新区划图双参数调整对剪力墙结构土建成本的影响

考虑到《中国地震动参数区划图》（GB 18306—2015）（中华人民共和国国家质量监督检验检疫总局等,2016）,提出了双参数调整原则,即对场地地震动峰值加速度和反应谱特征周期进行同时调整,以确定设计地震动反应谱,这势必会增加结构的土建成本。因此,基于Ⅱ类场地,对抗震设防烈度7度（0.15 g）的剪力墙结构在不同场地类别下的地震动参数进行推导。采用单一控制变量法,对某12层剪力墙结构按不同抗震设防烈度和不同场地类别进行设计,使其满足规范最低标准,计算相应的钢筋和混凝土材料用量;根据现时市场定额,比较分析单一地震动参数变化时的土建成本,研究结果可为工程实践提供一定参考。     

柳州市某小区高层商住楼地基基础选型探讨

介绍了柳州市某小区高层商住楼各个勘察阶段的岩土工程地质条件,重点通过对基础方案的技术可行性和经济成本两方面对比,探讨了该商住楼地基基础的选型问题,以工程实例告诫地质技术人员从事岩土工程勘察需要注意细节工作。     

再论平果铝土矿的勘探网度

关于平果岩溶堆积型铝土矿的勘探网度 ,过去已进行探讨和论述。现根据近年对那豆、太平两矿床的 10个矿体的地探、生探、开采等资料进行系统整理和对比验证 ,又提出一些意见和建议。     

Structural analysis of FAST reflector supporting system

According to the deformation and movement requirements of the FAST reflector, a multi-purpose analysis, including the load-bearing behavior, deformation, construction costs of the reflector supporting structure and its model, is presented in this paper. The advantages and disadvantages of steel and aluminum alloy structures are also discussed and compared through detailed design calculations under load-bearing capacity and normal working conditions. This revised version was published online in July 2006 with corrections to the Cover Date.     

改进的ELU卷积神经网络在SAR图像舰船检测中的应用

随着航天技术的发展,我国SAR载荷的探测体系呈现多种类、多分辨率的发展趋势。传统的检测识别方法很难适应多分辨率、多种类的SAR图像数据,从而需要寻求一种能从多分辨率的图像数据中提取有效特征的方法。智能化发展非常迅速,本文基于SAR图像的特点,提出了改进的ELU激活函数卷积神经网络的方法,建立了结合ELU激活函数和二次代价函数的深度学习模型。同时,在训练样本中建立样本特征与所在分类中心的距离函数,用模糊支持向量机（FSVM）对提取的特征进行了分类。试验结果表明,本文方法提高了SAR图像舰船检测的抗噪性,并且检测率达到了98.6%。     

地块尺度城市水源地生态补偿标准核算——以贵阳市阿哈水库实证分析为例

水源地保护是解决城市供水问题的有效途径,合理的补偿标准是水源地保护计划顺利实施的重要保障。以贵阳市阿哈水库为例,以耕地收益作为林地保护的机会成本,在地块尺度上从自然和交通2个方面建立影响耕地收益的指标体系,利用田野调查及实验数据,结合GIS技术,建立多元线性回归方程,核算林地保护的机会成本。结果显示:1)阿哈水库汇水流域耕地自然条件指数值介于0.549~0.823之间,指数高值区主要集中在河流沿岸及水库东南沿岸地势较低地区,低值区域主要分布于地势较高、坡度较陡的区域;交通条件指数值介于0.224~0.900之间。2)自然条件指数和交通条件指数对耕地收益均呈正向影响,自然条件指数的影响较大。3)选取了14个林地地块测算机会成本,其值介于896.405~1 523.772元/亩之间,平均机会成本值为1 274.623元/亩。保护不同林地地块损失的机会成本差异较大,应当采取有差别的补偿标准。     

Using the social cost of carbon to value earth observing systems

The goal of this study is to show how to quantify the benefits of accelerated learning about key parameters of the climatic system and use this knowledge to improve decision-making on climate policy. The US social cost of carbon (SCC) methodology is used in innovative ways to value new Earth observing systems (EOSs). The study departs from the strict US SCC methodology, and from previous work, in that net benefits are used instead of only damages to calculate the value of information of the enhanced systems. In other respects the US SCC methodology is followed closely. We compute the surfeit expected net benefits of learning the actionable information earlier, with the enhanced system, versus learning later with existing systems. The enhanced systems are designed to give reliable information about climate sensitivity on accelerated timescales relative to existing systems; therefore, the decision context stipulates that a global reduced emissions path would be deployed upon receiving suitable information on the rate of temperature rise with a suitable level of confidence. By placing the enhanced observing system in a decision context, the SCC enables valuing this system as a real option.

Policy relevance

Uncertainty in key parameters of the climatic system is often cited as a barrier for near-term reductions of carbon emissions. It is a truism among risk managers that uncertainty costs money, and its reduction has economic value. Advancing policy making under uncertainty requires valuing the reduction in uncertainty. Using CLARREO, a new proposed EOS,as an example, this article applies value of information/real option theory to value the reduction of uncertainty in the decadal rate of temperature rise. The US interagency social cost of carbon directive provides the decision context for the valuations. It is shown that the real option value of the uncertainty reduction, relative to existing observing systems, is a very large multiple of the new system's cost.     

Does the CDM discourage emission reduction targets in advanced developing countries?

Under the Kyoto Protocol, developing countries can voluntarily participate in climate change mitigation through the Clean Development Mechanism (CDM), in which industrialized countries, in order to meet their mitigation commitments, can buy emission reduction credits from projects in developing countries. Before its implementation, developing-country experts opposed the CDM, arguing that it would sell-off their countries’ cheapest emission reduction options and force them to invest in more expensive measures to meet their future reduction targets. This ‘low-hanging fruit’ argument is analysed empirically by comparing marginal abatement cost curves. Emissions abatement costs and potentials for CDM projects are estimated for different technologies in eight countries, using capital budgeting tools and information from project documentation. It is found that the CDM is not yet capturing a large portion of the identified abatement potential in most countries. Although the costs of most emissions reduction opportunities grasped are below the average credit price, there are still plenty of available low-cost opportunities. Mexico and Argentina appear to use the CDM predominantly for harvesting the low-hanging fruit, whereas in the other countries more expensive projects are accessing the CDM. This evidence at first sight challenges the low-hanging fruit claim, but needs to be understood in the light of the barriers for the adoption of low-cost abatement options.     

Marginal abatement cost curves: a call for caution

Legal commitments to reduce CO₂ emissions require policy makers to find cost-efficient means to meet these obligations. Marginal abatement cost (MAC) curves, which illustrate the economics associated with climate change mitigation, have recently attracted a great amount of attention. A number of limitations with MAC curves are explained by the implication they should be just one tool in a broader set of decision-making aids used in assessing climate policy. MAC curves, for example, omit ancillary benefits of greenhouse gas emission abatement, treat uncertainty in a limited manner, exclude intertemporal dynamics and lack the necessary transparency concerning their assumptions. MAC curves based on the individual assessment of abatement measures suffer from additional shortcomings such as the non-consideration of interactions and non-financial costs, a possibly inconsistent baseline, double counting and limited treatment of behavioural aspects. Reducing emissions from deforestation and forest degradation exhibit many of the above-mentioned problems, making it particularly difficult to capture in a cost curve. Policy makers should therefore be cautious when interpreting MAC curves, pay attention to the underlying assumptions, consider non-financial costs and be aware of the important uncertainties and underlying path dependencies.     

A ‘safety deposit’ mechanism for US climate policy

US policy makers are currently evaluating options to reduce domestic carbon dioxide emissions, and several economy-wide cap-and-trade proposals have been put forward in the 111th Congress. Despite mounting enthusiasm for cap-and-trade, advocates of this approach have had to defend such proposals against the criticisms that prices in the resulting carbon market will be unstable and that the implied costs of policy might exceed society's willingness to pay for the expected environmental benefits. Allowance borrowing has been proposed as one solution to both of these concerns, with firm-level borrowing intended to mitigate the impacts of transient cost shocks, and system-level borrowing intended to hedge against the risk of early technology bottlenecks. Each of these mechanisms, as proposed, relies upon prescribed constraints, such as interest payments or quantity limits, to protect against overuse. This article introduces a novel mechanism that offers qualitatively similar protection—a firm-level deposit on borrowed allowances that is refundable upon repayment of the emissions debt. However, the deposit mechanism is shown to be both more economically efficient and more effective in mitigating performance risk, when compared to the existing alternatives.