Toxic gas effect models

The analysis of the potential consequences of an accident is a useful way of understanding the relative inherent safety of process alternatives. These consequences might consider, for example, the distance to a benchmark level of damage resulting from a fire, explosion, or toxic material release. Accident consequence analysis is of particular value in understanding the benefits of minimization, moderation, and limitation of effects. This discussion includes several examples of the use of potential accident consequence analysis as a way of measuring inherent safety, such as the BLEVE and toxic gas plume model results shown in Figures 4, 5, and 6. 

Toxic Gas Release Modeling. A form of consequence analysis performed by a growing number of operations is the study of the dispersion of released gases into the atmosphere. This is most often used to determine the possible effects of a hypothetical accident. One can calculate a concentration profile at any time, or the concentration at any distance from the source as a function of time, if given the following information ... 

Gas dispersion models provided the toxic effects of chemical releases, fire, or unconfined vapor cloud explosion. 

Effect models describe the impact of the physical effects of a fire, e.xplosion, or toxic gas release on exposed people, the environment or property, based on the results of tlie source, dispersion, and fire and explosion models. 

The determination of toxic release consequences consists from modelling release, dispersion, exposure and effects of toxic gas. The consequences are quantified as ... 

Clarity and Flexibility of Output Results. Complete output results are preferably stored in a file with only a summary displayed on screen. In heavy gas dispersion modeling, the applicability is commonly the description of hazard effects (toxicity, flammability) for use in risk analysis. 

The Model Characteristics. A selection should be made of the variables to be compared with the output data of the model. These variables are called dependent variables. Some consideration and explicit documentation is required concerning the selection. In heavy gas dispersion modeling, the application is commonly the description of hazard effects (toxicity, flammability) for use in risk analysis. The validation attaches weights to specific variables in a manner that depends on the model characteristics. Variables that are directly relevant to the intended (possibly restricted) use of the model should be weighted more heavily than those of peripheral interest. 

For prediction of toxic consequences, two common approaches are the use of either a specific toxic concentration or a toxic dose criterion. Toxic dose is determined as toxic gas concentration for the duration of exposure to determine an effect based on specified probit models (Chapter 4). 

Toxic effect models are employed to assess die consequences to human health as a result of exposure to a known concentration of toxic gas for a known period of time. Mitigation of these consequences by sheltering or evasive action is discussed in Chapter 5. 

For toxic gas clouds, concentration-time information is estimated using dispersion models (Section 2.3). Probit models are used to develop exposure estimates for situations involving continuous emissions (approximately constant concentration over time at a fixed downwind location) or puff emissions (concentration varying with time at a downwind location). It is much more difficult to apply other criteria that are based on a standard exposure duration (e.g., 30 or 60 min) particularly for puff releases that involve short exposure times and varying concentrations over those exposure times. The object of the toxic effects model is to determine whether an adverse health outcome can be expected following a release and, if data permit, to estimate the extent of injury or fatalities that are likely to result. 

In this research, physical effects of the reference scenarios were calculated using ALOHAS one of the widely accepted atmospheric dispersion model used for evaluating releases of hazardous chemical vapors, including toxic gas clouds, fires, and explosions. For calculation purpose, we used data about the hazardous facilities, as obtained from the RMIS database and the most frequently occurring atmospheric condition with an average wind speed of 3.0 m/s, 35°C temperature and stability class of D as input parameters. 

It has been shown that carbon dioxide also increases the toxicity of the other gases currently included in the model. For example, the 30 minute plus 24 hour LC50 value of HCN decreases to 75 ppm and that of 02 increases to 6.6% in the presence of 5% C02. However, we empirically found that the effect of the C02 can only be added into this equation once. At this time, we have data on the effect of various concentrations of C02 on CO and only have information on the effect of 5% C02 on the other gases. Since CO is the toxicant most likely to be present in all real fires, we have included the C02 effect into the CO factor. As more information becomes available, the N-Gas equation will be changed to indicate the effect of C02 on the other gases as well. 

Detailed studies have also been made on the toxicity of HC1, an irritant gas often present in fires. It does not cause baboon or rat incapacitation up to very high exposure doses which are sufficient (or very close) to cause eventual death [12]. Furthermore, a recent study has shown that the effects of irritants are heavily dependent on the animal model used [13]. 

This chapter first reviews and discusses selected research on local dose aspects of ozone toxicity, the morphology of the respiratoty tract and mucus layer, air and mucus flow, and the gas, liquid, and tissue components of mathematical models. Next, it discusses the approaches and results of the few models that exist. A similar review was recently done to defme an analytic framework for collating experiments on the effects of sulfur oxides on the lung. Pollutant gas concentrations are generally stated in parts per million in this chapter, because experimental uptake studies are generally quoted only to illustrate behavior predicted by theoretical models. Chapter 5 contains a detailed discussion of the conversion from one set of units to another. 

The development of new models for the prediction of chemical effects in the environment has improved. An Eulerian photochemical air quality model for the prediction of the atmospheric transport and chemical reactions of gas-phase toxic organic air pollutants has been published. The organic compounds were drawn from a list of 189 species selected for control as hazardous air pollutants in the Clean Air Act Amendments of 1990. The species considered include benzene, various alkylbenzenes, phenol, cresols, 1,3-butadiene, acrolein, formaldehyde, acetaldehyde, and perchloroethyl-ene, among others. The finding that photochemical production can be a major contributor to the total concentrations of some toxic organic species implies that control programs for those species must consider more than just direct emissions (Harley and Cass, 1994). This further corroborates the present weakness in many atmospheric models. 

Both equations have been taken from ISO 1334431 and use LC50 values for lethality to provide reference data for the individual gases to calculate toxic potency, based on rats exposed for 30 min. The N-Gas model in Equation 17.1 assumes that only the effect of the main toxicant CO is enhanced by the increase in respiration rate caused by high C02 concentrations (expressed as a step function with one value of m and b for C02 concentrations below and another for those above 5%). 

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