How certain are we about the certainty-equivalent long term social discount rate?

Theoretical arguments for using a term structure of social discount rates (SDR) that declines with the time horizon have influenced government guidelines in the US and Europe. The certainty equivalent discount rate that often underpins this guidance embodies uncertainty in the primitives of the SDR, such as growth. For distant time horizons the probability distributions of these primitives are ambiguous and the certainty equivalent itself is uncertain. Yet, if a limited set of characteristics of the unknown probability distributions can be agreed upon, ‘sharp’ upper and lower bounds can be defined for the certainty-equivalent SDR. Unfortunately, even with considerable agreement on these features, these bounds are widely spread for horizons beyond 75 years. So while estimates of the present value of intergenerational impacts, including the social cost of carbon, can be bounded in the presence of this ambiguity, they typically remain so imprecise as to provide little practical guidance.     

Fine‐resolution conservation planning with limited climate‐change information

Climate‐change induced uncertainties in future spatial patterns of conservation‐related outcomes make it difficult to implement standard conservation‐planning paradigms. A recent study translates Markowitz's risk‐diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate‐change scenarios for carrying out fine‐resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk‐return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate‐change information and full climate‐change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate‐change forecasts such that the best possible risk‐return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate‐change information could be reduced by 17% relative to other iterative approaches.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.     

30MHz-1000MHz显示器辐射骚扰测试及其不确定度评定

本文以显示器辐射骚扰测试为例对10米半电波暗室的辐射骚扰试验进行不确定度评定。并与相应标准进行比较，确认该辐射测试系统的测量结果是可信的。     

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.     

Predicting vehicle fuel consumption patterns using floating vehicle data

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers'' information and vehicles'' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model.     

中国国道和省道机动车尾气排放特征

近年来,随着我国机动车保有量的持续增长,机动车排放已成为我国重要的大气污染物来源之一.现有的机动车排放研究多关注城市内的机动车大气污染物排放,针对城市间的大气污染物排放研究较少.我国城市间交通道路主要包括国道和省道,截止至2015年我国国道里程18.53万km、省道里程32.97万km,约占全国等级公路总里程的13%,因此开展我国国道和省道机动车大气污染物排放研究十分重要.本研究基于全国国道和省道交通监测站的年均监测数据,采用环境保护部发布的《道路机动车大气污染物排放清单编制技术指南(试行)》中的指导方法,计算了2015年我国国道和省道机动车的大气污染物排放清单,分析了污染物排放的时空分布特征.结果表明,我国国道和省道公路机动车排放的一氧化碳(CO)、氮氧化物(NO_x)、颗粒物(PM)和碳氢化合物(HC)排放量分别占全国机动车污染物总排放量的4.5%、27.9%、14.4%和7.7%;不同车型对国道和省道机动车大气污染物排放的分担率不同,其中大货车是NO_x、PM_(10)、PM_(2.5)的主要来源,摩托车是CO和HC的主要来源;不同道路类型中各车型的大气污染物排放分担率也不同,如高速路上大货车是NO_x、PM_(10)和PM_(2.5)的主要来源,普通道路上大客车和大货车是NO_x、PM_(10)和PM_(2.5)的主要来源.     

CEMS比对监测数据偏差研究

简述CEMS比对监测技术背景,总结实际监测工作中导致数据偏差的各方面因素,分析问题产生原因并提出解决措施和建议。     

基于遥感监测的黄海绿潮漂移路径及分布面积特征分析

本文利用2008～2012年的多源卫星遥感序列图像,动态监测各年绿潮发生的漂移路径、影响海域面积,得到各年绿潮漂移趋势、分布面积和最大分布面积出现时间。根据监测结果,划分出影响绿潮漂移路径的关键区域,并分析了2008、2009和2010年关键区域内各年绿潮漂移方向和面积变化情况。     

适应性环境管理模式在大型赛事筹备中的应用（上）——管理模式构建

针对我国环境保护行政管理存在的直线式管理、缺乏弹性等问题,将适应性管理的理论和方法引入环境管理领域,提出适应性环境管理的概念和管理模式,通过构建基于AHP（层次分析法）的适应性环境管理绩效评估体系,在环境管理中对各项任务进行跟踪管理和绩效评估,反馈于阶段性目标的制定,从而灵活调整工作方案,最大限度地降低环境管理中的不确定性,保证环境管理总目标的达成.