Chemical risks, quantitative methods

The third category of methods addressed in this chapter are error analysis and reduction methodologies. Error analysis techniques can either be applied in a proactive or retrospective mode. In the proactive mode they are used to predict possible errors when tasks are being analyzed during chemical process quantitative risk assessment and design evaluations. When applied retrospectively, they are used to identify the underlying causes of errors giving rise to accidents. Very often the distinction between task analysis and error analysis is blurred, since the process of error analysis always has to proceed from a comprehensive description of a task, usually derived from a task analysis. 

An Overview of Quantitative Methods for Assessment and Evaluation of Chemical Risks... 

Our assignment for EPA was to apply quantitative risk analysis methods to the determination of risk for a particular chemical. The health risks for perchloroethylene turned out to be highly uncertain, but by using decision analysis concepts we were able to display this uncertainty in terms of alternative assumptions about the dose response relationship. Similar methods might be used to characterize uncertainties about human exposure to a chemical agent or about the costs to producers and consumers of a restriction on chemical use. 

Process Hazard Analysis— An organized effort to identify and evaluate hazards associated with chemical processes and operations to enable their control. This review normally involves the use of qualitative techniques to identify and assess the significance of hazards. Conclusions and appropriate recommendations are developed. Occasionally, quantitative methods are used to help prioritize risk reduction measures. 

Bayesian statistics are applicable to analyzing uncertainty in all phases of a risk assessment. Bayesian or probabilistic induction provides a quantitative way to estimate the plausibility of a proposed causality model (Howson and Urbach 1989), including the causal (conceptual) models central to chemical risk assessment (Newman and Evans 2002). Bayesian inductive methods quantify the plausibility of a conceptual model based on existing data and can accommodate a process of data augmentation (or pooling) until sufficient belief (or disbelief) has been accumulated about the proposed cause-effect model. Once a plausible conceptual model is defined, Bayesian methods can quantify uncertainties in parameter estimation or model predictions (predictive inferences). Relevant methods can be found in numerous textbooks, e.g., Carlin and Louis (2000) and Gelman et al. (1997). 

In summary, in studies of chemical toxicity, pathways and rates of metabolism as well as effects resulting from toxicokinetic factors and receptor affinities are critical in the choice of the animal species and experimental design. Therefore it is important that the animal species chosen as a model for humans in safety evaluations metabolize the test chemical by the same routes as humans and, furthermore, that quantitative differences are considered in the interpretation of animal toxicity data. Risk assessment methods involving the extrapolation of toxic or carcinogenic potential of a chemical from one species to another must consider the metabolic and toxicokinetic characteristics of both species. 

A hazard is anything that will produce an adverse effect on human health and the environment. In environmental risk assessment, the hazard component generally refers to toxicity. Exposure is the quantitative or qualitative assessment of contact to the skin or orifices of the body by a chemical. Traditional pollution prevention techniques focus on reducing waste as much as possible however, risk assessment methods used in pollution prevention can help quantify the degree of environmental impact for individual chemicals. This approach provides a powerful tool that enables engineers to better design processes and products by focusing on the most beneficial methods to minimize all aspects of risk. 

The public concern is aimed at the danger of any kind of intoxication arising from the contact of human beings and living nature with chemicals in our environment. The scientifically based quantitative toxic risk assessment methods have been advanced to extrapolate the animal studies to human exposure levels. In the stabilizer business, the health risk must be assessed for all opportunities where human beings are expected to come into contact with stabilizers, i.e. during the... 

Chemical process quantitative risk analysis (CPQRA) is a methodology designed to provide management with a tool to help evaluate overall process safety in the chemical process industry (AIChE, 2000). This analysis provides a quantitative method to evaluate risk and to identify areas for cost-effective risk reduction. 

The European legislation neither determines nor recommends any method in this area. In spite of that, it can be stated that the most suitable methods are those like Chemical Process Quantitative Risk Analysis (CPQRA) and Chemical Transportation Risk Analysis (TRA) issued by the Center for Chemical Process Safety (CCPS) of the American Institute of Chemical Engineers (AIChE). 

The model contains a surface energy method for parameterizing winds and turbulence near the ground. Its chemical database library has physical properties (seven types, three temperature dependent) for 190 chemical compounds obtained from the DIPPR" database. Physical property data for any of the over 900 chemicals in DIPPR can be incorporated into the model, as needed. The model computes hazard zones and related health consequences. An option is provided to account for the accident frequency and chemical release probability from transportation of hazardous material containers. When coupled with preprocessed historical meteorology and population den.sitie.s, it provides quantitative risk estimates. The model is not capable of simulating dense-gas behavior. 

In order to extrapolate laboratory animal results to humans, an interspecies dose conversion must be performed. Animals such as rodents have different physical dimensions, rates of intake (ingestion or inhalation), and lifespans from humans, and therefore are expected to respond differently to a specified dose level of any chemical. Estimation of equivalent human doses is usually performed by scaling laboratory doses according to observable species differences. Unfortunately, detailed quantitative data on the comparative pharmacokinetics of animals and humans are nonexistent, so that scaling methods remain approximate. In carcinogenic risk extrapolation, it is commonly assumed that the rate of response for mammals is proportional to internal surface area... 

Among the possible alternative methods, in vitro assay (for ATMs) and quantitative structure-activity relationships (QSARs) models (for ANTMs) are the most applied approaches in the toxicological and ecotoxicological evaluation of chemicals profiles, even in the field of environmental research and risk assessment. 

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