Risk-based decision support system for life cycle management of industrials plants

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

Handheld-assisted field data collection for occupational risk assessment.

A computerized handheld procedure is presented in this paper. It is intended as a database complementary tool, to enhance prospective risk analysis in the field of occupational health. The Pendragon forms software (version 3.2) has been used to implement acquisition procedures on Personal Digital Assistants (PDAs) and to transfer data to a computer in an MS-Access format. The data acquisition strategy proposed relies on the risk assessment method practiced at the Institute of Occupational Health Sciences (IST). It involves the use of a systematic hazard list and semi-quantitative risk assessment scales. A set of 7 modular forms has been developed to cover the basic need of field audits. Despite the minor drawbacks observed, the results obtained so far show that handhelds are adequate to support field risk assessment and follow-up activities. Further improvements must still be made in order to increase the tool effectiveness and field adequacy.

Rockfall hazard and risk assessments along roads at a regional scale: Example in Swiss Alps

Unlike fragmental rockfall runout assessments, there are only few robust methods to quantify rock-mass-failure susceptibilities at regional scale. A detailed slope angle analysis of recent Digital Elevation Models (DEM) can be used to detect potential rockfall source areas, thanks to the Slope Angle Distribution procedure. However, this method does not provide any information on block-release frequencies inside identified areas. The present paper adds to the Slope Angle Distribution of cliffs unit its normalized cumulative distribution function. This improvement is assimilated to a quantitative weighting of slope angles, introducing rock-mass-failure susceptibilities inside rockfall source areas previously detected. Then rockfall runout assessment is performed using the GIS- and process-based software Flow-R, providing relative frequencies for runout. Thus, taking into consideration both susceptibility results, this approach can be used to establish, after calibration, hazard and risk maps at regional scale. As an example, a risk analysis of vehicle traffic exposed to rockfalls is performed along the main roads of the Swiss alpine valley of Bagnes.

Angiotensin converting enzyme inhibitor induced angio-oedema: a review of the pathophysiology and risk factors.

Angio-oedema (AE) is a known adverse effect of angiotensin converting enzyme inhibitor (ACE-I) therapy. Over the past several decades, evidence of failure to diagnose this important and potentially fatal reaction is commonly found in the literature. Because this reaction is often seen first in the primary care setting, a review was undertaken to analyse and document the keys to both diagnostic criteria as well as to investigate potential risk factors for ACE-I AE occurrence. A general review of published literature was conducted through Medline, EMBASE, and the Cochrane Database, targeting ACE-I-related AE pathomechanism, diagnosis, epidemiology, risk factors, and clinical decision making and treatment. The incidence and severity of AE appears to be on the rise and there is evidence of considerable delay in diagnosis contributing to significant morbidity and mortality for patients. The mechanism of AE due to ACE-I drugs is not fully understood, but some genomic and metabolomic information has been correlated. Additional epidemiologic data and clinical treatment outcome predictors have been evaluated, creating a basis for future work on the development of clinical prediction tools to aid in risk identification and diagnostic differentiation. Accurate recognition of AE by the primary care provider is essential to limit the rising morbidity associated with ACE-I treatment-related AE. Research findings on the phenotypic indicators relevant to this group of patients as well as basic research into the pathomechanism of AE are available, and should be used in the construction of better risk analysis and clinical diagnostic tools for ACE-I AE.

Sensitivity analysis, dominant factors, and robustness of the ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5 occupational exposure models

Occupational exposure modeling is widely used in the context of the E.U. regulation on the registration, evaluation, authorization, and restriction of chemicals (REACH). First tier tools, such as European Centre for Ecotoxicology and TOxicology of Chemicals (ECETOC) targeted risk assessment (TRA) or Stoffenmanager, are used to screen a wide range of substances. Those of concern are investigated further using second tier tools, e.g., Advanced REACH Tool (ART). Local sensitivity analysis (SA) methods are used here to determine dominant factors for three models commonly used within the REACH framework: ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5. Based on the results of the SA, the robustness of the models is assessed. For ECETOC, the process category (PROC) is the most important factor. A failure to identify the correct PROC has severe consequences for the exposure estimate. Stoffenmanager is the most balanced model and decision making uncertainties in one modifying factor are less severe in Stoffenmanager. ART requires a careful evaluation of the decisions in the source compartment since it constitutes ∼75% of the total exposure range, which corresponds to an exposure estimate of 20-22 orders of magnitude. Our results indicate that there is a trade off between accuracy and precision of the models. Previous studies suggested that ART may lead to more accurate results in well-documented exposure situations. However, the choice of the adequate model should ultimately be determined by the quality of the available exposure data: if the practitioner is uncertain concerning two or more decisions in the entry parameters, Stoffenmanager may be more robust than ART.

The Pay-Off Method as a Tool for Evaluating the Risk and Profitability of Public Real Estate Investments

Real option valuation, in particular the fuzzy pay-off method, has proven to be useful in defining risk and visualizing imprecision of investments in various industry applications. This study examines whether the evaluation of risk and profitability for public real estate investments can be improved by using real option methodology. Firstly, the context of real option valuation in the real estate industry is examined. Further, an empirical case study is performed on 30 real estate investments of a Finnish government enterprise in order to determine whether the presently used investment analysis system can be complemented by the pay-off method. Despite challenges in the application of the pay-off method to the case company’s large investment base, real option valuation is found to create additional value and facilitate more robust risk analysis in public real estate applications.

Risk Assessment of Modern Landfill Structures in Finland

The purpose of this thesis was to investigate environmental permits of landfills with respect to the appropriateness of risk assessments focusing on contaminant migration, structures capable to protect the environment, waste and leachate management and existing environmental impacts of landfills. According to the requirements, a risk assessment is always required to demonstrate compliance with environmental protection requirements if the environmental permit decision deviates from the set requirements. However, there is a reason to doubt that all relevant risk factors are identified in current risk assessment practices in order to protect people end environment. In this dissertation, risk factors were recognized in 12 randomly selected landfills. Based on this analysis, a structural risk assessment method was created. The method was verified with two case examples. Several development needs were found in the risk assessments of the environmental permit decisions. The risk analysis equations used in the decisions did not adequately take into account all the determining factors like waste prospects, total risk quantification or human delineated factors. Instead of focusing on crucial factors, the landfill environmental protection capability is simply expressed via technical factors like hydraulic conductivity. In this thesis, it could be shown, that using adequate risk assessment approaches the most essential environmental impacts can be taken into account by consideration of contaminant transport mechanisms, leachate effects, and artificial landfill structures. The developed structural risk analysing (SRA) method shows, that landfills structures could be designed in a more cost-efficient way taking advantage of recycled or by-products. Additionally, the research results demonstrate that the environmental protection requirements of landfills should be updated to correspond to the capability to protect the environment instead of the current simplified requirements related to advective transport only.

Learning from risks: A tool for post-project risk assessment

Risk management (RM) comprises of risk identification, risk analysis, response planning, monitoring and action planning tasks that are carried out throughout the life cycle of a project in order to ensure that project objectives are met. Although the methodological aspects of RM are well-defined, the philosophical background is rather vague. In this paper, a learning-based approach is proposed. In order to implement this approach in practice, a tool has been developed to facilitate construction of a lessons learned database that contains risk-related information and risk assessment throughout the life cycle of a project. The tool is tested on a real construction project. The case study findings demonstrate that it can be used for storing as well as updating risk-related information and finally, carrying out a post-project appraisal. The major weaknesses of the tool are identified as, subjectivity of the risk rating process and unwillingness of people to enter information about reasons of failure.

Risk pricing practices in finance, insurance and construction

A review of current risk pricing practices in the financial, insurance and construction sectors is conducted through a comprehensive literature review. The purpose was to inform a study on risk and price in the tendering processes of contractors: specifically, how contractors take account of risk when they are calculating their bids for construction work. The reference to mainstream literature was in view of construction management research as a field of application rather than a fundamental academic discipline. Analytical models are used for risk pricing in the financial sector. Certain mathematical laws and principles of insurance are used to price risk in the insurance sector. construction contractors and practitioners are described to traditionally price allowances for project risk using mechanisms such as intuition and experience. Project risk analysis models have proliferated in recent years. However, they are rarely used because of problems practitioners face when confronted with them. A discussion of practices across the three sectors shows that the construction industry does not approach risk according to the sophisticated mechanisms of the two other sectors. This is not a poor situation in itself. However, knowledge transfer from finance and insurance can help construction practitioners. But also, formal risk models for contractors should be informed by the commercial exigencies and unique characteristics of the construction sector.

Fuzzy analysis: a vague way of dealing with uncertainty in real estate analysis?

Risk and uncertainty are, to say the least, poorly considered by most individuals involved in real estate analysis - in both development and investment appraisal. Surveyors continue to express 'uncertainty' about the value (risk) of using relatively objective methods of analysis to account for these factors. These methods attempt to identify the risk elements more explicitly. Conventionally this is done by deriving probability distributions for the uncontrolled variables in the system. A suggested 'new' way of "being able to express our uncertainty or slight vagueness about some of the qualitative judgements and not entirely certain data required in the course of the problem..." uses the application of fuzzy logic. This paper discusses and demonstrates the terminology and methodology of fuzzy analysis. In particular it attempts a comparison of the procedures with those used in 'conventional' risk analysis approaches and critically investigates whether a fuzzy approach offers an alternative to the use of probability based analysis for dealing with aspects of risk and uncertainty in real estate analysis

Implementing systematic review techniques in chemical risk assessment: challenges, opportunities and recommendations

Systematic review (SR) is a rigorous, protocol-driven approach designed to minimise error and bias when summarising the body of research evidence relevant to a specific scientific question. Taking as a comparator the use of SR in synthesising research in healthcare, we argue that SR methods could also pave the way for a “step change” in the transparency, objectivity and communication of chemical risk assessments (CRA) in Europe and elsewhere. We suggest that current controversies around the safety of certain chemicals are partly due to limitations in current CRA procedures which have contributed to ambiguity about the health risks posed by these substances. We present an overview of how SR methods can be applied to the assessment of risks from chemicals, and indicate how challenges in adapting SR methods from healthcare research to the CRA context might be overcome. Regarding the latter, we report the outcomes from a workshop exploring how to increase uptake of SR methods, attended by experts representing a wide range of fields related to chemical toxicology, risk analysis and SR. Priorities which were identified include: the conduct of CRA-focused prototype SRs; the development of a recognised standard of reporting and conduct for SRs in toxicology and CRA; and establishing a network to facilitate research, communication and training in SR methods. We see this paper as a milestone in the creation of a research climate that fosters communication between experts in CRA and SR and facilitates wider uptake of SR methods into CRA.

Semiparametric modeling of the spatial distribution of occupational accident risk in the casual labor market, Piracicaba, southeast Brazil

The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.

Mortality Risk in Insects

Understanding how and why insect numbers fluctuate through time and space has been a central theme in ecological research for more than a century. Life tables have been used to understand temporal and spatial patterns in insect numbers. In this study, we estimated cause-of-death probabilities for phytophagous insects using multiple decrement life tables and the irreplaceable mortality analytic technique. Multiple decrement life tables were created from 73 insect life tables published from 1954 to 2004. Irreplaceable mortality (the portion of mortality that cannot be replaced by another cause) from pathogens, predators, and parasitoids was 8.6 +/- 7.2, 7.8 +/- 4.9, and 6.2 +/- 1.6%, respectively. In contrast, the mean irreplaceable mortality from all non-natural enemy mortality factors (mortality from factors other than natural enemies) was 35.1 +/- 4.4%. Irreplaceable mortality from natural enemies was significantly lower compared with non-natural enemy factors. Our results may partially explain cases of unsuccessful efficacy in classical biological control, after successful establishment, by showing low irreplaceable mortality for natural enemies, including 5.2 +/- 1.6% for introduced natural enemies. We suggest that the environment (i.e., the degree of environmental stability) influences the magnitude of the irreplaceable mortality from natural enemies. Our results lead to several testable hypotheses and emphasize that it is not possible to estimate the effect of any mortality factor without considering its interaction with competing mortality factors, which has far-reaching consequences for population biology and applied ecology.

Mapping soil pollution by spatial analysis and fuzzy classification

Spatial analysis and fuzzy classification techniques were used to estimate the spatial distributions of heavy metals in soil. The work was applied to soils in a coastal region that is characterized by intense urban occupation and large numbers of different industries. Concentrations of heavy metals were determined using geostatistical techniques and classes of risk were defined using fuzzy classification. The resulting prediction mappings identify the locations of high concentrations of Pb, Zn, Ni, and Cu in topsoils of the study area. The maps show that areas of high pollution of Ni and Cu are located at the northeast, where there is a predominance of industrial and agricultural activities; Pb and Zn also occur in high concentrations in the northeast, but the maps also show significant concentrations of Pb and Zn in other areas, mainly in the central and southeastern parts, where there are urban leisure activities and trade centers. Maps were also prepared showing levels of pollution risk. These maps show that (1) Cu presents a large pollution risk in the north-northwest, midwest, and southeast sectors, (2) Pb represents a moderate risk in most areas, (3) Zn generally exhibits low risk, and (4) Ni represents either low risk or no risk in the studied area. This study shows that combining geostatistics with fuzzy theory can provide results that offer insight into risk assessment for environmental pollution.