Documentation of the Educational Benefits of the Project

Documentation of the educational benefits of the project

Contribution April 2010

1. Abstract

The goal of the SchoolCO2web is to give pupils more insight into the carbon cycle and the fluctuations of CO2 in the atmosphere. This is a multidisciplinary topic, which includes mathematics, physics, chemistry and biology.

Pupils also learn how to extract valuable information from a large dataset by means of spreadsheet programs and statistics. Data analysis is an important skill within scientific research. That's why this project creates a bridge between highschool and university. Moreover, you bring science closer to the pupils, because the measurements take place on the schools themselves and because the measurements might be useful within scientific research.

The SchoolCO2web is a European network of schools. This emphasizes the international nature of the greenhouse gas science and opens up possibilities for project cooperation between pupils from different countries.

2. Atmospheric CO2 cycles in a nutshell

The higher you get into the troposphere (0 -16 km), the more mixed the air becomes. So if you want to establish the average CO2 concentration in the air, which is also representative for a larger area, it's important to measure at a high location. The measuring station at Mauna Loa (Hawaii) is a good example. It is located at a volcano at an altitude of 3400 m.

In figure 1 the red line shows the monthly average CO2 levels as measured at the station. As you can see, the CO2 levels are oscillating over a period of one year. These are seasonal effects, due to the increased fixation of CO2 of plants from May until September at the northern hemisphere. As a result, the atmospheric CO2 drops with a few ppm.

The black line shows the monthly average levels of CO2 corrected for seasonal effects. During the last years, the average CO2 level increased with almost 2 ppm per year. This rise is due to the combustion of fossil fuels.More data on the Mauna Loa, starting from 1958, can be found on

The closer you get to the earth's surface, the less mixed the air becomes. The atmospheric CO2 levels close to the earth’s surface fluctuate a lot as a result of photosynthesis by plants and respiration by animals. We can clearly see this fluctuations within the measurements of the SchoolCO2web. In figure 2 you see the CO2 levels of the Carl-Zeiss-Gymnasium in Jena (DE) and the Maartenscollege in Haren (NL) from the 10th until the 14th of November. You can make these kind of graphs yourself with the SchoolCO2web tool which you can find on the Carboschools website. Chapter 4 contains a tutorial on how to use this tool.

The grey and white areas of the graph represent the night and day respectively. Especially during the 13th and 14th of November, you see a big rise of CO2 during the night and a drop during the day. There are two reasons for this effect, which we call inversion. The first one is that plants only fix CO2 during daylight, resulting in a dropof the CO2 levels during the day. The other, more important reason is that the air is more mixed during the day. When the sun heats the earth, the earth emits heat to the air. This evokes turbulence and mixture of surface air layers with layers higher in the atmosphere. During the night the earth cools down rapidly. As a result, the air close to the surface cools down. But the higher air layers are still warmer and function as a blanket to prevent mixture of the air. As a result, all the CO2 exhaled by organisms accumulates in the surface layer.

Although we saw a strong inversion during the 13th and 14th of November, this inversion is almost absent during the 11th and the 12th of November. Why is that?

Figure 3 reveals the answer. This time, the graph only shows the CO2 levels of the Carl-Zeiss-Gymnasium. A right y-axis is added with the wind speed. During the first days of the period, there was a lot of wind. This wind causes the atmosphere to mix and thus prevents inversion. During the last days there was hardly wind, so inversion occurred.

3. Topics for in the classroom

Atmospheric CO2 cycles

Chapter 2, already discussed the annual, seasonal and daily oscillations of the CO2 levels. As thedatabase expands, it will be possible to study more and more the effects of different factors on the CO2 concentrations.

It is already possible to study the seasonal effects and maybe the first results of the annual effects become visible.

Possibilities to study effects on the CO2 concentrations are:

• Is there a difference in day-night cycle between a summer and a winter day? (different day lengths, photosynthesis)
• Are their differences in patterns between a relatively warm and a very cold day in winter
• What correlation can be found between temperature and CO2 concentrations
• Is there a difference in length or start of the growing season between different schools? (e.g. north and south of Europe)
• Is it already possible to see any annual effects? (For this it is important to do correct filtering).
• Under what conditions does inversion occur? Can you find correlations with other factors than wind speed? Is it possible to estimate the thickness of the inversion layer?

For direct use in the classroom, a few examples of these topics will be elaborated into worksheets(to be developed by 2 students, at the moment unsure what the results will be)

-example of a day-night cycle

-example of a seasonal effects

-example of inversion at night at low wind speed

-example of annual effects (if already available)

These worksheets can also be used as inspiration for teachers and students to find other topics or as a start for more extensive projects.

(Maybe the following can be added in this document:

Also available is a module WorldWide Climate Change. This module of 8 lessons consists of the following items:

-an introduction on climate change, based on the Carboschool booklet part 1, with questions .

-an experiment: influence of light on plants

-working with the data of the schoolCO2web, with the emphasis on day-night fluctuations (including inversion and the effect of wind)

It is also possible to use parts of the module

(Problem is that the module has not been tested at schools, needs probably some revisions)

Calibration errors

As you can see in figure 2, there is a structural difference of about 12 ppm between the Maartenscollege and the Carl-Zeiss-Gymnasium. This difference has not been caused by natural effects, but is a result of inaccuracy of the meters. For the meters to measure accurately, it is important to calibrate them with a calibration gas a few times per year. You can use this calibration errors to make the pupils aware of the famous expression “never trust a meter”.

Accurate measurements

Especially in the field of atmospheric CO2 research, performing accurate measurements and calibrations is one of the more difficult and time consuming tasks. When well calibrated, the meters of the SchoolCO2web are 1 ppm accurate. This is already a lot compared to classroom sensors from Coach, Pasco, etc. They reach an accuracy of about 25 – 50 ppm. The professional measuring tower from the Center of IsotopeResearch in Groningen reaches an accuracy of 0.1 ppm and higher. To realize this, the meter automatically calibrates itself. And not just once every few months. The meters takes a measurement, recalibrates, takes another measurement and so on.

Sinks and sources

Why is it so important to take such accurate samples? The reason for this is that CO2 levels between different regions do not differ that much. In order to still distinguish the differences, accurate measurements are necessary. And why do we want to know these small differences? In the past, the main aim of carbon science was to determine the average global CO2 levels, to see whether they increase or not. But recently, the differences between regions are taken into account. The current challenge of carbon research is to model the carbon cycle as accurate as possible. Some regions function as a sink for atmospheric CO2, for example when there is a lot of vegetational growth or water which functions as a sink. Other regions are a source, so more CO2 is emitted to the atmosphere than compared to the uptake.

Two types of sources of CO2 can be distinguished:

1. natural sources, by respiration of vegetation, animals and soils,

2: anthropogenic sources, caused by humans which include burning of fossil fuels and deforestation. Use of fossil fuels involve strong local sources, like traffic, industry and heating sources in the winter.

It is not easy to detect local sources by CO2 measurements, due to the mixing of the air. Only nearby sources might be detected, depending on the wind direction.

For direct use in the classroom, an example might be elaborated into a worksheet (to be developed)

For working with data on local sources, see also further on the topic on measuring CO2 outdoors.

With dispersion models students can try to estimate the possibility to measure the increase of CO2 emissions of specific sources.

For this purpose a Gaussian Plume model can be used.

Go to

• Select: Gaussian Model using user-entered data
• Fill in the coordinates of the source you want to study: degrees latitude and longitude, Continue
• Only change relevant data like wind direction (mind the units), wind speed
• Click on Request Dispersion Run

You will now get the results of the dispersion as shown in the picture

From this data, the expected rise of CO2 emissions to be measured by the CO2 meter can be estimated (to be elaborated on how to do this, example to be added).

How do the meters work

The Vaisala is a so called non-dispersive infrared sensor. The Vaisala contains a lamp which emits infrared light. This light is reflected by a mirror to a detector for infrared light. During the way, the light encounters CO2 molecules in the air, that absorb a part of the light. The infrared sensor thus will sense less light that the lamp emitted. This difference in intensity is a measure for the number of CO2 molecules that absorbed light, and thus a measure for the CO2 concentration in the air.

On every school a Davis Vantage PRO weather station has been installed as well. This weather station sends values for the air pressure, temperature and the humidity to the Vaisala. The Vaisala needs this data to compensate the CO2-measurements.This can be best explained with an example. When the air pressure in the Vaisala rises, itmeans that there are more air particles in the same space. Thus there are also more CO2 molecules. That's why the Vaisala measures more CO2 with a higher air pressure. Because you want to know the CO2 concentration independently from the air pressure, the weather station sends the value for the air pressure to the Vaisala. The Vaisala calculates the CO2 concentration according to a fixed value for the air pressure. The weather station also keeps track of other factors, like the amount of rain, the wind speed and wind direction.

A topic for a student project could be to study the working of the meters and to try to build a simple CO2 meter.

Statistics

The context of the schoolCO2web can be used to learn students more about measuring and statistics.

A module Measuring and knowing is developed. The goal of this module is to learn students how to get useful information from a large datasets using statistics. The measurements of the schoolCO2web form the context.

This module of 3 lessons contains the following items:

-general introduction on climate change

-introduction on the schoolCO2web and how to work with the data and make graphs

-statistics: measuring errors and significancy; terms like mean, median and modus; standard deviation; correlation

(Problem is that the module has not been tested at schools, needs probably some revisions)

Identifying the origin of air packages

With this application you can calculate were the wind or air packages come from.

Go to

• Select Compute archive trajectories, Next
• Select 1 for Number of Trajectory Starting Locations and Normal for Type for Trajectory, Next
• Select GDAS (global, 2006-present) for meteorological data
• Fill in the coordinates of the location: degrees latitude and longitude, Continue
• Select a specific week for GDAS1 Meteorological File, Default is the current7days, Next
• In this fill in screen only change under Trajectory direction: Forward into Backward
• Click Request trajectory. The model will now calculate and produce a plot which might take a minute
• The plot will show where the air package is coming from at the default height of 500 m. The model can be rerun after changing the scenario, e.g. changing the height

(to be elaborated on effect height differences, maybe example to be added).

Measuring CO2 by hand

Measurements of CO2-concentrations on the roof can be combined with measurements with a hand meter. The Vaisala meter on the roof can be removed. It is however easier to use a separate small hand meter, although such a meter is less accurate. For measuring large differences, e.g. in the classroom this will be accurate enough. But for measuring e.g. photosynthesis on the ground, a Vaisala will give better results.

Measuring CO2 indoors

This can be done for 2 purposes: 1: measuring the effect of respiration by humans indoors 2. measuring the indoor air quality;

1. Effect of respiration

In classrooms with many students and only little ventilation the CO2 concentrations will rise quickly.

The rate at which CO2 is generated in a classroom depends on the number of people, the size of the people and the physical activity. CO2 concentrations can be decreased by ventilation.

The averageadult’s breath contains about 35,000 to 50,000 ppm of CO2 (100 times higher thanoutdoor air).

Students can do experiments by measuring CO2 concentrations under different circumstances. They can make estimations of the CO2 concentrations based on the conditions (amount of people, size of the room, ventilation) and compare this with the measurements. Students can make a research plan by themselves or work according to a protocol prepared by the teacher.

2. Indoor air quality

In recent years, measuring CO2 in classrooms has received more attention.

Research has shown that CO2 levels are too high most of the time. CO2 concentrations are often used as an indicator for the indoor air quality. The CO2 concentration itself is not a health concern. Conditions with high CO2 concentrations however, lead to lower learning performances and absence through illness.

Students can measure the indoor air quality under different circumstances. If temperature and humidity sensors are available, it is also possible to study the correlation between CO2 concentrations, temperature and humidity.

Measuring CO2 outdoors

Measuring outdoors can be done directly in the open air or on the ground. For measurements on the ground a box can be used to measure the uptake or emissions of CO2 from the soil or vegetation. (to be added: how to build a box or a picture).

The students can study their environment with the help of software like Google Earth and look for interesting sources and sinks. Based on this, the students can make a plan with a list of places where to measure (and when) and what they expect to find. Interesting is also to consider weather conditions. If possible, wind speed can be measured. Concentrations can become very high in a lee zone, and air will be mixed quickly at high wind speeds.

In addition to the measurements, students can also try to estimate if the area they studied is an overall source or a sink. For this purpose all sources and sinks in an area need to be mapped and estimations of CO2 emissions all sources and CO2-uptake of sinks have to be done.

(If available an example will be added later on or sources for data on CO2 emissions and uptake)

It could be interesting to compare the calculations with the CO2 data from the web under strong inversion conditions, when local CO2 concentrations are high.

Working with the meteorological data

Phenology

Based on meteorological data it is possible to study phenological issues. What is the relationship between factors like temperature, rain fall and day length and for instance the return of migratory birds or the start of the blooming of plants

Students can study changes in nature themselves. Historical data can be found on the internet. Many countries have phenological observation networks.

Weather patterns

Weather patterns can be studied based on the data from weather stations on different schools.

Is there for instance a relationship between weather conditions and the coverage of the sky?

Projects with other schools

The schoolCO2web is also an interesting tool to use as a basisto do projects with other schools (schools do not necessarily have to be connected to the schoolCO2web).

Students can contact each other through the internet (or even meet). Several ideas for activities for the project can be found in the earlier mentioned topics. It might be interesting to:

-compare the activities done with the CO2 data. What similarities and differences can be found.

-have discussions about the different climate policies of the countries

-exchange cultural differences regarding CO2 topics

4. How to work with theCO2 data from the SchoolCO2web

How to download the CO2 data

Within the SchoolCO2web a tool has been developed to download or graphically display the CO2 and weather measurements of the SchoolCO2web. This tool can be found on the Carboschools website on the SchoolCO2web section. The tool is also available in Dutch on

Operation of this tool is quite easy. Creating a graph exists of the following steps: