[Determination of anilines in environmental water samples by simultaneous derivatization and ultrasound assisted emulsification microextraction combined with gas chromatography-flame ionization detectors].

This research demonstrated a new method, simultaneous derivatization and ultrasound assisted emulsification microextraction combined with gas chromatography-flame ionization detector (SD-USAEME-GC-FID), for the determination of anilines in environmental water samples. In this study, several factors, such as the volume of butylchloroformate (as derivatization agent/ extraction solvent), ultrasonication time, solution pH, salt addition, and centrifuging time and speed, were optimized in order to obtain good method performance. As a result, under the optimal conditions, the method showed good linearity in the concentration range of 6-60 000 μg x L(-1) with correlation coefficients (R2) ranging from 0.

Transformation of heavy metal speciation during sludge drying: mechanistic insights.

Speciation can fundamentally affect on the stability and toxicity of heavy metals in sludge from wastewater treatment plants. This research investigated the speciation of heavy metals in sludge from both municipal and industrial sources, and metal speciation change as a result of drying process to reduce sludge volume. The changes in sludge properties including sludge moisture content, temperature, density, and electrical conductivity were also monitored to provide insights into the mechanisms causing the change in heavy metal speciation.

[High precision all-reflection Fourier transform imaging spectrometer spectral calibration using homogeneous broadening of the wave number model].

All-reflection Fourier transform imaging spectrometer (ARFTIS) is a novel imaging spectrometer. The specialty is not only high spectrum resolution, but also wide band and non-chromatism. It is good for remote sensing field of wide band imaging.

[Identification of cucumber disease using hyperspectral imaging and discriminate analysis].

Hyperspectral imaging (400-720 nm) and discriminate analysis were investigated for the detection of normal and diseased cucumber leaf samples with powdery mildew (Sphaerotheca fuliginea), angular leaf spot (Pseudomopnas syringae), downy mildew (Pseudoperonospora cubensis), and brown spot (Corynespora cassiicola). A hyperspectral imaging system was es tablished to acquire and pre-process leaf images, as well as to extract leaf spectral properties. Owing to the complexity of the original spectral data, stepwise discriminate and canonical discriminate were executed to reduce the numerous spectral information, in order to decrease the amount of calculation and improve the accuracy.