Highly contaminated groundwater, with arsenic (As) and fluoride (F(-)) concentrations of up to 2.4 and 22.8 mg/L, respectively, has been traced to anthropogenic inputs to the soil. In the present study, samples collected from the soil surface and sediments from the most heavily polluted area of Punjab were analyzed to determine the F(-) and As distribution in the soil. The surface soils mainly comprise permeable aeolian sediment on a Pleistocene terrace and layers of sand and silt on an alluvial flood plain. Although the alluvial sediments contain low levels of F, the terrace soils contain high concentrations of soluble F(-) (maximum, 16 mg/kg; mean, 4 mg/kg; pH > 8.0). Three anthropogenic sources were identified as fertilizers, combusted coal, and industrial waste, with phosphate fertilizer being the most significance source of F(-) accumulated in the soil. The mean concentration of As in the surface soil samples was 10.2 mg/kg, with the highest concentration being 35 mg/kg. The presence of high levels of As in the surface soil implies the contribution of air pollutants derived from coal combustion and the use of fertilizers. Intensive mineral weathering under oxidizing conditions produces highly alkaline water that dissolves the F(-) and As adsorbed on the soil, thus releasing it into the local groundwater.

No abstract

Lehmer defined a measure depending on numbers beta_i used in a Machin-like formula for pi. When the beta_i are integers, Lehmer's measure can be used to determine the computational efficiency of the given Machin-like formula for pi. However, because the computations are complicated, it is unclear if Lehmer's measure applies when one or more of the beta_i are rational. In this article, we develop a new algorithm for a two-term Machin-like formula for pi as an example of the unconditional applicability of Lehmer's measure. This approach does not involve any irrational numbers and may allow calculating pi rapidly by the Newton-Raphson iteration method for the tangent function.

In this work we show how to perform a rapid computation of the Voigt/complex error over a single domain by vectorized interpolation. This approach enables us to cover the entire set of the parameters x, y ∈ R required for the HITRAN-based spectroscopic applications. The computational test reveals that within domains x ∈ [0, 15] ∩ y ∈ 10 −8 , 15 and x ∈ [0, 50000] ∩ y ≥ 10 −8 our algorithmic implementation is faster in computation by factors of about 8 and 3, respectively, as compared to the fastest known C/C++ code for the Voigt/complex error function. A rapid MATLAB code is presented.

No abstract