Massachusetts v. Environmental Protection Agency: Constructing “Certainty” as Rebuttal

Massachusetts v. Environmental Protection Agency was the first Supreme Court opinion generated specifically as a response to the issue of anthropogenic CO₂ emissions, alleging that Environmental Protection Agency's (EPA) failure to regulate is leading to environmental harms for plaintiffs. This essay examines the majority opinion of Justice Stevens and his use of presumption and burden of proof, within a logic of problematic integration, to construct “certainty” as a rebuttal to and rejection of the “uncertainty” offered by EPA. I examine how this strategically constructed rebuttal to “uncertainty” functions as a declarative act of “certainty,” advancing a proposition whose scientific, legal, or political acceptance could function as a tipping point away from the claims of “uncertainty” used by opponents on this contentious issue. Because of the court's influence, the implications of their “certainty” extend beyond the case and into the broader discussion of climate change science and environmental communication.     

Inexact multistage stochastic integer programming for water resources management under uncertainty

In this study, an inexact multistage stochastic integer programming (IMSIP) method is developed for water resources management under uncertainty. This method incorporates techniques of inexact optimization and multistage stochastic programming within an integer programming framework. It can deal with uncertainties expressed as both probabilities and discrete intervals, and reflect the dynamics in terms of decisions for water allocation through transactions at discrete points of a complete scenario set over a multistage context. Moreover, the IMSIP can facilitate analyses of the multiple policy scenarios that are associated with economic penalties when the promised targets are violated as well as the economies-of-scale in the costs for surplus water diversion. A case study is provided for demonstrating the applicability of the developed methodology. The results indicate that reasonable solutions have been generated for both binary and continuous variables. For all scenarios under consideration, corrective actions can be undertaken dynamically under various pre-regulated policies and can thus help minimize the penalties and costs. The IMSIP can help water resources managers to identify desired system designs against water shortage and for flood control with maximized economic benefit and minimized system-failure risk.     

Database uncertainty as a limiting factor in reactive transport prognosis

The effect of uncertainties in thermodynamic databases on prediction performances of reactive transport modeling of uranium (VI) is investigated with a Monte Carlo approach using the transport code TReaC. TReaC couples the transport model to the speciation code PHREEQC by a particle tracking method. A speciation example is given to illustrate the effect of uncertainty in thermodynamic data on the predicted solution composition. The transport calculations consequently show the prediction uncertainty resulting from uncertainty in thermodynamic data. A conceptually simple scenario of elution of uranium from a sand column is used as an illustrating example. Two different cases are investigated: a carbonate-enriched drinking water and an acid mine water associated with uranium mine remediation problems. Due to the uncertainty in the relative amount of positively charged and neutral solution species, the uncertainty in the thermodynamic data also infers uncertainty in the retardation behavior. The carbonated water system shows the largest uncertainties in speciation calculation. Therefore, the model predictions of total uranium solubility have a broad range. The effect of data uncertainty in transport prediction is further illustrated by a prediction of the time when eluted uranium from the column exceeds a threshold value. All of these Monte Carlo transport calculations consume large amounts of computing time.     

利用top down控制图评定库伦法测定煤中全硫的不确定度

利用top-down控制图评定库伦法测定煤中全硫的不确定度，通过对标准煤品的多次测试结果计算正态统计量，并对数据的正态性和独立性作判别，在确保数据随机排列的基础上，计算期间精密度标准差，最终得到该项目的不确定度评定结果。     

How rational are investment decisions in the copper industry?

This paper examines ex-post 51 investment decisions made in regard to copper mines coming on stream from 1957 through 1999. It discusses two critical variables: investment timing and mine capacity choice. Using a 15% discount rate, results suggest that fewer than half of decisions were made at the right time – i.e., low price periods – confirming countercyclical investment as the optimal policy. In terms of capacity choice, the distortion is even higher, as 36 projects should have entered at least 40% larger or smaller. Realized investment decisions for timing and capacity choice would have caused a 49.1% loss over the NPV potentially achievable under optimal resolutions. Although the difference could be specifically attributed to copper price uncertainty, this paper discusses how investment evaluation methodologies could be contributing to firms not being fully rational (in the neoclassical sense) when investing.     

The use of experimental data and their uncertainty for assessing ozone photochemistry in the Eastern Iberian Peninsula

Observation-based methods are useful tools to explore the sensitivity of ozone concentrations to precursor controls. With the aim of assessing the ozone precursor sensitivity in two locations: Paterna (suburban) and Villar del Arzobispo (rural) of the Turia river basin in the east of Spain, the photochemical indicator O₃/NO_y and the Extent-of-Reaction (EOR) parameter have been calculated from field measurements. In Paterna, the O₃/NO_y ratio varied from 0 to 13 with an average value of 5.1 (SD 3.2), whereas the averaged value for the EOR was 0.43 (SD 0.14). In Villar del Arzobispo, the O₃/NO_y ratio changed from 5 to 30 with a mean value of 13.6 (SD 4.7) and the EOR gave an averaged value of 0.72 (SD 0.11). The results show two different patterns of ozone production as a function of the location. The suburban area shows a VOC-sensitive regime whereas the rural one shows a transition regime close to NO_x-sensitive conditions. No seasonal differences in these regimes are observed along the monitoring campaigns. Finally, an analysis of the influence of the measurement quality of NO_y, NO_x and O₃ on the uncertainty of the O₃/NO_y ratio and the EOR was performed showing that the uncertainty of O₃/NO_y is not dependent on either its value or the individual values of O₃ and NO_y but just on the quality of O₃ and NO_y measurements. The maximum uncertainty is 26% as long as the combined uncertainties of O₃ and NO_y remain below the 7.5%. The case of the EOR is different and its uncertainty depends on both the value of the EOR parameter and the individual concentration values of NO_y and NO_x. The uncertainty of the EOR estimation can be very high (>200%) if the combined uncertainties of both NO_y and NO_x are high (>7.5%), or especially, if u(NO_y) and u(NO_x) differ considerably from each other (>3.5%).     

Including risk in stated-preference economic valuations: Experiments on choices for marine recreation

Stated-preference surveys for the economic valuation of environmental resources typically assume no uncertainty in the hypothetical valuation scenarios. However, the outcomes of environmental policies are uncertain. We explored the effects of including information on probabilities of attribute improvement and provision in choice experiments. Our results suggest that stating explicitly a high probability for the occurrence of the valuation scenario can improve the goodness of fit of choice models and the consistency of choices. As the general public becomes more aware of the uncertainty of environmental outcomes under global change, omitting information on scenario risk may contribute to hypothetical bias and impair the validity of stated-preference valuations.     

Comparison of first-order-decay modeled and actual field measured municipal solid waste landfill methane data

The first-order decay (FOD) model is widely used to estimate landfill gas generation for emissions inventories, life cycle assessments, and regulation. The FOD model has inherent uncertainty due to underlying uncertainty in model parameters and a lack of opportunities to validate it with complete field-scale landfill data sets. The objectives of this paper were to estimate methane generation, fugitive methane emissions, and aggregated collection efficiency for landfills through a mass balance approach using the FOD model for gas generation coupled with literature values for cover-specific collection efficiency and methane oxidation. This study is unique and valuable because actual field data were used in comparison with modeled data. The magnitude and variation of emissions were estimated for three landfills using site-specific model parameters and gas collection data, and compared to vertical radial plume mapping emissions measurements. For the three landfills, the modeling approach slightly under-predicted measured emissions and over-estimated aggregated collection efficiency, but the two approaches yielded statistically equivalent uncertainties expressed as coefficients of variation. Sources of uncertainty include challenges in large-scale field measurement of emissions and spatial and temporal fluctuations in methane flow balance components (generated, collected, oxidized, and emitted methane). Additional publication of sets of field-scale measurement data and methane flow balance components will reduce the uncertainty in future estimates of fugitive emissions.     

Assessment of uncertainties in a long range atmospheric transport model: Methodology, application and implications in a UK context

Acid deposition models are inherently simplified representations of real world behaviour and their performance is best evaluated by comparison with observations. National and international acid rain policy assessments handle observed and modelled deposition fields in different ways. Here, both the observed and modelled deposition fields are seen as uncertain and the Generalised Likelihood Uncertainty Estimation (GLUE) framework is used to choose acceptable sets of model input parameters that minimise the differences between them. These acceptable sets of model parameters are then used to estimate deposition budgets to the UK and to provide a probabilistic treatment of excess deposition over environmental quality standards (critical loads).     

Evaluation of uncertainties originating from the different modeling approaches applied to analyze regional groundwater flow in the Tono area of Japan

Qualitative evaluation of the effects of uncertainties originating from scenario development, modeling approaches, and parameter values is an important subject in the area of safety assessment for high-level nuclear waste disposal sites. In this study, regional-scale groundwater flow analyses for the Tono area, Japan were conducted using three continuous models designed to handle heterogeneous porous media. We evaluated the simulation results to quantitatively analyze uncertainties originating from modeling approaches. We found that porous media heterogeneity is the main factor which causes uncertainties. We also found that uncertainties originating from modeling approaches greatly depend on the types of hydrological structures and heterogeneity of hydraulic conductivity values in the domain assigned by modelers. Uncertainties originating from modeling approaches decrease as the amount of labor and time spent increase, and iterations between investigation and analyses increases.