(10) Environmental Science


Environmental Science: Air Pollution


What Is Science?

Science is an adventure of the human spirit.

It is essentially an artistic enterprise,

Stimulated largely by curiosity,

Served largely by disciplined imagination, and

Based largely on faith in the reasonableness,

Order and beauty of the universe.

Warren Weaver

Concept 2-1 Scientists collect data and develop theories, models, and laws about how nature works.

Science is a Search for Order in Nature

Have you ever seen an area in a forest where all the trees were cut down? If so, you might wonder about the effects of cutting down all those trees. You might wonder how it affected the animals and people living in that area and how it affected the land itself. That is exactly what scientists Bormann and Likens (Core Case Study) thought about when they designed their experiment.

Such curiosity is what motivates scientists. Science is an endeavor to discover how nature works and to use that knowledge to make predictions about what is likely to happen in nature. It is based on the assumption that events in the natural world follow orderly cause and effect patterns that can be understood through careful observation, measurements, experimentation, and modeling.

There is nothing mysterious about this process. You use it all the time in making decisions. Here is an example of applying the scientific process to an everyday situation:

Observation: You switch on your flashlight and nothing happens.

Question: Why didn’t the light come on?

Hypothesis: Maybe the batteries are dead.

Test the hypothesis: Put in new batteries and switch on the flashlight.

Result: Flashlight still does not work.

Identify a problem

Find out what is known about the problem (literature search)

Ask a question to be investigated

Perform an experiment to answer the question and collect data - Scientific law Well-accepted pattern in data

Analyze data (check for patterns)  

Propose a hypothesis to explain data

Use hypothesis to make testable predictions

Perform an experiment to test predictions

                                Accept hypothesis – Revise hypothesis - Make testable predictions

                                                                            Test predictions


Scientific theory Well-tested and widely accepted hypothesis

What scientists do? The essence of science is this process for testing ideas about how nature works. Scientists do not necessarily follow the order of steps described here. For example, sometimes a scientist might start by formulating a hypothesis to answer the initial questions and then run experiments to test the hypothesis.

New hypothesis: Maybe the bulb is burned out.

Experiment: Replace bulb with a new bulb, and switch on flashlight.

Result: Flashlight works.

Conclusion: Second hypothesis is verified.

Here is a more formal outline of steps scientists often take in trying to understand nature, although not always in the order listed:

Identify a problem. Bormann and Likens (Core Case Study) identified the loss of water and soil nutrients from cutover forests as a problem worth studying.

Find out what is known about the problem. Bormann and Likens searched the scientific literature to find out what was known about the retention and loss of water and soil nutrients in forests.

Ask a question to be investigated. The scientists asked: “How does clearing forested land affect its ability to store water and retain soil nutrients?

Design an experiment to answer the question and collect data. To collect data, or information needed to answer their questions, scientists often conduct experiments, or procedures carried out under controlled conditions to gather information and test ideas. Bormann and Likens collected and analyzed data on the water and soil nutrients flowing from a patch of an undisturbed forest and from a nearby patch of forest which they had cleared of trees for their experiment.

Propose a hypothesis to explain the data. Scientists suggest a scientific hypothesis, or possible explanation of what they observe in nature. The data collected by Bormann and Likens showed a decrease in the ability of a cleared forest to store water and retain soil nutrients such as nitrogen. They came up with the following hypothesis, or tentative explanation for their data: When a forest is cleared, it retains less water and loses large quantities of its soil nutrients when water from rain and melting snow flows across its exposed soil.

Make testable predictions. Scientists use a hypothesis to make testable predictions about what should happen if the hypothesis is valid. They often do this by making “If . . . then” predictions.

Bormann and Likens predicted that if their original hypothesis was valid for nitrogen, then a cleared forest should also lose other soil nutrients such as phosphorus.

Test the predictions with further experiments, models, or observations. To test their prediction, Bormann and Likens repeated their controlled experiment and measured the phosphorus content of the soil. Another way to test predictions is to develop a model, an approximate representation, or simulation of a system being studied. Since Bormann and Likens performed their experiments, scientists have developed increasingly sophisticated mathematical and computer models of how a forest system works. Data from Bormann and Likens’s research and that of other scientists can be fed into such models and used to predict the loss of phosphorus and other types of soil nutrients. These predictions can be compared with the actual measured losses to test the validity of such models.

Accept or reject the hypothesis. If their new data do not support their hypotheses, scientists come up with other testable explanations.

This process continues until there is general agreement among scientists in the field being studied that a particular hypothesis is the best explanation of the data. After Bormann and Likens confirmed that the soil in a cleared forest also loses phosphorus, they measured losses of other soil nutrients, which also supported their hypothesis. A well tested and widely accepted scientific hypothesis or a group of related hypotheses is called a scientific theory. Thus, Bormann and Likens and their colleagues developed a theory that trees and other plants hold soil in place and help it to retain water and nutrients needed by the plants for their growth.

Three important features of any scientific process are skepticism, peer review of results by other scientists, and reproducibility. Scientists tend to be highly skeptical of new data and hypotheses until they can be verified. Peer review happens when scientists report details of the methods they used, the results of their experiments and models, and the reasoning behind their hypotheses for other scientists working in the same field (their peers) to examine and criticize. Ideally, other scientists repeat and analyze the work to see if the data can be reproduced and whether the proposed hypothesis is reasonable and useful.

For example, the results of the forest experiments by Bormann and Likens (Core Case Study) were submitted to other soil and forest experts for their review before a respected scientific journal would publish their results. Other scientists have repeated the measurements of soil content in undisturbed and cleared forests of the same type and also for different types of forests. Their results have also been subjected to peer review. In addition, computer models of forest systems have been used to evaluate this problem, with the results subjected to peer review. Scientific knowledge advances because scientists continually question measurements, make new measurements, and try to come up with new and better hypotheses (Science Focus, at right).

Scientific Theories and Laws

Are the Most Important Results of Science?

If an overwhelming body of observations and measurements supports a scientific hypothesis, it becomes a scientific theory. Scientific theories are not to be taken lightly. They have been tested widely, are supported by extensive evidence, and are accepted by most scientists in a particular field or related fields of study. Another important outcome of science is a scientific,

or natural, law: a well-tested and widely accepted description of what we find happening over and over in the same way in nature. An example is the law of gravity, based on countless observations and measurements of objects falling from different heights. According to this law, all objects fall to the earth’s surface at predictable speeds.

A good way to summarize the most important outcomes of science is to say that scientists collect data and develop theories, models, and laws that describe and explain how nature works (Concept 2-1). Scientists use reasoning and critical thinking skills. But the best scientists also use intuition, imagination, and creativity in asking important questions, developing hypotheses, and designing ways to test them. Scientist Warren Weaver’s quotation found reflects of this aspect of science.

The Results of Science Can Be Tentative, Reliable, or Unreliable

A fundamental part of science is testing. Scientists insist on testing their hypotheses, models, methods, and results over and over again to establish the reliability of these scientific tools, and the resulting conclusions. Media news reports often focus on disputes among scientists over the validity of scientific data, hypotheses, models, methods, or results. This reveals differences in the reliability of various scientific tools and results. Simply put, some science is more reliable than other science, depending on how carefully it has been done, and on how thoroughly the hypotheses, models, methods, and results have been tested.

Sometimes, preliminary results that capture news headlines are controversial because they have not been widely tested and accepted by peer review. They are not yet considered reliable, and can be thought of as tentative science or frontier science. Some of these results will be validated and classified as reliable and some will be discredited and classified as unreliable. At the frontier stage, it is normal for scientists to disagree about the meaning and accuracy of data and the validity of hypotheses and results. This is how scientific knowledge advances.

By contrast, reliable science consists of data, hypotheses, theories, and laws that are widely accepted by scientists who are considered experts in the field. The results of reliable science are based on the self-correcting process of testing, open peer review, reproducibility, and debate. New evidence and better hypotheses (Science Focus, at right) may discredit or alter tried and accepted views. But unless that happens, those views are considered to be the results of reliable science.

Scientific hypotheses and results that are presented as reliable without having undergone the rigors of peer review, or that have been discarded as a result of peer review, are considered to be unreliable science. Here are some critical thinking questions you can use to uncover unreliable science:

• Was the experiment well designed? Did it involve enough testing? Did it involve a control group? (Core Case Study).

• Have the data supporting the proposed hypotheses been verified? Have the results been reproduced by other scientists?

• Do the conclusions and hypotheses follow logically from the data?

• Are there no better scientific explanations?

• Are the investigators unbiased in their interpretations of the results? Are they free of a hidden agenda? Were they funded by an unbiased source?

• Have the conclusions been verified by impartial peer review?

• Are the conclusions of the research widely accepted by other experts in this field?

If “yes” is the answer to each of these questions, then the results can be classified as reliable science. Otherwise, the results may represent tentative science that needs further testing and evaluation, or they can be classified as unreliable science.

Science and Environmental Science Have Some Limitations

Before we continue our study of environmental science, we need to recognize some of its limitations, as well as those of science in general. First, scientists can disprove things but cannot prove anything absolutely because there is always some degree of uncertainty in scientific measurements, observations, and models. Instead scientists try to establish that a particular model, theory, or law has a very high probability (90–99%) of being true and thus is classified as reliable science. Most scientists rarely say something like, “Cigarettes cause lung cancer.” Rather, they might say, “Overwhelming evidence from thousands of studies indicates that people who smoke have an increased risk of developing lung cancer.”

Thinking about Scientific Proof

Does the fact that science can never prove anything absolutely mean that its results are not valid or useful? Explain.

Second, scientists are human and cannot be expected to be totally free of bias about their results and hypotheses. However, bias can be minimized and often uncovered by the high standards of evidence required through peer review.

A third problem is that many environmental phenomena involve a huge number of interacting variables and complex interactions, which makes it too costly to test one variable at a time in controlled experiments such as the one, described in the Core Case Study. Using multivariable analysis by developing mathematical models that include the interactions of many variables and running them on computers can sometimes overcome this limitation and save both time and money. In addition, computer models can be used to simulate global experiments on phenomena like climate change, which are impossible to do in a controlled physical experiment.

A fourth problem is that environmental and other scientists must use statistical sampling and methods to estimate some numbers. For example, there is no way to measure accurately how much soil is eroded worldwide or how much forest is cleared every year. So these numbers are estimated by using the best available sampling and statistical techniques. Finally, the scientific process is limited to understanding the natural world. It cannot be applied to answer moral or ethical questions for which we cannot collect data from the natural world.

Scientific Focus

Easter Island: Some Revisions in a Popular Environmental Story

For years, the story of Easter Island has been used in textbooks as an example of how humans can seriously degrade their own life-support system. It concerns a civilization that once thrived and then disappeared from a small, isolated island in the great expanse of the South Pacific, located about 3,600 kilometers (2,200 miles) off the coast of Chile.

Scientists used anthropological evidence and scientific measurements to estimate the ages of certain artifacts found on Easter Island (also called Rapa Nui). They hypothesized that about 2,900 years ago, Polynesians used double-hulled, seagoing canoes to colonize the island. The settlers probably found a paradise with fertile soil that supported dense and diverse forests and lush grasses. According to this hypothesis, the islanders thrived, and their population increased to as many as 15,000 people.

Measurements made by scientists indicated that over time the Polynesians began living unsustainably by using the island’s forest and soil resources faster than they could be renewed. When they had used up the large trees, the islanders could no longer build their traditional seagoing canoes for fishing in deeper offshore waters, and no one could escape the island by boat.

Without the once-great forests to absorb and slowly release water, springs and streams dried up, exposed soils were eroded, crop yields plummeted, and famine struck. There was no firewood for cooking or keeping warm. According to the original hypothesis, the population and the civilization collapsed as rival clans fought one another for dwindling food supplies and the island’s population dropped sharply. By the late 1870s, only about 100 native islanders were left. But in 2006, anthropologist Terry L. Hunt evaluated the accuracy of past measurements and other evidence and carried out new measurements to estimate the ages of various artifacts. He used these data to formulate an alternative hypothesis describing the human tragedy on Easter Island. Hunt came to several conclusions. First, the Polynesians arrived on the island about 800 years ago, not 2,900 years ago. Second, their population size probably never exceeded 3,000, contrary to the earlier estimate of up to 15,000. Third, the Polynesians did use the island’s trees and other vegetation in an unsustainable manner and by 1722 visitors reported that most of the island’s trees were gone.

But one question not answered by the earlier hypothesis was, why did the trees never grow back? Recent evidence and Hunt’s new hypothesis suggest that rats (which came along with the original settlers either as stowaways or as a source of protein for their long ocean voyage) played a key role in the island’s permanent deforestation. Over the years, the rats multiplied rapidly into the millions and devoured the seeds that would have regenerated the forests.

Another of Hunt’s conclusions was that after 1722, the population of Polynesians on the island dropped to about 100, mostly from contact with European visitors and invaders. These newcomers introduced fatal diseases, killed off some of the islanders, and took large numbers of them away to be sold as slaves.

This story is an excellent example of how science works. The gathering of new scientific data and reevaluation of older data led to a revised hypothesis that challenged our thinking about the decline of civilization on Easter Island. The tragedy may not be as clear an example of ecological collapse caused mostly by humans as was once thought. However, there is evidence that other earlier civilizations did suffer ecological collapse largely from unsustainable use of soil, water, and other resources.

Critical Thinking

Does the new doubt about the original Easter Island hypothesis mean that we should not be concerned about our apparent and growing unsustainable use of essential natural capital on the island in space we call the earth? Explain.

Joomla Templates and Joomla Extensions by ZooTemplate.Com



ar bg ca zh-chs zh-cht cs da nl en et fi fr de el ht he hi hu id it ja ko lv lt no pl pt ro ru sk sl es sv th tr uk vi


Subscribe our Newsletter