响应面法和神经网络优化Acinetobactersp．DNS32发酵基质

为了提高阿特拉津降解菌Acinetobactersp．DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分（玉米粉、豆饼粉、K：HPO。）进行优化研究。响应曲面法确定3种成分的含量为玉米粉39．494g／L,豆饼粉25．638g／L和K。HPO。3．265g／L时,预测发酵活菌最大生物量为7．079×10^8CFU／mL,实测量为7．194×10^8CFU／mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39．650g／L,豆饼粉为25．500g／L,K2HPO4为2．624g／L时,预测最大值为7．199×10^8CFU／mL,实测量为7．244×10。CFU／mL;最终确定培养基配方：玉米粉为39．650g／L,豆饼粉为25．500g／L,K2HPO4为2．624g／L,CaCO3为3．000g／L,MgSO4·7H2O和NaCl均为0．200g／L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36．6％。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

响应面法和神经网络优化Acinetobacter sp. DNS32发酵基质

为了提高阿特拉津降解菌Acinetobacter sp.DNS32的产量,分别采用响应曲面法和基于人工神经网络的遗传算法对阿特拉津降解菌DNS32发酵培养基中3个重要基质成分(玉米粉、豆饼粉、K2HPO4)进行优化研究。响应曲面法确定3种成分的含量为玉米粉39.494 g/L,豆饼粉25.638 g/L和K2HPO43.265 g/L时,预测发酵活菌最大生物量为7.079×108CFU/mL,实测量为7.194×108CFU/mL;人工神经网络结合遗传算法优化确定3种主要成分含量为玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L时,预测最大值为7.199×108CFU/mL,实测量为7.244×108CFU/mL;最终确定培养基配方:玉米粉为39.650 g/L,豆饼粉为25.500 g/L,K2HPO4为2.624 g/L,CaCO3为3.000 g/L,MgSO4.7H2O和NaCl均为0.200 g/L;优化后阿特拉津降解菌DNS32发酵生物量比优化前提高了36.6%。结果表明,在阿特拉津降解菌DNS32发酵培养基组分优化方面,响应面法和基于人工神经网络的遗传算法都是可行的,基于人工神经网络的遗传算法具有更好的拟合度和预测准确度。     

响应面法优化聚丙烯酸/腐殖酸/累托石吸附剂的制备条件

以累托石、丙烯酸及腐殖酸为原料制备出能同时吸附重金属和多环芳烃的吸附剂聚丙烯酸/腐殖酸/累托石,采用响应面试验设计法优化吸附剂的制备条件。利用Design Expert软件,建立了预测吸附剂对Cd2+、菲吸附量的二次回归模型,对回归模型进行了方差分析,并确定了吸附剂的最佳制备条件。结果表明,二次回归模型能较好地模拟Cd2+、菲的吸附量与影响因子丙烯酸中和度、引发剂量和交联剂量之间的关系。各因子对Cd2+吸附量的影响次序为:交联剂量>引发剂量>丙烯酸中和度;对菲吸附量的影响次序为引发剂量>交联剂量>丙烯酸中和度。吸附剂的最佳制备条件为:累托石、丙烯酸和腐殖酸三者的质量比为65∶30∶5,丙烯酸中和度、引发剂量和交联剂量分别为75.16%、2.57%和0.44%。在此优化条件下制备的吸附剂对Cd2+和菲的吸附量分别为170.19 mg/g和7.36 mg/g。     

响应面优化CCl4增强超声降解左旋氧氟沙星模拟废水

利用响应面优化实验设计方法对CCl₄增强超声降解左旋氧氟沙星模拟废水的影响因素进行探讨和分析,考察了溶液初始pH值、超声功率、左旋氧氟沙星初始浓度的影响。应用Box-Behnken中心组合设计得到一个二次多项式数学模型,确定了US/CCl₄降解左旋氧氟沙星的优化条件:初始pH值6.8,超声功率189 W,左旋氧氟沙星初始浓度为5 mg/L时,左旋氧氟沙星的去除率达到最大(82.99%)。经实验验证, 实际值与模型预测值吻合性良好,偏差仅为0.036%。     

Dyella ginsengisoli LA-4吸附Cu2+特性及其动力学研究

研究一种新型吸附菌剂Dyella ginsengisoli LA-4(以下简称菌株LA-4)对Cu2+的吸附特性及其动力学,并利用表面响应法优化菌株LA-4对Cu2+的吸附条件.结果表明:(1)菌株LA-4的接种量、pH对Cu2+的吸附有重要的影响.(2)根据表面响应法 优化模型预测出菌株LA-4吸附Cu2+的最...     

响应面法优化黄粉虫幼虫处理餐厨垃圾饲养条件的研究

研究了黄粉虫幼虫处理餐厨垃圾的方法.首先在饲养温度、饲料含水量和饲养密度等条件下进行单因素实验,然后,以利用率为指标,运用响应面法优化了黄粉虫幼虫处理餐厨垃圾的饲养条件,结果表明,最佳饲养条件为饲养温度26.7℃、饲料含水量14.5％、饲养密度4.1头/cm2.在此饲养条件下,黄粉虫对餐厨垃圾利用率理论值为38.72％,实际餐厨垃圾利用率为38.88％,相对误差为0.41％,说明利用黄粉虫幼虫处理餐厨垃圾具有较好的效果.     

气候变化经济学研究综述

对近10 a来国内外有关气候变化经济学研究成果作了综述。气候变化经济学是一门研究人类干预气候变化过程中涉及经济过程的学科。当前的研究热点包括气候变化的经济影响、适应措施的成本和收益、国际合作机制和涉及代际公平的折现率选取。 在研究方法上,对得到广泛运用的成本收益分析法和碳税机制作了详细的评述。在应用层面上,欧美发达国家在城市气候变化经济评估系统建立和碳税征收方面都有成功的应用,但我国在这方面的实践还处于起步阶段。对于我国气候变化经济学领域的研究来说,比较适合在发达省份以市域或省域为单位开展成本收益评估,发展中省份则应将更多关注放在评估气候变化可能造成的经济损害及相应的防范措施。此外,我国也应关注在欧盟地区实施较为成功的碳税政策,虽然目前在中国开征碳税的可能性较低,但是对碳税在中国实施的可行性、税率选取及立法保障机制等方面的探讨和研究仍是必要的     

环境工艺方法论研究——资源扩容法

资源扩容法是探索新型环境工程工艺的重要方法,其核心思想是认为世界上不存在绝对的废弃物,只有放错位置的资源。本文通过对资源扩容法理论及其应用实例的详细论述,揭示了资源扩容法所蕴涵的哲学理论。     

Network design for water quality monitoring of surface freshwaters: a review

To date, many water quality monitoring networks for surface freshwaters have been rather haphazardly designed without a consistent or logical design strategy. Moreover, design practices in recent years indicate a need for cost-effective and logistically adaptable network design approaches. There are many variables that need to be included in a comprehensive yet practical monitoring network: a holistic appraisal of the monitoring objectives, representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples. In order to investigate the factors which affect the development of an effective water quality monitoring network design methodology, a review of past and current approaches is presented.     

Use of USLE/GIS Methodology for Predicting Soil Loss in a Semiarid Agricultural Watershed

The Universal Soil Loss Equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices in agricultural watersheds by the effective integration of the GIS-based procedures to estimate the factor values in a grid cell basis. This study was performed in the Kazan Watershed located in the central Anatolia, Turkey, to predict soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Rain erosivity (R), soil erodibility (K), and cover management factor (C) values of the model were calculated from erosivity map, soil map, and land use map of Turkey, respectively. R values were site-specifically corrected using DEM and climatic data. The topographical and hydrological effects on the soil loss were characterized by LS factor evaluated by the flow accumulation tool using DEM and watershed delineation techniques. From resulting soil loss map of the watershed, the magnitude of the soil erosion was estimated in terms of the different soil units and land uses and the most erosion-prone areas where irreversible soil losses occurred were reasonably located in the Kazan watershed. This could be very useful for deciding restoration practices to control the soil erosion of the sites to be severely influenced.