Ultra-trace determination of arsenic species in environmental waters,food and biological samples using a modified aluminum oxide nanoparticle sorbent and AAS detection after multivariate optimization

We describe a simple and efficient method for solid phase extraction and speciation of trace quantities of arsenic. It is based on the use of functionalized aluminum oxide nanoparticles and does not require any oxidation or reduction steps. The experimental parameters affecting extraction and quantitation were optimized using fractional factorial design methods. Adsorbed arsenic was eluted from the sorbent with 1 M hydrochloric acid and determined by graphite furnace atomic absorption spectrometry. Preconcentration factors up to 750 were achieved depending on the sample volume. Studies on potential interferences by various anions and cations showed the method to be highly selective. Under optimum conditions, the calibration plots are linear in the 5.0 to 280 ng L^?1 and 8.0 to 260 ng L^?1 concentration ranges for As(III) and total arsenic, respectively. The detection limits (calculated for S/N ratios of 3) are 1.81 and 1.97 ng L^?1 for As(III) and total arsenic, respectively. The method was successfully applied to the determination and speciation of arsenic in (spiked) environmental, food and biological samples and gave good recoveries. The method was validated using a certified geological reference material.

Novel functionalized Al₂O₃ nanoparticles were synthesized and used for speciation and determination of arsenic in different samples. The experimental variables were optimized using fractional factorial design that can save time and operational costs.