Right from the beginning of the earth’s existence, human beings have always been exposed to radiation either from natural sources or manmade/artificial sources. There is a wide range of sources of natural radiation to which we are continuously being exposed. Of these sources, the most familiar to us is the sun which produces infrared radiation that we feel as warmth, visible light, and ultraviolet light. The other sources are cosmic radiation which consists of high energy particles and rays that emanate from outside our earth, terrestrial radiation which comes from naturally occurring radionuclides in the earth’s crust, and internal radiation from radioactivity that is generally present in our bodies. Naturally-occurring radioactive materials were discovered in 1896. Naturally-occurring radiation accounts for approximately 80 percent of our exposure. Man-made/artificial radiation is radiation produced in devices, such as x-ray machines, and artificially produced radioisotopes made in a reactor or accelerator. This type of radiation is utilized in both medicine and industry. Main users of man-made radiation include: medical facilities, such as hospitals and pharmaceutical facilities; research and teaching institutions; nuclear reactors and their supporting facilities, such as uranium mills and fuel preparation plants; and federal facilities involved in nuclear weapons production. Radiation accidents are the most likely events that threaten population and environment. A radiation accident is a situation in which there is a real or suspected unintentional exposure to ionizing radiation or radioactive contamination. Radiation accidents involved radiation devices, radioisotopes, and criticality incidents. It must be emphasized that radiation accidents could involve either high- or low-level radiation exposures. Since the discovery of radiation, people have profited from the use of radiation in medicine and industry. Man-made sources of radiation account for about 20 percent of our total exposure to radiation.
When human beings are exposed, in general, the amount and duration of radiation exposure affects the severity or type of health effect such as acute radiation sickness, cancer, teratogenic (fetal) damage, hereditary changes etc.
Therefore, when hazardous substances are discharged into the environment, an evaluation is required to determine possible impact these substances may have on human health and environment. To resolve this issue, radiological assessment is carried out to estimate dose and risk to humans from radioactive materials in the environment. Assessment of risk is routed through dose computation. Dose computation basically depends on the basic dose assessment model and exposure pathways.
At the fundamental level risk can be explained as a structured process for identifying and analysing the most important contributions to the overall risk that an establishment or activity poses to people, the environment or some other vulnerable part of society (Kushwaha, 2009). But unfortunately, every step of the risk assessment process is laid with uncertainty. Uncertainty in risk estimation may originate from many different sources such as measure or estimates of parameters, environmental monitoring of data, natural variability in individual response, variability in environmental concentration in toxicants or radionuclides over time and space and unverifiable assumptions in dose response models or extrapolations of results of these models. In risk assessment available data are collected and utilized to make decisions regarding the associated with a particular stressor such as a chemical, biological or physical (radionuclides) agent. Uncertainty analysis is a part of risk assessment that focuses on uncertainties in the assessment. Important components of uncertainty analysis include qualitative analysis and identifying the uncertainties, quantitative analysis of the effects of the uncertainties on the decision process and communication of the uncertainty.
Chapter-I, which is the current chapter, provides a general introduction to the human health risk, risk assessment process, uncertainties involved in the risk assessment process and different methods of uncertainty representation in risk assessment.
In chapter-II, human health risk assessment is carried out utilizing fuzzy vertex method and related uncertainty associated with output risk is measured using average width of fuzzy set, fuzziness and nonspecificity. Risk assessment is also performed using fuzzy set in which Ganesan et al interval arithmetic is used to combine fuzzy numbers and compare the results with fuzzy vertex method. In a similar fashion related uncertainty associated with output risk is measured for both the methods using the same uncertainty measure technique.
We use Gaussian fuzzy number to represent epistemic type uncertainty and try to fuse with triangular fuzzy. To demonstrate and make use of the Gaussian fuzzy number and triangular fuzzy number and their fusion a hypothetical case study for health risk assessment is presented there.
We have proposed new methods for multiplication and division of fuzzy numbers by modifying the existing alpha-cut method. We have named as algebraic multiplication of fuzzy numbers and algebraic division of fuzzy numbers respectively. Also, risk assessment is performed using the newly introduced operations. The results are then compared with that of fuzzy Vertex method.
In chapter-III, we first propose three methods of assigning BPA when only three values of the parameter are known, viz. minimum, maximum and most likely value. Also, we define arithmetic combination of interval focal elements. We study for fuzzy focal elements and discussed the Dempster’s rule of combination for fuzzy focal elements. We have also extended the idea of arithmetic combination of interval focal elements for fuzzy focal elements. Risk assessment is carried out for interval focal elements using proposed arithmetic combination of focal elements (PACF) and Yager arithmetic combination of focal elements (YACF) and results are compared. Finally, risk assessment is performed for fuzzy focal elements.
In chapter-IV, we propose a hybrid approach for combining probability and possibility distribution functions within the same computation of risk. We have used both Monte Carlo simulation and possibility theory in our method in which the vertex method is taken to perform interval operation. Further we assume independency between the parameters and risk assessment is performed using this hybrid approach. In a similar manner, we propose a hybrid approach for combining probability and possibility distribution functions within the same computation of risk. In this method the interval arithmetic proposed by Ganesan et al. (2005) is chosen instead of vertex method to perform interval operation. Risk assessment is also performed using both the methods and finally results are compared. Also, we extend our proposed hybrid approach by incorporating probability bounds. That is, in risk assessment models some parameters are considered as probabilistic in which mean and standard deviation (variance) are available in the form of interval or fuzzy number while some other parameters are represented as precise probability distribution or possibilistic distribution. Risk assessment is also performed using this method.
In chapter-V, we reviewed the transformation principles as given by various authors viz., Zadeh, Klir, Dubois & Prade. Then risk assessment is carried out using Probability-Possibility transformations. Also, we have made a comparative case study of uncertainty propagation by considering three different scenarios using probability- possibility transformation satisfying consistency conditions.
