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UV photochemical hydride generation using ZnO nanoparticles for arsenic speciation in waters, sediments, and soils samples

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Abstract

The environmental disasters that occurred due to the leakage of mining waste in Mariana-MG (2015) and Brumadinho-MG (2019), located in Brazil, attracted the attention of the scientific community. This designated efforts to investigate the environmental consequences of toxic waste in the affected ecosystem. Therefore, a simple, easily executed and accessible method was presented for arsenic speciation [As(III), As(V), and DMA]. Using an atomic absorption spectrometer coupled to the hydride generation system, the heterogeneous photocatalysis was applied in the reduction of As(V) and DMA to As(III). After the optimization, a calibration curve was constructed, with LODs equivalent to 3.20 μg L−1 As(III), 3.86 μg L−1 As(V), and 6.68 μg L−1 DMA. When applying the method for quantification in environmental samples, a concentration of up to 103.1 ± 9.4 μg L−1 As(V) was determined for surface water samples. The soil samples, 84.1 ± 3.6 μg L−1 As(III) and 112.4 ± 9.9 μg L−1 As(V) were quantified, proving the contamination of the ecosystems impacted by the environmental disasters. We proceeded the study through an addition/recovery method with samples of water, soil, and sediments (collected from impacted environments). Recovery values were equivalent to 99.0% for As(III), 93.8% for As(V), and 99.2% for DMA.

Photocatalytic reduction mechanism of As(V) and DMA to As(III) by heterogeneous photocatalysis.

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Funding

The authors received financial support from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and Fundação de Amparo a Pesquisa do Estado de Minas Gerais (FAPEMIG), and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES - 88881.068088/2014-01).

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Correspondence to Ailton José Moreira.

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Pinheiro, B.S., Moreira, A.J., Gimenes, L.L.S. et al. UV photochemical hydride generation using ZnO nanoparticles for arsenic speciation in waters, sediments, and soils samples. Environ Monit Assess 192, 331 (2020). https://doi.org/10.1007/s10661-020-08316-z

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