In this study, preparation of Eichhornia crassipes stem biochar (ECSBC) was optimized and applied for the removal of Cd²⁺ from aqueous solution. To obtain the best adsorption capacity of ECSBC, the response surface methodology (RSM) was used to optimize the preparation conditions of ECSBC (OECSBC). The interactions among heating time (X₁), heating temperature (X₂) and heating rate (X₃) were designed by Box-Behnken Design (BBD) experiments. The software gave seventeen runs experiment within the optimal conditions towards two response variables (removal rate and adsorption capacity for Cd²⁺). The results showed that the mathematical model could fit the experimental data very well and the significance of the influence factors followed the order as heating temperature (X₂) > heating rate (X₃) > heating time (X₁), and the influence of interaction term is: X₁ and X₂ (heating time and heating temperature) > X₂ and X₃ (heating temperature and heating rate) > X₁ and X₃ (heating time and heating rate). Based on the analysis of variance and the method of numerical expected function, the optimal conditions were heating time of 2.42 h, heating temperature of 393 °C, and heating rate of 15.56 °C/min. Under the optimum conditions, the predicted the maximum removal rate and adsorption capacity were 85.2724% and 21.168 mg/g, respectively, and the experimental value of removal rate and adsorption capacity for Cd²⁺ were 80.70% and 20.175 mg/g, respectively, the deviation from the predicted value were 5.36% and 4.69%. The results confirmed that the RSM can optimize the preparation conditions of ECSBC, and the adsorption capacity of OECSB was improved.

The purpose of this work is to study the pyrolysis conditions of target biochar suitable for target heavy metal ion, to characterize the optimized target biochar, and to study the adsorption performance of biochar. With Cu²⁺ and Zn²⁺ as the target pollutants, the pyrolysis conditions involved in the preparation process as pyrolysis temperature, pyrolysis time, and heating rate were evaluated and optimized from Box–Behnken Design (BBD), response surface methodology (RSM) and desirability function, the optimized pyrolysis conditions of target biochar for Cu²⁺ (Cu-BC) and Zn²⁺ (Zn-BC) were obtained. The optimum pyrolysis parameters for Cu-BC and Zn-BC were pyrolysis time of 3.09 and 2.19 h, pyrolysis temperature of 425.27 and 421.97 °C, and heating rate of 19.65 and 15.88 °C/min. The pseudo-second-order kinetic and Langmuir isotherm model proved to be the best fit for the equilibrium data, with a maximum adsorption capacity (Q_max) fitted by Langmuir model were 210.56 mg/g for Cu²⁺ by Cu-BC and 223.32 mg/g for Zn²⁺ by Zn-BC, which were both higher than the Q_max of unoptimized biochar (BC) for Cu²⁺ (177.66 mg/g) and Zn²⁺ (146.14 mg/g). The physical properties, chemical structure, surface chemistry properties of Cu-BC and Zn-BC were characterized by Zeta potential meter, Scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). This study puts forward a new perspective for optimizing target biochar production for special environmental application.

The sustainability of regional water resources has important supporting data needed for establishing policies on the sustainable development of the social economy. The purpose of this paper is to propose an assessment method to accurately reflect the sustainability of regional water resources in various areas. The method is based on the relative entropy of the information entropy theory. The steps are as follows. Firstly, the pretreatment of the evaluation sample data is required, before the relative entropy of each standard evaluation sample and evaluation grade (SEG) is calculated to obtain the entropy weight of each evaluation index. After this, the entropy weighted comprehensive index (WCI) of the standard evaluation grade sample is obtained. The function relation between WCI and SEG can be fitted by the cubic polynomial to construct the evaluation function. Using the above steps, a generalized entropy method (GEM) for the sustainable assessment of regional water resources is established and it is used to evaluate the sustainability of water resources in the Pingba and Huai River areas in China. The results show that the proposed GEM model can accurately reflect the sustainable water resources in the two regions. Compared with the other evaluation models, such as the Shepherd method, Artificial Neural Network and Fuzzy comprehensive evaluation, the GEM model has larger differences in its evaluation results, which are more reasonable. Thus, the proposed GEM model can provide scientific data support for coordinating the relationship between the sustainable development and utilization of regional water resources in order to improve the development of regional population, society and economy.

The issue motivating the paper is the quantification of students’ academic performance and learning achievement regarding teaching quality, under interval number condition, in order to establish a novel model for identifying, evaluating, and monitoring the major factors of the overall teaching quality. We propose a projection pursuit cluster evaluation model, with entropy value method on the model weights. The weights of the model can then be obtained under the traditional real number conditions after a simulation process by Monte Carlo for transforming interval number to real number. This approach can not only simplify the evaluation of the interval number indicators but also give the weight of each index objectively. This model is applied to 5 teacher data collected from a China college with 4 primary indicators and 15 secondary sub-indicators. Results from the proposed approach are compared with the ones obtained by two alternative evaluating methods. The analysis carried out has contributed to having a better understanding of the education processes in order to promote performance in teaching.