摘要：
Chromium is not only an essential trace element for the growth and development of living organisms; it is also a heavy metal pollutant. Excessive chromium in farmland soil will not only cause harm to crops, but could also constitute a serious threat to human health through the cumulative effect of the food chain. The determination of heavy metals in tailings of farmland soil is an essential means of soil environmental protection and sustainable development. Hyperspectral remote sensing technology has good characteristics, e.g., high speed, macro, and high resolution, etc., and has gradually become a focus of research to determine heavy metal content in soil. However, due to the spectral variation caused by different environmental conditions, the direct application of the indoor spectrum to conduct field surveys is not effective. Soil components are complex, and the effect of linear regression of heavy metal content is not satisfactory. This study builds indoor and outdoor spectral conversion models to eliminate soil spectral differences caused by environmental conditions. Considering the complex effects of soil composition, we introduce a support vector machine model to retrieve chromium content that has advantages in solving problems such as small samples, non-linearity, and a large number of dimensions. Taking a mining area in Hunan, China as a test area, this study retrieved the chromium content in the soil using 12 combination models of three types of spectra (field spectrum, lab spectrum, and direct standardization (DS) spectrum), two regression methods (stepwise regression and support vector machine regression), and two factors (strong correlation factor and principal component factor). The results show that: (1) As far as the spectral types are concerned, the inversion accuracy of each combination of the field spectrum is generally lower than the accuracy of the corresponding combination of other spectral types, indicating that field environmental interference affects the modeling accuracy. Each combination of DS spectra has higher inversion accuracy than the corresponding combination of field spectra, indicating that DS spectra have a certain effect in eliminating soil spectral differences caused by environmental conditions. (2) The inversion accuracy of each spectrum type of SVR_SC (Support Vector Regression_Strong Correlation) is the highest for the combination of regression method and inversion factor. This indicates the feasibility and superiority of inversion of heavy metals in soil by a support vector machine. However, the inversion accuracy of each spectrum type of SVR_PC (Support Vector Regression_Principal Component) is generally lower than that of other combinations, which indicates that, to obtain superior inversion performance of SVR, the selection of characteristic factors is very important. (3) Through principal component regression analysis, it is found that the pre-processed spectrum is more stable for the inversion of Cr concentration. The regression coefficients of the three types of differential spectra are roughly the same. The five statistically significant characteristic bands are mostly around 384-458 nm, 959-993 nm, 1373-1448 nm, 1970-2014 nm, and 2325-2400 nm. The research results provide a useful reference for the large-scale normalization monitoring of chromium-contaminated soil. They also provide theoretical and technical support for soil environmental protection and sustainable development.
摘要：
A comprehensive mathematical model to simulate a serial composite process for biomass and coal co-gasification has been built. The process is divided into combustion stage and gasification stage in the same gasifier, it is a new process for the co-gasification of biomass and coal. The model is based on reaction kinetic, hydrodynamics, mass and energy balances, it is a one-dimensional, K-L three-phase, unsteady state model. The model is divided into two sub-models, one is the combustion sub-model, the other is the coal-biomass serial gasification sub-model. Combustion sub-model includes coal pyrolysis, dense phase combustion, and dilute phase combustion model. Gasification sub-model includes biomass pyrolysis, dense phase coal gasification, dense phase biomass gasification, and dilute phase gasification model. The model studies the effects of key parameters on gasification properties, including gasification temperature, S/B, B/C, and predicts the composition of product gas and gas calorific value along the reactor's axis at different time. The model predictions agree well with experimental results and can be used to study and optimize the operation of the process.
作者机构：
[Wang, Aihe; Deng, Yumei; Zhang, Chun; Jiang, Haiyan] Hunan City Univ, Sch Municipal & Mapping Engn, Yiyang 413000, Peoples R China.
通讯机构：
[Zhang, Chun] H;Hunan City Univ, Sch Municipal & Mapping Engn, Yiyang 413000, Peoples R China.
摘要：
Antimony pollution resulting from industrial production is a great threat to the environment, ecology and the human body. Zero-valent iron powder is low-cost and easy to obtain. Nevertheless, the lower adsorption capacity limits its application when it is used as an adsorbent. In the present study, ball-milling and acid modification were developed to change its surface characteristics and gamma-Fe2O3, gamma-FeOOH and Fe3O4 were obtained after treatment, which promoted its adsorption capacity. Compared with the raw iron powder, the adsorption capacities for Sb(iii) and Sb(v) using the modified material were increased from 12.93 mg g(-1) and 5.47 mg g(-1) to 17.96 mg g(-1) and 10.58 mg g(-1), respectively. The study showed that the experimental data fitted the Langmuir model and the pseudo-first-order kinetic model better; the adsorption process was monolayer and chemically controlled at pH 5.0 +/- 0.2. XPS and FT-IR analysis showed that Fe-O-Sb bonds arose during the adsorption process. The effect of pH on the adsorption capacity was also studied and the pH affected the adsorption of Sb(v) more than the adsorption of Sb(iii). In addition, the modified iron powder presented better efficiency when applied to the removal of low levels of antimony in drinking water. Based on the increase of adsorption capacity and low cost, iron powder should be a promising adsorbent for aqueous antimony removal.
