Quantitative assessment of variability and uncertainty of hazardous trace element (cd, cr, and pb) contents in chinese coals by using bootstrap simulation

Abstract

The quantitative measurements of uncertainties regarding the contents of hazardous trace elements (HTEs) serve as a basis for better assessment of the geochemistry and mineralogical characteristics of coals and their environmental impacts. In this paper, by using bootstrap simulation methodology, a quantitative procedure was demonstrated to characterize the variability and uncertainty of HTE (Cd, Cr, and Pb) contents in Chinese coals, which were specified by 27 different provinces and mining areas. Original data samples for Cd, Cr, and Pb contents in Chinese coals were compiled and summarized from the results reported in published literature. Sampling distributions for uncertainties in statistics such as the mean, median, and confidence interval were calculated. The national average contents were estimated at approximately 0.61 μg/g for Cd, 30.37 μg/g for Cr, and 23.04 μg/g for Pb. The ranges of uncertainties for bootstrap samples of national HTE contents were nearly symmetrical, and the ranges of the 95% confidence interval for the arithmetic mean were relatively small, with relative uncertainties of -16.39% to +21.31% for Cd, -10.11% to +11.72% for Cr, and -8.55% to +8.64% for Pb. This shows that the arithmetic mean contents of HTEs in Chinese coals are higher in southern provinces than those in northern provinces, obviously differing because of different coal basins. The high values of HTE contents occur in provinces such as Sichuan, Chongqing, Yunnan, Hubei, and Guangxi. Provinces with low contents are located in northwestern China and include Xinjiang, Qinghai, Gansu, and Inner Mongolia; this can be mainly attributed to the medium moisture content, low ash, and low sulfur content in coals. Several provinces with high HTE contents such as Ningxia for Cd, Guangdong for Cr, and Shaanxi for Pb may be associated with the representativeness of the original data samples. © 2011 Air & Waste Management Association.