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Weather Watchers – Engager: Skill Level Two
ENGAGER – Skill Level: Two
Exploring Climate Change and Public Perceptions
Objectives: Explain the concept of ‘sources’ and ‘sinks’ as they relate to CO2, use an indicator solution (BTB) to reveal the presence of CO2 and understand the differences between animal and fossil fuel sources of global CO2. Science Skills: Collecting Data, Measuring, Summarizing Life Skills: Critical thinking, wise use of resources
Activity 1: “Where in the World is Carbon”
The activity in Explore More provides a great introduction to the chemical Carbon Dioxide and some of its origins.
Objectives: Explain the concept of ‘sources’ and ‘sinks’ as they relate to CO2, use an indicator solution (BTB) to reveal the presence of CO2 and understand the differences between animal and fossil fuel sources of global CO2.
Life Skills: Critical thinking, wise use of resources
Preparation Activities Review the activity linked in “Explore More.” Collect materials or check to see if they can be borrowed from your Extension Office.
Activity 2 : Measuring Your Carbon Footprint
Objective: Use online tools to make an estimation of personal carbon footprint
Science Skills: Measure, Use Numbers and Tools, Interpret Findings
Review Carbon Calculators in Explore More and chose one to use with group
There are several good websites in Explore More and tools to help you estimate your carbon footprint, and they each vary depending on how accurate you want to be. Why not compare your answer between sites?
Activity 3: Climate Change Survey
Have the youth explore public opinion based on the perceptions of locals regarding climate and weather. Ask the youth to make sure that at least ½ of their interviewees are over 40 years old. It will be important youth can adequately explain the difference between weather and climate before delivering this survey to others.
Ask the Right Questions:
Have the team pool their results. Decide how to compile the responses. Are there patterns in responses? Do variables of age, occupation or time in the area appear to affect perceptions? How does the way we categorize our data effect how it is interpreted by others?