methods in Mohr Basin of Fars province in Iran

Prediction of groundwater depth and elevation is important in quantitative water management especially in arid areas. There are several basins in southwest of Iran, in Zagross Mountain, in which the water wells are distributed along a narrow elliptic ring band around the region. To find the most applicable interpolation method, both of the groundwater depth and elevation are predicted by different kriging methods. It is found that the groundwater elevation and depth can be predicted by different methods. Furthermore, it is found that the methods in which the trend is eliminated predicted the groundwater elevation and depth in central part of the region is with less standard error. Furthermore, the methods with no trend elimination, predicted the groundwater depths with less error near the water wells. Dividing the area to hydro-geologically homogeneous sub-areas improved the interpolation precision.     

Water and waste load allocation in rivers with emphasis on agricultural return flows: application of fractional factorial analysis

In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.     

Monitoring of trace amounts of heavy metals in different food and water samples by flame atomic absorption spectrophotometer after preconcentration by amine-functionalized graphene nanosheet

We are introducing graphene oxide modified with amine groups as a new solid phase for extraction of heavy metal ions including cadmium(II), copper(II), nickel(II), zinc(II), and lead(II). Effects of pH value, flow rates, type, concentration, and volume of the eluent, breakthrough volume, and the effect of potentially interfering ions were studied. Under optimized conditions, the extraction efficiency is >97 %, the limit of detections are 0.03, 0.05, 0.2, 0.1, and 1 μg L^?1 for the ions of cadmium, copper, nickel, zinc, and lead, respectively, and the adsorption capacities for these ions are 178, 142, 110, 125, and 210 mg g^?1. The amino-functionalized graphene oxide was characterized by thermogravimetric analysis, transmission electron microscopy, scanning electron microscopy, and Fourier transform infrared spectrometry. The proposed method was successfully applied in the analysis of environmental water and food samples. Good spiked recoveries over the range of 95.8–100.0 % were obtained. This work not only proposes a useful method for sample preconcentration but also reveals the great potential of modified graphene as an excellent sorbent material in analytical processes.     

Rapid spectrophotometric determination of trace amounts of palladium in water samples after dispersive liquid–liquid microextraction

A simple, rapid, and efficient dispersive liquid–liquid microextraction method, followed by UV–Vis spectrophotometry was developed for the preconcentration and determination of Pd ions in water samples. Pd ions react with α-furildioxime (chelating agent) to form a hydrophobic complex. Various parameters were altered to study and optimize their effects on the extraction efficiency, such as pH, ligand concentration, the type and volume of extraction and dispersive solvents, extraction time, and salt concentration. Under optimized conditions, the method exhibited an enrichment factor (C _org/C _aq) of 25 and recovery more than 98 % within a very short extraction time. The linearity of the method ranged from 10 to 200 μg?L^?1. The limit of detection was 1.1 μg?L^?1. The relative standard deviation for the concentration of 100 μg?L^?1 of Pd was 2.3 % (n?=?10). Finally, the developed method was successfully applied to the extraction and determination of Pd in tap, river, mineral, and sea water samples.     

Identification of effective best management practices in sediment yield diminution using GeoWEPP: the Kasilian watershed case study

Identifying areas that are susceptible to soil erosion is crucial for water resource planning and management efforts. Furthermore, modeling has proven helpful in recognizing and monitoring high-risk areas at the watershed scale. The Water Erosion Prediction Project (WEPP) geospatial interface (GeoWEPP) software integrates GIS with the WEPP to analyze the spatial variation in soil loss, and it has been used as a modeling tool to determine the areas that are most prone to soil erosion and to evaluate best management practices for the Kasilian watershed in Iran. As much as 62.4 % of the agronomic land in the Kasilian watershed is affected by a high magnitude of erosion (>5 t/ha). On the basis of this study, by using soybeans, high fertilization levels, and the drill-no-tillage system, reductions of erosion by almost 32.68–34.02 % are perceivable in three critical subwatersheds that are located in the cultivated lands. Also, it is projected that reductions in the production of sediment in the range of about 36.7–47.1 % are achievable by structural management within two critical, upland subwatersheds. So, by utilizing the best management strategies, sediment yield can be lowered and the conservation of soil and water is feasible at the watershed scale. These results objectively indicate that GeoWEPP can be efficaciously used for evaluating effective management practices for developing watershed conservation.     

Changes in urinary catecholamines in response to noise exposure in workers at Sarcheshmeh Copper Complex, Kerman, Iran

Noise is one of the most harmful agents in the workplace. In addition to the adverse effects of noise on the auditory system, as a stressor it may cause increased blood pressure, cardiovascular disease, anxiety, and impaired secretion of hormones. The purpose of this study was to evaluate changes in urinary catecholamines in workers exposed to industrial noise. This is an experimental study of the workers at the smelter section of Sarcheshmeh Copper Industries done on two separate days. During the first day, urine samples from 20 workers who did not use any hearing protection device, were collected during an 8-h work shift and on the second day the same was done but they were asked to use earplugs. Also 20 people were selected as a control group from people who were not exposed to noise at work. Urinary catecholamine levels were measured with ELISA kits. The mean urinary epinephrine and norepinephrine levels in the workers (without earplugs) was respectively 8.69 and 35.56 μg/8h on the first day and on the second day (with earplugs) dropped to 6.45 and 30.95 μg/8h. Noise reduction by earplugs led to almost significant reductions in urinary epinephrine (p?=?0.05) and significant reductions in norepinephrine (p?=?0.02). The results showed that with noise reduction the urinary excretion of stress hormones, especially norepinephrine significantly decreases and workers are probably less prone to stress-related disorders.