Because it recognizes the importance of U.S. coastal areas to the nation's economy, the U.S. National Ocean Service has formed a task force that is studying the trends and impacts of hurricanes on coastal regions. They have invited your students to participate.

Students will learn about and describe the different classifications of Air Quality Index and the importance of standards in air quality monitoring. Students will also use scientific evidence and reasoning to support a claim about long-term trends in air quality in the United States.  

Students will review the sources of the six criteria pollutants for which the EPA has established standards for and describe their impacts on human health and the environment. 

Students will analyze how air pollution may be transported over time. Students will also differentiate between sources of air pollution and describe how air pollution interacts with the Earth System. 

Students will analyze and describe the relationship between air pollution and minority and poverty populations. Students will evaluate environmental problems in relation to social inequalities. 

By matching pie charts with dates between 2002 and 2020, students will predict how air quality has changed over the past two decades. They will then use color-coded Air Quality Index signatures to assess the accuracy of their predictions.

In this story map students will learn about what air pollution is, its environmental impact, the standards used to describe air quality as defined by the Clean Air Act, and the Earth System interactions that drive the transport of air pollution.

These resources are intended to be used with teachers and students to help model how to apply data literacy skills to analyzing patterns as they relate to stability and change in COVID-19 (and related human geographic) and nitrogen dioxide data.

Information from satellites if often used to display information about objects. This information can include how things appear, as well as their contents. Explore how pixel data sequences can be used to create an image and interpret it.

Scientific data are often represented by assigning ranges of numbers to specific colors. The colors are then used to make false color images which allow us to see patterns more easily. Students will make a false-color image using a set of numbers.