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Is Your Bus Exhausting? Stevens Institute of Technology

 

TEACHERS: Smog City Investigation

Objectives
Students will be able to:
  • utilize an interactive smog visualization application, Smog City;
  • see the relationship between ozone levels and variables such as population levels and emissions;
  • design an experiment about ozone levels using a Smog City.

Materials

 

Background:

Smog City is an interactive air pollution simulator that demonstrates how personal choices, environmental factors, and land use can contribute to air pollution. While using the Smog City application, the user is in control so the “visit” can be a healthy or unhealthy experience. Users can see how ground level ozone, the biggest part of summertime smog, increases or decreases depending on the time of day in Smog City. Since ozone can irritate respiratory systems, cause breathing difficulty, coughing, and chest pain, knowing how and why ozone forms and what can be done is important to the residents of Smog City and everyone else on the planet.

Cautionary Note: Relationships between ozone, emissions, and weather conditions are very complex. Smog City's relationships are based on a simplified model of complex atmospheric processes in Sacramento, California, therefore there is no guarantee that the model is scientifically accurate for this or other regions. Results only illustrate general behavior of air pollution processes, and cannot be used for any quantitative purpose or in detailed planning of future control strategies.

Ozone levels depicted in Smog City are estimated by simulating the air quality over Sacramento, California using a computerized model of the region. The computer model creates an imaginary box over the area to represent the atmosphere above Sacramento. Air quality conditions in the box are simulated to account for both human influences and natural factors that affect ozone formation. Each simulation represents one day. In the morning, the box has healthy air quality conditions. As each hour of the day passes, pollutants from human activities such as industry and operating cars and trucks, are released into Smog City's atmosphere. In this model, pollutants take into account variations in human activity, such as morning rush-hour traffic and movement and mixing, which are influenced by weather characteristics such as wind speed, sunlight, and temperature.

One weather characteristic that can have influence over ground level ozone production is the presence of a temperature inversion layer.  Temperature inversion layers typically form when the temperature of the ground rapidly decreases as the sun sets in the evening. The cooling of the ground subsequently cools the air directly above it. This cool layer of air is heavier than the warmer air above, causing the cool air to become trapped close to the ground. This is the opposite of what normally occurs, air temperature decreasing with altitude, so it is called an inversion.  Temperature inversion layers can occur between 100 to a thousand feet above the ground depending on the weather conditions. Inversions act like a cap on the atmosphere causing air pollutants from human activities to build up in the cool air trapped under the inversion layer, resulting in an increase of air pollution levels. In some places when there is little or no wind, inversion layers can linger for several days.

The development of Smog City was a collaborative community outreach effort between public agencies and private sector consultants. Funded by a grant from the U.S. Environmental Protection Agency, Smog City is a copyright of the Sacramento Metropolitan Air Quality Management District. Smog City is authorized for use as an educational and demonstration tool and may be downloaded for non-profit use by the general public, other agencies, associations, and educational institutions. Smog City: Copyright 1999 Sacramento Metropolitan Air Quality Management District.

In this lesson, students will create their own investigation using the ozone modeling tool. For the investigation, the student must create a hypothesis, design the experiment, run the experiment and discuss the results. The Procedure section contains directions for using the Smog City model.

For additional information about the scientific method and the importance of controls in an experiment, view The Principles of Science example.

Procedure:

PART 1: SMOG CITY EXPERIMENT
NOTE: If you've already completed Smog City Modeling activity, you can begin this activity at step 12.

  1. Access the Smog City web site (http://www.smogcity.com/).
     
  2. Click "Run Smog City” from the left-side navigation bar.
    • NOTE: Smog City is a JAVA Applet that runs in your Microsoft Internet Explorer or Netscape Navigator browser. For offline use, follow the Download link for instructions on downloading Smog City to your computer.
       
  3. Once Smog City loads to your computer, take note of the following areas of Smog City, including Weather Condition, Population Level, and Emissions Levels. All areas have “clickable” choices. Mouse-over or click on the choices.
    • NOTE: in the status bar at the bottom of the your browser, there is information about each choice when the mouse is hovering over one of the settings.
       
  4. Click the Red “Reset” button.
     
  5. Look at all the choices again. Notice how each of the choices are pre-set to a certain level. These are called the default settings. In the chart on your student worksheet (see example below), circle or highlight the default setting for each choice. The first setting, Maximum Daily Temperature, has already been completed for you.

    Area Name:

    Choices Included in the Area:

    Select Weather Conditions

    Maximum Daily Temperature
    80ºF - 90ºF - 100ºF - 110ºF - 120ºF

    Inversion Layer
    Low inversion - High inversion - No inversion

    ...

  1. Click the Red “Reset” button to make sure that the defaults are set.
     
  2. Click on the Green “Start” button. Record what happens on the Student Worksheet.
    Settings Health Effects at Peak Ozone Level
    • Default
     

  3. Turn all of the Emissions Levels Dials (Cars and Trucks, Off Road, Industry, and Consumer Products) down to 1. Leave all other choices at the default settings. Click the Green “Start” button. Record what happens on the Student Worksheet (see HELP for more information).
     
  4. Turn only the Cars and Trucks dial up to 3. Leave all other settings alone as illustrated in the chart below. Click the Green “Start” button and record what happens on the Student Worksheet. Continue to change the Cars & Trucks settings according to the Student Worksheet and record the results in the table.

    Cars & Trucks Emissions Ozone Investigation Table

    Cars &
    Trucks
    Off Road Industry Consumer
    Products
    Health Effects at Peak Ozone Level
    1 1 1 1  
    3 1 1 1  
    5 1 1 1  

  5. Click on the Red “Reset” button.
  6. Now that you are familiar with the basics of Smog City, you are going to design your own experiment. The experiment will involve changing the Population Level and Emissions Levels, choices that humans have control over. The experiment must be written in the Scientific Method format on the Student Worksheet. The explanations below may help you with your experiment.
    • Hypothesis – a question or idea that you might have about the relationship between Population Levels and Emissions Levels. For example; As Population Levels decrease, and Consumer Products increase, there will be an increase in unhealthy levels of ozone.
    • Experiment – select the appropriate choices described in your hypothesis and run the experiment by clicking on the Green “Start” button. Make sure to list all of the steps you took while setting up the experiment.
    • Data – collect the data from the experiment, including the Health Effects at Peak Ozone Levels resulting from your choices.
    • Conclusions – reflect upon the choices you made and the resulting data and discuss (explain) if the data supports your hypothesis. If the data does not support your hypothesis, explain what you think may have occurred and how you would change your hypothesis.
       
  7. Would you change any part of your experiment? If so, restate your hypothesis and run the experiment under the new conditions. Write a few sentences to update your conclusions based on your revised experiment.

PART 2: CLASS / GROUP DISCUSSION
In a Class or Group Discussion based on all the data collected, answer the following questions on the Student Worksheet:

  1. Was there any one variable that seemed to have a greater increase in smog than others tested? Which one?
  2. What steps could be taken to control Emissions Levels?
  3. Can you think of ways to reduce ozone levels?
  4. How could a population increase occur without an increase of emissions?

 

 - - Based on all the data you have collected, answer the questions on the Student Worksheet - -

 

Assessment

  1. Was there any one variable that seemed to create a greater increase of smog than others tested?  Which one?
  2. Can you think of ways to control ozone levels?
  3. How could a population increase occur without an increase of emissions?

 

Implementation Tips
For this lesson, it is necessary for students to test their hypotheses by using the simulation, Smog City. If the network connection is down or very slow, you can:

  • download the Smog City program to all computers before the class begins (warning: this is a time consuming task)
  • collaborate with the Computer Teacher

 

Notes
Three major factors affect ground-level ozone in Smog City: weather, population, and emissions. Smog City allows the user to modify the environment by adjusting the pollutant factors. The complexity of the lesson can be increased by challenging the students to work with all three sets of variable, Weather Conditions, Population Levels, and Emissions Levels.

It might be helpful to lead the class through a simulation to demonstrate how to use the model more as a tool instead of a toy.

After completing the exercise that introduces the students to the basics of Smog City, have the students design their own experiment using Smog City by selecting and changing only one variable. Suggestion: Encourage the students to select the variable they think will most affect ozone levels.

For example:

  • Hypothesis:
    As Population Levels decrease, and Consumer Products increase, will result in unhealthy levels of ozone.
  • Experiment:
    1. Reset Smog City to ensure all variables are back to "default" levels.
    2. Decrease the Population Levels to Half the Current Population. As the population decreased, it was observed in the animation that houses disappeared.
    3. Increase the Consumer Products dial to maximum output. As the dial was turned, it was observed in the animation that emissions from the houses increased.
    4. All other choices were left at the default settings.
    5. Press Start.
    6. The simulation ran, showing the results of increasing consumer products emissions for that system.
  • Data:
    • After the simulation ran, the line graph showed that the ozone levels did change as a result of increasing Consumer Products and decreasing the Population to Half the Population. The ozone levels slowly began to rise out of the "good" level around noon. Quickly after that, the ozone levels rose and peaked to "unhealthy for sensitive groups" levels around 4 p.m. After 4 p.m., the ozone levels slowly declined and around 7 p.m. were low enough to register in the "good" range again.
    • Ozone levels reaching the "unhealthy for sensitive groups" range are serious because according to the EPA, Active children and adults, and people with respiratory disease, such as asthma, should limit prolonged outdoor exertion.
  • Conclusions:
    Raising the level of Consumer Products and decreasing the Population does create an impact on the ozone level. Although the resulting increase did create an unhealthy environment, it was not the variable that had the greatest impact on ground level ozone (smog). Upon further investigation, increasing the amount of cars and trucks increased the ground level ozone to the Unhealthy range.

 


 
 
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