Modelling pollution in the Great Lakes
Modelling pollution in the Great Lakes

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Modelling pollution in the Great Lakes

1 Modelling pollution in the Great Lakes

The main teaching text of this course is provided in the workbook below. The answers to the exercises that you'll find throughout the workbook are given in the answer book. You can access it by clicking on the link under the workbook. When prompted to watch the video for this course, return to this page and watch the clips below. After you've watched the clips, return to the workbook.

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Workbook contents

  • Chapter 1: Pollution in the Great Lakes

    • Summary of modelling stages

  • End-of-section Exercises

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Bob Thomann:
I was in the Public Health Service as a Commissioned Officer at the time, and I remember writing some of these equations down and one of the other mad scientists in the Public Health Service said: "You know that's a model", and that was the first time I heard that word. And I said: "What's a model?" He says: "Well that's interesting". And it was a defining moment, you know, one of those defining moments. I remember him saying: "That's a model", and I'd never heard of that word before, even though the equations had been around at that point for maybe fifty or sixty years.
Susan Rae:
Bob Thomann was one of the founders of water quality modelling in the United States. And modelling - mathematical modelling - has provided one of the biggest success stories in pollution control over the past thirty years: the story of the Great Lakes. The Great Lakes of North America are five large freshwater inland seas on the border between Canada and the USA. Biggest of all, and furthest west, is Lake Superior. South of Superior, and entirely within the USA, is Lake Michigan. Water from both Superior and Michigan flows into Lake Huron. The flow then runs through the Detroit River into Lake Erie, the smallest of the Lakes. Finally, it passes over Niagara Falls, through Lake Ontario, and then out into the St. Lawrence River and the Atlantic.
The lakes now are very much cleaner than they were in the fifties and sixties, and their traditional use for recreation is regaining its popularity. Lakeside resorts are centres for fishing, sailing and other water-based sport. And the lakes contain fresh water, so they're used to provide drinking water for a large part of the North American population. Much of the political impetus for cleaning up the lakes came from the international Water Quality Agreement, signed in 1972 by Richard Nixon and Pierre Trudeau. In the United States, responsibilities for monitoring water quality - and advising on changes - was given to the Environmental Protection Agency. And much of the modelling work was carried out at their Large Lakes Research Lab in Grosse Ile, and island in the Detroit River at the north-west tip of Lake Erie.
Bill Richardson is former station chief at the Lab.
Bill Richardson:
I was accepted in the Public Health Service, and through the course of my discussions with these fellow students, I became aware of, you know, the tremendous pollution problem that was going on in this country. Of course we'd discuss that in classes. It was on National news, Kennedy had just been elected president and he was making quite an issue out of this. The state of Michigan was going through turmoil with the pollution problems in the Great Lakes. Actually the Great Lakes clean up, and whole effort on water polution control, focused on Lake Erie and the Detroit River in the late fifties early sixties, when there were tremendous oil slicks coming down the river from the industries, from the auto plants and the steel industry.
Susan Rae:
Industrial plants like these produce the most obvious forms of pollution. This is River Rouge, just south of metropolitan Detroit, and one of the centres of heavy industryin the state of Michigan. Even now some of the waste products from these factories are washed down the River Rouge, out into the Detroit River and then into Lake Erie. But Pollution doesn't come only from industry. Much of it is a result of ordinary, everyday life.
Bob Thomann:
We could start with bacterial pollution which is a direct result of human sewage. From sewers, combined sewer overflows, which is a combination of rainfall and sewage, and from treatment plants. Then sewage also has various kinds of organic material in it that is not of a toxic chemical point of view, but organic waste that can use up oxygen when discharged to a stream or a lake. And that oxygen then impacts...the loss of oxygen impacts the aquatic ecosystem. Then of the problem of nutrient enrichment from both treatment plants, from humans, as obviously we discharge nitrogen and phosphorous in our waste and from agricultural run off. So bacteriological pollution; organic materialthat contributes to lowering of oxygen; nutrient enrichment is another area. And then finally the toxic chemicals, heavy metals - zinc, mercury, copper, cadmium - which have been around since...since the very beginning, and the newer chemicals, the organic chemicals synthesised by and large since the Second World War, of which there are hundreds of thousand. So in a very broad category those are the major pollution problems.
Susan Rae:
Some fo these newer chemicals are called PCBs - poly-chlorinated biphenyls. There are nearly two hundred different kinds of PCBs, and they've been used in many different manufacturing processes.
Bill Richardson
The problem that became more evident in the late seventies, eighties was that of toxic substances. It was determined that PCBs was a major problem, affecting the possible risks for human health was determined that children of mothers who ate a lot of Great Lakes fish, the infants were displaying certain abnormalities and characteristics that were very disturbing to people. So it was determined to actually ban PCBs even before we modelled it. The problem with PCBs is that a lot of it was produced since 1929, so it was all out in the environment. In inks, carbonless paper, in florescent light fixtures, industrial oils. Even though we banned the use...the manufacture of PCBs in the country, this...millions and millions of pounds of this were distributed in the environment.
Susan Rae:
But despite the apparent size of the problem, the environment can often be forgiving. Lake Michigan alone contains five million million cubic metres of water - enough to swamp modest amounts of pollution. And the holiday resorts in the north of the lake are four hundred kilometres away from the polluting factories of the south. But still, the pollution has to go somewhere. It could decay naturally, into harmless substances. It could be washed out to sea by the flow of water. Or, it could accumulate. And if it does accumulate, how much of it will there be next year? Or in five years? Or ten years? And what will happen if the input of pollution is restricted? Or if it's stopped altogether? The only way to find out is by modelling.
Bob Thomann:
Why modelling and what's the options. The options are to guess at what the effetiveness of certain control actions are, and guessing - maybe my guess, maybe as good as your guess, and that's when controversy arises. So that to the degree to which a model provides at least some objective assessment of the situation, and is credible in the sense that it reproduces observed information, then we might agree that yes, this kind of technique is a useful way to make assessments of the impacts of various environmental control actions.
But without a model we'd always be flying blind, we'd always be guessing, we'd say: "Well maybe on the one hand this, on the other hand that"/ And then I mean also sometimes argue: "Why don't we just go out and measure everything we need to measure, and on the basis of the measurements make an assessment of what the impacts will be". Well that's fine up to a certain point. Most of the time the decisions we're asked to make are to extend the environmental controls beyond what we've already observed, so the question is always a forecasting question, a projection question which we can't measure. So measurement by themselves will never answer the question of what are the impacts of different kinds of environmental control actions. So hence modelling enters the door.
End transcript: Pollution in the Great Lakes (1)
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And the kind of modelling that's needed to make quantitative predictions is mathematical modelling.The kind of modelling where features are represented by mathematical variables and parameters; and where relationshipscanoftenbedescribedbyequations. Bill Richardson has strong views on when mathematical modelling is needed
Why it's important to do mathematical modelling? I am asked that a lot.We spend a lot of money on computers,and of course our salaries, and a lot of other things, to do what we do. And my first response to that is that you don't always have to do mathematical modelling to solve water pollution problems. Infact, I mean it's maybe the last thing you would do. The Cuyahoga river in Cleveland, the Rouge river in Detroit, the oil slicks and the gasoline on it that floated to the surface caught fire from sparks from a welder'storch. First you have to take care of those obvious problems. Now, once you've taken care of the obvious problems,what remains,what are. What are the issues? What happens is, decisions have to be made that are much more subtle, that involve the gross pollution problems. It becomes a matter of degree now. How much of these toxic substances, should we ban DDT - I mean that was a big decision back in the early seventies, doweban PCBs. These were important agricultural and industrial chemicals that had great benefits to solving other kinds of problems. So by banning those we might even create a worse public health problem. So once you start asking these economic and social public health problems, then you need a scientific basis for making those decisions. They might have to go to court. The judge may have...have to have you prove, or show scientifically, that if we spend a certain amount of money, or if we do make a certain decision, ban a certain chemical, that we infact will get a return, there will be a benefit to what we do. So in order to do that, we have to understand how these chemicals behave in the environment. What the cause and effect relationships are between what is coming in from the various sources, industry, municipalities, run off from agriculture,run off from urban lands, atmospheric deposition. We have to understand how those impact...those loads impact the environment, how the chemicals move around, transport, what their fate is, how they bio-accumulate into the fish, how they can work their way up into the human body. And the only way that we know how to do that, is to develop mathematical models that define these processes.. And once we have the mathematical models and that basic understanding, the next question is, how valid are these models?
To help validate its models, the EPA has its own survey ship, the Lake Guardian. This cruises the Lakes throughout the summer months, using a range of specialist equipment to take samples. Each mission is carefully planned. The samples aren't taken at random: the map reference of each sample source is chosen deliberately. These samples come from Grand Traverse Bay, in the north-east of Lake Michigan. Taking samples from different places allows the mixing of the lake to be monitored. And water samples can come from different levels in the lake. The bottles on this device have special mechanisms, so that they open and close at predetermined depths. These samples help to monitor the mixing between different layers of water.
Water quality is measured by going out in a boat, taking a sample of the water, bringing it back to the laboratory and characterising the chemical and biological variables in the water. For example the oxygen level in the water, the nitrogen, the phosphorous level, whether there are any toxic chemicals, PCBs, the heavy metals. So water quality would be characterised by a suite of parameters that describe the chemical and physical and biological integrity of the water. We also measure water quality by examining the sediment, because the sediment in the water are clearly interactive.. And in the same way, you go and you drop a dredge into the bottom of the sediment and you bring up the sediment, bring it back to the laboratory and measure it.
But however simple or complicated the model, there'll always be a need to measure some of the basic parameters· involved -forinstance, the volume of the Lake. Knowing the volume is the only way we can relate the mass of pollution that's been deposited, to the eventual concentration that can be measured.
Well the volume is a very important parameter.Without that we don't know how long the pollutant will be retained in the Lake, or how long the water will be retained. So we need to know the volume. And basically there's a very simple procedure. We have information on the bathymetry of the Lake that they've collected over many years. The Lake levels are measured, so we know fairly accurately the depth of the water at pretty much every square kilometre in the Lake. And basically we just add up these segments of water, knowing their area and the depth - we add up all these segments for the entire Lake, and that becomes the total volume of the lake.
As well as the volume of the water, another quantity that has to be investigated is the water flow-rate. For pollutants that don't degrade, flow of water is the only way of clearing them from the lake. The mathematical models used for pollution in the Great Lakes will obviously get very complicated, as more and more features are included. But there's a role for simple models too.
A lot of scientific modellers, people who are corning from a....from an academic point of view, really start complicated and try to include everything, and try to include as much as possible because they're scientists and they want to understand the wholething. But what I've learned over the years, and what. of the basic engineering principles that I go by, that I think Bob Thomann actually taught me, was to start simple and work toward the complex. And the reason you do that - now there are several reasons why you do that. One is that these models that end up being very complex actually build, you build your building blocks, and one thing builds on another. And you build this you need to gain understanding of basic simple things, and then build the next level of complexity, and then the next level of complexity, and then finally you have the whole thing. But along the way, you have much more confidence in what you've done.
Well a simple model is useful because it's simple. Itallows a rapid computation on a global type of question. For example, for the Great Lakes the global type of question would be, to first approximation how long would it take this Lake to flush out the concentration starting at a given level. And when you first do that kind of calculation you don't need a lot of complicated features, because the principal mechanism is the volume of the Lake, and the flow through the Lake, and the degradation process of the chemical.. Those are gonna be operative even in the most complicatedmodelsSo the simple model is very helpful for those initial first estimates. Infact since modelling is a type of art form, it's very important to start with the more simple calculations, and sometimes a major portion of the information that the decision-makers really want is accomplished from simple models.
End transcript: Pollution in the Great Lakes (2)
Pollution in the Great Lakes (2)
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