Teacher resources and professional development across the curriculum

Teacher professional development and classroom resources across the curriculum

# Interactive Labs

## Lessons > Curb Emissions > Step 2

As you saw in Step 1, even with no further input from humans, the elevated levels of atmospheric CO2 caused by a century of fossil fuel burning will continue to impact the carbon cycle because the system attempts to reach a state of equilibrium, with the exception of the gradual moving of carbon from the surface to the deep ocean, which happens only over longer time-scales. It could take 2000 years or more for this process to restore atmospheric CO2 to pre-industrial levels.

Reducing carbon emissions to zero is far from realistic. Many scientists agree that a doubling of the pre-industrial CO2 concentration to approximately 550 ppm is a reasonable target to shoot for in order to avoid the most serious impacts on climate and ecosystems. How much of a change in fossil fuel consumption would we have to make to limit atmospheric CO2 to that level?

Return to the simulation and change the annual percentage increase in fossil fuel usage until you can keep atmospheric CO2 below 550 ppm in 2100. Once you have found an appropriate level of fossil fuel percentage increase, predict what would happen if fuel use stayed at the that percentage increase and deforestation decreased. In fifty years, if deforestation were decreased 50%, how would the carbon levels in the soil change? Run the simulation to test your hypothesis. Were you correct? Were you surprised by the result? What about your result surprised you?

1. What effect does a high carbon level have on the deep ocean? Why might it be important to keep an eye on the deep ocean carbon levels? What could that one number tell you about the cycle as a whole?
2. Try reducing the level of fossil fuel percentage increase and decrease deforestation by 1 GT per year. Predict what will happen to the atmospheric carbon levels and record it in your Data Table. Run the simulation to test your hypothesis. Were you correct? Were you surprised by the result? What about your result surprised you?