Valuation of socio-economic indicators for progressing urban sustainability under distinctive rubrics

The key objective of the study is to collect the factors which play an important role in the city's sustainability and implementation advantages for the development of cities in future. This article develops an urban sustainability assessment framework by giving GIS-based decision support tools to guide cities toward sustainability. Multicriteria analysis was used as the decision support system and provides an analytical framework for assessing differences in the level of criteria and ranking decision options. It has the capability for assessment of urban sustainability because it brings sustainability criteria from three pillars of sustainability, environmental, social, and economic, which provide an integrated approach for assessment of urban sustainability. The GIS-based multicriteria analysis serves as a sustainability support system that maps urban sustainability and the underlying environmental, social, and economic conditions. The results from the study show that the four cities - Faisalabad, Lahore, Gujranwala, and Multan - have better economic conditions while only Lahore and Faisalabad showed social progress and the remaining cities showed less suitability. For the environmental index, none of the cities attained high suitability. Lahore, Faisalabad, and Rawalpindi showed better conditions than Gujranwala and Multan. It is demonstrated that Punjab cities have made progress in economic condition and improvement in social condition but have poor environmental condition. In the study, the environmental dimension has indicators which have more impact on the urban sustainability. Environmental degradation is observed in all selected regions and not a single region showed suitability toward its environmental condition and due to this none of the cities gained suitable scores for urban sustainability. Consequently, urban sustainability is a multidimensional and dynamic process that needs regular evaluation and monitoring. Thus, this article contends that the tools help to highlight and emphasize those areas that need guidance in achieving urban sustainability.     

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.     

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.     

Distribution of heavy metals in the clastic fine-grained sediments of Gavkhuni playa lake (Southeast of Isfahan,Iran)

The sedimentary basin of Gavkhuni playa lake includes two sedimentary environments of delta and playa lake. These environments consist of mud, sand and salt flats. There are potentials for concentration of heavy metals in the fine-grained sediments (silt and clay) of the playa due to existence of Pb/Zn ore deposits, industrial and agricultural regions in the water catchment of Zayandehrud River terminating to this area. In order to study the concentration of heavy metals and the controlling factors on their distribution in the fine-grained sediments, 13 samples were taken from the muddy facies and concentration of the heavy metals were determined. The results showed that the heavy metal concentrations range in the sediments (in ppm) are Mn (395.5–1,040), Sr (100.4–725.76), Pb (14.66–91.06), Zn (23.59–80.9), Ni (37–73.66), Cu (13.83–29.83), Co (5.73–13.78), Ag (3.03–4.76) and Cd (2.3–5.5) in their order of abundances. The concentration of Ag is noticeable in the sediments relative to the average concentration of this element in mud sediments. The amounts of Pb and Zn are relatively high in all the samples in comparison with the other elements. The concentration of Ni is relatively high in the oxidized samples. The distribution of Pb is directly related to organic matter content of the sediments. The concentrations of Zn, Sr, Cu, Co and Cd in the samples of the playa are lower than those in the delta. The amount of illite is another factor influencing Zn and Pb concentrations. Sr is more concentrated in the sediments with the high content of calcium carbonate. The distribution pattern of Cu, Co, Pb and Mn resembles to that of the clay content of the sediments. The clay content shows positive correlations with Co, Cu and Mn concentrations and negative correlation with Ag. The Sr and Ag concentrations are positively correlated with the amount of CaCO₃. The amounts of Co, Cu, Ni and Mn show negative correlations with the calcium carbonate content. Pb and Co are noticeably correlated with Mn.     

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.     

Nitrate contamination in irrigation groundwater,Isfahan, Iran

Groundwater is one of the major sources of water in Isfahan. Efficient management of these resources requires a good understanding of its status. This paper focuses on the hydrochemistry and also it wants to assess the nitrate concentration in irrigation groundwater of Isfahan suburb. All the groundwater samples are grouped into three categories, including Na-Cl + Ca-Cl (63 %), Na-SO₄ + Ca-SO₄ (23 %) and Ca-HCO₃ (14 %). According to the EC and SAR, the most dominant classes are C3S1, C4S2 and C4S3. 55 % of samples indicate very high salinity and medium to very high alkalinity that is not suitable for irrigation. 84 % of the groundwater samples show nitrate contents higher than HAV (13 mg l^?), while more than 25 % exceeded the maximum contamination level (44.27 mg l^?) according to EPA regulations. The horizontal and vertical distribution patterns of nitrate in groundwater samples show a surficial origin for nitrate contamination. The high nitrate content can be attributed to the agricultural activities along with domestic sewage and industrial wastewaters in populated area. Based on results, using high nitrate groundwater for irrigation can minimize the requirement for inorganic fertilizers and reduce the cost of cultivation and nitrate contamination.