Metagovernance and policy forum outputs in Swiss environmental politics

Policy forums are lightly institutionalized and stable forms of governance networks that include administrative authorities, interest groups, and scientists. They are said to produce different types of outputs, from simple actor coordination to position papers and implementation documents, but their productivity has also been questioned. Metagovernance strategies can improve the capability of policy forums to produce outputs. To determine how different metagovernance strategies influence the capability of forums to produce joint position papers, 29 policy forums in the Swiss environmental sector are compared through a qualitative comparative analysis. Results indicate that metagovernance strategies such as state actors as forum members or majority decision rules need to be combined with small forum size or low actor heterogeneity. Furthermore, forum foundation by the state complicates the production of position papers.     

产业园区碳排放核算方法研究

产业园区是一个协同实现经济效益和环境效益的重要单元,同时也是重点碳排放源,其转型和发展对实现国家和地区的低碳战略起到关键作用。碳排放核算方法影响园区碳排放水平的评估,是制定有效碳减排策略的基础。产业园区碳排放核算需要明确核算对象、核算结果表征和核算范围。本研究首先界定核算对象,辨析"二氧化碳量"与"二氧化碳当量"两种表征方式,认为二氧化碳量可以反映产业园区能源结构,而二氧化碳当量则能够量化园区的不同排放过程和环境效应。同时,从价值链角度出发,将园区碳排放核算划分为三个Scope,分别反映园区直接排放和上下游关联企业的间接排放。然后,从排放活动和部门关联出发,分析三种典型碳排放核算方法(清单分析法、投入产出分析和生态网络分析),进一步划分为流量分析模式和结构分析模式。流量分析模式主要从排放量角度对园区内部及其上下游产业链相关的碳排放活动进行核算;结构分析模式则聚焦园区相关碳排放部门和价值链的组织形式,从投入产出或者网络关联角度开展分析。研究发现清单分析法可以自下而上量化产业园区碳排放活动的流量,投入产出法则自上而下揭示碳排放单元的直接和间接流量以及平行结构,而生态网络分析则采用混合式核算模式刻画碳排放单元之间的网状关联结构。最后,本研究初步提出了产业园区碳排放核算方法的研究框架,力求提高排放因子精度,改进核算模式和建立动态核算模型,对碳排放总量和结构进行预测,从而实现产业园区的低碳发展。     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

基于轴-辐理论的皖江城市带物流网络空间构建

大力发展现代物流业和皖江城市带承接产业转移示范区建设是两大重要国家级战略。首先对轴-辐理论的国内外研究现状进行了总结和归纳,分析了轴-辐网络的结构及其优劣势。其次,设计了物流中心性指数的评价指标体系,运用主成分分析法对皖江城市带的9个地级城市进行物流节点等级划分,根据分析结果的总得分和区位特征确定合肥、芜湖、安庆3个一级物流节点,形成轴三角。分析了各级物流节点间的干线及支线物流通道,构建了皖江城市带轴-辐物流网络空间。     

村镇供水管网优化设计探讨

如何合理确定村镇供水管网敷设方案,关系到整个供水系统的安全性和可靠性。通过生成树变化法,将环状管网转化成树状管网,确定供水管网中最短供水路线,再计算最短供水路线下的最低综合费用、供水系统的经济管径,以确定最优管道敷设方案。根据该方法对四川省某镇供水系统进行了设计。     

大气细粒子(PM2.5)监测技术进展

大气细粒子(PM2.5)的污染对人和生态环境等影响巨大,迫切需要进行PM2.5质量浓度的监测;本文介绍了PM2.5国内外监测研究进展、监测网络应用情况以及监测技术;重点介绍了几种先进的技术:β射线法、振荡天平法和光散射法,并详细描述了各种监测设备的原理及结构,提出最好采用PM2.5在线监测仪进行日常监测。     

基于人工蜂群算法与BP神经网络的水质评价模型

针对BP网络水质评价模型的不足,引入人工蜂群(ABC)算法,将求解BP神经网络各层权值、阀值的过程转化为蜜蜂寻找最佳蜜源的过程,提出了一种新的结合人工蜂群算法的BP网络水质评价方法(ABC-BP)。并以2000—2006年渭河监测断面的10组实测数据作为测试样本对其水质进行了评价,实验结果表明该方法得到的水质评价结果准确,并具有很强的稳定性和鲁棒性。     

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。