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Section Two POLLUTION PREVENTION/WASTE MINIMIZATION 4 ESTIMATING UNCERTAIN BENEFITS AND COSTS OF POLLUTION PREVENTION James D. Englehardt, Assistant Professor Department of Civil and Architectural Engineering University of Miami Coral Gables, Florida 33134-0630 INTRODUCTION Although explicit recognition of risk may raise fears of financial and legal implications within management, it is now recognized that good business practice includes identification of risk in corporate decision making.1 If environmental, health, and safety risks are recognized, the Securities and Exchange Commission (SEC) and Financial Accounting Standards Board (FASB) may require liabilities to be disclosed, and financial reserves or insurance policies to be established. However, the analysis can increase profitability, by aiding selection of production processes having reduced environmental and health liabilities, often large compared to other costs, and by reducing waste disposal costs. Simply performing the risk analysis is often enough to suggest ways of reducing risks and associated costs, once recognized. And, finally, self-insurance requirements, or the value of environmental and health insurance, can be estimated with such methods, which may be of interest, for example, to chemical manufacturers. No one expects risk-free technology, but employees and customers value honest management policies that minimize risks while protecting product quality and economic health. Difficulty in estimating environmental risks, health risks, marketing risks, and the risk of production stoppages (due to contamination introduced with recycled raw materials, for example) can be due either to inherent variability, or to a lack of information.2 In planning, it is often necessary to estimate both types of uncertainty. When the value of the project justifies an in-depth, site-specific analysis of risk, detailed models may be used. However, it is unlikely that a large amount of data or information on most risks will be available within the time and budget available for selecting many pollution prevention processes. In this paper, a Bayesian method of estimating typical risks associated with industrial hazardous waste and processes of minimizing wastes, when little data or specific information are available, is outlined. The risk estimates can be obtained in monetary terms, for example, for use in a benefit-cost analysis to select efficient waste minimization approaches. An example analysis of the economic risk associated with transportation of solvents to and from a commercial recycler is given. Such risk estimates can then be included in the analysis of overall project economics.3 THE MODEL Risk can be defined as the probability of loss. Losses associated with the use and generation of hazardous materials are primarily health, environmental, safety, and economic risks, and may be measured in dollars, lives, quantity of material, or other units. In reality, probabilities, and therefore risks, depend not only on inherent uncertainties, but on the information available for risk estimation. For example, the probability that a prize is behind door one of three is 1/3, until door three is found not to hide the prize, when the probability becomes one-half. Unfortunately, traditionally derived probability distributions do not reflect information content. That is, the shape of a traditionally derived probability distribution that has been revised with 48th Purdue Industrial Waste Conference Proceedings, 1993 Lewis Publishers, Chelsea, Michigan 48118. Printed in U.S.A. 23
Object Description
Purdue Identification Number | ETRIWC199304 |
Title | Estimating uncertain benefits and costs of pollution prevention |
Author | Englehardt, James D. |
Date of Original | 1993 |
Conference Title | Proceedings of the 48th Industrial Waste Conference |
Conference Front Matter (copy and paste) | http://earchives.lib.purdue.edu/u?/engext,21159 |
Extent of Original | p. 23-28 |
Collection Title | Engineering Technical Reports Collection, Purdue University |
Repository | Purdue University Libraries |
Rights Statement | Digital object copyright Purdue University. All rights reserved. |
Language | eng |
Type (DCMI) | text |
Format | JP2 |
Date Digitized | 2009-11-03 |
Capture Device | Fujitsu fi-5650C |
Capture Details | ScandAll 21 |
Resolution | 300 ppi |
Color Depth | 8 bit |
Description
Title | page 23 |
Collection Title | Engineering Technical Reports Collection, Purdue University |
Repository | Purdue University Libraries |
Rights Statement | Digital object copyright Purdue University. All rights reserved. |
Language | eng |
Type (DCMI) | text |
Format | JP2 |
Capture Device | Fujitsu fi-5650C |
Capture Details | ScandAll 21 |
Transcript | Section Two POLLUTION PREVENTION/WASTE MINIMIZATION 4 ESTIMATING UNCERTAIN BENEFITS AND COSTS OF POLLUTION PREVENTION James D. Englehardt, Assistant Professor Department of Civil and Architectural Engineering University of Miami Coral Gables, Florida 33134-0630 INTRODUCTION Although explicit recognition of risk may raise fears of financial and legal implications within management, it is now recognized that good business practice includes identification of risk in corporate decision making.1 If environmental, health, and safety risks are recognized, the Securities and Exchange Commission (SEC) and Financial Accounting Standards Board (FASB) may require liabilities to be disclosed, and financial reserves or insurance policies to be established. However, the analysis can increase profitability, by aiding selection of production processes having reduced environmental and health liabilities, often large compared to other costs, and by reducing waste disposal costs. Simply performing the risk analysis is often enough to suggest ways of reducing risks and associated costs, once recognized. And, finally, self-insurance requirements, or the value of environmental and health insurance, can be estimated with such methods, which may be of interest, for example, to chemical manufacturers. No one expects risk-free technology, but employees and customers value honest management policies that minimize risks while protecting product quality and economic health. Difficulty in estimating environmental risks, health risks, marketing risks, and the risk of production stoppages (due to contamination introduced with recycled raw materials, for example) can be due either to inherent variability, or to a lack of information.2 In planning, it is often necessary to estimate both types of uncertainty. When the value of the project justifies an in-depth, site-specific analysis of risk, detailed models may be used. However, it is unlikely that a large amount of data or information on most risks will be available within the time and budget available for selecting many pollution prevention processes. In this paper, a Bayesian method of estimating typical risks associated with industrial hazardous waste and processes of minimizing wastes, when little data or specific information are available, is outlined. The risk estimates can be obtained in monetary terms, for example, for use in a benefit-cost analysis to select efficient waste minimization approaches. An example analysis of the economic risk associated with transportation of solvents to and from a commercial recycler is given. Such risk estimates can then be included in the analysis of overall project economics.3 THE MODEL Risk can be defined as the probability of loss. Losses associated with the use and generation of hazardous materials are primarily health, environmental, safety, and economic risks, and may be measured in dollars, lives, quantity of material, or other units. In reality, probabilities, and therefore risks, depend not only on inherent uncertainties, but on the information available for risk estimation. For example, the probability that a prize is behind door one of three is 1/3, until door three is found not to hide the prize, when the probability becomes one-half. Unfortunately, traditionally derived probability distributions do not reflect information content. That is, the shape of a traditionally derived probability distribution that has been revised with 48th Purdue Industrial Waste Conference Proceedings, 1993 Lewis Publishers, Chelsea, Michigan 48118. Printed in U.S.A. 23 |
Resolution | 300 ppi |
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