Environmental and Health Risk Assessment and Management: Principles and PracticesSpringer Science & Business Media, 2006 M01 27 - 480 pages This textbook is about the law, economics, practical assessment, and the management of risky activities arising from routine, catastrophic environmental and occupational exposures to hazardous agents. The textbook begins where emission and exposure analysis end by providing estimates or predictions of deleterious exposures. Thus, we deal with determining the nature and form of relations between exposure and response, damage functions, and with the principles and methods used to determine the costs and benefits of risk management actions from the vantage point of single and multiple decision-makers. Today, national and international laws, conventions and protocols are increasingly concerned with reducing environmental and health risks through minimizing exposure to toxic substances, bacteria, viruses and other noxious agents. They do so through risk methods. The reason for the now worldwide use of risk assessment and management is that individuals and society must decide when, and at what cost, past and future hazardous conditions can either be avoided or minimized. In this process, society must account for the limited resources it can spend to remain sustainable. Risk-based methods play a pivotal role in identifying and ranking alternative, sustainable choices, while accounting for uncertainty and variability. Specifically, most reductions in risks require a balancing of the costs and benefits associated with the action to reduce exposure to a hazard and thus risk. This balancing necessarily involves linking exposure and response through causation. This essential aspect of risk assessment and management, if done incorrectly, can be costly to society. |
From inside the book
Results 1-5 of 72
Page xix
... errors, corrected them and provided useful comments to earlier drafts. Alan Hubbard, at UC Berkeley, reviewed and clarified many of the statistical discussions. Finally, at least three graduate classes have read initial drafts of the ...
... errors, corrected them and provided useful comments to earlier drafts. Alan Hubbard, at UC Berkeley, reviewed and clarified many of the statistical discussions. Finally, at least three graduate classes have read initial drafts of the ...
Page 11
... error on the side of overprotection rather than underprotection.” The US Supreme Court then held that the OSHA may issue regulations reasonably necessary to reduce significant risk of k material impairment; but these regulations should ...
... error on the side of overprotection rather than underprotection.” The US Supreme Court then held that the OSHA may issue regulations reasonably necessary to reduce significant risk of k material impairment; but these regulations should ...
Page 17
... errors . This last error is the error of providing an accurate answer to the wrong problem . The sciences and law intersect in the drafting and implementation of the precautionary principle . Their intersection becomes critical at the ...
... errors . This last error is the error of providing an accurate answer to the wrong problem . The sciences and law intersect in the drafting and implementation of the precautionary principle . Their intersection becomes critical at the ...
Page 22
... errors (such as) random errors in analytical devices (e.g., imprecision of continuous monitors that measure stack emissions) ... error (e.g., estimation of risk to laboratory animals or exposed workers in a small sample), (and) non ...
... errors (such as) random errors in analytical devices (e.g., imprecision of continuous monitors that measure stack emissions) ... error (e.g., estimation of risk to laboratory animals or exposed workers in a small sample), (and) non ...
Page 23
... errors ( e.g. , incorrectly inferring the basis of correlations between chemical structure and biological activity ) , b ) oversimplified representations of reality ( e.g. , representing a three - dimensional aquifer with a two ...
... errors ( e.g. , incorrectly inferring the basis of correlations between chemical structure and biological activity ) , b ) oversimplified representations of reality ( e.g. , representing a three - dimensional aquifer with a two ...
Contents
SUSTAINABILITY AND MAKING DECISIONS UNDER | 39 |
RISK COST AND BENEFIT ANALYSIS RCBA IN RISK | 70 |
EXPOSURERESPONSE MODELS FOR RISK ASSESSMENT | 113 |
PROBABILISTIC DOSERESPONSE MODELS | 171 |
MONTE CARLO BOOTSTRAPS AND OTHER METHODS | 226 |
INFLUENCE DIAGRAMS BAYESIAN | 257 |
METAANALYSIS POOLING SAMPLE DATA | 277 |
CONTINGENCY TABLES IN RISK ASSESSMENT | 312 |
STATISTICAL ASSOCIATIONS AND CAUSATION FOR RISK | 333 |
RISK ASSESSMENT FRAMEWORKS CALCULATIONS | 367 |
PRACTICAL ANALYSIS OF DECISIONS FOR RISK | 417 |
REFERENCES | 447 |
GLOSSARY | 465 |
Other editions - View all
Environmental and Health Risk Assessment and Management: Principles and ... Paolo Ricci Limited preview - 2005 |
Environmental and Health Risk Assessment and Management: Principles and ... Paolo Ricci No preview available - 2009 |
Environmental and Health Risk Assessment and Management: Principles and ... Paolo Ricci No preview available - 2010 |
Common terms and phrases
action air pollution alternative analysis approximately assessment and management assessor associated assumptions Bayesian Bayesian networks calculated cancer carcinogenic causal cell chapter chemical chi-square chi-square distribution choice coefficient of correlation concentration confidence interval confidence limits Consider consists contingency table costs and benefits cumulative distribution data set decision-maker degrees of freedom density function depicts determine deterministic developed discussed disease dose dose-response models economic emission empirical environmental equal equation error estimated example expected value exposure exposure-response factors Figure follows formula frequency independent variables individual influence diagram likelihood linear magnitude maximum mean measured meta-analysis methods Monte Carlo normally distributed null hypothesis observations obtain outcomes p-value parameters Poisson Poisson regression population precautionary principle probabilistic random variable ratio regression model relevant response risk assessment risk management sample scientific specific standard Suppose toxic uncertainty and variability utility function variance zero