甲醇中十氯酮溶液标准样品不确定度评定

介绍了甲醇中十氯酮溶液标准样品的研制过程,该标准样品采用称量法制备,用气相色谱质谱法进行均匀性检验和稳定性检测,对不确定度来源进行了全面评估,并与国际同类标准样品进行了量值比对分析。结果表明：该溶液标准样品均匀性良好,在18个月内质量稳定,与国外同类标准样品具有量值一致性,可用于环境监测和科学研究工作。     

湿地甲烷排放估算模型的研究进展

湿地是大气甲烷（CH₄）的主要排放源,大气甲烷排放量的日益增加,给全球气候变化带来很大影响,准确估算湿地甲烷的排放量意义重大。目前湿地甲烷排放量估算模型主要有经验模型、机理过程模型和遥感参数模型,通过对三种模型的发展过程、应用状况及优缺点的对比分析和总结,分析了湿地甲烷排放、监测过程及模型估算方面的不确定性,指出了湿地甲烷排放估算的发展趋势,提出遥感参数模型将是湿地甲烷排放估算模型今后的发展方向。     

气候试验箱内部条件不确定度计算(下)

提供了对温度和湿度气候试验箱内部环境条件进行不确定度分析的方法。首先介绍了测量的不确定度概念,然后讨论容差的意义。考虑到湿度和温度测量是采用确定和合成不确定度。结合校准空载试验箱和有负载试验箱的条件测量的案例。最后,逐条整理成为范本用于分析结果以给出规范的不确定度评估依据。     

Testing the feasibility of a hypothetical whaling‐conservation permit market in Norway

A cap‐and‐trade system for managing whale harvests represents a potentially useful approach to resolve the current gridlock in international whale management. The establishment of whale permit markets, open to both whalers and conservationists, could reveal the strength of conservation demand, about which little is known. This lack of knowledge makes it difficult to predict the outcome of a hypothetical whale permit market. We developed a bioeconomic model to evaluate the influence of economic uncertainty about demand for whale conservation or harvest. We used simulations over a wide range of parameterizations of whaling and conservation demands to examine the potential ecological consequences of the establishment of a whale permit market in Norwegian waters under bounded (but substantial) economic uncertainty. Uncertainty variables were slope of whaling and conservation demand, participation level of conservationists and their willingness to pay for whale conservation, and functional forms of demand, including linear, quadratic, and log‐linear forms. A whale‐conservation market had the potential to yield a wide range of conservation and harvest outcomes, the most likely outcomes were those in which conservationists bought all whale permits.     

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.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

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。     

Uncertainty in Agricultural CH<Subscript>4</Subscript> AND N<Subscript>2</Subscript>O Emissions from Finland – Possibilities to Increase Accuracy in Emission Estimates

According to the United Nations Framework Convention on Climate Change (UNFCCC) and Kyoto Protocol under it, industrial countries have to estimate their greenhouse gas emissions annually, and assess the uncertainties in these estimates. In Finland, agricultural methane (CH₄) and nitrous oxide (N_2O) emissions represent 7% of anthropogenic greenhouse gas emissions, and globally the share is much higher. Agriculture is one of the most uncertain emission categories (representing over 20% of greenhouse gas inventory uncertainty in Finland), due to both high natural variability of the emission sources and poor knowledge of the emission-generating processes. In this paper, we present an uncertainty estimate of agricultural CH₄ and N₂O emissions from Finland in 2002. Uncertainties were estimated based on measurement data, literature and expert judgement, and total uncertainty in agriculture was calculated using Monte Carlo simulation. According to the calculations, agricultural CH₄ and N₂O emissions from Finland were 3.7 to 7.8 Tg carbon dioxide (CO₂) equivalents, 5.4 Tg being the mean value.Estimates of CH₄ emissions are more reliable than those of N₂O. N₂O from agricultural soils was the most uncertain emission category, and the uncertainty was not reduced by using available national measurement data of N₂O fluxes. Sensitivity study revealed that the uncertainty in total agricultural inventory could be 7% points lower, if more accurate emission estimation methods were used, including 1) improved data collection in area estimates of organic soils, 2) climate-specific methods for N₂O from agricultural soils as already presented in literature, and 3) more detailed CH₄ estimation methods for enteric fermentation which can be achieved by investigating national circumstances and digestible systems of animals in more detail.     

测量不确定度在空气自动监测中的应用

根据测量原理建立数学模型，分析各种不确定分量的来源，评定标准不确定度，确定合成不确定度和扩展不确定度。通过不确定影响分量的分析，找出最大不确定分量，重点控制其分量，可保证测量的准确性和精度，也可通过重新评估显著性不确定分量，找出方法存在的不足和问题，提出控制不确定分量的步骤和方法，改善测量方法和手段提高测量准确性和精度。     

Informational uncertainties of risk assessment about accidents of chemicals

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