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.     

Integrated groundwater resource management in Indus Basin using satellite gravimetry and physical modeling tools

Reliable and frequent information on groundwater behavior and dynamics is very important for effective groundwater resource management at appropriate spatial scales. This information is rarely available in developing countries and thus poses a challenge for groundwater managers. The in situ data and groundwater modeling tools are limited in their ability to cover large domains. Remote sensing technology can now be used to continuously collect information on hydrological cycle in a cost-effective way. This study evaluates the effectiveness of a remote sensing integrated physical modeling approach for groundwater management in Indus Basin. The Gravity Recovery and Climate Experiment Satellite (GRACE)-based gravity anomalies from 2003 to 2010 were processed to generate monthly groundwater storage changes using the Variable Infiltration Capacity (VIC) hydrologic model. The groundwater storage is the key parameter of interest for groundwater resource management. The spatial and temporal patterns in groundwater storage (GWS) are useful for devising the appropriate groundwater management strategies. GRACE-estimated GWS information with large-scale coverage is valuable for basin-scale monitoring and decision making. This frequently available information is found useful for the identification of groundwater recharge areas, groundwater storage depletion, and pinpointing of the areas where groundwater sustainability is at risk. The GWS anomalies were found to favorably agree with groundwater model simulations from Visual MODFLOW and in situ data. Mostly, a moderate to severe GWS depletion is observed causing a vulnerable situation to the sustainability of this groundwater resource. For the sustainable groundwater management, the region needs to implement groundwater policies and adopt water conservation techniques.     

Climatology of atmospheric circulation patterns of Arabian dust in western Iran

Being in vicinity of vast deserts, the west and southwest of Iran are characterized by high levels of dust events, which have adverse consequences on human health, ecosystems, and environment. Using ground based dataset of dust events in western Iran and NCEP/NCAR reanalysis data, the atmospheric circulation patterns of dust events in the Arabian region and west of Iran are identified. The atmospheric circulation patterns which lead to dust events in the Arabian region and western Iran were classified into two main categories: the Shamal dust events that occurs in warm period of year and the frontal dust events as cold period pattern. In frontal dust events, the western trough or blocking pattern at mid-level leads to frontogenesis, instability, and air uplift at lower levels of troposphere in the southwest of Asia. Non-frontal is other pattern of dust event in the cold period and dust generation are due to the regional circulation systems at the lower level of troposphere. In Shamal wind pattern, the Saudi Arabian anticyclone, Turkmenistan anticyclone, and Zagros thermal low play the key roles in formation of this pattern. Summer and transitional patterns are two sub-categories of summer Shamal wind pattern. In summer trough pattern, the mid-tropospheric trough leads to intensify the surface thermal systems in the Middle East and causes instability and rising of wind speed in the region. In synthetic pattern of Shamal wind and summer trough, dust is created by the impact of a trough in mid-levels of troposphere as well as existing the mentioned regional systems which are contributed in formation of summer Shamal wind pattern.     

Eco-Friendly, Vascular Shape and Interpenetrating Poly (Acrylic Acid) Grafted Pectin Hydrogels; Biosorption and Desorption Investigations

The synthesis and characterization of poly (acrylic acid) grafted pectin hydrogel followed by biosorption and desorption characteristics of cadmium, as a model heavy metal, have been studied. The grafted eco-friendly pectin based interpenetrating hydrogel was prepared in the presence of gluteraldehyde crosslinker under N₂ atmosphere and characterized using ¹H-NMR, FTIR, TGA and SEM techniques. Gluteraldehyde was found to form one-arm and two-arm crosslinks in the copolymer. Upon grafting, two-dimensional sheet structures bounded to tubular and vascular cylindrical rods were observed. The biosorption and desorption data, determined experimentally, were fitted to pseudo-second order reaction kinetics. At higher ionic strength values, the maximum metal uptake value (q _max) was lowered and pseudo-second order rate constant (k ₂) was increased. Whereas, at higher pH values the maximum metal uptake value (q _max) was increased and Pseudo-second order rate constant (k ₂) was decreased. 0.1?M HCl solution was a suitable eluent to regenerate the hydrogel surface and recover the adsorbed cadmium metal ions. Pectin based copolymer could be used as an efficient candidature biosorbent for the recovery of cadmium metal ions from aqueous solutions.     

Recovery of heavy metals from waste printed circuit boards: statistical optimization of leaching and residue characterization

Environmental Science and Pollution Research - Despite attempts to enhance the recycling of waste printed circuit boards (WPCBs), the simultaneous recovery of major metals of WPCBs using an...     

Phytoextraction of heavy metals from contaminated soil,water and atmosphere using ornamental plants: mechanisms and efficiency improvement strategies

Environmental Science and Pollution Research - Accumulation of heavy metals (HMs) in soil, water and air is one of the major environmental concerns worldwide, which mainly occurs due to...     

Elemental composition of particulate matters around Urmia Lake,Iran

Atmospheric particulate matters and their elements were concurrently measured at two sites located in the north and southeast parts of Urmia Lake from January to September 2013. At both sampling sites, average concentrations of total suspended particulate, particles with the aerodynamic diameter of smaller than 10 µm, smaller than 2.5 µm, and smaller than 1 µm were 260 ± 106, 180 ± 73, 30 ± 8, and 25 ± 7 µg m^?3, respectively. The analyzed water soluble ions accounted for approximately 11%–13% mass concentrations of total suspended particulate and 8%–9% of particles smaller than 10 µm, and the sum of the concentrations of the analyzed elements associated with both ranged from 9 to 41 µg m^?3 (6.5%–9.6% in mass) and 7 to 26 µg m^?3 (5.5%–11.3% in mass), respectively. Thus, particulate matter was composed of a complex mixture of minerals such as halite, quartz, gypsum, hexahydrite, and Bassanite.