Characteristics and source-pathway of microplastics in freshwater system of China: A review.

China plays a key role in global plastic production, consumption and disposal, which arouses growing concern about microplastics (MPs) contamination in Chinese freshwater systems. However, few reviews have discussed the characteristics of MP pollution in whole freshwater systems at a national scale. In this review, we summarized the characteristics, sources and transport pathways of MPs in Chinese freshwater systems including surface water and sediment. Results showed that current research mainly focused on the middle and lower reaches of the Yangtze River and its tributaries, as well as lakes and reservoirs along the Yangtze River. Large-scale reservoirs, rivers and lakes located in densely populated areas usually showed higher abundances of MPs. The majority of MPs in Chinese surface water and sediment mainly consisted of polyethylene and polypropylene, and the most common morphologies were fibers and fragments. To identify the sources and pathways, we introduced the source-sink-pathway model, and found that sewage system, farmland and aquaculture area were the three most prevalent sinks in freshwater systems in China. The source-sink-pathway model will help to further identify the migration of MPs from sources to freshwater systems.

An online surface water COD measurement method based on multi-source spectral feature-level fusion.

To overcome the shortcomings of single or multi-wavelength ultraviolet-visible (UV-Vis) absorbance spectroscopic methods, fluorescence spectroscopic or wet chemistry methods for chemical oxygen demand (COD) measurement, an online detection method based on multi-source spectral feature-level fusion was developed and evaluated. In this method, UV-Vis absorbance spectra (deuterium-halogen lamp as light source) and fluorescence emission spectra (405 nm wavelength laser as excitation source) were measured online by a spectrophotometer (PG2000-Pro-Ex, Ocean Optics). Discrete wavelet transform (DWT) and a successive projections algorithm (SPA) were utilized to realize signal de-noising and feature extraction on the two types of spectra, respectively. Feature-level fusion and least-square support vector regression (LS-SVR) were used to establish the COD measurement model. Through comparison of experiments and results, it is shown that the proposed method has a good performance on both noise tolerance and measurement accuracy.

A UV-visible absorption spectrum denoising method based on EEMD and an improved universal threshold filter.

When using ultraviolet-visible spectroscopy (UV-visible spectroscopy) to detect water quality parameters, the measured absorption spectrum signal often contains a lot of interference information. Therefore, denoising is extremely important in spectrum data processing and analysis, which directly affects the subsequent quantitative analysis and information mining. Choosing an appropriate denoising method is key to improve the spectral analysis accuracy and promote the spectral analysis ability. In this paper, a new UV-visible absorption spectrum denoising method is proposed: a denoising method based on ensemble empirical mode decomposition (EEMD) and improved universal threshold filtering (EEMD-based method). The noisy UV-visible absorption spectrum signal is firstly decomposed into a finite set of band limited signals called intrinsic mode functions (IMFs) via EEMD. Spearman's rank correlation coefficient (Spearman's rho) is then used as a criterion for the IMFs dominated by noise or useful signals, and the improved universal threshold filtering method is applied to the noise dominant IMFs to eliminate the noise. Finally, the denoised UV-visible absorption spectrum signal is reconstructed. In order to discuss the effectiveness of the EEMD-based denoising method proposed in this paper, we compare it with various wavelet-based threshold denoising methods. Both methods have been implemented on synthetic signals with diverse waveforms ('Blocks', 'Bumps' and 'Heavy sine'). It is demonstrated that the proposed method outperforms the wavelet-based methods. Then, the measured UV-visible absorption spectra with different SNR were denoised by the wavelet and proposed methods. The method proposed also performs well in the spectrum denoising experiment.

Process service quality evaluation based on Dempster-Shafer theory and support vector machine.

Human involvement influences traditional service quality evaluations, which triggers an evaluation's low accuracy, poor reliability and less impressive predictability. This paper proposes a method by employing a support vector machine (SVM) and Dempster-Shafer evidence theory to evaluate the service quality of a production process by handling a high number of input features with a low sampling data set, which is called SVMs-DS. Features that can affect production quality are extracted by a large number of sensors. Preprocessing steps such as feature simplification and normalization are reduced. Based on three individual SVM models, the basic probability assignments (BPAs) are constructed, which can help the evaluation in a qualitative and quantitative way. The process service quality evaluation results are validated by the Dempster rules; the decision threshold to resolve conflicting results is generated from three SVM models. A case study is presented to demonstrate the effectiveness of the SVMs-DS method.

Chromium (VI) reduction in aqueous solutions by Fe3O4-stabilized Fe0 nanoparticles.

This paper describes the use of highly reactive magnetite (Fe(3)O(4)) nanoparticles-stabilized Fe(0) nanocomposites for the reduction and mitigation of hexavalent chromium Cr(VI) species in aqueous solutions. Higher proportions of Fe(3)O(4) in the nanocomposites could increase the rate of Cr(VI) reduction. In the absence of magnetite, the Cr(VI) mitigation rate was just 51.4% after 60 min of reaction, while with an initial Fe(3)O(4) mass loading of 3 g l(-1), the Cr(VI) mitigation rate was nearly 100% after 60 min. The optimal ratio of Fe(3)O(4):Fe(0) for the mitigation of Cr(VI) was found to be 40:1. Otherwise, solution pHs significantly affected the rate of Cr(VI) reduction, with reactions occurring more rapidly under acidic or neutral than basic conditions. It is hypothesized that the high efficiency of the Fe(3)O(4) nanoparticles-stabilized Fe(0) nanocomposites for Cr(VI) reduction was a direct result of the attachment of Fe(0) nanoparticles to the surface of magnetite, which prevents the aggregation of nano-Fe(0), moreover, the electron transfer during the reduction process most likely takes place via Fe(0) nanoparticles that are located at the magnetite octahedral sites, which are versatile redox centers as they can accommodate both Fe(III) and Fe(II), and this will promote the reduction of Cr(VI). Cr(VI) reduction is coupled with nano-Fe(0) oxidation. Nano-Fe(0) particles are located at the magnetite octahedral sites. Ions of Fe(II) and Fe(III) accommodated by magnetite octahedral sites are products of nano-Fe(0) oxidation. Therefore, Cr(VI) reduction is mediated either by nano-Fe(0) (direct reduction) or Fe(II) species (indirect reduction). Additionally, catalytic Cr(VI) reduction by molecular H(2) (or atomic H) is possible.