User Scenario: Atmospheric Urban Pollution Project Using the NSDL
This material was originally developed as part of the
Carleton College Teaching Activity Collection
through its collaboration with the SERC Pedagogic Service.
through its collaboration with the SERC Pedagogic Service.
Initial Publication Date: January 12, 2007
Harry Ungar -- Cabrillo Community College
Trish Ferrett -- Carleton College
Chris Klaus -- Argonne National Laboratory
The individual pollutant teams will then join forces to overlay all data onto a common scales (spatial, time). The purpose is to find patterns, correlations, and trends relating the pollutant gases. This central data overlay exercise is the groundwork for future course explorations into understanding the sources and sinks for primary pollutants and interactions among pollutants. The ultimate goal is to have students predict the locale of "hot spots" for secondary/tertiary pollutants, for which data may be available for later analysis and comparison to their predictions. Students will eventually explore the chemistry and mechanisms of reactions among the pollutant compounds, revisiting and explaining the pollutant data patterns.
Students will leave a record of their work and findings on the NSDL site (using wiki technology) so others can build on their work.
Trish Ferrett -- Carleton College
Chris Klaus -- Argonne National Laboratory
Audience:
Upper-level atmospheric chemistry course (majors)Learning Goals for Students:
- Impact of human activity on the environment
- Understanding and dealing with complexity in a natural system
- Applying chemistry to a real world problem
- Making careful observations of complex data
- Moving from data patterns to research questions
- Connections between chemistry and social, political, economic, and polical issues
- Development of research skills
- Constructing an investigation as a team
- Communication skills in reporting research results
- Integration and synthesis of complex information
- Data analysis skills
Activity Description:
Students will investigate atmospheric pollutant concentration data over a localized geographical airshed (like the LA Basin) and over time (daily/diurnal, seasonal) as a way to begin a larger course investigation into the chemistry of air pollution. An initial data exercise opens the exploration of the topic of air pollution and primary pollutants. Students will be divided into research teams. Each team will choose a pollutant, probably including: O3, aerosols, PAN, NOx, SOx, HC (hydrocarbons), CO2, CH4. Some environmental parameters will be tracked by all groups (temperature, humidity, rainfall, solar radiation). Students will retrieve and plot pollutant concentration using the NSDL communication portal and software repository. Each team will look for trends and then reconfigure into new groups so they can talk and further check each other on their observations and emerging issues/questions. Groups will eventually report out to the entire class on their pollutant data (poster session, panel discussion with written report).The individual pollutant teams will then join forces to overlay all data onto a common scales (spatial, time). The purpose is to find patterns, correlations, and trends relating the pollutant gases. This central data overlay exercise is the groundwork for future course explorations into understanding the sources and sinks for primary pollutants and interactions among pollutants. The ultimate goal is to have students predict the locale of "hot spots" for secondary/tertiary pollutants, for which data may be available for later analysis and comparison to their predictions. Students will eventually explore the chemistry and mechanisms of reactions among the pollutant compounds, revisiting and explaining the pollutant data patterns.
Students will leave a record of their work and findings on the NSDL site (using wiki technology) so others can build on their work.
Data Needs and NSDL Implications:
Data sources:
Regional air pollution control boards, state agencies, EPA, other.NSDL:
Students will download software visualization tools (which need to be developed!). Software needs to be: easy to use, fast, including simple documentation with examples that illustrate plotting options. Ideally, we would also need "moviemaking tools" to convert geographical data that is time-distributed into a time series (movie). The NSDL site could also serve as a repository on the topic of air pollution, including the software visualization tools, student reporting/work repository area, educational materials and curriculum, and links to or information on the relevant data and literature.Outcomes:
Students will make a final report on the augmented data set including a multi-dimensional pollutants map and movies for showing pollutant concentration changes over time, which will be deposited on the NSDL site for future use.Back to the User Scenarios page.