Chemical uncertainties

Eisenberg JNS, McKone TE. 1998. Decision tree method for the classification of chemical pollutants Incorporation of across-chemical pollutants Incorporation of across-chemical variability and within-chemical uncertainty. Environ Sci Technol 32 3396-3404. 

IGHRC. 2003. The Interdepartmental Group on Health Risks from Chemicals. Uncertainty factors Their use in human health risk assessment by UK Government. Leicester Institute for Environment and Health, University of Leicester, http //www.silsoe.cranfield.ac.uk/ieh/pdf/cr9.pdf... 

Several epidemiology studies have reported increased mortality among workers in viscose rayon plants who were occupationally exposed to carbon disulfide as well as other chemicals (Hemberg et al. 1970, 1973 Tolonen et al. 1975, 1979). Deaths have also been reported in a community in India following an accidental release of large amounts of carbon disulfide, hydrogen sulfide, and sulfuric acid from a viscose rayon plant (Kamat 1994). However, no definitive or consistent conclusions can be drawn from these studies because of concomitant exposure to other chemicals, uncertainty about exposure concentrations, and the likelihood of multiple routes of exposure. 

If formation wafer production is expected, a chemical analysis of the water will also be required. It is good practice to record the details of the methods used for sampling and analysis in each case so that measurement uncertainties can be assessed. 

The flash lamp teclmology first used to photolyse samples has since been superseded by successive generations of increasingly faster pulsed laser teclmologies, leading to a time resolution for optical perturbation metliods tliat now extends to femtoseconds. This time scale approaches tlie ultimate limit on time resolution (At) available to flash photolysis studies, tlie limit imposed by chemical bond energies (AA) tlirough tlie uncertainty principle, AAAt > 2/j. 

For a method to be useful it must provide reliable results. Unfortunately, methods are subject to a variety of chemical and physical interferences that contribute uncertainty to the analysis. When a method is relatively free from chemical interferences, it can be applied to the determination of analytes in a wide variety of sample matrices. Such methods are considered robust. 

Many chemical calculations involve a combination of adding and subtracting, and multiply and dividing. As shown in the following example, the propagation of uncertainty is easily calculated by treating each operation separately using equations 4.6 and 4.7 as needed. 

Because they are weak acids or bases, the iadicators may affect the pH of the sample, especially ia the case of a poorly buffered solution. Variations in the ionic strength or solvent composition, or both, also can produce large uncertainties in pH measurements, presumably caused by changes in the equihbria of the indicator species. Specific chemical reactions also may occur between solutes in the sample and the indicator species to produce appreciable pH errors. Examples of such interferences include binding of the indicator forms by proteins and colloidal substances and direct reaction with sample components, eg, oxidising agents and heavy-metal ions. 

Relevant hydrological fundamentals are utilized (21) to take account of the complex interaction of physical and chemical processes involving sod or rock, water, and contaminant. Attention is paid to uncertainties in calculated results. 

Production and Consumption. About 80% of the world s barite production is used as a weighting agent for the muds ckculated in rotary drilling of oil and gas wells (see PETROLEUM, DRILLING FLUIDS AND OTHER OIL RECOVERY CHEMICALS). Table 2 shows the U.S. production—consumption balance. The 1988 demand for barite increased nearly 40% over that recorded in 1987. However, by the end of 1988, oil prices had declined and renewed economic uncertainties depressed exploration and development activity. Barite demand fell accordingly and imports of lower cost foreign product exceeded domestic production. 

Descriptions of Physical Objects, Processes, or Abstract Concepts. Eor example, pumps can be described as devices that move fluids. They have input and output ports, need a source of energy, and may have mechanical components such as impellers or pistons. Similarly, the process of flow can be described as a coherent movement of a Hquid, gas, or coUections of soHd particles. Flow is characterized by direction and rate of movement (flow rate). An example of an abstract concept is chemical reaction, which can be described in terms of reactants and conditions. Descriptions such as these can be viewed as stmctured coUections of atomic facts about some common entity. In cases where the descriptions are known to be partial or incomplete, the representation scheme has to be able to express the associated uncertainty. 

A number of factors limit the accuracy with which parameters for the design of commercial equipment can be determined. The parameters may depend on transport properties for heat and mass transfer that have been determined under nonreacting conditions. Inevitably, subtle differences exist between large and small scale. Experimental uncertainty is also a factor, so that under good conditions with modern equipment kinetic parameters can never be determined more precisely than 5 to 10 percent (Hofmann, in de Lasa, Chemical Reactor Design and Technology, Martinus Nijhoff, 1986, p. 72). 

Designed to obtain such fundamental data as chemical rates free of mass transfer resistances or other complications. Some of the heterogeneous reactors of Fig. 23-29, for instance, employ known interfacial areas, thus avoiding one uncertainty. 

Contrac tors bids offer the most rehable information on cost. Order-of-magnitude costs, however, may be required for preliminary studies. One way of estimating them is to obtain cost information from similar facihties and scale it to the proposed installation. Costs of steel storage tanks and vessels have been found to vaiy approximately as the 0.6 to 0.7 power of their weight [see Happel, Chemical Process Economics, Wiley, 1958, p. 267 also Williams, Chem. Eng., 54(12), 124 (1947)]. AU estimates cased on the costs of existing eqiiipment must be corrected for changes in the price index from the date when the equipment was built. Considerable uncertainty is involved in adjusting data more than a few years old. 

Frey, H.C. and E.S. Rubin, Evaluate Uncertainties in Advanced Process Technologies, Chemical Engineeiing Piogiess, May 1992, 6.3-70. (Uncertainty evaluation)... 

Measurement Error Uncertainty in the interpretation of unit performance results from statistical errors in the measurements, low levels of process understanding, and differences in unit and modeled performance (Frey, H.C., and E. Rubin, Evaluate Uncertainties in Advanced Process Technologies, Chemical Engineering Progress, May 1992, 63-70). It is difficult to determine which measurements will provide the most insight into unit performance. A necessary first step is the understanding of the measurement errors hkely to be encountered. 

An example adapted from Verneuil, et al. (Verneuil, V.S., P. Yan, and F. Madron, Banish Bad Plant Data, Chemical Engineeiing Progress, October 1992, 45-51) shows the impact of flow measurement error on misinterpretation of the unit operation. The success in interpreting and ultimately improving unit performance depends upon the uncertainty in the measurements. In Fig. 30-14, the materi balance constraint would indicate that S3 = —7, which is unrealistic. However, accounting for the uncertainties in both Si and S9 shows that the value for S3 is —7 28. Without considering uncertainties in the measurements, analysts might conclude that the flows or model contain bias (systematic) error. 

Of all the uncertainties surrounding the hypothesis that environmental chemicals with endocrine disrupting properties are responsible for the observed effects in humans and wildlife, one of the major unknowns relates to exposure. Humans and wildlife can be, and sometimes are, exposed to these substances in the environment but our knowledge of the levels, routes and timing of exposure is poor. 

QRA is fundamentally different from many other chemical engineering activities (e.g., chemistry, heat transfer, reaction kinetics) whose basic property data are theoretically deterministic. For example, the physical properties of a substance for a specific application can often be established experimentally. But some of the basic property data used to calculate risk estimates are probabilistic variables with no fixed values. Some of the key elements of risk, such as the statistically expected frequency of an accident and the statistically expected consequences of exposure to a toxic gas, must be determined using these probabilistic variables. QRA is an approach for estimating the risk of chemical operations using the probabilistic information. And it is a fundamentally different approach from those used in many other engineering activities because interpreting the results of a QRA requires an increased sensitivity to uncertainties that arise primarily from the probabilistic character of the data. 

Like frequency estimates, consequence estimates can have very large uncertainties. Estimates that vary by orders of magnitude can result from (1) basic uncertainties in chemical/physical properties, (2) differences in average vs. time-dependent meteorological conditions, and/or (3) uncertainties in the release, dispersion, and effects models. Some... 

AccuracyAJncertainty The lack of specific data on component failure characteristics, chemical and physical properties, and phenomena severely limit accuracy and can produce large uncertainties. 

Chemical analyses should be provided for all anodes used in the offshore and harbor area, together with results for current content in A h kg and current output in amperes [2,3]. The geometric shape and the number of anodes required is determined by these parameters. Expensive calculations for design based on grounding resistances are made only in exceptional cases because in practice there are too many uncertainties and the number and mass of the anodes have to be quoted with a corresponding safety factor. 

The relationship between what is recorded in a SSIMS spectrum and the chemical state of the surface is not as straightforward as in XPS and AES (Chap. 2). Because of the large number of molecular ions that occur in any SSIMS spectrum from a multi-component surface (e. g. during the study of a surface reaction), much chemical information is obviously available in SSIMS, potentially more than in XPS. The problem in using the information from a molecular ion lies in the uncertainty of knowing whether or not the molecule represents the surface composition. For some materials. 

The assembly process (Figure 10-1) brings together all of the assessment tasks to provide the risk, its significance, how it was found, its sensitivity to uncertainties, confidence limits, and how it may be reduced by system improvements. Not all PSAs use fault trees and event trees. This is especially true of chemical PSAs that may rely on HAZOP or FMEA/FMECAs. Nevertheless the objectives are the same accident identification, analysis and evaluation. Figure 10-1 assumes fault tree and event tree techniques which should be replaced by the equivalent methods that are used. 

The nuclear equipment failure rate database has not changed markedly since the RSS and chemical process data contains information for non-chemical process equipment in a more benign environment. Uncertainty in the database results from the statistical sample, heterogeneity, incompleteness, and unrepresentative environment, operation, and maintenance. Some PSA.s use extensive studies of plant-specific data to augment the generic database by Bayesian methods and others do not. No standard guidance is available for when to use which and the improvement in accuracy that is achieved thereby. Improvements in the database and in the treatment of data requires, uhstaiui.il indu.sinal support but it is expensive. 

Nuclear PSAs contain considerable uncertainty associated with the physical and chemical processes involved in core degradation, movement of the molten core in the reactor vessel, on the containment floor, and the response of the containment to the stresses placed upon it. The current models of these processes need refinement and validation. Because the geometry is greatly changed by small perturbations after degradation has commenced, it is not clear that the phenomcn.i can be treated. 

In risk characterization, step four, the human exposure situation is compared to the toxicity data from animal studies, and often a safety -margin approach is utilized. The safety margin is based on a knowledge of uncertainties and individual variation in sensitivity of animals and humans to the effects of chemical compounds. Usually one assumes that humans are more sensitive than experimental animals to the effects of chemicals. For this reason, a safety margin is often used. This margin contains two factors, differences in biotransformation within a species (human), usually 10, and differences in the sensitivity between species (e.g., rat vs. human), usually also 10. The safety factor which takes into consideration interindividual differences within the human population predominately indicates differences in biotransformation, but sensitivity to effects of chemicals is also taken into consideration (e.g., safety faaor of 4 for biotransformation and 2.5 for sensitivity 4 x 2.5 = 10). For example, if the lowest dose that does not cause any toxicity to rodents, rats, or mice, i.e., the no-ob-servable-adverse-effect level (NOAEL) is 100 mg/kg, this dose is divided by the safety factor of 100. The safe dose level for humans would be then 1 mg/kg. Occasionally, a NOAEL is not found, and one has to use the lowest-observable-adverse-effect level (LOAEL) in safety assessment. In this situation, often an additional un-... 

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