In the Laboratory
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Geographical Information Systems (GIS) Mapping of Environmental Samples across College Campuses Kathleen L. Purvis-Roberts,* Harriet P. Moeur, and Andrew Zanella Department of Joint Science, Claremont McKenna, Pitzer, and Scripps Colleges, Claremont, CA 91711; *
[email protected]
One method for engaging students in the laboratory is to focus on real-world applications of chemistry that affect them (1, 2). Through these examples, students better understand the objectives and purpose of the experiment (3). Environmental chemistry methods are an excellent means for achieving these goals. Since samples can be taken at many different locations, there is a need to be able to organize efficiently the results from all of the sites. Recently, geospatial technologies such as global positioning systems (GPS) and geographical information systems (GIS) have been introduced into the environmental science and geosciences curricula (4, 5). With these applications, students can map environmental data and begin to grasp geospatial relationships (6). Such technologies are now used for environmental chemistry experiments in both upper-level courses and research, so general chemistry offers an excellent situation to introduce students to both GPS and GIS technology. The application described in this article relates to the geospatial mapping of nitrogen dioxide (NO2) samples taken by undergraduate students around three campuses of the Claremont Colleges by diffusion-tube sampling (7, 8). The average concentration of NO2 in the air sampled at each location was plotted on a campus map using ArcGIS (ESRI). Although we used the analysis of NO2, GIS mapping could also be applied to any environmental sampling project, such as lead analysis in water or soil or the measurement of ozone concentrations in the air (9, 10). Experimental The students each chose a sampling site to place their diffusion samplers for one week to absorb NO2 in the air. Each diffusion sampler was made from a plastic culture tube with a piece of stainless steel wire mesh in the bottom that was treated with a triethanolamine兾Brij-35 solution to absorb NO2 molecules. The NO2 trapped in the tube was converted to a red azo dye by reaction with sulfanilamide followed by N-(1naphthyl)ethylenediamine dihydrochloride (NEDA). To de-
termine the quantity of NO2 in a tube, the sample was then analyzed spectrophotometrically with a Spectronic 21 at 540 nm by comparison to a Beer–Lambert law graph based upon a series of standard nitrite solutions (7, 8). The chemical and data analysis can take place during one, four-hour laboratory period. However, the preparation and placement of the sample tubes, which takes about 20–30 minutes, must be done during a prior laboratory period, a week or two before analysis. Experimental details are outlined in refs 7 and 8. Hazards For the analysis of NO2 the nitrosodiethanolamine (NOA) produced when NO2 reacts with triethanolamine is a potential carcinogen. The NOA should adhere securely to the mesh in the tubes, so there should be little, if any, problem. However, the diffusion tubes should be kept in a secure place where they will not be mishandled. Also, the sulfanilamide is a toxic compound. Triethanolamine, Brij-35, and N-(1-naphthyl)ethylenediamine dihydrochloride are all irritants and contact with eyes, respiratory system, and skin should be avoided. The sodium nitrite is oxidizing, toxic, and dangerous to the environment. Results and Discussion The overall goals of the experiment were to help students understand variation of environmental sampling, introduce them to geospatial technology, and to have them compare their results to values listed by governmental agencies. Each student placed three diffusion samplers in the same location, somewhere on the college campuses, either indoors or outdoors. Students were often surprised with the variability of NO2 concentrations from the three samples at their chosen sites. After a student placed the samplers in a location, a GPS unit (Gecko 201, Garmin) was used to obtain precise latitude and longitude measurements. In order to work prop-
Table 1. Example Excel Table for Mapping NO2 Data Student College
a
Building
Type of Location
Latitude Reading b (North)
Longitude Reading (West)
b
NO2 Conc (ppb)
c
Avg. Dev. (ppb)
1
Scripps
Frankel
Dorm room
34.105220000
᎑117.7086100000
76
06
2
CMC a
Stark
Laundry
34.100000000
᎑117.7080400000
75
16
3
Scripps
Routt
Balcony
34.104760000
᎑117.7085900000
45
11
4
Pitzer
Mead
Dorm room
34.106243000
᎑117.4022860000
35
15
5
CMC
Beckett
Dorm room
34.100630000
᎑117.7086200000
66
05
Claremont McKenna College.
b
The software requires that trailing zeroes be entered after the last significant digit entry.
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c
Average of 3 samples.
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In the Laboratory
discovered spatial relationships, such as the closer a room is to a busy road, the higher the concentration of NO2. Conclusions Through this experiment, students can use the environmental data that they collect and geospatially map their values across the college campuses. The students can then propose reasons for why the concentrations of environmental samples vary as they do in different locations and compare their values to that taken by governmental agencies to provide context for their measurements. Acknowledgments
Figure 1. Concentration of NO2 (ppb) during fall 2006 semester at various locations across the Claremont McKenna College (lower left quadrant), Pitzer College (upper right quadrant), and Scripps College (upper left quadrant) campuses. (The geospatially referenced map was obtained from the Claremont Colleges physical plant.)
erly the GPS unit must be able to receive signals from at least three satellites. This requires that the readings be done outof-doors, so students who chose a dorm room or other indoor site were instructed to stand as close to their sampling location as possible while still receiving a strong signal from the GPS unit. Once the students have determined the concentrations of NO2, they place their values into an Excel spreadsheet, including their GPS data, location on campus, and so forth (Table 1). The results are then mapped onto a geo-referenced campus map, using ArcGIS (Figure 1) (see the Supplemental MaterialW for details). Once the data have been mapped, students are asked to think about why certain sampling sites exhibit higher concentrations of NO2 than others. Are concentrations higher in indoor or outdoor locations? Do locations close to or further away from roads exhibit higher concentrations? Does having a window open compared to using air conditioning make a difference? Do NO2 concentrations in locations near smoking areas differ from other areas? Nitrogen dioxide is one of the components of smog and therefore a “criteria air pollutant” measured by the Environmental Protection Agency (EPA) to ensure limited health impacts (11). When students compare their data with that recorded by governmental agencies, they can determine whether their measurements are of the correct order of magnitude and whether they live in an unhealthy environment. Students can compare the NO2 concentrations they measured to actual data from EPA monitors (12). They can also learn if the observed levels exceed guidelines through reference to the air quality index (AQI). For example, the South Coast Air Quality Management District provides AQI advisories for NO2 for the Los Angeles area (13), while the EPA provides AQI data for ozone, fine particulate matter (PM2.5), and overall air quality (14). The EPA National Ambient Air Quality Standard for NO2 is 53 ppb and students often measure higher concentrations in their dorm room (11). Students have also 1692
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This article is in memory of Harriet Moeur, who passed away during the preparation of this manuscript. We would like to thank the Andrew W. Mellon Foundation for financial support and Boyle Ke and Mary Martin for technical assistance during the development of this experiment. W
Supplemental Material
A detailed description for taking a point sample with the Gecko 201 GPS along with instructions for data entry into the Excel spreadsheet and mapping the NO2 concentrations on the campus map are available in this issue of JCE Online. Literature Cited 1. Habraken, Clarisse L.; Buijs, Wim; Borkent, Hens; Ligeon, Willy; Wender, Harry; Meijer, Marijn. J. Sci. Educ. Tech. 2001, 10, 249–256. 2. Loyo-Rosales, Jorge E.; Torrents, Alba; Rosales-Rivera, Georgina C.; Rice, Clifford P. J. Chem. Educ. 2006, 83, 248–249. 3. Phelps, Amy J.; Lee, Cherin. J. Chem. Educ. 2003, 80, 829– 832. 4. Tinker, Robert F. J. Sci. Educ. Tech. 1992, 1, 35–48. 5. Reed, Philip A.; Ritz, John. Tech. Teacher 2004, 63, 17–20. 6. Stewart, Meg E.; Schneiderman, Jill S.; Andrews, Stephanie B. J. Geosci. Educ. 2001, 49, 227–234. 7. Shooter, David J. J. Chem. Educ. 1993, 70, A133–A140. 8. Wink, Donald J.; Gislason, Sharon F.; Kuehn, Julie E. Working with Chemistry: A Laboratory Inquiry Program, 1st ed.; W. H. Freeman & Co.: New York, 2000; pp 251–255. 9. Butala, Steven J.; Zarrabi, Kaveh; Emerson, David W. J. Chem. Educ. 1995, 72, 441–444. 10. Seeley, John V.; Bull, Arthur W.; Fehir, Richard J.; Cornwall, Susan; Knudsen, Gabriel A.; Seeley, Stacy K. J. Chem. Educ. 2005, 82, 282–285. 11. National Ambient Air Quality Standards in the Clean Air Act 1990. http://www.epa.gov/air/caa/ (accessed Jul 2007). 12. Environmental Protection Agency. AirData. http://www..epa. gov/air/data/geosel.html (accessed Jul 2007). 13. South Coast Air Quality Management District. Current Hourly Readings For Air Monitoring Subregion. http://www.aqmd.gov/ telemweb/areamap.aspx (accessed Jul 2007). 14. United States Government. Today’s National Air Quality Forecast. http://airnow.gov/index.cfm?action=airnow.national (accessed Jul 2007).
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