Probabilistic cost benefit analysis of generation investment in a deregulated electricity market

A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.

Development of a probabilistic graphical structure from a model of mental health clinical expertise

This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

An aquatic risk assessment of ethion and bromacil inputs to the C-25 Canal and Indian River Lagoon

Pesticide monitoring in St. Lucie County by various local, state and federal agencies has indicated consistent residues of several pesticides, including ethion and bromacil. Although pesticides have long been known to pose a threat to non-target species and much background monitoring has been done, no pesticide aquatic risk assessment has been done in this geographical area. Several recognized United States Environmental Protection Agency (USEPA) methods of quantifying risk are employed here to include hazard quotients (HQ) and probabilistic modeling with sensitivity analysis. These methods are employed to characterize potential impacts to aquatic biota of the C-25 Canal and the Indian River Lagoon (in St. Lucie County, Florida) based on current agricultural pesticide use and drainage patterns. The model used in the analysis incorporates available physical-chemical property data, local hydrology, ecosystem information, and pesticide use practices. HQ's, probabilistic distributions, and field sample analyses resulted in high levels of concern (LOCs), which usually indicates a need for regulatory action, including restrictions on use, or cancellation. ^

A probabilistic approach to assess hydrate formation and design preventive measures

Formation of hydrates is one of the major flow assurance problems faced by the oil and gas industry. Hydrates tend to form in natural gas pipelines with the presence of water and favorable temperature and pressure conditions, generally low temperatures and corresponding high pressures. Agglomeration of hydrates can result in blockage of flowlines and equipment, which can be time consuming to remove in subsea equipment and cause safety issues. Natural gas pipelines are more susceptible to burst and explosion owing to hydrate plugging. Therefore, a rigorous risk-assessment related to hydrate formation is required, which assists in preventing hydrate blockage and ensuring equipment integrity. This thesis presents a novel methodology to assess the probability of hydrate formation and presents a risk-based approach to determine the parameters of winterization schemes to avoid hydrate formation in natural gas pipelines operating in Arctic conditions. It also presents a lab-scale multiphase flow loop to study the effects of geometric and hydrodynamic parameters on hydrate formation and discusses the effects of geometric and hydrodynamic parameters on multiphase development length of a pipeline. Therefore, this study substantially contributes to the assessment of probability of hydrate formation and the decision making process of winterization strategies to prevent hydrate formation in Arctic conditions.

On the Advancement of Probabilistic Models of Decompression Sickness

The work presented in this dissertation is focused on applying engineering methods to develop and explore probabilistic survival models for the prediction of decompression sickness in US NAVY divers. Mathematical modeling, computational model development, and numerical optimization techniques were employed to formulate and evaluate the predictive quality of models fitted to empirical data. In Chapters 1 and 2 we present general background information relevant to the development of probabilistic models applied to predicting the incidence of decompression sickness. The remainder of the dissertation introduces techniques developed in an effort to improve the predictive quality of probabilistic decompression models and to reduce the difficulty of model parameter optimization.

The first project explored seventeen variations of the hazard function using a well-perfused parallel compartment model. Models were parametrically optimized using the maximum likelihood technique. Model performance was evaluated using both classical statistical methods and model selection techniques based on information theory. Optimized model parameters were overall similar to those of previously published Results indicated that a novel hazard function definition that included both ambient pressure scaling and individually fitted compartment exponent scaling terms.

We developed ten pharmacokinetic compartmental models that included explicit delay mechanics to determine if predictive quality could be improved through the inclusion of material transfer lags. A fitted discrete delay parameter augmented the inflow to the compartment systems from the environment. Based on the observation that symptoms are often reported after risk accumulation begins for many of our models, we hypothesized that the inclusion of delays might improve correlation between the model predictions and observed data. Model selection techniques identified two models as having the best overall performance, but comparison to the best performing model without delay and model selection using our best identified no delay pharmacokinetic model both indicated that the delay mechanism was not statistically justified and did not substantially improve model predictions.

Our final investigation explored parameter bounding techniques to identify parameter regions for which statistical model failure will not occur. When a model predicts a no probability of a diver experiencing decompression sickness for an exposure that is known to produce symptoms, statistical model failure occurs. Using a metric related to the instantaneous risk, we successfully identify regions where model failure will not occur and identify the boundaries of the region using a root bounding technique. Several models are used to demonstrate the techniques, which may be employed to reduce the difficulty of model optimization for future investigations.

Public Risk Interpretation and Community Resilience Planning: A Case Study in Aberdeen, Washington

Thesis (Master's)--University of Washington, 2016-06

The Use of Multi-Criteria Decision Analysis in Performing Alternatives Assessment and Comparative Risk Analysis: The Case Study of Codling Moth Pesticides

Thesis (Ph.D.)--University of Washington, 2016-08

Is there a health risk concerning the children´s consumption of cereal-based products? A cumulative mycotoxin risk assessment approach

Historically, the health risk of mycotoxins had been evaluated on the basis of single-chemical and single-exposure pathway scenarios. However, the co-contamination of foodstuffs with these compounds is being reported at an increasing rate and a multiple-exposure scenario for humans and vulnerable population groups as children is urgently needed. Cereals are among the first solid foods eaten by child and thus constitute an important food group of their diet. Few data are available relatively to early stages child´s exposure to mycotoxins through consumption of cereal-based foods. The present study aims to perform the cumulative risk assessment of mycotoxins present in a set of cereal-based foods including breakfast cereals (BC), processed cereal-based foods (PCBF) and biscuits (BT), consumed by children (1 to 3 years old, n=75) from Lisbon region, Portugal. Children food consumption and occurrence of 12 mycotoxins (aflatoxins, ochratoxin A, fumonisins and trichothecenes) in cereal-based foods were combined to estimate the mycotoxin daily intake, using deterministic and probabilistic approaches. Different strategies were used to treat the left censored data. For aflatoxins, as carcinogenic compounds, the margin of exposure (MoE) was calculated as a ratio of BMDL (benchmark dose lower confidence limit) and aflatoxin daily exposure. For the remaining mycotoxins, the output of exposure was compared to the dose reference values (TDI) in order to calculate the hazard quotients (HQ, ratio between exposure and a reference dose). The concentration addition (CA) concept was used for the cumulative risk assessment of multiple mycotoxins. The combined margin of exposure (MoET) and the hazard index (HI) were calculated for aflatoxins and the remaining mycotoxins, respectively. Main results revealed a significant health concern related to aflatoxins and especially aflatoxin M1 exposure according to the MoET and MoE values (below 10000), respectively. HQ and HI values for the remaining mycotoxins were below 1, revealing a low concern from a public health point of view. These are the first results on cumulative risk assessment of multiple mycotoxins present in cereal-based foods consumed by children. Considering the present results, more research studies are needed to provide the governmental regulatory bodies with data to develop an approach that contemplate the human exposure and, particularly, children, to multiple mycotoxins in food. The last issue is particularly important considering the potential synergistic effects that could occur between mycotoxins and its potential impact on human and, mainly, children health.

Combined exposure to multiple mycotoxins in food: are we ready for risk assessment and risk management?

It is nowadays recognized that the risk of human co-exposure to multiple mycotoxins is real. In the last years, a number of studies have approached the issue of co-exposure and the best way to develop a more precise and realistic assessment. Likewise, the growing concern about the combined effects of mycotoxins and their potential impact on human health has been reflected by the increasing number of toxicological studies on the combined toxicity of these compounds. Nevertheless, risk assessment of these toxins, still follows the conventional paradigm of single exposure and single effects, incorporating only the possibility of additivity but not taking into account the complex dynamics associated to interactions between different mycotoxins or between mycotoxins and other food contaminants. Considering that risk assessment is intimately related to the establishment of regulatory guidelines, once the risk assessment is completed, an effort to reduce or manage the risk should be followed to protect public health. Risk assessment of combined human exposure to multiple mycotoxins thus poses several challenges to scientists, risk assessors and risk managers and opens new avenues for research. This presentation aims to give an overview of the different challenges posed by the likelihood of human co-exposure to mycotoxins and the possibility of interactive effects occurring after absorption, towards knowledge generation to support a more accurate human risk assessment and risk management. For this purpose, a physiologically-based framework that includes knowledge on the bioaccessibility, toxicokinetics and toxicodynamics of multiple toxins is proposed. Regarding exposure assessment, the need of harmonized food consumption data, availability of multianalyte methods for mycotoxin quantification, management of left-censored data and use of probabilistic models will be highlight, in order to develop a more precise and realistic exposure assessment. On the other hand, the application of predictive mathematical models to estimate mycotoxins’ combined effects from in vitro toxicity studies will be also discussed. Results from a recent Portuguese project aimed at exploring the toxic effects of mixtures of mycotoxins in infant foods and their potential health impact will be presented as a case study, illustrating the different aspects of risk assessment highlighted in this presentation. Further studies on hazard and exposure assessment of multiple mycotoxins, using harmonized approaches and methodologies, will be crucial towards an improvement in data quality and contributing to holistic risk assessment and risk management strategies for multiple mycotoxins in foodstuffs.

Application of mathematical models to mycotoxins children risk assessment: a case study of Portuguese children exposure to co-occurring mycotoxins in processed cereal-based foods

People, animals and the environment can be exposed to multiple chemicals at once from a variety of sources, but current risk assessment is usually carried out based on one chemical substance at a time. In human health risk assessment, ingestion of food is considered a major route of exposure to many contaminants, namely mycotoxins, a wide group of fungal secondary metabolites that are known to potentially cause toxicity and carcinogenic outcomes. Mycotoxins are commonly found in a variety of foods including those intended for consumption by infants and young children and have been found in processed cereal-based foods available in the Portuguese market. The use of mathematical models, including probabilistic approaches using Monte Carlo simulations, constitutes a prominent issue in human health risk assessment in general and in mycotoxins exposure assessment in particular. The present study aims to characterize, for the first time, the risk associated with the exposure of Portuguese children to single and multiple mycotoxins present in processed cereal-based foods (CBF). Portuguese children (0-3 years old) food consumption data (n=103) were collected using a 3 days food diary. Contamination data concerned the quantification of 12 mycotoxins (aflatoxins, ochratoxin A, fumonisins and trichothecenes) were evaluated in 20 CBF samples marketed in 2014 and 2015 in Lisbon; samples were analyzed by HPLC-FLD, LC-MS/MS and GC-MS. Daily exposure of children to mycotoxins was performed using deterministic and probabilistic approaches. Different strategies were used to treat the left censored data. For aflatoxins, as carcinogenic compounds, the margin of exposure (MoE) was calculated as a ratio of BMDL (benchmark dose lower confidence limit) to the aflatoxin exposure. The magnitude of the MoE gives an indication of the risk level. For the remaining mycotoxins, the output of exposure was compared to the dose reference values (TDI) in order to calculate the hazard quotients (ratio between exposure and a reference dose, HQ). For the cumulative risk assessment of multiple mycotoxins, the concentration addition (CA) concept was used. The combined margin of exposure (MoET) and the hazard index (HI) were calculated for aflatoxins and the remaining mycotoxins, respectively. 71% of CBF analyzed samples were contaminated with mycotoxins (with values below the legal limits) and approximately 56% of the studied children consumed CBF at least once in these 3 days. Preliminary results showed that children exposure to single mycotoxins present in CBF were below the TDI. Aflatoxins MoE and MoET revealed a reduced potential risk by exposure through consumption of CBF (with values around 10000 or more). HQ and HI values for the remaining mycotoxins were below 1. Children are a particularly vulnerable population group to food contaminants and the present results point out an urgent need to establish legal limits and control strategies regarding the presence of multiple mycotoxins in children foods in order to protect their health. The development of packaging materials with antifungal properties is a possible solution to control the growth of moulds and consequently to reduce mycotoxin production, contributing to guarantee the quality and safety of foods intended for children consumption.

Portuguese children exposure to multiple mycotoxins through food consumption: toward a holistic approach for multiple mycotoxins risk assessment

Humans can be exposed to multiple chemicals at once from a variety of sources, and human risk assessment of multiple chemicals poses several challenges to scientists, risk assessors and risk managers. Ingestion of food is considered a major route of exposure to many contaminants, namely mycotoxins, especially for vulnerable population groups, as children. A lack of sufficient data regarding mycotoxins children risk assessment, could contribute to an inaccuracy of the estimated risk. Efforts must be undertaken to develop initiatives that promote a broad overview of multiple mycotoxins risk assessment. The present work, developed within the MYCOMIX project, aims to assess the risk associated to the exposure of Portuguese children (< 3 years old) to multiple mycotoxins through consumption of foods primarily marketed for this age group. A holistic approach was developed applying deterministic and probabilistic tools to the calculation of mycotoxin daily intake values, integrating children food consumption (3-days food diary), mycotoxins occurrence (HPLC-UV, HPLC-FD, LC-MS/MS and GC-MS), bioaccessibility (standardized in vitro digestion model) and toxicological data (in vitro evaluation of cytotoxicity, genotoxicity and intestinal impact). A case study concerning Portuguese children exposure to patulin (PAT) and ochratoxin A (OTA), two mycotoxins co-occurring in processed cereal-based foods (PCBF) marketed in Portugal, was developed. Main results showed that there is low concern from a public health point of view relatively to PAT and OTA Portuguese children exposure through consumption of PCBF, considering the estimated daily intakes of these two mycotoxins (worst case scenarios, 22.930 ng/kg bw/day and 0.402 ng/kg bw/day, for PAT and OTA, respectively), their bioaccessibility and toxicology results. However, the present case study only concerns the risk associated with the consumption of PCBF and child diet include several other foods. The present work underlines the need to adopt a holistic approach for multiple mycotoxins risk assessment integrating data from exposure, bioacessibility and toxicity domains in order to contribute to a more accurate risk assessment.

Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models.

For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors.

Children at risk, attachment and institutionalization: contributions to the socio-educational intervention

Introduction: Institutionalized children exposed to early adverse experiences are a particularly vulnerable group with a high risk of developing health problems. Objectives: i) to know the representations of attachment in institutionalized children; ii) to understand if there are differences of attachment, according to some sociodemographic variables; iii) outline socio-educational intervention strategies in the children’s life’s contexts. Methods: This is an exploratory and cross-sectional study, using for this purpose, a non-probabilistic and convenience sample composed of 82 institutionalized children, aged between 8 and 17 years old. The gathering instruments were the Sociodemographic Questionnaire and the Inventory Attachment for Children and Adolescents. Results: The results show that most children have secure attachment representations, followed by the avoidant attachment representations. We also found signiicant differences in the results of attachment, according to the gender (in avoidant attachment and ambivalent attachment) and in the institutionalization time (in the ambivalent attachment). Conclusions: The results show promising lines of research, being our purpose to outline socio-educational intervention strategies for children in their pathways of life by promoting protective factors, especially the establishment of secure relationships, thus promoting better quality of life and well-being.

Nat2, Xrcc1 And Hogg1 Polymorphisms, Cigarette Smoking, Alcohol Consumption And Risk Of Upper Aerodigestive Tract Cancer.

To evaluate associations between polymorphisms of the N-acetyltransferase 2 (NAT2), human 8-oxoguanine glycosylase 1 (hOGG1) and X-ray repair cross-complementing protein 1 (XRCC1) genes and risk of upper aerodigestive tract (UADT) cancer. A case-control study involving 117 cases and 224 controls was undertaken. The NAT2 gene polymorphisms were genotyped by automated sequencing and XRCC1 Arg399Gln and hOGG1 Ser326Cys polymorphisms were determined by Polymerase Chain Reaction followed by Restriction Fragment Length Polymorphism (PCR-RFLP) methods. Slow metabolization phenotype was significantly associated as a risk factor for the development of UADT cancer (p=0.038). Furthermore, haplotype of slow metabolization was also associated with UADT cancer (p=0.014). The hOGG1 Ser326Cys polymorphism (CG or GG vs. CC genotypes) was shown as a protective factor against UADT cancer in moderate smokers (p=0.031). The XRCC1 Arg399Gln polymorphism (GA or AA vs. GG genotypes), in turn, was a protective factor against UADT cancer only among never-drinkers (p=0.048). Interactions involving NAT2, XRCC1 Arg399Gln and hOGG1 Ser326Cys polymorphisms may modulate the risk of UADT cancer in this population.

[association Between Breast Arterial Calcifications And Cardiovascular Risk Factors In Menopausal Women].

To analyze associations between mammographic arterial mammary calcifications in menopausal women and risk factors for cardiovascular disease. This was a cross-sectional retrospective study, in which we analyzed the mammograms and medical records of 197 patients treated between 2004 and 2005. Study variables were: breast arterial calcifications, stroke, acute coronary syndrome, age, obesity, diabetes mellitus, smoking, and hypertension. For statistical analysis, we used the Mann-Whitney, χ2 and Cochran-Armitage tests, and also evaluated the prevalence ratios between these variables and mammary artery calcifications. Data were analyzed with the SAS version 9.1 software. In the group of 197 women, there was a prevalence of 36.6% of arterial calcifications on mammograms. Among the risk factors analyzed, the most frequent were hypertension (56.4%), obesity (31.9%), smoking (15.2%), and diabetes (14.7%). Acute coronary syndrome and stroke presented 5.6 and 2.0% of prevalence, respectively. Among the mammograms of women with diabetes, the odds ratio of mammary artery calcifications was 2.1 (95%CI 1.0-4.1), with p-value of 0.02. On the other hand, the mammograms of smokers showed the low occurrence of breast arterial calcification, with an odds ratio of 0.3 (95%CI 0.1-0.8). Hypertension, obesity, diabetes mellitus, stroke and acute coronary syndrome were not significantly associated with breast arterial calcification. The occurrence of breast arterial calcification was associated with diabetes mellitus and was negatively associated with smoking. The presence of calcification was independent of the other risk factors for cardiovascular disease analyzed.