Initial Publication Date: July 7, 2011

Carbon In the Atmosphere

Part C: Keeping track of CO2 in today's atmosphere

In Lab 3B, you observed that changes in the global carbon cycle can operate at very long time scales associated with past ice ages. In this section, you will investigate recent trends in changes in atm CO2 over much shorter time scales of years to decades. First, take a few minutes to examine the graph on the right. Click to enlarge.

Checking In

How does the current trend of atm CO2 since 1950 compare to atm CO2 over the past 650,000 years?

Variations and trends are important patterns that scientists look for in complex systems

Long-term time series data are important to scientists who study complex systems such as climate and the carbon cycle. Time series data taken at equal time intervals often generate important trends that help explain the behavior of a system over time. Scientists use trends to understand the past, the present and to predict the future. Long-term trends can emerge from data that is often quite variable and operates at very different time and spatial scales. You have already seen examples of this variability when you analyzed CO2 and temperature data from the Vostok ice cores.

To help you understand the difference between trend and variation, watch the video below:

If the video does not play, watch here: Trend and Variation - YouTube

Watching Earth Breathe: Seasonal changes in vegetation and CO2

Different components of a complex system such as the carbon cycle can operate over many different time scales and spatial scales. For example, NASA has detected seasonal changes in atm CO2 concentration measured by AIRS and in vegetation growth measured by another instrument on the Aqua satellite called MODIS. NASA has used the data from AIRS and MODIS to create a year long animation of these seasonal changes in CO2 and vegetation. Before you watch the NASA animation below, make note of the following:

  • CO2 in the atmosphere is represented by the color orange. The deeper the orange, the greater the amount of CO2.
  • Changes in vegetation growth is represented by the color green. The deeper the green, the denser the vegetation.
  • You can pause the animation by clicking on the date (example SEPT 01) or by clicking pause.
  • It helps to first pay careful attention to what the vegetation is doing and then pay attention to what CO2 is doing.
  • Remember that vegetation and photosynthesis are linked.

NOTE: You can also view this video animation at NASA Viz: A Sky for All Seasons which has background information and an accompanying audio. Scroll down to the second image and click to watch and listen.


With a group or with the class, discuss the following:

  • What patterns in atm CO2 and vegetation over time can you observe in this animation? List all that you can.
  • On what time scales are the changes in atm CO2 and vegetation changing?
  • How do the spatial scales of atm CO2 and vegetation differ between the Northern Hemisphere and the Southern Hemisphere? What might account for those differences? Hint: Think about differences in land mass.
  • Explain how a seasonal change in vegetation and photosynthesis can drive a seasonal change in levels of atm CO2.
  • Did you observe any long-term trend(s) in concentrations of CO2 in the animation?

The Keeling Curve reveals seasonal patterns and a decadal trend in atm CO2

As the leading greenhouse gas, atm CO2 is the most closely studied and measured gas in our atmosphere. In the 1950s, the United States Air Force studied atm CO2 as part of their Cold War missile program. In 1958, regular measurements of atm CO2 began when a young geochemist named Charles Keeling collected and analyzed samples of CO2 on top of the Mauna Loa volcano on the Island of Hawaii in the Pacific Ocean. When analyzing his atm CO2 data, Dr. Keeling discovered some interesting patterns in CO2 and a worrisome trend. Watch the video below on Charles Keeling and his data. As you watch, pay attention to the pattern of variations in CO2.

NOTE: You can also watch this video here: Keeling's Curve: The Story of CO2 on Vimeo

Next, use the animation below to investigate Keeling's atm CO2 data in greater depth. As you go through the animation:

  • Keep in mind what you have already learned about the seasonality of the carbon cycle and its relationship to vegetation and photosynthesis.
  • At the end of the Animation there is a More Info screen where you will find hints to understanding Dr. Keeling's data. You can also find a link to the most recent monthly average CO2 data measured from Mauna Loa below.
  • atm CO2 is measured in ppmor parts per million per volume. Watch this visualization of 392 ppm of carbon dioxide molecules compared to nitrogen and oxygen molecules in the atmosphere to help you understand ppm.

Data from Mauna Loa Observatory & NOAA's ESRL; Developer: Candace Dunlap, TERC; Animation Developer: Lenni Armstrong, informmotion


With a peer or group, discuss the following:

  • Describe the pattern of variations that emerged from Keeling's CO2 data. Did you see these same types of variations in the NASA animation of seasonal CO2 and vegetation? Explain.
  • Describe the time series trend of atm CO2measured at Mauna Loa. What does this trend "say" about the concentration of atm CO2 since 1958?
  • What evidence, if any, does Keeling's data provide that the carbon chemistry of our atmosphere is changing?
  • The Keeling Curve represents atm CO2 data taken from the top of the Mauna Loa volcano in the Hawaiian Islands. Because of this, some people on the Internet have claimed that Keeling's data is influenced by CO2 released from the nearby volcano. Does the rise in atm CO2concentration over Mauna Loa represent a trend only on a regional scale or on a global scale? What makes you think so?

Using ESRL's CarbonTracker program to measure trends and variations in levels of atm CO2 around the world

The Keeling Curve CO2 data indicates that the amount of atm CO2measured at the Mauna Loa Observatory has been increasing since 1958, the date of the first measurement taken by Charles Keeling. Is this same trend occurring elsewhere in the world?

You may find the answer to this important question by using CarbonTracker, a program developed by The Earth System Research Laboratory (ESRL) in Boulder, Colorado and operated by the National Oceanic and Atmospheric Administration (NOAA). ESRL collects greenhouse gas measurements from participating monitoring stations around the world and inputs the data into the Interactive Atmospheric Data Visualization (IADV) CarbonTracker database tool. Scientists and non-scientists can access this database at any time.

Laboratory Investigation: Instructions

In this investigation, your group will use CarbonTracker to generate graphs of atm CO2 data measured from different sampling locations around the world. You will compare these graphs to each other and to Mauna Loa data to look for differences and similarities in trends and variations.

  1. Before you begin your investigation, it is important to spend some time familiarizing yourself with the CarbonTracker tool.
  2. Make a 9 column table in your lab notebook with the following headings:
    • Name of monitoring station: (ex. Mauna Loa)
    • Location description (ex. country, hemisphere, ocean, top of mountain, Arctic etc.)
    • Latitude and longitude: (ex. Mauna Loa is at 19.54 N latitude; 155.5 W longitude)
    • Polar, temperate or tropical latitude
    • Type of measurement used – (ex. tower, surface flask, in-situ.)
    • How measurements are taken – (ex. on land, boat, or plane)
    • Elevation (masl = meters above sea level)
    • Time span (ex. 1960-2015)
    • How CO2 has changed (in ppm) in this time span.
  3. Enter the Carbon Tracker: Interactive Atmospheric Data Visualization (IADV)Tool. Once there, use CarbonTracker to generate a graph of CO2 time series data measured at Mauna Loa. NOTE: Your teacher may decide to do this with you as a class and show the graph on a smartboard.
  4. In your group, decide which three CO2 monitoring stations around the world you would like to investigate.
  5. Decide the time series you will investigate for each CO2data set. NOTE: If possible, select the same time series for all of the graphs you generate. This will allow you to more easily compare trends across your graphs.
  6. Use CarbonTracker to generate a CO2 time series graph for each sampling location you have chosen. NOTE: Your teacher will tell you how you will share these graphs with your group and with the entire class. For example, you can create a PDF which you can print, download, e-mail or send to a new window.
  7. Within your group, compare your CO2 time series graphs to each other and to the Mauna Loa CO2 time series graph. Analyze the graphs for differences and similarities in trends and variations. Use the discussion questions below to guide your analysis.
  8. Compare your graphs and your analysis with the class. NOTE: Your teacher may decide to have you do a jigsaw activity or a gallery walk. Use the post-investigation discussion questions below to guide your analysis.


  • Describe the trends and variations of atm CO2 in the three sampling sites your group investigated. How do they compare with the Mauna Loa data?
  • Are the data trends across the class exactly the same as each other or are there differences? What might account for those differences?
  • Is the rise of CO2 concentration in the atmosphere happening on a regional scale or a global scale? What is the evidence from CarbonTracker?

Is Earth experiencing a stronger greenhouse effect? What's the evidence?

Most scientists claim that the increasing concentration of CO2 in the atmosphere is creating a stronger (or amplified) greenhouse effect leading to a warmer atmosphere. What data supports this claim? The graph pictured on the right brings three different data sets together to tell a more complete story about changes in atm CO2 and global temperatures since the Industrial Revolution began. Click to enlarge the graph on the right and carefully examine each of its three data sets as described below:

  • Global long term temperature data 1880-2006 (Blue lines).
  • Ice core CO2 data from the Siple Dome in Antartica, 1880-1950 (Red lines)
  • Keeling Curve CO2 data taken at Mauna Loa 1958-2006 (Yellow lines)


With a partner or a group, discuss the following and then share with the class.

  • What trends do you see in these three data sets?
  • What "story" does this graph tell you about the relationship between CO2 and temperature since the 1800's?
  • What trends in atm CO2 and temperature have you observed thus far support or refute the claim that the greenhouse effect is amplifying? Explain why.

Stop and Think

3: Describe the overall trend in atmospheric CO2 and temperature since the 1880s.

4: Based on the current scientific data, what is causing the increases in atmospheric CO2? Describe one piece of evidence that supports your claim.

Optional extensions

Want to learn more about carbon in the atmosphere and the keeling Curves? Check out these resources:

  • Research the latest research! New research on the carbon cycle, climate and the environment is on-going. You can use ScienceDaily and to research recent research on greenhouse gases and climate by using combinations of the following tags: greenhouse gases, climate change, carbon cycle, Keeling Curve. Here are two examples:

Climate change caused by ocean, not just atmosphere -- ScienceDaily

Seeing carbon dioxide as a raw material rather than a waste product could lead to a more sustainable future

Flash is no longer supported