Rice straw biochar that produced at three pyrolysis temperatures (400, 500 and 600 degrees C) were used to investigate the adsorption properties of 17beta-estradiol (E2). The biochar samples were characterized by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), elemental analysis and BET surface area measurements. The influences of pyrolysis temperature, E2 concentration, pH, ionic strength, background electrolyte and humic acid were studied. Kinetic and isotherm results illustrated that the adsorption process could be well described by pseudo-second-order and Freundlich models. Experimental results showed that ionic strength had less influence on the adsorption of E2 by 500 and 600 degrees C rice straw biochar. Further, multivalent ions had positive impact on E2 removal than monovalent ions and the influence of the pyrolysis temperature was unremarkable when background electrolyte existed in solutions. The adsorption capacity of E2 decreased with the pH ranged from 3.0 to 12.0 and the humic acid concentration from 2 to 10 mg L(-1). Electrostatic attractions and pi-pi interaction were involved in the adsorption mechanisms. Compared to low-temperature biochar, high-temperature biochar exhibited a better adsorption capacity for E2 in aqueous solution, indicated it had a greater potential for E2 pollution control.
Land use allocation;Multi-objective optimization;Multi-agent system;Sustainable land use;China
Achieving multi-objective land use optimization allocation (MOLUOA) for sustainable development is an important issue in land use. In consideration of the multi-dimensional characteristics of MOLUOA in terms of quantity, space, and time, and under the constraints of maximizing economic, ecological, and social benefits of land use, a MOLUOA model is developed in this study by integrating multi-agent system with particle swarm optimization. The MOLUOA model is applied to the simulation of land use optimization allocation in Changsha, a typical city located in central China. Simulation results show that the MOLUOA model can achieve multi-objective land use optimization allocation in terms of quantity, space, and time. The model can provide decision-making support for generating land use alternatives to achieve sustainable land use. (C) 2015 Elsevier B.V. All rights reserved.
[Tang, Jia; Deng, Zong-Wei; Tan, Xian-Liang] Planning and Architecture Design and Research Institute, Hunan City University, Yiyang 413000, China;[Li, Zhi-Yong] Hunan Communication Scientific Academy, Changsha 410015, China;[Deng, Zong-Wei] School of Resources and Safty Engineering, Central South University, Changsha 410083, China
Planning and Architecture Design and Research Institute, Hunan City University, China
[孔纲强] Key Laboratory of Education Ministry for Geomechanics and Embankment Engineering, Hohai University, Nanjing 210098, China;[胡庆春] Architecture and City Planning College, Hunan City University, Yiyang, Hunan 413000, China;[杨庆; 年廷凯; 孔纲强] State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China
Key Laboratory of Education Ministry for Geomechanics and Embankment Engineering, Hohai University, China