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The current study investigates the water quality parameters of drinking water resources in District Neelam (DNLM), Azad Jammu & Kashmir (AJK), Northwestern Pakistan. The studied area has been recently reported with many waterborne diseases, which probed this analytical study. The samples were aseptically collected from springs, taps, and surface water bodies. The water quality parameters, such as physical, microbiological, anions, and heavy metals, were tested. Results showed that the electrical conductance (EC) and total dissolved solids (TDS), were 974.60 µS/cm and 912.10 mg/L, respectively, exacerbating the quality of drinking water in DNLM. For microbial water testing, we used 3M-Petrifilms as a detection source, which could separate coliform bacteria from E. coli by creating unique surface chromophores. Out of sixty collected samples, 76% had bacterial contamination. Nitrite, nitrate, and phosphate (9.8, 15.0, and 15.1 mg/L), were also surpassing the safe limits of the World Health Organization (WHO) standards for water quality measurement. The heavy metals, i.e., As, Cr, Cu, and Pb were also tested in current analysis. Pb and Cr (0.04 mg/L and 0.06 mg/L) exceeded from safe drinking water guidelines of the WHO and more than 50% of the collected samples had Pb as a major water pollutant in DNLM. Poor waste management, open sludge discharge, lack of municipality measures, and mineral leaching into the freshwaters of DNLM due to mining and metal extraction processes were the main sources of water pollution in the region. The inorganic pollutants were responsible for the sudden rise of different malignancies and other fatal diseases (vital organ failures and reproductive disorders) in the region, which has not been reported in the past. The current investigation yielded useful baseline data of the drinking water reserves of NW Pakistan that could help to develop techniques for the mitigation of water pollutants present in the region. [ABSTRACT FROM AUTHOR]

To minimize catastrophic impacts of earthquakes, many researchers have directed their efforts to developing novel computational techniques and models that forecast natural disasters based upon earthquake catalogues, anomalies in the ionosphere, and radon time series databases, etc. In this article, we propose a methodology that categorizes the soil radon gas (SRG) concentration into seismically active and non-active time series by taking the advantage of a stacking ensemble approach and utilizing an automatic anomaly indication function as a post-processing technique. The main idea behind the proposed methodology is of two layers. The first layer uses a stacking ensemble-based approach that incorporates three learners, i.e. a generalized linear model, linear regression and K-nearest neighbors, to train on seismically active and inactive periods to predict SRG concentration. These predictions are then combined with the labeled anomaly data to train a meta-learner, i.e., support vector machine with a radial kernel, that categorizes the series into active and non-active radon time series data. In the second layer, these classifications are then passed to an automatic anomaly indication function that further labels the time series in a group of readings where the level of received indications is greater than or equal to the indication factor. Radon time series (RTS) data has been recorded over a fault line present in Muzaffarabad, a city in the Pakistan territory of Kashmir, ranging from 1 March 2017 to 28 February 2018. Four seismic events occurred during the study period. The conclusion of the study reveals that the proposed methodology accurately locates the anomaly in the RTS data at different window sizes, i.e. with respect to individual days. The evaluation is based purely on the classification after processing of RTS data by both layers of the proposed methodology. [ABSTRACT FROM AUTHOR]

The areas pertaining the hydrocarbon and non-hydrocarbon in the Attock district of Pakistan were selected for the measurement of indoor radon concentration. This area was not previously surveyed for such kind of study. CR-39-based NRPB radon dosimeters were utilized for this study. Attock city, Hassan Abdal and Jand belong to the non-hydrocarbon areas, where radon concentration was measured to be 57 ± 11, 58 ± 11 and 56 ± 11 Bq m−3, respectively. The hydrocarbon pertaining areas consist of Toot and Meyal villages, the concentration of radon was found to be 48 ± 10 and 37 ± 8 Bq m−3, respectively. The cap rock in the geological structures of the hydrocarbon areas may have restricted the migration of underneath radon. The annual effective dose in the studied locations was estimated to be 1.28 ± 0.25 mSv y−1, which is less than the action level recommended by the ICRP. Estimated excess lung cancer risks per million persons per year in the surveyed area show higher values 96, 69, 32–110 and 41–124 as compared to the world average reported by the BEIR-IV (1988), ICRP (1987), US-EPA (1986) and UNSCEAR (1993) models, respectively. Present results could be used as a reference for any future studies in Pakistan for the problems of radon emissions with respect to the types of rocks. [ABSTRACT FROM AUTHOR]

With many advantages over well-established methods, laser induced breakdown spectroscopy (LIBS) has emerged as a useful analytical technique for the compositional analysis of multi-elemental geological materials. In this study, LIBS was employed for qualitative and quantitative analysis of a rare mineral, astrophyllite, bearing precious elements of industrial and technological interest. The experiment was carried out using second harmonic generation of Nd:YAG laser of pulse width 5 ns and repetition rate of 10 Hz. Microplasma was produced by focusing laser beam on an astrophyllite target, and optical emissions from the generated plasma were recorded in the spectral range of 200–720 nm with the help of a LIBS2000+ detection system. On analyzing the optical spectra, existence of 15 elements in astrophyllite target were revealed. These elements include: Ti, W, Ag, Al, Ba, Ca, Cr, Cu, Fe, Li, Mg, Na, Ni, Si and H. For quantification, calibration-free method was used. Only ten elements, namely Ti, W, Fe, Cr, Cu, Ca, Mg, Ni, Si and Al, were quantified with relative weight concentrations of 55.39%, 18.79%, 18.30%, 4.05%, 2.66, 0.43%, 0.18%, 0.12%, 0.06% and 0.02%, respectively. To benchmark these results, XRF analysis was performed, which confirmed the presence of all the elements detected in the optical spectrum of the sample, except for Na, Li, and H. The concentrations of these ten elements as measured by XRF were in reasonable agreement, especially for the major elements. The presence of a significant amount of Ti and W in an astrophyllite sample, found in Pakistan, highlights the economic value of this mineral. This study may be of further interest in commissioning LIBS technology for exploration of minerals in the region. [ABSTRACT FROM AUTHOR]