Color removal from industrial wastewater with a novel coagulant flocculant formulation

Chemically enhanced wastewater treatment is attracting substantial interest among the currently employed chemical unit processes in wastewater treatment. Coagulation-flocculation has received considerable attention for yielding high pollutant removal, especially color removal. This investigation presents a novel formulation of coagulation-flocculation for color removal from industrial wastewater and illustrates its efficiency, with aid of measurement of solid sludge content, suspended solid content, percentage of solid recovery, UV absorption in wastewater effluent from two automotive factories. The results show that the novel formulation can remove color content from wastewater efficiently. The treated wastewater had UV absorption close to distillated water and color was removed up to 96% by flocculation / coagulation treatment.     

Spatial and Temporal Distribution of Dust‐Bound Trace Metal Elements around Kuhdasht Watershed Area in Iran

Dust, as a source of trace metal elements, affects the health of society. The spatial and temporal concentrations of dust‐bound trace metals (Cd, Pb, Ni, Zn, Cu, and Mn) in Kuhdasht watershed (456 km²), Lorestan Province, Iran, is investigated. Dust is collected using glass traps placed in ten research stations in the region. The spatial and temporal distribution of dust trace metals are plotted using ARC‐GIS. The highest and the lowest concentrations of Zn (9751150 mg kg^?1), Pb (46.352.9 mg kg^?1), and Cd (2.443.30 mg kg^?1) are obtained in winter, of Ni (98110 mg kg^?1) and Cu in autumn (16.053.5 mg kg^?1), and of Mn in summer (385505 mg kg^?1). The spatial concentrations of dust‐bound trace metals indicate all, except Cu, show a decreasing trend from the mountains toward the plains, similar to that of soil and of dust, except for Zn, which shows higher concentrations in dust than in soil. The potential sources of dust‐bound trace metals and their rate of contamination are also investigated using the enrichment and contamination factors. The major sources of Cd and Zn in the dust of watershed are due to anthropogenic activities or from activities outside the borders.     

Characteristics of magnetic and non-magnetic lag in the Cobar area, NSW

Geochemical patterns from two lag anomalies in the Cobar region of central New South Wales are described. The region is semi-arid, deeply weathered and some areas are covered by variable thicknesses of aeolian and alluvial transported overburden.Lag morphology and mineralogy are related to landform. In erosional landforms the surface is covered by lag, which is composed of coarse fragments derived locally from bedrock and displays varying degrees of ferruginization, together with a range of secondary pisoids. In depositional landforms the lag is less abundant and contains more pisoids. Deflation by sheetwash may lead to lag being partially buried by alluvium. In a large proportion of pisoid lag, hematite and goethite have been converted to maghemite, allowing ready separation into magnetic and non-magnetic fractions. The non-magnetic fraction is dominated by the lithic lag whereas the magnetic fraction is dominated by pisoid lag.The magnetic and non-magnetic components of the 2–11 mm lag fraction, milled to < 75 μm and subjected to HF-HNO₃-HClO₄ attack, give rise to distinct geochemical patterns at targets related to a variant of the Cobar style of Pb-Zn mineralization with variable silicification and to Zn mineralization in a swarm of quartz and carbonate veinlets. The patterns are influenced by metal source, lag type, surface chemical conditions and landtbrm. Differences in the correlation between metal contents in the magnetic and non-magnetic lag components, and between trace elements and Fe. indicate variable loss of Cu and Zn from the magnetic lag at some targets but retention of Pb. The presence of a readily cxtractable base metal component in the lag has implications for detecting anomalies in transported cover in the region.     

A vision for Iran’s fuel cell and hydrogen development

Hydrogen combined with fuel cell (FC) technology has been widely discussed as a long-term fuel option to address environmental and energy security concerns. Iran, despite outlining a long-term plan to develop its renewable energies’ (REs) infrastructures, is faced with difficulties in deploying fuel cell hydrogen (FCH). These obstacles—led by lack of adequate funding—have caused a slowdown in the government-driven initiatives in recent years, thus resulting in projects delays and suspensions. This paper focuses on current status of Iran’s FCH within and among leading and neighboring countries. Barriers and challenges of the three main actors (government, university, and industry) on Iran’s FCH development are analyzed and then supported with a policy perspective. It is shown that the government obligations play a significant role to overcome these obstacles and also act as the main driving force to perform the required actions. The paper also proposes strategic measures in a short-, medium-, and long-term framework to promote the technology in Iran in hopes of a clear national policy and a proper vision. It is shown that the responsibility for the short- and medium-term actions lies predominantly upon the government while it will be fully devolved to the private sector in the long term.     

The latest Carboniferous–Early Permian Dorud Group of the eastern Alborz (Iran): biostratigraphy and taxonomy of smaller foraminifers

The latest Carboniferous–Early Permian Dorud Group in the Chaman‐Saver area of eastern Alborz, Iran is more than 222 m thick and includes thick sequences of oncolitic limestone, sandy limestone, sandstones and shales. The Emarat and Ghosnavi formations of this Group are dated here as latest Gzhelian to early Sakmarian Stages. During the Asselian Stage, the sea level fell abruptly and epeirogenic episodes occurred. These events generated a broad, shallow carbonate platform suitable for the growth and diversity of smaller foraminifers in the Chaman‐Saver area which, consequently, displays faunal differences with the rest of the Alborz Mountains. Three foraminiferal biozones are proposed: Nodosinelloides potievskayae–Vervilleina bradyi Zone (latest Gzhelian), Calcitornella heathi–Nodosinelloides sp. Zone (latest Gzhelian–Asselian), and Rectogordius iranicus n. gen. n. sp.–Hemigordius schlumbergeri Zone (early Sakmarian). The new taxa described herein include: Pseudovidalina iranica n. sp., P. damghanica n. sp., Rectogordius iranicus n. gen. n. sp. and Tezaquina sp. 1. Copyright © 2012 John Wiley & Sons, Ltd.     

Gas-oil gravity drainage mechanism in fractured oil reservoirs: surrogate model development and sensitivity analysis

Computational Geosciences - In this study, a surrogate model is developed based on single porosity modelling approach to predict the gas-oil gravity drainage recovery curves. The single porosity...     

Streamflow prediction under extreme data scarcity: a step toward hydrologic process understanding within severely data-limited regions

Streamflow prediction in ungauged basins is necessary to support water resources management decisions. Herein we refine and evaluate the Streamflow Prediction under Extreme Data-scarcity (SPED) model, a framework designed for streamflow prediction within regions of sparse hydrometeorological observation. With the SPED framework, inclusion of soft data directs optimization to balance runoff efficiency with the selection of hydrologically representative parameters. Here SPED is tested in catchments around the world, including four well-gauged catchments, by mimicking data-scarcity and comparing against data-intensive approaches. By differentiating equifinal models, SPED succeeds where traditional approaches are likely to fail: partially dissimilar reference/target catchments. For instance, in a pair of reference/target catchments with different base flow regimes, SPED outperforms a model calibrated only to maximize efficiency (NSE of 0.54 versus 0.08). SPED performs consistently (NSE range: 0.54–0.74) across the diverse climatological and physiographic settings tested and proves comparable to state-of-the-science methods that use robust data networks.     

Rock mass excavatability estimation using artificial neural network

One important decision in design of surface mine is the selection of mine equipment and plant. Demand for mechanical excavation is growing in mining industry because of its high productivity and excavation in large scale with lower costs. Several models have been developed over the years to evaluate the ease of excavation and machine performance against rock mass properties. Due to complexity of excavation process and large number of effective parameters, approaches made for this purpose are essentially empirical. There are many uncertainties in results of these models. An attempt is made in this paper to revise the exisiting models. Neural network models for estimation of rock mass excavatability and production rate of VASM-2D excavating machine at Limestone quarry in Retznei, Austria, is presented. Input parameters of this model are Uniaxial compressive strength, tensile strength and discontinuities spacing of rocks. Output is the specific excavation rate per power consumption (bcm/Kwh) as the productivity indicator. Average of deviation between actual data and results estimated by neural network model was only 15% which is in an acceptable range.