大坝下游定点区域溶解氧饱和度预测

大坝通过坝身泄流时，巨大的洪水卷吸空气中的大量气体直泻到下游河床，造成下游河道特别是近坝区域气体含量过饱和，给下游水生生物带来不利影响，其中鱼类气泡病就是水体气体过饱和造成的典型病症。为探明大坝泄流对坝下河道溶解氧饱和度的影响，以三峡 葛洲坝区域坝下近坝区定点区域的溶解氧实测资料为基础，建立溶解氧饱和度的BP网络预测模型，对大坝不同运行工况进行下游溶解氧饱和度的预测仿真计算，并将仿真预测值与实测及数值模拟结果进行比较分析。结果得出BP网络模型能很好地逼近坝下近坝区指定区域的溶解氧饱和度，可根据大坝运行工况对下游水体溶解氧饱和度进行快速预测，为有效控制坝下水体溶解氧饱和度提供借鉴     

Population dynamics and the economics of invasive species management: the greenhouse whitefly in California-grown strawberries

In agriculture, relatively few efficacious control measures may be available for an invasive pest. In the case of a new insect pest, insecticide use decisions are affected by regulations associated with its registration, insect population dynamics, and seasonal market price cycles. We assess the costs and benefits of environmental regulations designed to regulate insecticide applications on an invasive species. We construct a bioeconomic model, based on detailed scientific data, of management decisions for a specific invasion: greenhouse whiteflies in California-grown strawberries. The empirical model integrates whitefly population dynamics, the effect of whitefly feeding on strawberry yields, and weekly strawberry price. We use the model to assess the optimality of alternative treatment programs on a simulated greenhouse whitefly population. Our results show that regulations may lead growers to "under-spray" when placed in an economic context, and provide some general lessons about the design of optimal invasive species control policies.     

高危作业有害因素预防控制水平预警模型

针对职业卫生领域出现的急慢性职业病及突发性化学中毒等事件，本文采用预防控制水平指标体系，用因子分析法构建了单项有害因素的预警模型。在此基础上，利用加权平均法给出了多项有害因素的综合预警模型，其中，应用层次分析法确定各个有害因素的权重。高危作业有害因素预警模型的提出为高危作业有害因素防治提供了量化的科学依据。     

Balancing Conservation and Economic Sustainability: The Future of the Amazon Timber Industry

Logging has been a much maligned feature of frontier development in the Amazon. Most discussions ignore the fact that logging can be part of a renewable, environmentally benign, and broadly equitable economic activity in these remote places. We estimate there to be some 4.5 ± 1.35 billion m³ of commercial timber volume in the Brazilian Amazon today, of which 1.2 billion m³ is currently profitable to harvest, with a total potential stumpage value of $15.4 billion. A successful forest sector in the Brazilian Amazon will integrate timber harvesting on private lands and on unprotected and unsettled government lands with timber concessions on public lands. If a legal, productive, timber industry can be established outside of protected areas, it will deliver environmental benefits in synergy with those provided by the region’s network of protected areas, the latter of which we estimate to have an opportunity cost from lost timber revenues of $2.3 billion over 30 years. Indeed, on all land accessible to harvesting, the timber industry could produce an average of more than 16 million m³ per year over a 30-year harvest cycle—entirely outside of current protected areas—providing $4.8 billion in returns to landowners and generating $1.8 billion in sawnwood sales tax revenue. This level of harvest could be profitably complemented with an additional 10% from logging concessions on National Forests. This advance, however, should be realized only through widespread adoption of reduced impact logging techniques.     

凹凸棒土的氨氮吸附性能研究

在以氨氮去除率为指标,在振荡时间60 min,振荡温度25℃,振荡速度140r/min的条件下发现凹凸棒土的最佳投加量2.5 g;添加凹凸棒土可以加强SBR生物系统去除氨氮的能力;拟合凹凸棒土吸附氨氮的等温线方程符合Freundlich吸附模型.     

Pesticide residue dynamics in passion fruits: Comparing field trial and modelling results

We evaluated the exposure to pesticides from the consumption of passion fruits and subsequent human health risks by combining several methods: (i) experimental field studies including the determination of pesticide residues in/on passion fruits, (ii) dynamic plant uptake modelling, and (iii) human health risk assessment concepts. Eight commonly used pesticides were applied onto passion fruits cultivated in Colombia. Pesticide concentrations were measured periodically (between application and harvest) in whole fruits and fruit pulp. Measured concentrations were compared with predicted residues calculated with a dynamic and crop-specific pesticide uptake model, namely dynamiCROP. The model accounts for the time between pesticide application and harvest, the time between harvest and consumption, the amount of spray deposition on plant surfaces, uptake processes, dilution due to crop growth, degradation in plant components, and reduction due to food processing (peeling). Measured and modelled residues correspond well (r² = 0.88-0.99), with all predictions falling within the 90% confidence interval of the measured values. A mean error of 43% over all studied pesticides was observed between model estimates and measurements. The fraction of pesticide applied during cultivation that is eventually ingested by humans is on average 10⁻⁴-10⁻⁶, depending on the time period between application and ingestion and the processing step considered. Model calculations and intake fractions via fruit consumption based on experimental data corresponded well for all pesticides with a deviation of less than a factor of 2. Pesticide residues in fruits measured at recommended harvest dates were all below European Maximum Residue Limits (MRLs) and therefore do not indicate any violation of international regulatory thresholds.     

成都市餐厨垃圾产量分析预测及监管体系建设研究

整理汇总了成都市中心城区及郊县餐厨垃圾产生和收运现状,对其产量作出预测;在此基础上提出适合成都市自身情况的餐厨垃圾监管体系构建设想。     

基于因子分析法优选河流水体中氮浓度预测方法的研究

定量的河流水体中氮浓度预测方法有很多种,如何优选出预测精度较高的方法一直是学术界多年来致力于研究的重点。本研究采用因子分析法对预测方法的精度评价指标进行分析,并建立了预测方法精度的评价模型,对回归分析法、神经网络法、灰色系统法和增长率统计法4种水体氮浓度预测方法进行综合评估,优选出精度较高的河流水体氮浓度预测模型——BP神经网络预测模型。结果表明,此评估模型对类似研究具有一定的参考价值,能为选择出合适的河流水体氮浓度预测方法提供依据。     

基于产业链的区域环境污染物排放的产业贡献

区域经济增长与环境质量之间的关系研究是目前学者们探讨的重要学术议题之一.其中较多的是对EKC曲线的验证,近几年部分学者从国民经济各部门中的产业自身特征、产业结构、技术进步、FDI效应等方面考察产业发展对污染物排放的影响.然而以上研究议题中学者均没有讨论污染物的发生主体-各产业部门与排污的直接关系.故本文将从宏观尺度下的综合水平测度区域经济发展与环境质量关系、中观尺度下的产业属性特征与排污关系的研究视角转移至分析具体产业部门的污染物排放效应,同时将产业置于产业链的结构形式中,研究产业链上产业发展与污染物排放的关系.发现:第一,通过借助复杂网络思想的社区划分方法,将山东省39个产业部门分为3个社团.其中社团I主要由制造业部门组成,共有18个产业部门,社团II包括了15个部门,主要是第三产业,杜团III由6个产业部门组成且内部异质性高.第二,选择其中以制造业为主的社团I,并在社团I内识别出一条彼此间联系最为紧密的产业链,包括农林牧渔业、食品制造及烟草加工业、化学工业、纺织工业、服装皮革羽绒及其制品业、通用/专用设备制造业和交通运输设备制造业.以一种定量的方法获取了通过价值流传递而串在一起的产业链条.该产业链的经济规模、污染物规模在山东省均有重要地位.第三,采用岭回归分析方法,构建了6个制造业与产业链工业废水、固体废弃物排放的关系模型,6个制造业中对工业废水、固体废弃物排放相对贡献度最大的部门分别为服装皮革羽绒及其制品业、食品制造及烟草加工业.这是由于上游产业排污的链式传递效应与产业自身污染物排放效应的共同叠加作用.     

基于ARIMA和BP神经网络组合模型的我国碳排放强度预测

预测我国碳排放强度的长期变动趋势, 对国家进行宏观经济管理和节能减排工作具有重要的参考价值。运用深入分析自回归移动平均模型和神经网络的特性，并在此基础上建立ARIMA模型和BP神经网络组合模型，将碳排放强度的时间序列的数据结构分解为线性和非线性残差部分，对我国碳排放强度的变化趋势进行了综合分析与预测。结果显示:今后10 a我国碳排放强度总体是逐步下降的，但到2020年我国碳排放强度仅比2005年下降34%，比我国政府提出碳排放强度下降40%~45%的目标还有一定的差距。因此，要在2020年实现我国碳排放强度目标，必须要调整宏观经济政策，采取各种政策措施以实现目标