The Application of Expectation and Standard Deviation Calculations in the Evaluation of Dissolved Arsenic in the Pu River, Liaoning Province, Northeastern China

Bull Environ Contam Toxicol. 2019 Jan;102(1):84-91. doi: 10.1007/s00128-018-2503-5. Epub 2018 Nov 26.

Abstract

Water samples were collected from the Pu River in 2017 to research the distribution and accumulation characteristics of dissolved arsenic. We mainly built three types of expectation and standard deviation calculations corresponding to discrete, weighted and continuous random variables. The continuous expectation and standard deviation calculations are defined based on the concentration function and average formula, and the weighted expectation and standard deviation calculations are defined based on the relationship between the concentration and distance. The results indicate that the discrete expectation (1.8351 [Formula: see text]/L) and standard deviation (0.6410 [Formula: see text]/L) describe the average level and the deviation degree, respectively, of dissolved arsenic, and the continuous expectation (1.8684 [Formula: see text]/L) and standard deviation (0.5375 [Formula: see text]/L) mainly describe the average level and the dispersion degree, respectively, of dissolved arsenic after its accumulation. The weighted expectation (1.2997 [Formula: see text]/L) and standard deviation (0.2816 [Formula: see text]/L) reflect the average level and the dispersion degree, respectively, of dissolved arsenic and reveal the quantitative relationship between the concentration of dissolved arsenic and distance. The combination of the three types of expectation and standard deviation calculations and the concentration function may comprehensively describe the distribution and accumulation characteristics of dissolved arsenic, which can provide a theoretical foundation for guiding the reduction of arsenic pollution in the Pu River.

Keywords: Arsenic; Concentration function; Expectation; Pu River; Standard deviation.

MeSH terms

  • Arsenic / analysis*
  • China
  • Environmental Monitoring
  • Models, Theoretical
  • Rivers / chemistry*
  • Water Pollutants, Chemical / analysis*

Substances

  • Water Pollutants, Chemical
  • Arsenic