ABSTRACT
TiO2 nanoparticles (TiO2-NPs) have a wide range of industrial applications (paintings, sunscreens, food and cosmetics) and is one of the most intensively used nanomaterials worldwide. Leaching from commercial products TiO2-NPs are predicted to significantly accumulate in wastewater sludges, which are then often used as soil amendment. In this work, sludge samples from four wastewater treatment plants of the Chihuahua State in Mexico were obtained during spring and summer (2017). A comprehensive characterization study was performed by X-ray based (laboratory and synchrotron) techniques and electron microscopy. Ti was detected in all sludge samples (1810-2760 mg/kg) mainly as TiO2 particles ranging from 40 nm up to hundreds of nm. Micro-XANES data was analyzed by principal component analysis and linear combination fitting enabling the identification of three predominant Ti species: anatase, rutile and ilmenite. Micro-XANES from the smaller Ti particles was predominantly anatase (68% + 32% rutile), suggesting these TiO2-NPs originate from paintings and cosmetics. TEM imaging confirmed the presence of nanoscale Ti with smooth surface morphologies resembling engineered TiO2-NPs. The size and crystalline phase of TiO2-NPs in the sludge from this region suggest increased reactivity and potential toxicity to agro-systems. Further studies should be dedicated to evaluating this.
ABSTRACT
Mining is a major source for metals and metalloids pollution, which could pose a risk for human health. In San Guillermo, Chihuahua, Mexico mining wastes are found adjacent to a residential area. A soil-surface sampling was performed, collecting 88 samples for arsenic determination by atomic absorption. Arsenic concentration data set was interpolated using the ArcGis models: inverse distance weighting (IDW), ordinary kriging (OK), and radial basis function (RBF). For method validation purposes, a set of the data was selected and two tests were performed (P1 and P2). In P1 the models were processed without the validation data; in P2 the validation data were removed one by one, models were processed every time that a data point was removed. An arsenic concentration range of 22.7 to 2190 mg/kg was reported. The 39% of data set was classified as contaminated soil and 61% as industrial land use. In P1 the method of interpolation with the lowest RMSE was RBF (0.80), the highest coefficient of E was RBF (46.25), and the highest Ceff value was with RBF (0.48). In P2 the method with the lowest RMSE was OK (0.76), the highest E value was 50.65 with OK, and the Ceff reported the highest value with OK (0.52). The high arsenic contamination in soil of the site indicates an abundant dispersion of this metalloid. Furthermore, the difference between the models was not very wide. The incorporation of more parameters would be of interest to observe the behavior of interpolation methods.
