DECLARACIÓN AMBIENTAL
6- EMISIONES ATMOSFÉRICAS
erton, Ontario received a call from the local hospital reporting two cases of severe diarrhea. The public health unit called the local water treatment plant and asked whether the water supply was the cause and was assured by the operators that all was well with the water. On the next day, the number of ill- nesses continued to rise, and the water treatment plant operators were again asked whether the water quality was safe, and they again assured the pub- lic health people that it was. On the third day, the first confirmed case of E. coli 157 infection was confirmed, and the public health personnel deter- mined that the only reasonable source had to be the drinking water.
It turned out that the chlorinator at the water treatment plant had been down for some time and that the plant had stopped testing the water in its own lab. The independent laboratory that had responsibility for doing the bacteriological testing had informed the plant operators that excessive coliforms were in the water, a fact they would have suspected because the chlorinator was mal- functioning. Neither the laboratory nor the water treatment plant operators, however, contacted the
public health agency to report the problem. As a result, there were 195 cases of E. coli infec- tion and 118 cases of infection by other intestinal pathogens. Of those who were infected, 26 individ- uals developed hemolytic uremic syndrome, a seri- ous complication of the E. coli 157 infection that results in swelling of the face and other extremities and abnormal kidney function, with some people requiring long-term dialysis.
The direct cause for the outbreak was the malfunctioning chlorinator, but the indirect cause was shown to be the 50% reduction in funding from the provincial government for water testing. As a result of the outbreak, the water lines in Walkerton were flushed with high chlorine solu- tions, and some lines that could not be adequately cleaned had to be replaced, resulting in a cost far exceeding the estimated savings from cutting the funding.
Source: Reprinted from Controlling Environmen- tal Pollution, Vesilind, P. A. and DiStefano, T. D.,
2006. Lancaster, PA: DEStech Publications, Inc. Reproduced with permission of DEStech Publica- tions, Inc.
his wealth. But this action would have triggered a similar response by his neighbors. Why should they stay with one cow when they saw their friend getting wealthy? So they all would buy more cows, and all of these cows would graze on the common. Eventually, however, the number of cows would overwhelm the capacity of the common and all of the cows would have to be killed.
The sharing of the cost of dirty air is similar to the tragedy of the commons. Each one of us, in using clean air, uses it for personal benefit, but the cost of polluting it is shared by everyone. Is it possible for humans to rethink the way they live and to agree voluntarily to limit their pollutional activities? This is unlikely, and as a result, government has to step in and limit each one of us to only one cow.
Another significant problem with benefit/cost analyses is that they can and often are subverted by a technique known as “sunk cost.” Suppose a government agency decides to construct a public facility and estimates that the construction costs will be $100 million. It argues that, because the benefits (however they might be calculated) are $120 million, the
46 Chapter 2 Engineering Decisions
project is worth constructing because the benefit/cost ratio is greater than 1.0 ($120/$100). It then receives appropriations from Congress to complete the project.
Somewhere in the middle of the project, having already spent the original $100 mil- lion, the agency discovers that it underestimated the construction cost. It turns out that the project will actually cost $180 million. Now, of course, the benefit/cost ratio is 0.67
($120/$180), which is less than 1.0, so the project is not economically justifiable. But, the
agency has already spent $100 million on construction. This cost is considered a sunk cost, or money that will be lost forever if the project is not completed. Hence, the agency argues that the true cost of the project is the increment between what the estimated cost is and what has already been spent, or $80 million($180 − $100). The benefit/cost ratio is then calculated as $120/$80= 1.5, which is substantially greater than 1.0 and indicates that the project should be completed. It is absolutely astounding how many times this scam works, and nobody seems to ask the agencies why their next estimates should be believed if all the previous ones were wildly undervalued.
2.4 DECISIONS BASED ON RISK ANALYSES
Often the benefits of a proposed project are not such simple items as recreational values but the more serious concern of human health. When life and health enter benefit/cost calculations, the analyses are generally referred to as risk/benefit/cost analyses to indi- cate that people are at risk. They have become more widely known as simply risk
analyses.
Risk analysis is further divided into risk assessment and risk management. The former involves a study and analysis of the potential effect of certain hazards on human health. Using statistical information, risk assessment is intended to be a tool for making informed decisions. Risk management, on the other hand, is the process of reducing risks that are deemed unacceptable.
In our private lives we are continually doing both. Smoking cigarettes is a risk to our health, and it is possible to calculate the potential effect of smoking. Quitting smoking is a method of risk management because the effect is to reduce the risk of dying of certain diseases.
In effect, the risk of dying of something is 100%. The medical profession has yet to save anyone from death. The question, then, becomes when death will occur and what the cause of death will be.
There are three ways of calculating risk of death due to some cause. First, risk can be defined as the ratio of the number of deaths in a given population exposed to a pollutant divided by the number of deaths in a population not exposed to the pollutant. That is,
Risk= D1
D0
where D1= number of deaths in a given population exposed to a specific pollutant, per unit time
D0= number of deaths in a similar sized population not exposed to the pollutant, per unit time.
2.4 Decisions Based on Risk Analyses 47
E X A M P L E
2.4 Problem Kentville, a community of 10,000 people, resides next to a krypton mine, and there is concern that the emissions from the krypton smelter have resulted in adverse effects. Specifically, kryptonosis seems to have killed 10 of Kentville’s inhabitants last year. A neighboring community, Lanesburg, has 20,000 inhabitants and is far enough from the smelter to not be affected by the emissions. In Lanesburg only two people last year died of kryptonosis. What is the risk of dying of kryptonosis in Kentville?
Solution If risk is so defined, then
Risk of dying of kryptonosis= 10 10,000
2 20,000
= 10
That is, a person is 10 times more likely to die of kryptonosis in Kentville than in a noncontaminated locality.
Note, however, that, even though statistically there is a far greater chance of dying of kryptonosis in Kentville than in Lanesburg and even though Kentville just happens to have a krypton smelter, we have not proven that the smelter is responsible. All we have is statistical evidence of a relationship.
A second method of calculating risk is to determine the number of deaths due to various causes per population and compare these ratios. That is
Relative risk of dying of cause A= DA
P
where DA= number of deaths due to a cause A in a unit time
P= population
E X A M P L E
2.5 Problem The number of deaths in Kentville and their causes last year were Heart attack 5
Accidents 4
Kryptonosis 10
Other 6
What is the risk of dying of kryptonosis relative to other causes?
Solution The risk of dying of a heart attack in Kentville is 5/10,000, whereas the risk of dying of kryptonosis is 10/10,000. That is, the risk of dying of kryptonosis is twice as large as the chance of dying of a heart attack, 2.5 times the chance of dying of an accident,
48 Chapter 2 Engineering Decisions
and 1.7 times the chance of dying of other causes. The risks may be different in Lanesburg, of course, and can be compared.
Finally, risk can be calculated as the number of deaths due to a certain cause divided by the total number of deaths, or
Risk of dying of cause A= DA
Dtotal where Dtotal= total number of deaths in the population in a unit time. E X A M P L E
2.6 Problem What is the risk of dying of kryptonosis in Kentville relative to deaths due to other causes, using the data in Example 2.5?
Solution The total number of deaths from Example 2.5 is 25. Hence Risk of dying of kryptonosis=10
25= 0.4
That is, of all the ways to go, the inhabitants of Kentville have a 40% chance of dying of kryptonosis.
Some risks we choose to accept while other risks are imposed upon us from outside. We choose, for example, to drink alcohol, drive cars, or fly in airplanes. Each of these activities has a calculated risk because people die every year as a result of alcohol abuse, traffic accidents, and airplane crashes. Most of us subconsciously weigh these risks and decide to take our chances. Typically, people seem to be able to accept such risks if the chances of death are on the order of 0.01, or 1% of deaths are attributed to these causes.
Some risks are imposed from without, however, and these we can do little about. For example, it has been shown that the life expectancy of people living in a dirty urban atmo- sphere is considerably shorter than that of people living identical lives but breathing clean air. We can do little about this risk (except to move), and it is this type of risk that people resent the most. In fact, studies have shown that the acceptability of an involuntary risk is on the order of 1000 times less than our acceptability of a voluntary risk. Such human behavior can explain why people who smoke cigarettes still get upset about air quality or why people will drive while intoxicated to a public hearing protesting the siting of an airport because they fear the crash of an airplane.
Some federal and state agencies use a modified risk analysis, wherein the benefit is a life saved. For example, if a certain new type of highway guardrail is to be installed, it might be possible that its use would reduce expected highway fatalities by some number. If a value is placed on each life, the total benefit can be calculated as the number of lives saved times the value of a life. Setting such a number is both an engineering as well as a public policy decision, answerable ideally to public opinion.
2.4 Decisions Based on Risk Analyses 49
E X A M P L E
2.7 Problem The 95% reduction of kryptonite emissions from a smelter will cost $10 mil- lion. Toxicologists estimate that such a pollution control scheme will reduce the deaths due to krypton poisoning from 10/yr to 4/yr. Should the money be spent?
Solution Assume that each life is worth $1.2 million based on lifetime earnings. Six lives saved would be worth $7.2 million. This benefit is less than the cost of the con- trol. Therefore, based on risk analysis, it is not cost-effective to install the pollution equipment.
But what about the assumption of a human life being worth $1.2 million? Is this really true? If in Example 2.7 a human life is assumed to be worth $5 million, then the pollution control is warranted. But this then means that the $10 million spent on pollution control could not be spent on expanding the plant or otherwise creating jobs that may increase the tax base that could provide money for other worthy projects, such as improving education, health, or transportation. More on this later.
Risk calculations are fraught with these types of great uncertainty. For example, the National Academy of Sciences’ report on saccharin concluded that over 70 years the expected number of cases of human bladder cancer in the United States resulting from daily exposure to 120 mg of saccharin might range from 0.22 to 1.144 million cases. That is quite an impressive range, even for toxicologists. The problem, of course, is that we have to extrapolate data over many orders of magnitude, and often the data are not for humans but for other species, thus requiring a species conversion. Yet governmental agencies are increasingly placed in positions of having to make decisions based on such spurious data.
2.4.1
Environmental Risk Analysis Procedure
Environmental risk analysis takes place in discrete steps.
I. Define the source and type of pollutant of concern. From where is it coming, and what is it?
II. Identify the pathways and rates of exposure. How can it get to humans so it can cause health problems?
III. Identify the receptors of concern. Who are the people at risk?
IV. Determine the potential health impact of the pollutant on the receptor. That is, define the dose-response relationship, or the adverse effects observed at specific doses. V. Decide what impact is acceptable. What effect is considered so low as to be
acceptable to the public?
VI. Based on the allowable effect, calculate the acceptable level at the receptor, and then calculate the maximum allowable emission.
VII. If the emission or discharge is presently (or planned to be) higher than the maximum allowable, determine what technology is necessary to attain the maximum allowable emission or discharge.
50 Chapter 2 Engineering Decisions
I. Defining the source and type of pollutant is often more difficult than it might seem. Suppose a hazardous waste treatment facility is to be constructed near a populated area. What types of pollutants should be considered? If the facility is to mix and blend various hazardous wastes in the course of reducing their toxicity, which products of such processes should be evaluated? In other cases the identification of both the pollutant of concern and the source are a simple matter, such as the production of chloroform during the addition of chlorine to drinking water or gasoline from a leaking underground storage tank.
II. Identifying the pathway may be fairly straightforward as in the case of water chlo- rination. In other situations, such as the effect of atmospheric lead, the pollutant can enter the body in a number of ways, including through food, skin, and water.
III. Identifying the receptor can cause difficulty because not all humans are of standard size and health. The USEPA has attempted to simplify such analyses by suggesting that all adult human beings weigh 70 kg, live for 70 years, drink 2 L of water daily, and breathe 20 m3air each day. These values are used for comparing risks.
IV. Defining the effect is one of the most difficult steps in risk analysis because this presumes a certain response of a human body to various pollutants. It is commonplace to consider two types of effects: cancerous and noncancerous.
The dose-response curve for toxic noncancerous substances is assumed to be linear with a threshold. As shown in curve A of Figure 2.4, a low dose of a toxin would not cause measurable harm, but any increase higher than the threshold would have a detrimental effect. It is considered acceptable, for example, to ingest a certain amount of mercury because it is impossible to show that this has any detrimental effect on human health. However, high doses have documented negative impacts.
Some toxins, such as zinc, are in fact necessary nutrients in our metabolic system and are required for good health. The absence of such chemicals from our diet can be detrimental, but high doses can be toxic. Such a curve is shown as B in Figure 2.4.
Some authorities suggest that the dose-response curve for carcinogens is linear, start- ing at zero effect at zero concentration, and the harmful effect increases linearly as shown by curve C in Figure 2.4. Every finite dose of a carcinogen can then cause a finite increase in the incidence of cancer. An alternative view is that the body is resistant to small doses
C A
B
Threshold dose for A 0 0 Beneficial Harmful Dose Response
2.4 Decisions Based on Risk Analyses 51