PRINCIPLES OF ENVIRONMENTAL SCIENCE
Environmental Science and Policy 110
I. Instructors
Peter Richerson, Professor.
Office Hour Th 4-6 2120J Wickson,
Muamar Al-Najjar, Reader
Office Hour Wednesday 11-12 2120J Wickson, mmalnajjar@ucdavis.edu
Lecture: MWF 4:10-5:00 PM 119
Wellman
II. Text: Gilbert M. Masters.
1997. Introduction to Environmental Engineering and Science, Second Edition.
Prentice Hall. See also course materials on the web
http://www.des.ucdavis.edu/faculty/Richerson/esp110.htm
III. Objectives of the Course
This course has two major functions: (i) to introduce you to
the physical and chemical environmental sciences, and (ii) to improve your
quantitative analytical skills.
A decent knowledge of the physical/chemical environmental
sciences is essential for environmental professionals. Organisms, including
people, live in environments where they are buffeted by winds and currents,
exposed to nutrient and toxic chemicals, and heated and cooled by radiative
transfers of energy. The activities of organisms change the physical/chemical
environment which in turn affects other organisms. Thus, virtually all of the
environmental problems that you will spend your careers managing will have a
physical/chemical dimension. Some of these problems are relatively simple, such
as the management of the oxygen depleting, fish killing effects of sewage on
receiving water bodies. Some of them are awesomely complex. Moving water from
Northern to
Quantitative analysis is a fundamental part of
understanding and managing ecological systems. Hardly ever do environmental
problems yield to categorical analysis. The question is not whether to pollute
or not to pollute, but how much of a pollutant do we need to remove to achieve
some desirable outcome, such as reducing the mortality of fish (or humans) to a
tolerable level. We need to estimate the performance of alternative
protection or remediation plans in order to find a cost-effective
solution to the problem. The main tactic for solving management problems
consists of making a model of the physical, chemical, biological, and
socio-economic processes involved and using it as a tool to solve the problem.
We want you to come out of the course with the skills necessary to set up and
solve basic models of environmental processes and problems.
IV. Approach
This course is in the style of an engineering course in
environmental science. The lectures will lay out the basic physical, chemical
and biological processes that underlay problems in air pollution, water
pollution, solid waste management, and the like. Major components of the course
include weekly problem sets and a final project on a topic of your own
choosing.
We
want you to learn to think like an engineer. This isn’t the only way to think,
but engineers have a very useful set of tools that you will want to have in
your professional repertoire. Most fundamentally, engineers practice the art of
building practical quantitative models to solve concrete problems. You might
suppose that the models used in environmental science are normally complex
because the environmental processes involved are almost always complex. It is
true that complex models, such as General Circulation Models of the atmosphere,
are essential tools in their place. However, such models are extra-ordinarily
expensive to build and use. They often predict poorly because they are overfit.
The data one has available is generally very limited in quantity and noisy. If
a too-complex model is used, you will fit the noise in the data as well as the
real patterns. The too-complex model will “predict” the noisy data all too
well. But it will badly fit the next lot of data from the same system because
the fit was bamboozled by the noise in the original data. As a practical
matter, we always start out, and often finish, using simple models, even when
we know the problem is complex in principle. Engineers call the most basic of
such models back of the envelope calculations.
The idea is to boil a complex problem to a simplicity that lies at its heart.
You try to make some conservative simplifying assumptions, perhaps heroic
simplifying assumptions. This often requires the
killer instinct—a willingness to ignore all sorts of possible
objections to get to some kind of model you can solve to get some kind of
answer, any kind of answer. Then you turn the crank,
and see what sort of answer pops out. Then you ask if the answer is reasonable
given the science you know and whatever data you have at hand. If not, you take
another cut. Very often, you soon work out an answer that practically has to be
right to an order of magnitude (within factor of ten). Often, that
is all you need to know, at least for the moment. A particular pollutant caused
by a project may be well under a threshold of damage, for example—no action
needed. Or the calculation may suggest that it will be well over the
threshold—best available technology is obviously needed. Only if it is in
between do you need to get fancy. Even if you do no more than discover that a
more complex analysis is needed, you often gain a lot of insight into the
problem working on the back of the envelope. If you do make a complex model,
you’ll end up doing a lot of back of the envelope calculations to check that
the complex model is working right, at least under simplifying assumptions.
Thus, paradoxically, simple models are one
of the most important tools to analyze complex problems. Hence, we stress the art
of the back-of-the-envelope calculation in this course. We say “art” because no surefire recipe exists to
pick the right simple model to apply to a complex problem. You use all the
knowledge you have about the system, add a bit of creative thinking, and hope
for the best. Quite often, the uncertainty in
complex environmental problems remains large after our analysis is complete.
Hence, we often monitor systems, collect more data, and take new cuts at models
as the new data accumulates. This is called adaptive management.
The lecture part of the course introduces you to the
kinds of general physical and chemical knowledge you need to set up simple
models. Albert Einstein is supposed to have remarked “imagination is more
important than knowledge.” At least as far as solving practical problems, he
was only half right. Most of you also know about biological ecology from other
courses, so by the end of this course, you’ll know a lot about environmental
science. Of course, the details are endless, and when you come to solve real
problems on the job you’ll have to read deeper. We hope that this course will
give you a running start on most problems you’ll run into. Your project will
give you experience at ferreting out the knowledge you need to solve a
particular problem.
The problem sets are designed to give you lots of hands-on
experience solving problems. The text and the problems in it are quite
reflective of real-world situations. Many back-of-the-envelope calculations are
no more complex than these problems. The harder part, where Einstein’s
imagination comes in, is to set the problem up in a way that lets you get away
with a simple calculation—the art idea again. The project requirement is
designed to give you experience reviewing how others think about a problem of
your own choice, and trying you hand at setting up your own calculations.
This course is
designed to put marketable skills in your hands. Biological
ecologists with good practical quantitative skills and some knowledge of the
physical environmental sciences are not common, nor are engineers with a good knowledge
of ecology. You will be able to solve many problems that would ordinarily take
an engineer, saving your employer (or yourself, if self-employed) the cost of
hiring an expensive piece of talent. When problems do get too complex for your
physical/chemical expertise, you’ll be in a position to make a timely,
persuasive, recommendation to hire an expert. Often environmental professionals
work in multi-disciplinary
teams. Successful teams have members that appreciate each other’s
streng
V. Course Requirements
A. Exams. There will be a midterm and final exam, worth 15% and 30% of your grade, respectively. The exams will test your comprehension of the concepts and principles outlined in the reading and lectures. The exams will also have some quantitative problems to solve.
B. Problem sets. The problem sets will be worth 25% of your grade. You are perfectly free to seminar with other students about how to do a problem, but you must do your own work. Problem sets turned in late will be docked 10% per day up to a maximum loss of 50%.
C. Term project. This will be worth 25% of your grade. Choose a problem that interests you. It must have a physical/chemical environmental science component and be amenable to quantitative analysis. Your task is to write a technical briefing paper on your problem. Imagine you have been hired as a consultant or delegated by your employer to solve the problem, or at least recommend the next step in its solution. Describe the problem. Review the scientific principles involved. Illustrate the problem with a simple model implemented like a problem set. The idea here is not to make a fancy model but to think the problem down to something susceptible to a back-of-the-envelope calculation or small set of calculations. Be sure that your model is integrated into the text description of your project. Motivate the model, describe how it works and use the results to underpin your conclusions. In technical prose, about half your persuasive power rests on your words and about half on your numbers, and everything depends upon making the two work together. You may find Excel, or other more sophisticated programming tools, useful when problems get a bit more complex than those in the problem sets. If others have done a more complex quantitative analysis, critique it. Suggest what further data collection or modeling is required. You can pick a big problem like the effect of anthropogenic CO2 on global climate change or a small one, such as how to grow a good lawn without allowing excess nitrogen fertilizer to run off or leach downwards. You should submit a proposal for your project to Professor Richerson by February 1 and a first draft by March 8. Professor Richerson will make himself available to help with projects. Come to his office hour, shoot him an email, or make an appointment if you want help. If you are interested in a more ambitious project I can arrange for 198 credit, perhaps in Spring Quarter, to finish a project that gets out of hand.
D. Attendance and Participation. Your level of attendance and participation at
the weekly discussion sections will constitute 5% of your final grade. Attendance at office hours will also be taken
into account when the TA determines this portion of your grade. By putting in time at discussion and office
hours, your quantitative skills will improve more rapidly and with less effort
as you benefit from the interactions with others.
VI. Discussion Section
The discussion sections serve two purposes. First, they give you an opportunity to ask questions about the scientific concepts and principles reviewed in the text. Second, the TA will review the methods for handling the problems, particularly difficulties experienced by many students. Mr. Vaughn is especially committed to helping you get your problem solving skills honed to the highest level you can in one quarter. He will use the discussion session to introduce some analyses that are a little more imaginative than those in the text. These are intended to be a half-way house between the text problems and your project. If you need extra help with some of the problems please take advantage of our office hours. Our office hours are held in 2120J Wickson, the big teaching lab, in order to encourage students meet with each other as well as us to master the problem sets.
VII. Grading Policy
In the past, students in this course have differed widely
in background and skills. Our objective is to raise everyone’s skill level as far as
possible, whatever level you enter with. We will put out extra
effort to help those with weaker backgrounds achieve a decent level of
proficiency, if you will put in effort in proportion. We are also keen to help
skilled students who want to push the envelope of their skills, say to produce
a really outstanding project. We will not abandon curve grading entirely, but
will give a lot of consideration to students who show improvement relative to
their entry skills. We’d like to think that we can help any student who tries
hard at to get least a B in this course. We’d be happy to hand out any number
of A+s to able students who do elegant projects. In the past, abler students have often acted as
informal mentors for the less able. We will count this as a positive
contribution to the class.
VII. Lecture,
I. Introduction to the Course
(January 4, 6)
Due January 13, Problems 1.2 1.5
1.6, 1.12,1.22, 1.29
II. Environmental Chemistry (January 9, 11, 13)
Due January 20 Problems 2.1, 2.5
2.7, 2.10, 2.20, 2.26
Also do the Fickian diffusion problem from the web page
III. Water Pollution: Surface
Water (January 18, 20, 23)
Due January 27 Problems 5.2,
5.5, 5.7, 5.17, 5.23, 5.34, 5.36
IV. Water Pollution: Ground
Water (January 25, 27, 30)
Due February 1: Term Project Proposal
Due February 3 Problems 5.38, 5.40, 5.42, 5.43, 5.47, 5.52, 5.53
February 1 Clear
V. Air Pollution I (February
3, 6, 8)
Due February 10
Problems 7.1, 7.4, 7.5, 7.6, 7.11, 7.12,
7.13, 7.14
February 13 Midterm Exam
covering sections I-IV
VI. Air Pollution II
(February 15, 17, 22)
Due February 24 Problems 7.19, 7.20, 7.22, 7.28, 7.33, 7.38, 7.44, 7.47
VII. Risk Assessment (February 24, 27)
Due March 3 Problems 4.2, 4.6, 4.13, 4.20, 4.22
VIII. Global Atmospheric
Change (March 1, 3, 6)
Due March 10 Problems 8.1, 8.2,
8.4, 8.6, 8.7, 8.15, 8.20, 8.35
Due March 8: First Draft of Term Project
IX. Water Quality Control (March 8, 10)
No Problems: Work on Term Project
X. Solid Waste (March 13)
No Problems: Work on Term Project
March 16: Projects due
March 18 08:00-10:00 Final
Exam