浅析修缮工程的造价控制

修缮工程的造价控制相对于新建工程有其自身特点,需要从工程设计和招标阶段开始就制定严谨的造价控制计划,并在其后的工程管理中逐步实现。本文论述了修缮工程造价控制的难点和特点,并提出了解决建议。     

中国太阳能供热采暖技术的现状与发展

本文介绍了我国太阳能供热采暖技术的发展现状及工程实例,指出了该项技术与国际先进水平的差距及存在的主要问题,提出了太阳能供热采暖今后在我国的发展趋势、发展目标和重点任务。     

Go with the flow: geospatial analytics to quantify hydrologic landscape connectivity for passively dispersed microorganisms

Understanding the diverse ways that landscape connectivity influences the distribution of microbial species is central to managing the spread and persistence of numerous biological invasions. Here, we use geospatial analytics to examine the degree to which the hydrologic connectivity of landscapes influences the transport of passively dispersed microbes, using the invasive plant pathogen Phytophthora ramorum as a case study. Pathogen occurrence was analyzed at 280 stream baiting stations across a range of watersheds – exposed to variable inoculum pressure – in California over a 7-year period (2004–2010). Using logistic regression, we modeled the probability of pathogen occurrence at a baiting station based on nine environmental variables. We developed a novel geospatial approach to quantify the hydrologic connectivity of host vegetation and inoculum pressure derived from least cost distance analyses in each watershed. We also examined the influence of local environmental conditions within the immediate neighborhood of a baiting station. Over the course of the sampling period, the pathogen was detected at 67 baiting stations associated with coastal watersheds with mild climate conditions, steep slopes, and higher levels of inoculum pressure. At the watershed scale, hydrologic landscape connectivity was a key predictor of pathogen occurrence in streams after accounting for variation in climate and exposure to inoculum. This study illustrates a geospatial approach to modeling the degree to which hydrologic systems play a role in shaping landscape structures conducive for the transport of passively dispersed microbes in heterogeneous watersheds.     

Utilization of a multicriteria least cost path model in an aquatic environment

A critical component of maintaining biodiversity in fragmented habitats is maintaining connectivity among the usable fragments. Least cost path (LCP) analysis is a tool that can be used for predicting the ability of an organism to move from one habitat patch to another, based on geographical features of the landscape and life history traits of the organism. While this analysis has been utilized for terrestrial habitats, it is rarely applied to aquatic environments. Aquatic hypoxic conditions occur when dissolved oxygen falls below 2 mg/L. These conditions can create barriers in the water column that can either force fish to leave a habitat, or avoid that habitat altogether. Using the lower St. Johns River (LSJR) estuary in Florida, USA, as a study system, the ability of an adult silver perch, Bairdiella chrysoura, to escape a large-scale hypoxic event was modeled using a multicriteria LCP approach. Criteria-specific cost grids were constructed based upon current speed, risk of predation, and whether oxygen levels in the habitat area were normoxic (>5.5 mg/L), or hypoxic (<2.0–1.5 mg/L) as a function of water depth for the LSJR. The criteria cost grids were combined using relative weighting to produce the multicriteria cost grid used to implement the LCP analysis. Three origin and destination point locations within the LSJR study area were selected for modeling whether or not a silver perch would be able to escape a hypoxic zone. Since the LCP model will always determine a LCP from the specified origin point location, ecologically relevant swimming capacities for silver perch under normoxic and hypoxic conditions were then applied to assess the model, and to determine whether the fish would be able to reach areas unimpacted by hypoxia. The LCP model and the swimming capacity results for this study predict that under normoxic conditions, fish movement was unimpeded. During the rapidly developing hypoxic event that was modeled, the results from the LCP model indicate that the fish could move outside the hypoxic zone, but when swimming capacities were applied to the model, the silver perch could not escape. Ecologically, the results of this study suggest that silver perch would experience high mortality under a rapidly developing hypoxic event. Additionally, the results of this study indicate that a LCP model can be applied to an aquatic habitat, as long as the cost grids incorporate relevant abiotic and biotic factors.     

The maintenance costs of marine natural capital: A case study from the initial assessment of the Marine Strategy Framework Directive in France

There are two ways of assessing the costs of environmental degradation: as the costs associated with the loss of benefits resulting from the degradation of natural capital, and as the maintenance costs required to compensate for the actual or potential degradation of natural capital. The first of these methods is based on the Total Economic Value (TEV) of benefits forgone because of the depletion of ecosystem services delivered by marine biodiversity. The second method is based on the costs required to maintain a good state of marine biodiversity, one which makes it possible to deliver ecosystem services.This paper gives an illustration of this second approach. It details how these maintenance costs have been calculated in the initial assessment of the Marine Strategy Framework Directive (MSFD) in France. It addresses nine problem areas – corresponding to nine sources of environmental degradation – from non-native invasive species to oil spills. It gives a total figure for these degradation costs (around 2 billion Euros). The results are compared with those of other Member States who have taken similar approaches in the context of the MSFD. One key conclusion is that it is not really possible to make meaningful comparisons at this stage, since the methods of data collection and the nature of the costs are very different. The need to develop such assessments in a standardised way is noted.     

Risk mitigation and the social cost of carbon

The social cost of carbon – i.e., the marginal present-value cost imposed by greenhouse gas emissions – is determined by a complex interaction between factual assumptions, modeling methods, and value judgments. Among the most crucial factors is society's willingness to tolerate potentially catastrophic environmental risks. To explore this issue, the present analysis employs a stochastic climate–economy model that accounts for uncertainties in baseline economic growth, baseline emissions, greenhouse gas mitigation costs, carbon cycling, climate sensitivity, and climate change damages. In this model, preferences are specified to reflect the high degree of risk aversion revealed by private investment decisions, signaled by the large observed gap between the average rates of return paid by safe and risky financial instruments. In contrast, most climate–economy models assume much lower risk aversion. Given high risk aversion, the analysis finds that investment in climate stabilization yields especially large net benefits by forestalling low-probability threats to long-run human well-being. Accordingly, the social cost of carbon attains the markedly high value of $25,700 per metric ton of carbon dioxide in a baseline scenario in which emissions are unregulated. This value falls to just $4 per ton as the stringency of control measures is successively increased. These results cast doubt on the idea that the social cost of carbon takes on a uniquely defined, objective value that is independent of policy decisions. This does not, however, rule out the use of carbon prices to achieve the benefits of climate stabilization using least-cost mitigation measures.     

The economic impact of extreme sea-level rise: Ice sheet vulnerability and the social cost of carbon dioxide

The possibility of extreme sea-level rise is one of the commonly cited reasons for concern about climate change. Major increases in sea level would likely be driven by the melting or collapse of major ice sheets. This possibility has implications for the social cost of carbon dioxide, which is a key policy value as well as a useful summary measure of damage caused by greenhouse gas emissions.This paper extends earlier work on the importance of low-probability, high-impact events for the social cost of carbon dioxide to incorporate the possibility of extreme sea-level rise.To estimate its impact, an integrated assessment model is used, which allows a probabilistic assessment of climate change damages based on the linkages between the economic and climate systems. In the model, the generic discontinuity damage is replaced with the possibility of large-scale damage from factors that are taken to be correlated with temperature rise and, crucially for this paper, explicit consideration of extreme sea-level rise.Estimates of the amount of increase in the social cost of carbon dioxide that can be expected from incorporating extreme sea-level rise show that the increase is significant, though not especially large in percentage terms.The paper contributes to the literature of how to represent uncertain climate impacts in integrated assessment models and the associated estimation of the social cost of carbon dioxide.     

基于弱势人群个体可达性评价的社区服务设施配置研究

当前我国人口形势面临老龄化与少子化风险,抓好“一老一小”、确保老有所养和幼有所育成为我国城乡发展中特别关注的方面。在这一背景下,如何营造有利于养老和生育的社会环境,如何针对老年人、育龄妇女和儿童等弱势人群提供更为合理的设施配置成为民生工程的重要内容。社区服务设施作为城市公共服务的空间载体,其配置模式的完善与提升是落实以人为本、集中体现社会公平的重要路径。当前,从网络地图规划路径API获取的出行时间成本矩阵能够为可达性研究提供接近真实的出行时间数据,此外个体化的人口数据如实有人口数据能够以其丰富的属性信息为识别各类弱势人群提供依据,同时精确刻画人口的空间分布。本文基于弱势人群的需求特征与相关规范,对老年人、育龄妇女和儿童三类弱势人群提出了明确定义,并构建了面向各类弱势人群个体使用需求的社区服务设施供给标准。在此基础上,利用实有人口数据、网络地图出行时间成本矩阵和POI数据,综合考虑社区服务设施的服务容量,提出了基于弱势人群个体可达性评价的社区服务设施供给评价与布局优化方法,并以广州市人民南社区为例进行了应用实践。研究表明,人民南社区的弱势人群服务设施供给存在不足,优化配置后设施的供需情况更加合理,服务人口覆盖率亦明显提升。本文提出的方法能够从独立个体尺度精确评价社区弱势人群服务设施的布局合理性,在拓展数据类型及应用方法方面为当前人口形势下精细化研究服务设施的空间分布和供需问题提供新的思路。     

Hoare分类算法的效率改进研究

本文是一篇如何实现改进Hoare分类算法效率的方法研究。文中提出的一个新的快速分类的改进方案优于其它的快速分类算法,其平均分类速度是Hoare原算法的1.6倍左右,额外的内存开销仅为2*[log_2(N/10)]。文中还给出了在IBM-PC/XT微机上对大量随机数排序的实验结果。