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Teaching about air pollution The burning of fossil fuels causes pollution by generating compounds such as ozone, carbon monoxide and dioxide, oxides of nitrogen and sulphur, and particulate matter. The Environment Agency monitors the air quality in terms of these pollutants at many sites around the country. There will be an air-monitoring station near you. Results are updated every hour and are available on the UK National Air Quality Archive website. The archive also contains data stretching back a number of years. Information is stored in CSV (comma separated value) format and can be easily downloaded into a spreadsheet such as Excel and then interrogated. The plotting of graphs can identify trends. Programmes such as Excel allow pupils to plot graphs and explore patterns very quickly. Testing
hypotheses The levels of ozone generally follow trends in traffic density. You would expect to see higher levels of ozone during, or soon after rush hour, and indeed this is generally the case. You will often obtain two peaks during the day. In addition, the summer months often produce higher levels, as do dry days. Using the archive Go to the UK National Air Quality Information Archive, then follow the instructions below. 1. Click on a location
in the table of sites to show the data available for that site. Introducing the activity 1. Discuss with students what they know about the causes of ozone pollution. Where does the pollution come from? (Expect answers such as cars, lorries, burning coal or oil in power stations, etc.) 2. Ask students to look at the graph and suggest the most likely cause for the rise in ozone during the day (expect the answer to be 'increased traffic'). 3. Ask pupils to speculate about when they are likely to see the highest levels (at rush hours) and point out to them that the data in the example was for Easter Saturday. Might this be an unusual case? If so, why? (The ozone level builds up during the day, because it is a holiday and a lot of traffic was in the city during the day.) 4. Ask the students to predict what a graph might look like over a normal weekday (expect a two-peak graph). Ask them to plot a graph of the data and check their predictions. |