Determination of arsenic chemical species in rice grains using high-performance liquid chromatography coupled to hydride generator with atomic fluorescence detector (HPLC-HG-AFS)

Unravelling arsenic bioavailability in floodplain soils impacted by mining activities

Gold mining not only introduces mercury (Hg) contamination to soils but also facilitates the mobilization of other toxic substances, including arsenic (As). This study assessed the total content, chemical species, and bioavailable fraction of As in surface soils impacted by mining residues during frequent flooding. Analysis of 207 soil samples across the floodplain region of La Mojana, Colombia, screened to 2 mm with polyethylene mesh, revealed significant correlations (p < 0.05) between inorganic As, the residual phase, sulphur (S), iron (Fe), manganese (Mn), and aluminum (Al), indicating associations with sulfides and oxyhydroxides of Fe and Mn. The origin of toxicity was linked to suspended materials transported by rivers during flooding in areas with intense mining activity. Sites with better oxidizing conditions exhibited a higher presence of phases associated with amorphous and crystalline oxides in non-flooded areas. Although the bioavailable fraction was minimal in flooded sites, reducing conditions facilitated As mobility, resulting in higher concentrations in deeper soil layers, particularly as As(III). The contamination factor (CF) ranged from 1.3 to 11.1, and the geochemical index (Igeo) ranged from -0.2 to 2.9, indicating a moderate to high As contamination level in soils. This poses potential health risks, considering the agricultural use of these soils.

Brevibacterium sp. strain CS2: A potential candidate for arsenic bioremediation from industrial wastewater

A multiple metal-resistant Brevibacterium sp. strain CS2, isolated from an industrial wastewater, resisted arsenate and arsenate upto 280 and 40 mM. The order of resistance against multiple metals was Arsenate > Arsenite > Selenium = Cobalt > Lead = Nickel > Cadmium = Chromium = Mercury. The bacterium was characterized as per morphological and biochemical characteristics at optimum conditions (37 ℃ and 7 pH). The appearance of brownish color precipitation was due to the interaction of silver nitrate confirming its oxidizing ability against arsenic. The strain showed arsenic processing ability at different temperatures, pH, and initial arsenic concentration which was 37% after 72 h and 48% after 96 h of incubation at optimum conditions with arsenite 250 mM/L (initial arsenic concentration). The maximum arsenic removal ability of strain CS2 was determined for 8 days, which was 32 and 46% in wastewater and distilled water, respectively. The heat-inactivated cells of the isolated strain showed a bioremediation efficiency (E) of 96% after 10 h. Genes cluster (9.6 kb) related to arsenite oxidation was found in Brevibacterium sp. strain CS2 after the genome analysis of isolated bacteria through illumine and nanopore sequencing technology. The arsenite oxidizing gene smaller subunit (aioB) on chromosomal DNA locus (Prokka_01508) was identified which plays a role in arsenite oxidation for energy metabolism. The presence of arsenic oxidizing genes and an efficient arsenic oxidizing potential of Brevibacterium sp. strain CS2 make it a potential candidate for green chemistry to eradicate arsenic from arsenic-contaminated wastewater.

3D-printed device for the kinetic determination of As(III) in groundwater samples by digital movie analysis

High concentrations of inorganic arsenic in groundwater for human consumption is a worldwide common problem. Particularly, the determination of As(III) becomes important, since this species is more toxic than organic, pentavalent and elemental arsenic forms. In this work, a 3D-printed device that included a 24-well microplate was developed to perform the colourimetric kinetic determination of arsenic (III) by digital movie analysis. A smartphone camera attached to the device was used to take the movie during the process where As(III) inhibited the decolourization of methyl orange. The movie images were subsequently transformed from RGB to YIQ space to obtain a new analytical parameter called "d", which was related to the chrominance of the image. Then, this parameter allowed the determination of the inhibition time of reaction (t_in), which was linearly correlated with the concentration of As(III). A linear calibration curve (R = 0.9995) in the range from 5 μg L^-1 to 200 μg L^-1 was obtained. The method was precise (RSD = 1.2%), and the limits of detection (LOD) and quantification (LOQ) were 1.47 μg L^-1 and 4.44 μg L^-1, respectively. These values were lower than the limit established by the World Health Organization for total arsenic in drinking water (10 μg L^-1). The accuracy of the method was assessed by a recovery study with optimal results (94.3%-104.0%). Additionally, the Analytical GREEnness metric approach was applied, obtaining a score 1.7 times higher than previously published works. The method is simple, portable and low-cost, being in compliance with various principles of green analytical chemistry.

Arsenic Exposure via Contaminated Water and Food Sources

Arsenic poisoning constitutes a major threat to humans, causing various health problems. Almost everywhere across the world certain “hotspots” have been detected, putting in danger the local populations, due to the potential consumption of water or food contaminated with elevated concentrations of arsenic. According to the relevant studies, Asia shows the highest percentage of significantly contaminated sites, followed by North America, Europe, Africa, South America and Oceania. The presence of arsenic in ecosystems can originate from several natural or anthropogenic activities. Arsenic can be then gradually accumulated in different food sources, such as vegetables, rice and other crops, but also in seafood, etc., and in water sources (mainly in groundwater, but also to a lesser extent in surface water), potentially used as drinking-water supplies, provoking their contamination and therefore potential health problems to the consumers. This review reports the major areas worldwide that present elevated arsenic concentrations in food and water sources. Furthermore, it also discusses the sources of arsenic contamination at these sites, as well as selected treatment technologies, aiming to remove this pollutant mainly from the contaminated waters and thus the reduction and prevention of population towards arsenic exposure.

A simple and cost-effective smartphone-based digital imaging device for the quantification of selected heavy metals in Thai rice

This paper describes smartphone-based digital imaging equipment for lead, cadmium, copper, and zinc determination in Thai rice that is both convenient and cost-effective. This smartphone-based digital imaging device has a built-in light control box made of poly(lactic acid) or PLA, a compostable and biodegradable plastic, with a light control circuit box underneath that uses a single white light-emitting diode (LED) lamp and takes photos at only 20 lux, which is very low but clearly captures the color of heavy metal complexes. In the present study, the dithizone ligand in different buffers is employed to produce a specific color solution for each heavy metal. According to the output from the free Color Name application, the concentration of heavy metals is proportional to the intensity of the resulting red color. A linear range of 0.1-1.0 mg L^-1 was obtained. The lower detection limit was determined to be between 0.01 and 0.05 mg L^-1, whereas the quantification limit was in the range from 0.04 to 0.15 mg L^-1. The intra-day precision (%RSD, n = 5) was 0.4-0.8 with high consistency, while the inter-day precision (%RSD, n = 5) was 0.5-0.8 with good efficacy. The recovery rate for heavy metals added to samples of Thai rice ranged from 99.4 to 105.5 percent. Heavy metals were detected in a variety of rice samples utilizing the smartphone-based digital imaging equipment, with acceptable accuracy when compared to atomic absorption spectrophotometric data using a paired t-test. This smartphone-based digital imaging is efficient, accessible, and cost-effective, and it provides a viable alternative to existing heavy metal detection methods in Thai rice.