Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

CO2 capture and storage from a bioethanol plant: Carbon and energy footprint and economic assessment

Biomass energy and carbon capture and storage (BECCS) can lead to a net removal of atmospheric CO₂. This paper investigates environmental and economic performances of CCS retrofit applied to two mid-sized refineries producing ethanol from sugar beets. Located in the Region Centre France, each refinery has two major CO₂ sources: fermentation and cogeneration units. “carbon and energy footprint” (CEF) and “discounted cash flow” (DCF) analyses show that such a project could be a good opportunity for CCS early deployment. CCS retrofit on fermentation only with natural gas fired cogeneration improves CEF of ethanol production and consumption by 60% without increasing much the non renewable energy consumption. CCS retrofit on fermentation and natural gas fired cogeneration is even more appealing by decreasing of 115% CO₂ emissions, while increasing non renewable energy consumption by 40%. DCF shows that significant project rates of return can be achieved for such small sources if both a stringent carbon policy and direct subsidies corresponding to 25% of necessary investment are assumed. We also underlined that transport and storage cost dilution can be realistically achieved by clustering emissions from various plants located in the same area. On a single plant basis, increasing ethanol production can also produce strong economies of scale.     

Precaution,uncertainty and causation in environmental decisions

What measures of uncertainty and what causal analysis can improve the management of potentially severe, irreversible or dreaded environmental outcomes? Environmental choices show that policies intended to be precautionary (such as adding MTBE to petrol) can cause unanticipated harm (by mobilizing benzene, a known leukemogen, in the ground water). Many environmental law principles set the boundaries of what should be done but do not provide an operational construct to answer this question. Those principles, ranging from the precautionary principle to protecting human health from a significant risk of material health impairment, do not explain how to make environmental management choices when incomplete, inconsistent and complex scientific evidence characterizes potentially adverse environmental outcomes. Rather, they pass the task to lower jurisdictions such as agencies or authorities. To achieve the goals of the principle, those who draft it must deal with scientific casual conjectures, partial knowledge and variable data. In this paper we specifically deal with the qualitative and quantitative aspects of the European Union's (EU) explanation of consistency and on the examination of scientific developments relevant to variability and uncertain data and causation. Managing hazards under the precautionary principle requires inductive, empirical methods of assessment. However, acting on a scientific conjecture can also be socially unfair, costly, and detrimental when applied to complex environmental choices. We describe a constructive framework rationally to meet the command of the precautionary principle using alternative measures of uncertainty and recent statistical methods of causal analysis. These measures and methods can bridge the gap between conjectured future irreversible or severe harm and scant scientific evidence, thus leading to more confident and resilient social choices. We review two sets of measures and computational systems to deal with uncertainty and link them to causation through inductive empirical methods such as Bayesian Networks. We conclude that primary legislation concerned with large uncertainties and potential severe or dreaded environmental outcomes can produce accurate and efficient choices. To do so, primary legislation should specifically indicate what measures can represent uncertainty and how to deal with uncertain causation thus providing guidance to an agency's rulemaking or to an authority's writing secondary legislation. A corollary conclusion with legal, scientific and probabilistic implications concerns how to update past information when the state of information increases because a failure to update can result in regretting past choices. Elected legislators have the democratic mandate to formulate precautionary principles and are accountable. To preserve that mandate, imbedding formal methods to represent uncertainty in the statutory language of the precautionary principle enhances subsequent judicial review of legislative actions. The framework that we propose also reduces the Balkanized views and interpretations of probabilities, possibilities, likelihood and uncertainty that exists in environmental decision-making.     

First-trimester prenatal diagnosis of Sanfilippo C disease

At 10 weeks' gestation, chorionic villus biopsy was obtained from a woman at risk for Sanfilippo type C disease. Acetyl-CoA: α-glucosaminide N-acetyltransferase activity was markedly deficient. The pregnancy was terminated at 12 weeks' gestation and follow-up study on fetal fibroblasts confirmed the diagnosis.     

The protection of wildlife from mortality: hypothesis and results for risk assessment

Wildlife deaths associated with cyanide-bearing tailings dams are a significant environmental issue that has affected the gold mining industries for many years and still characterized by little knowledge about how to measure, monitoring, reduce or eliminate those deaths. The purpose of this paper is statistically to determine: the potential for establishing causal relations between exposure to cyanide (in its most common species relevant to tailings) and response (measured by death counts), to develop a protocol of data analysis, the understanding of the significance of data gaps, and the effect of likely risk management interventions to achieve the goals of the International Cyanide Management Code (ICMC); [ICMC The International Cyanide Management Institute. International cyanide management code, the international cyanide management institute 2005, www.cyanidecode.org.]. However, operator's certification under the ICMC is difficult because of the limited data and potentially serious under-estimation of the death counts. This is due to observational skill and monitoring frequency, the small size of the carcasses, large extent of tailings facilities, carcasses loss by; entombment in tailings, sink, or taken by scavenging wildlife. This (1st order or bounding) assessment results focus on bird-deaths, which appear to be most frequent at sites where elevated cyanide concentrations are found. Those results indicate that the empirical causal associations we generate support the hypotheses that: This paper also develops the basis for a complete risk assessment study to be based on additional data gathering activities and detailed statistical analyses. These two activities, combined with a risk management plan also being developed, will provide a tool for compliance with the ICMC.     

Causation in risk assessment and management: models, inference, biases, and a microbial risk-benefit case study

Causal inference of exposure-response relations from data is a challenging aspect of risk assessment with important implications for public and private risk management. Such inference, which is fundamentally empirical and based on exposure (or dose)-response models, seldom arises from a single set of data; rather, it requires integrating heterogeneous information from diverse sources and disciplines including epidemiology, toxicology, and cell and molecular biology. The causal aspects we discuss focus on these three aspects: drawing sound inferences about causal relations from one or more observational studies; addressing and resolving biases that can affect a single multivariate empirical exposure-response study; and applying the results from these considerations to the microbiological risk management of human health risks and benefits of a ban on antibiotic use in animals, in the context of banning enrofloxacin or macrolides, antibiotics used against bacterial illnesses in poultry, and the effects of such bans on changing the risk of human food-borne campylobacteriosis infections. The purposes of this paper are to describe novel causal methods for assessing empirical causation and inference; exemplify how to deal with biases that routinely arise in multivariate exposure- or dose-response modeling; and provide a simplified discussion of a case study of causal inference using microbial risk analysis as an example. The case study supports the conclusion that the human health benefits from a ban are unlikely to be greater than the excess human health risks that it could create, even when accounting for uncertainty. We conclude that quantitative causal analysis of risks is a preferable to qualitative assessments because it does not involve unjustified loss of information and is sound under the inferential use of risk results by management.     

A Multimethodological Approach for the Sustainable Management of Perifluvial Wetlands of the Po River (Italy)

/ Marginal aquatic systems (wetlands) of the Po River (Italy) have become the target of a renewed interest because of their value for recreation, natural reserves, and deposits of sand. To preserve these sites, wise management must be the objective of local administrations. In this paper a strategy for the sustainable use of 11 wetlands is presented. It uses simple economic analysis and multiple criteria techniques and provides suggestions to promote sustainability in terms of conservation of natural resources, economic self-sufficiency, and minimization of potential conflicts about the use of the wetlands. In the understanding that sustainability is framed in a long-term perspective, stability analysis is also considered and performed by means of loop analysis, a qualitative technique. Conditions for stability are then discussed about management opportunities.     

The clinical impact of the first-trimester nuchal translucency between the 95th–99th percentiles

Objectives

To evaluate the clinical significance of nuchal translucency (NT) between the 95th–99th percentile in terms of typical and atypical chromosomal abnormalities (ACAs), associated fetal congenital defects and postnatal outcome.

Methods

A retrospective cohort study of fetuses with NT between the 95th–99th percentile. Data regarding the rate of associated fetal defects, genetic abnormalities and postnatal outcome were collected.

Results

A total of 306 cases of fetuses with an NT between the 95th–99th percentiles were included. The overall rate of genetic abnormalities was 12.1% (37/306). Chromosomal abnormalities were found in 10.1% (31/306) of cases and 2% were ACA (6/306). Within this group, two were pathogenic Copy Number Variants (CNVs) and four were single gene disorders. The overall rate of fetal congenital defects was 13.7% (42/306). All ACAs were found in fetuses with congenital defects. Postnatally, a new diagnosis of a single gene disorder was made in 0.85% of cases (2/236).

Conclusions

The presence of an NT between the 95th–99th percentiles carries a 10-fold increased risk of fetal defects, representing an indication for referral for a detailed fetal anatomy evaluation. The risk of ACA is mainly related to the presence of fetal defects, irrespective of the combined test risk.     

Integration of ozonation and an anaerobic expanded granular sludge bed reactor for micropollutant removal from sewage

Environmental Science and Pollution Research - Conventional sewage treatment systems are generally not designed to remove micropollutants, requiring the development of new technologies, such as the...     

Acceptable Cancer Risks: Probabilities and Beyond

The acceptability of cancer risk requires consideration of factors that extend beyond mere numerical representations, such as either individual lifetime risk in excess of background and excess incidence. Recently, use of these numbers has been tempered by the addition of qualitative weights-of-evidence that describe the degree of support provided by animal and epidemiologic results. Nevertheless, many other factors, most of which are not quantitative, require incorporation but remain neglected by the analyst eager to use quantitative results.

In this paper we show that simple risk measures are often fraught with problems. Moreover, these measures do not incorporate the very essence of acceptability, which includes notions of responsibility, accountability, equity, and procedural legitimacy, among others. We link the process of risk assessment to those legal and regulatory standards that shape it. These standards are among the principal means to resolve risk-related disputes and to enhance the balancing of competing interests when science and law meet on uncertain and often conjectural ground.

We conclude the paper with a proposal for the portfolio approach to manage cancer risks and to deal with uncertain scientific information. This approach leads to the concept of "provisional acceptability," which reflects the choices available to the decisionmaker, and the trade-offs inherent to such choices.