ALBERT

Description: Rural runoff with abundant nutrients has become a great threat to aquatic environment. Hence, more and more attention has been focused on nutrients removal. In this study, an improved aerobic/anaerobic/aerobic three-stage water spinach constructed wetland (O-A-O-CW) was used to improve the removal of nitrogen and phosphorus of rural runoff. The removal rate of the target pollutants in O-A-O-CW was compared with the common matrix flow wetland as well as the no-plant wetland. The results showed that the O-A-O-CW significantly increased the chemical oxygen demand, total phosphorus, ammonium-nitrogen, nitrate, and total nitrogen removal rate, and the corresponding removal rate was 55.85%, 81.70%, 76.64%, 89.78%, and 67.68%, respectively. Moreover, the best hydraulic condition of the wetland, including hydraulic retention time and hydraulic loading, was determined, which were 2 days and 0.45 m3·m−2·day−1, respectively. Furthermore, the removal mechanism of the constructed wetland was thoroughly studied, which included the adsorption of nitrogen and phosphorus by the matrix and water spinach, and the nitrification and denitrification by the bacteria. The results demonstrated that the mechanisms of nitrogen removal in the new type wetland were principally by the nitrification and denitrification process. Additionally, adsorption and precipitation by the matrix are mainly responsible for phosphorus removal. These results suggested that the new O-A-O-CW can efficiently removal nutrients and enhance the water quality of the rural runoff.

Description: Fixed carbon content is an important factor in measuring the carbon content of gangue, which is important for monitoring the spontaneous combustion of gangue and reusing coal gangue resources. Although traditional measurement methods of fixed carbon content, such as chemical tests, can achieve high accuracy, meeting the actual needs of mines via these tests is difficult because the measurement process is time consuming and costly and requires professional input. In this paper, we obtained the thermal infrared spectrum of coal gangue and developed a new spectral index to achieve the automated quantification of fixed carbon content. Thermal infrared spectroscopy analyses of 42 gangue and three coal samples were performed using a Turbo FT thermal infrared spectrometer. Then, the ratio index (RI), difference index (DI) and normalized difference index (NDI) were defined based on the spectral characteristics. The correlation coefficient between the spectral index and the thermal infrared spectrum was calculated, and a regression model was established by selecting the optimal spectral DI. The model prediction results were verified by a ten times 5-fold cross-validation method. The results showed that the mean error of the proposed method is 5.00%, and the root mean square error is 6.70. For comparison, the fixed carbon content was further predicted by another four methods, according to the spectral depth H, spectral area A, the random forest and support vector machine algorithms. The predicted accuracy calculated by the proposed method was the best among the five methods. Therefore, this model can be applied to predict the fixed carbon content of coal gangue in coal mines and can help guide mine safety and environmental protection, and it presents the advantages of being economic, rapid and efficient.