Estimation of the Land Surface Emissivity in the Hinterland of Taklimakan Desert

An accurate accounting of land surface emissivity(ε) is important both for the retrieval of surface temperatures and the calculation of the longwave surface energy budgets.Since ε is one of the important parameterizations in land surface models(LSMs),accurate accounting also improves the accuracy of surface temperatures and sensible heat fluxes simulated by LSMs.In order to obtain an accurate emissivity,this paper focuses on estimating ε from data collected in the hinterland of Taklimakan Desert by two different methods.In the first method,ε was derived from the surface broadband emissivity in the 8–14 μm thermal infrared atmospheric window,which was determined from spectral radiances observed by field measurements using a portable Fourier transform infrared spectrometer,the mean ε being 0.9051.The second method compared the observed and calculated heat fluxes under nearneutral atmospheric stability and estimated ε indirectly by minimizing the root-mean-square difference between them.The result of the second method found a mean value of 0.9042,which is consistent with the result by the first method.Although the two methods recover ε from different field experiments and data,the difference of meanvalues is 0.0009.The first method is superior to the indirect method,and is also more convenient.     

Geomorphological analysis of the morphometric characteristics that determine the volume of sediment yield of Wadi Al-Arja,South Jordan

This study addresses the morphometric variables that determine the sediment yield in Wadi Al-Arja through the analysis of the impact of different morphometric characteristics along the course of the valley on its sediment yield, as well as the analysis of spatial and formal dimensions and morphologies of the basin and its relationship to the sediment yield. The study also addresses the size of variation in the volume of sediment yield of the river tributaries that make up the water network of the valley under the differences of its morphometric and hydrological characteristics. The study found several results, most notably: The classification of Wadi Al-Arja basin according to the hypsometric integral value (72.1%) within an uneven topography, which increases the force of the erosive activity and the size of the sediment yield if the basin was exposed to moist climatic periods. The study also showed the presence of convergence in the intra-spaces between the river tributaries in the water network. This increases the volume of water flows when these tributaries meet with each other and thus increasing their erosive ability and sediment yield.The study also showed the presence of marked variation in the sediment yield of the river tributaries depending on the differences in its morphometric characteristics. The results of the step-wise regression analysis confirmed the importance of the morphometric and hydrological variables, and plant coverage in interpreting the variation in the size of the sediment yield of the river tributaries of different stream order in Wadi Al-Arja basin, where these variables interpreted 43% of the total variation, with statistical significance less than 0.05.     

A study of aerosol properties over Lahore (Pakistan) by using AERONET data

It is well established that aerosols affect the climate in a variety of ways. In order to understand these effects, we require an insight into the properties of aerosols. In this paper we present a study of aerosol properties such as aerosol optical depth (AOD), single scattering albedo (SSA) and aerosol radiative forcing (ARF) over mega city of Lahore (Pakistan). The data from Aerosol Robotic Network (AERONET) have been used for the period December 2009 to October 2011. The seasonal average values of AOD, asymmetry parameter (ASY) and volume size distribution in coarse mode were observed to be highest in summer. On the other hand, the average values of Angstrom exponent (AE) and imaginary part of refractive index (RI) were found to be maximum in winter. The average value of real part of RI was found to be higher in spring than in all other seasons. The SSA exhibited an increasing trend with wavelength in the range 440 nm–1020 nm in spring, summer and fall indicating the dominance of coarse particles (usually dust). However, a decreasing trend was found in winter in the range 675 nm–1020 nm pointing towards the dominance of biomass and urban/industrial aerosols. As far as aerosol radiative forcing (ARF) is concerned, we have found that during the spring season ARF was lowest at the surface of Earth and highest at top of the atmosphere (TOA). This indicates that the atmosphere was warmer in spring than in all the remaining seasons.     

Geochemical Characteristics,Origin, and Evolution of Ore‐Forming Fluids of the Khut Copper Skarn Deposit,West of Yazd in Central Iran

The Khut copper skarn deposit is located at about 50 km northwest of Taft City in Yazd province in the middle part of the Urumieh‐Dokhtar magmatic arc. Intrusion of granitoid of Oligocene–Miocene age into carbonate rocks of the Triassic Nayband Formation led to the formation of marble and a calcic skarn. The marble contains high grade Cu mineralization that occurs mainly as open space filling and replacement. Cu‐rich sulfide samples from the mineralized marble are also anomalous in Au, Zn, and Pb. In contrast, the calcic skarn is only weakly anomalous in Cu and W. The calcic skarn is divided into garnet skarn and garnet–pyroxene skarn zones. Paragenetic relationships and microthermometric data from fluid inclusions in garnet and calcite indicate that the compositional evolution of skarn minerals occurred in three main stages as follows. (i) The early prograde stage, which is characterized by Mg‐rich hedenbergite (Hd_53.7Di_42.3–Hd_86.1Di_9.5) with Al‐bearing andradite (69.8–99.5 mol% andradite). The temperature in the early prograde skarn varies from 400 to 500°C at 500 bar. (ii) The late prograde stage is manifested by almost pure andradite (96.2–98.4 mol% andradite). Based on the fluid inclusion data from garnet, fluid temperature and salinity in this stage is estimated to vary from 267 to 361°C and from 10.1 to 21.1 wt% NaCl equivalent, respectively. Pyrrhotite precipitation started during this stage. (iii) The retrograde stage occurs in an exoskarn, which consists of an assemblage of ferro‐actinolite, quartz, calcite, epidote, chlorite, sphalerite, pyrite, and chalcopyrite that partially replaces earlier mineral assemblages under hydrostatic conditions during fracturing of the early skarn. Fluids in calcite yielded lower temperatures (T < 260°C) and fluid salinity declined to ～8 wt% NaCl equivalent. The last stage mineralization in the deposit is supergene weathering/alteration represented by the formation of iron hydroxide, Cu‐carbonate, clay minerals, and calcite. Sulfur isotope data of chalcopyrite (δ³⁴S of +1.4 to +5.2‰) show an igneous sulfur source. Mineralogy and mineral compositions of the prograde assemblage of the Khut skarn are consistent with deposition under intermediately oxidized and slightly lower fS₂ conditions at shallow crustal levels compared with those of other typical Fe‐bearing Cu–Au skarn systems.     

Mixed precision parallel preconditioner and linear solver for compositional reservoir simulation

Reservoir simulation role in value creation and strategic management decisions cannot be over emphasized. Simulation of complex challenging reservoirs with millions of grid blocks especially in compositional mode is very time-consuming even with fast modern computers. On the other hand, high price of cluster supercomputers prevents them for being commonly used for fast simulation of such reservoirs. In recent years, the development of many-core processors like cell processors, DSPs, and graphical processing units (GPUs) has provided a very cost-effective hardware platform for fast computational operations. However, programming for such processors is much more difficult than conventional CPUs, and new parallel algorithm design and special parallel implementation methods are needed. Using the computational power of CPUs, GPUs, and/or any other processing unit, Open Computing Language (OpenCL) provides a framework for programming for heterogeneous platforms. In this paper, OpenCL is used to employ the computational power of a GPU to build a preconditioner and solve the linear system arising from compositional formulation of multiphase flow in porous media. The proposed parallel preconditioner is proved to be quite effective, even in heterogeneous porous media. Using data-parallel modules on GPU, the preconditioner/solver runtime reduced at least 1 order of magnitude compared to their serial implementation on CPU.     

Removal of lead (II) from synthetic and batteries wastewater using agricultural residues in batch/column mode

The present article explores the ability of five different combinations of two adsorbents (Arachis hypogea shell powder and Eucalyptus cameldulensis saw dust) to remove Pb(II) from synthetic and lead acid batteries wastewater through batch and column mode. The effects of solution pH, adsorbent dose, initial Pb(II) concentration and contact time were investigated with synthetic solutions in batch mode. The Fourier transform infrared spectroscopy study revealed that carboxyl and hydroxyl functional groups were mostly responsible for the removal of Pb(II) ions from test solutions. The kinetic data were found to follow pseudo-second-order model with correlation coefficient of 0.99. Among Freundlich and Langmuir adsorption models, the Langmuir model provided the best fit to the equilibrium data with maximum adsorption capacity of 270.2 mg g^?1. Column studies were carried out using lead battery wastewater at different flow rates and bed depths. Two kinetic models, viz. Thomas and Bed depth service time model, were applied to predict the breakthrough curves and breakthrough service time. The Pb(II) uptake capacity (q _e = 540.41 mg g^?1) was obtained using bed depth of 35 cm and a flow rate of 1.0 mL min^?1 at 6.0 pH. The results from this study showed that adsorption capacity of agricultural residues in different combinations is much better than reported by other authors, authenticating that the prepared biosorbents have potential in remediation of Pb-contaminated waters.     

Using distributed temperature sensing (DTS) technology in acid gas injection design

The use of slickline distributed temperature sensing (SL-DTS) technology is becoming widespread due to its ease of operation and ability to acquire real-time multiple temperature traces inside the wellbore. Injection of treated acid gas (TAG)—a mixture of CO₂ and H₂S—into geologic formations has become an attractive technical and economic option for oil and gas producers and processors who are faced with regulations concerning excess sulfur and greenhouse gas emissions. Acid gas injection (AGI) into geologic formations is more economical and more flexible in dealing with varying TAG compositions than sulfur recovery units (SRUs) using the Claus process. SRUs do not achieve air quality standards and have high operation and maintenance costs. In addition, there is low demand for sulfur and sulfur disposal costs are high. The results of the analysis of SL-DTS data acquired in conjunction with step rate and pressure falloff (PFO) tests are presented in this paper. These tests were conducted to evaluate the injection potential of geologic formations. The injection zone consisted of a carbonate formation characterized by Karst features, vugs, and natural fractures. The SL-DTS data during the initial injection flow rate for the step rate test (SRT) indicated that high permeability zones accepted fluid at lower injection rates. An increasing number of discrete zones began to accept fluid as the injection rate was increased. The results of the SRT provided the fracture pressure of the formation. This information was used to design an AGI program that would avoid fracturing the formation while allowing for the required volume of TAG to be injected. The results of the PFO test provided information on the reservoir pressure and permeability and also indicated the presence of one or more hydraulic fractures. This case study of SL-DTS measurements made during a SRT and a PFO test for the design of an AGI well provides valuable insights into the potential of DTS technology and its use in AGI and carbon capture/sequestration (CCS) operations. Its findings could be applied to analyze injection potential of geological formations not only for AGI projects but also for CCS, and CO₂ enhanced oil recovery opportunities.     

Chemical evolution of a gas-capped deep aquifer,southwest of Iran

The Kangan Aquifer (KA) is located below a gas reservoir in the crest of the Kangan Anticline, southwest of Iran. This aquifer is composed of Permo-Triassic limestone, dolomite, sandstone, anhydrite and shale. It is characterized by a total dissolved solid of about 332,000 mg/L and Na–Ca–Cl-type water. A previous study showed that the source of the KA waters is evaporated seawater. Chemical evolution of the KA is the main objective of this study. The major, minor and trace element concentrations of the KA waters were measured. The chemical evolution of KA waters occurred by three different processes: evaporation of seawater, water–rock and water–gas interactions. Due to the seawater evaporation process, the concentration of all ions in the KA waters increased up to saturation levels. In comparison to the evaporated seawater, the higher concentrations of Ca, Li, Sr, I, Mn and B and lower concentrations of Mg, SO₄ and Na and no changes in concentrations of Cl and K ions are observed in the KA waters. Based on the chemical evolution after seawater evaporation, the KA waters are classified into four groups: (1) no evolution (Cl, K ions), (2) water–rock interaction (Na, Ca, Mg, Li and Sr ions), (3) water–gas interaction (SO₄ and I ions) and (4) both water–rock and water–gas interactions (Mn and B ions). The chemical evolution processes of the KA waters include dolomitization, precipitation, ion exchange and recrystallization in water–rock interaction. Bacterial reduction and diagenesis of organic material in water–gas interaction also occur. A new type of chart, Ca_excess versus Mg_deficit, is proposed to evaluate the dolomitization process.     

Risk assessment of polycyclic aromatic hydrocarbons in the West Port semi-enclosed basin (Malaysia)

Sediment samples collected from the West Port, the west coastal waters of Malaysia, were analyzed by standard methods to determine the degree of hydrocarbon contamination and identify the sources of polyaromatic hydrocarbons (PAHs). Concentrations of PAHs in the port sediments ranged from 100.3 to 3,446.9 μg/kg dw. The highest concentrations were observed in stations close to the coastline, locations affected by intensive shipping activities and industrial input. These were dominated by high-molecular-weight PAHs (4–6 rings). Source identification showed that PAHs originated mostly pyrogenically, from the combustion of fossil fuels, grass, wood, and coal or from petroleum combustion. Regarding ecological risk estimation, only station 7 was moderately polluted, the rest of the stations suffered rare or slight adverse biological effects with PAH exposure in surface sediment, suggesting that PAHs are not considered as contaminants of concern in the West Port.     

Optimal water and waste load allocation in reservoir–river systems: a case study

In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.