原子荧光法测砷的测量不确定度评定报告

根据原子荧光光度法,用吉天AFS－830原子荧光光度计测定水样中的总砷,并且分析了主要的测量不确定度来源,即工作曲线不确定度、标准溶液不确定度、测量重复性不确定度和仪器分辨率不确定度,分别量化后合成测得总砷的测量不确定度。     

水中挥发酚的测量不确定度评定

建立了分光光度法测定水中挥发酚的合成标准不确定度的数学模式,它由质量的标准测量不确定度和体积的标准测量不确定度组成。应用一个实例对这两部分标准不确定度的分量作了详尽的分析和计算,得出测量扩展不确定度结果。     

Enforcement and price controls in emissions trading

This paper examines how enforcement affects the structure and performance of emissions trading programs with price controls under uncertainty about firms' abatement costs. The analysis highlights how an enforcement strategy can cause abatement-cost risk to be transmitted to enforcement costs via the price of permits. When this occurs, accommodating the effect of abatement-cost risk with an optimal policy results in higher expected emissions and lower expected permit price than their second-best optimal values. However, it is possible to design an enforcement strategy that shields enforcement costs from abatement-cost risk by tying sanctions directly to permit prices. This enforcement strategy stabilizes enforcement effort, the optimal permit supply and price controls are independent of enforcement costs, and the policy produces the second-best optimal outcome.     

Uncertainties in a risk management context in early phases of offshore petroleum field development

The current risk management approach for the Norwegian offshore petroleum industry came into effect in 2001 and has been stable with minor changes for 15 years. Relatively few new installations were slated for development until quite recently, and several new projects have been started in the last few years. The paper considers the risk management approach in the pre-FEED phase and builds on two case studies selected from the most recent cases. These case studies have been evaluated with respect to how uncertainties are considered in the early phase, based on the submission of the Plan for Development and Operation, their evaluations by authorities and the supporting documents. Both case studies involve new concepts for which there is no experience from similar environments and/or water depths. In spite of what could have been expected, the case studies conclude that uncertainties have not been in focus at all during concept development. This appears to be definitely the case for the licensees, but also to be the case for the authorities. Some suggestions are presented for what could have been considered by the licensees and authorities.     

Crediting uncertain ecosystem services in a market

The margin of safety (MOS) approach is an increasingly prevalent tool for ensuring the integrity of market-based programs for providing ecosystem services. Over-crediting is reduced by setting aside mean estimates of uncertain services in favor of a more conservative estimate. Like many environmental policy problems, ecosystem service markets involve the aggregation of uncertainty over multiple scales, e.g. from landowners to market intermediaries to the overall market. We examine how the MOS instrument affects, and is affected by, an ecosystem services market. We show that the common bottom-up approach of imposing risk preferences at a local, disaggregated level—held over from earlier development in the context of toxics and command and control-style health risk regulation—leads to several unintended consequences. Furthermore, discounting landowner services can actually increase their profits, conditional on the elasticity of credit demand. We illustrate theoretical insights with an empirical application to greenhouse gas offset crediting in agriculture.     

Sensitivity analysis of North American bird population estimates

The Partners in Flight North American Landbird Conservation Plan provided estimates of population sizes for 448 landbird species using a multiplicative model. Input parameters in this calculation included the area of state × Bird Conservation Region polygons, area-specific mean Breeding Bird Survey counts circa 1995, and adjustment factors for the distance over which species may presumably be correctly counted, the assumed pairing of singing males with non-singing females, and variability in the propensity of birds to sing over the course of the survey day. I assessed the sensitivity of this population calculation to changes in the input parameters. I assessed both local and global sensitivity of the model to changes in the parameters with Monte Carlo one-at-a-time simulations and the Fourier amplitude sensitivity test (FAST). Monte Carlo simulations were an estimate of local model sensitivity whereas FAST estimated global model sensitivity, accommodating the potential shared variance between model parameters. Monte Carlo simulations suggested population estimates were 39% more sensitive to changes in the detection distance adjustment than to the other parameters; the other parameters were nearly equal in their contribution to model sensitivity. Conversely, FAST analysis determined that each of the input variables aside from the pair adjustment provided roughly equal contributions to variability in population estimates. The most efficient means for improving continental population estimates for birds surveyed by the Breeding Bird Survey will be through increased scrutiny of the species-specific distance detection and time-of-day adjustments and improved understanding in the spatial and temporal variability in the mean Breeding Bird Survey count.     

Ecosystem network analysis indicators are generally robust to parameter uncertainty in a phosphorus model of Lake Sidney Lanier, USA

Understanding how data uncertainty influences ecosystem analysis is critical as we move toward ecosystem-based management. Here, we investigate how 18 Ecological Network Analysis (ENA) indicators that characterize ecosystem growth, development, and condition are affected by uncertainty in an ecosystem model of Lake Sidney Lanier (USA). We applied ENA to 122 plausible parameterizations of the ecosystem developed by Borrett and Osidele (2007, Ecological Modelling 200, 371-387), and then used the coefficient of variation (CV) to compare system indicator variability. We considered Total System Throughput (TST) as a measure of the underlying model uncertainty and tested three hypotheses. First, we hypothesized that non-ratio indicators whose calculation includes the TST would be at least as variable as TST if not more variable. Second, we postulated that indicators calculated as ratios, with TST in the numerator and denominator would tend to be less variable than TST because its influence will cancel. Last, we expected the Average Mutual Information (AMI) to be less variable than TST because it is a bounded function. Our work shows that the 18 indicators grouped into four categories. The first group has significantly larger CVs than the CV for TST. In this group, model uncertainty is amplified rendering these three indicators less useful. The second group of four indicators shows no significant difference in variability with respect to TST. Finally, there are two groups whose CV values are significantly lower than that for TST. The least variable group includes the ratio-based indicators and Average Mutual Information. Due to their low variability, we conclude that these indicators are the most robust to the parameter uncertainty and most useful for ecosystem assessment and comparative ecosystem analysis. In summary, this work suggests that we can be as certain, or more certain, in most of the selected ENA indicators as we are in the parameters of the model analyzed.     

An Integrated Monte Carlo Methodology for the calibration of water quality models

This paper proposes an Integrated Monte Carlo Methodology (IMCM) to solve the parameter estimation problem in water quality models. The methodology is based on Bayesian approach and Markov Chain Monte Carlo techniques and it operates by means of four modules: Markov Chain Monte Carlo (MCMC), Moving Feasible Ranges (MFR), Statistical Analysis of the Joint Posterior Distribution (SAD) and Uncertainty Propagation Analysis (UPA). The main innovation of the new proposal lies in the combination of MCMC and MFR modules which provides the joint posterior distribution of the calibrated parameters following the classical Bayesian approach. While MCMC module, based on Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm, is specially designed to sample complex joint posterior shapes within certain parameter ranges, the MFR readjusts these ranges until the coverage of the feasible parameter space is guaranteed. Once the joint posterior distribution is properly defined, the SAD provides the parameter statistics and the UPA performs an analysis of the uncertainty propagation through the model. The possibilities of the new proposal have been tested on the basis of a simple model featuring different activated sludge batch experiments. IMCM has been implemented in Matlab and it is prepared to be easily connected to any software package.