Our Changing Atmosphere
- Gridded chart paper with 1-inch squares, one sheet per group—or this pre-labeled graph paper, copied onto 11" x 17" paper
- Meter stick (not shown), if using chart paper
- 1/2-inch sticky dots (use smaller dots if you are using smaller graph paper), 12 dots per year of data; all dots should be the same color
- Mauna Loa monthly CO2 data, 2006–2019
- Earth globe
- Optional: South Pole monthly CO2 data, 2006–2018; a different color of sticky dots should be used for South Pole data, 12 dots per year of data
If you are using chart paper, complete Steps 1-3. Regardless of what graph paper you are using, complete Step 4.
- Use the meter stick and marker to draw a large x-axis and y-axis on the graph paper. You will need at least 24 squares of space along each axis.
- Label the y-axis “Average monthly CO2 data from Mauna Loa (in ppm)” and choose a scale that will accommodate values from 380 ppm to 404 ppm (if you are graphing data from earlier than 2008, you will need to adjust the scale accordingly), letting each 1-inch line equal 1 ppm along the y-axis.
- Label the x-axis “Month” and place the numbers 1 through 12 along the x-axis, letting two 1-inch lines equal one month.
- Print data sheets and cut so that each group receives one year’s worth of data.
The data you are going to graph are mean monthly atmospheric CO2 data from Mauna Loa, collected by the National Oceanic and Atmospheric Administration (NOAA). Use the globe to locate Mauna Loa. Is it in the Northern or Southern Hemisphere?
Place the dots appropriately on the graph, and also label the graph with the year in which your data were collected. You may want to write the Mauna Loa CO2 values from your data sheet on the sticky dots–one monthly value per dot.
What do you notice? When are the values the highest? The lowest?
Discuss this seasonal variation (see What’s Going On? below). This is usually a very interesting discussion, and is well worth the time before continuing.
If you are also graphing South Pole data, they should be added to the same graph paper (be sure the data are from the same year) using sticky dots that are a different color. What do you notice about the seasonal fluctuation pattern in the Northern Hemisphere and in the Southern Hemisphere? Why do think these different patterns occur in the data?
Tape all of the graphs together in chronological order, overlapping the “month 0” and “month 12” to create a continuous graph of multiple years’ data. What do you notice?
Direct measurements of atmospheric carbon dioxide (CO2) concentrations have been recorded at Mauna Loa since 1958. Its mid-Pacific location makes it an ideal place to collect atmospheric data. The units of atmospheric carbon dioxide measurements are ppm—parts per million. For every million molecules of air in our atmosphere, some number of them are carbon dioxide molecules.
Since 1958, the concentration of atmospheric CO2 has risen from 315 ppm to over 412 ppm (as of December, 2019). This is depicted in the graph shown below, known as the Keeling Curve (click to enlarge). The Keeling Curve is named for Charles David Keeling of the Scripps Institution of Oceanography, who was the first person to make frequent regular measurements of atmospheric CO2 concentrations at Mauna Loa.
The periodic annual fluctuations in the graph reflect seasonal changes. The Northern Hemisphere has far more land area than the Southern Hemisphere, and most of the land area in the Southern Hemisphere is desert. As plants in the Northern Hemisphere grow leaves each spring and summer, they remove some CO2 from the air via photosynthesis, causing CO2 levels to drop. There is a lag time for this effect to show in the data, so the lowest annual CO2 concentrations occur in the fall. During Northern Hemisphere fall and winter, plants lose their leaves, and the decrease in photosynthesis causes the CO2 level to rise. There is a lag time for this change to show in the data as well. Thus, highest CO2 concentrations occur in May each year. This seasonal fluctuation is the natural cycling of carbon from an atmospheric gas to solid plant material and back.
When you view multiple years of data together, the obvious upward trend is not part of the natural cycling of carbon between the atmosphere and the biosphere. Human activities are altering the carbon cycle—both by adding more CO2 to the atmosphere and, through land use changes such as deforestation, influencing the ability of natural sinks, like forests, to remove CO2 from the atmosphere. While CO2 emissions come from a variety of natural sources, human-related emissions are responsible for the increase that has occurred in the atmosphere since the Industrial Revolution (1760 - 1840). Until that time, atmospheric CO2 had not been higher than 280 ppm. Direct measurements of gas bubbles in ice cores from Antarctica show that atmospheric CO2 levels did not exceed 280 ppm during the previous 800,000 years.
The main human activity that emits CO2 is the combustion of fossil fuels (coal, natural gas, and oil) for energy and transportation. Certain industrial processes also emit CO2. Additionally, land use changes such as deforestation remove part of the land sink and thereby cause atmospheric CO2 levels to be higher.
Preparing the graphs before doing this Science Snack with a group will save you time. If students are preparing graphs themselves using chart paper, it is very important that they all use the same scales on their graph axes.
We’ve included data from 2006–201 in Tools and Materials, but if you want to get data for other years, they are available at the websites below. Export the text file for the years in which you are interested, put them into a spreadsheet, and eliminate the columns of data you don’t need.
- Mauna Loa CO2 Data: ftp.cmdl.noaa.gov/products/trends/co2/co2_mm_mlo.txt
- South Pole CO2 Data: ftp.cmdl.noaa.gov/data/trace_gases/co2/in-situ/surface/spo/co2_spo_surface-insitu_1_ccgg_MonthlyData.txt
- Sutro Tower Data, San Francisco: http://www.esrl.noaa.gov/gmd/dv/iadv/graph.php?code=STR&program=ccgg&type=ts
Keeling Curve: http://www.esrl.noaa.gov/gmd/ccgg/trends/
This Science Snack is part of a collection that showcases LGBT artists, scientists, inventors and thinkers whose work aids or expands our understanding of the phenomena explored in each Snack.
Dr.Geoffrey Roest (he/him) is a gay postdoctoral researcher at Northern Arizona University using data science to study urban greenhouse gas emissions. Currently, Dr. Roest is researching in the Gurney Group, primarily on the Vulcan project, a data-driven fossil fuel carbon dioxide emissions product for the entire United States. Outside of research, he is an avid snowboarder and long-distance runner and enjoys lots of other outdoor activities. In the Our Changing Atmosphere Science Snack, you can graph carbon dioxide data from the National Oceanic and Atmospheric Administration (NOAA) to learn about natural cycles and unnatural changes in our atmosphere!