Application of GIS for the identification and demarcation of selective heavy metal concentrations in the urban groundwater

Groundwater is the most appropriate and widely used source of drinking water, which is increasingly threatened by pollution from industrial and agricultural activities. To check the severity of the problem, 156 groundwater samples were collected from various depths (60-110 ft) of 52 different localities in Faisalabad city, the third largest metropolis in Pakistan, and analyzed for the metals (Zn, Cu, Cd, Ni, Pb, Mn and Fe) concentration in 2009. Quantification was done by using Flame Atomic Absorption Spectrophotometer technique and the results were compared with WHO standards for drinking water quality. Results showed that the levels of Cu, Mn and Fe were below the WHO standards while the concentrations of Zn, Cd, Ni and Pb were above the recommended levels of safe drinking water. Correlation analysis among the occurrence of these heavy metals revealed a highly significant and positive correlation of Mn with Zn and Fe. A significant and positive correlation of Cd was also found with Cu and groundwater depth showing that there is strong association between Cu-Cd pair and that the Cd concentration varies with depth of groundwater in the study area. Regional patterns of heavy metals occurrence were mapped using Geographical Information System (GIS) for the identification and demarcation of risk areas. The concentration maps may be used by policymakers of the city to mitigate groundwater pollution.     

A new developed approach for the prediction of ground vibration using a hybrid PSO-optimized ANFIS-based model

Ground vibration is one of the common environmental effects of blasting operation in mining industry, and it may cause damage to the nearby structures and the surrounding residents. So, precise estimation of blast-produced ground vibration is necessary to identify blast-safety area and also to minimize environmental effects. In this research, a hybrid of adaptive neuro-fuzzy inference system (ANFIS) optimized by particle swarm optimization (PSO) was proposed to predict blast-produced ground vibration in Pengerang granite quarry, Malaysia. For this goal, 81 blasting were investigated, and the values of peak particle velocity, distance from the blast-face and maximum charge per delay were precisely measured. To demonstrate the performance of the hybrid PSO–ANFIS, ANFIS, and United States Bureau of Mines empirical models were also developed. Comparison of the predictive models was demonstrated that the PSO–ANFIS model [with root-mean-square error (RMSE) 0.48 and coefficient of determination (R ²) of 0.984] performed better than the ANFIS with RMSE of?1.61 and R ² of 0.965. The mentioned results prove the superiority of the newly developed PSO–ANFIS model in estimating blast-produced ground vibrations.     

Distribution of gold in different size fractions of stream sediments as a guide to bedrock gold mineralisation along the Shyok Suture Zone and adjacent areas of the Kohistan Island Arc,Pakistan

Arabian Journal of Geosciences - This paper describes a new exploration methodology using stream sediments in remote and glaciated regions of northern Pakistan. Gold concentrations in 268 samples...     

New impact equation using barrier Froude number for the design of dual rigid barriers against debris flows

Landslides - In the design of multiple rigid barriers, the height of the first barrier governs the impact dynamics of debris flow on the next barrier in a channel. However, current design...     

The evolution of an electrical fittings industrial cluster in Pakistan

GeoJournal - This study provides an evolution process of electrical fittings industrial cluster in Pakistan by using two rounds of survey dataset (2008 and 2017) taken from the electrical fittings...     

Kalman filter estimation model in flood forecasting

Elementary precipitation and runoff estimation problems associated with hydrologic data collection networks are formulated in conjunction with the Kalman Filter Estimation Model. Examples involve the estimation of runoff using data from a single precipitation station and also from a number of precipitation stations. The formulations demonstrate the role of state-space, measurement, and estimation equations of the Kalman Filter Model in flood forecasting. To facilitate the formulation, the unit hydrograph concept and antecedent precipitation index is adopted in the estimation model. The methodology is then applied to estimate various flood events in the Carnation Creek of British Columbia.     

Temporal changes of soft-bottom zoobenthic communities in and around Alsancak Harbor (Izmir Bay, Aegean Sea), with special attention to the autecology of exotic species

Temporal and spatial variation in soft‐bottom benthic communities following recovery from a pollution episode were studied between January and September 2004 in and around Alsancak Harbor, located in the polluted part of Izmir Bay (Aegean Sea, eastern Mediterranean). Samples were collected at seven stations by van Veen grab. Three additional stations were sampled by means of a beam trawl to take into account large mobile animals and for a better estimate of the local biodiversity. A total of 231 species belonging to 10 zoobenthic groups were found. Polychaetes contributed 90% of the total faunal populations and mollusks 87% of the total biomass in the area. Community parameters varied significantly among stations and sampling periods; number of species ranged from 2 to 79 per 0.1 m² grab sample; density from 20 to 81,720 ind·m^?2; biomass from 0.1 to 4190 g·m^?2; Shannon–Wiener diversity index (log₂ base) from 0.4 to 4.4; and Pielou's evenness index from 0.11 to 1.0. Collections indicate that a number of species, including those sensitive to pollution, have colonized the area where azoic conditions had been previously reported. A total of six exotic species, Streblospio gynobranchiata, Polydora cornuta, Hydroides dianthus, Hydroides elegans, Anadara demiri and Fulvia fragilis, probably transferred to the area via ballast water or hull fouling, dominated soft or hard substrata in and near Alsancak Harbor. The first two species accounted for more than 70% of the total population in the area, while A. demiri contributed the most to the biomass (93%, at station 7).     

Determination of Free Nickel Ion Concentrations Using the Ion Exchange Technique: Application to Aqueous Mining and Municipal Effluents

Free metal ion concentration is generally considered a useful indicator of a metal’s bioavailability and ecotoxicity to aquatic biota. This article reports the speciation of nickel in mining and municipal effluents from Sudbury (Ontario, Canada), and also in model solutions containing a fully characterized laurentian fulvic acid (LFA) at environmentally relevant concentrations. A column ion exchange technique (IET) using a cation exchange resin (Dowex 50W-X8) was applied to determine free nickel ion concentrations. In model solutions, reasonable correlation was found between the predictions of an equilibrium-based computer speciation code, Windermere Humic Aqueous Model (WHAM) VI, and the results obtained by IET at low nickel-to-fulvic acid ratios. However at higher mole ratios, the WHAM VI predicted higher free nickel ion concentrations than IET. Only three out of six effluent samples showed reasonable agreement between the IET and the WHAM VI results, indicating the need for further development of IET for application to effluent waters.