FIGURE 2 ATMOSPHERIC CO2 LEVELS AT THE CARLZEISSGYMNASIUM IN

1 GENERAL INFORMATION FIGURE 11 MAP OF RIVER
1 PREDICTIVE ANALYSIS OF INTERVAL CHOLECYSTECTOMY FIGURE 1
1 QUALITY ASSESSMENT FIGURE S1 RISK OF BIAS ASSESSMENT

11 SUPPLEMENTAL FIGURES SF1 SAMPLES CLUSTER BY STRAIN PLOT
12 •• WHICH OF THE POSITIONVERSUSTIME CURVES IN FIGURE
3 SUPPLEMENTARY FIGURES 画布 196 FIGURE S1 PHYLOGENETIC PROFILES

D3

Figure 2 Atmospheric CO2 levels at the Carl-Zeiss-Gymnasium in Jena (DE) and the Maartenscollege in Haren (NL)

D3.2 Documentation of the educational benefits of the project

Contribution December 2008

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. Atmosperic CO₂ cycles in a nutshell

FIGURE 2 ATMOSPHERIC CO2 LEVELS AT THE CARLZEISSGYMNASIUM IN

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 vulcano at an altitude of 3400 m.

Figure 1 Average monthly CO2 levels at the Mauna Loa station

n 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.

FIGURE 2 ATMOSPHERIC CO2 LEVELS AT THE CARLZEISSGYMNASIUM IN

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 rize is due to the combustion of phosile fuels.

The closer you get to the earth's surface, the less mixed the air becomes. The atmospheric CO₂ levels close to earth 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 10^th until the 14^th of November. You can make these kind of graphs yourself with the SchoolCO2web tool which you can find on the Carboschools website. Chapter 3 contains a tutorial on how to use this tool.

T FIGURE 2 ATMOSPHERIC CO2 LEVELS AT THE CARLZEISSGYMNASIUM IN
he grey and white areas of the graph represent the night and day respectively. Especially during the 13^th and 14^th 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, which make the CO₂ levels drop during the day. But a 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.

Figure 3 Atmospheric CO2 levels and wind speed at the Carl-Zeiss-Gymnasium in Jena (DE)

lthough we saw a strong inversion during the 13^th and 14^th of November, this inversion is almost absent during the 11^th and the 12^th 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 occured.

3. Tool to download measurements of the SchoolCO2web

Within the SchoolCO2web a tool has been developped to download or graphically display the CO₂ and weather measurements of the SchoolCO2web. This tool can be found on the Carboschools website www.carboschools.org, on the SchoolCO2web section.

O FIGURE 2 ATMOSPHERIC CO2 LEVELS AT THE CARLZEISSGYMNASIUM IN peration of this tool is quite easy. Creating a graph exists of the following steps:

Select the parameter you want to display on the left Y-axis (right now the label says “y-axis right” but this is not correct). In this case “CO₂concentration (ppm)”
Select the parameter you want to display on the right Y-axis. In this case we selected “nothing”
C
Figure 4 Tool to download the measurements of the schoolCO2web
lick on the stations from which you want to display the measurements. If you want to select more than one school, keep the CTRL (Windows) of CMD (Mac) pressed down during selection
Enter the start and end date of the period from which you want to display the data
Click “Show graph”. It may take a while before the data is being displayed, especially if you select a long period. Once you displayed a certain range of data, this display will be stored in the cache of the server. This means that the next time you display exactly this range of data, you will see the graph directly. This is practical to keep in mind when you work with a group of pupils. If you let them select a range on their computers, make sure you already displayed this range before. This can save a lot of time
You can also download the measurements as a datafile (*.csv) which can be loaded into a spreadsheet. In this case you will download the data of the stations and during the period you selected. In this datafile, all the parameters will be stored, so not just the ones you selected for the y-axes.

4. Topics for in the classroom

Atmospheric CO₂ cycles

In chapter 2, I already discussed the anual, seasonal and daily oscillations of the CO₂ levels. As our database expands, it will not only be possible to see the effects of inversion within the measurements of the SchoolCO2web. We will also be able to see seasonal effects and in a few years the anual effects.

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.

How do the meters work

FIGURE 2 ATMOSPHERIC CO2 LEVELS AT THE CARLZEISSGYMNASIUM IN 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.

Figure 5 Composition of the Vaisala CO2 infrared sensor

n 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, is means 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.

5. Pupils work with the measurements in a spreadsheet

With the SchoolCO2web tool you can download the data (see chapter 3) from the schools in the form of a *.csv file. I advice you to select just one school at a time and merge data of different schools later. Once you downloaded the *.csv file you can import it into a spreadsheet.

How to import a *.csv file into MS Excel

There is a video tutorial called “Tutorial 01 - How to import csv files in Excel”. Basically importing exists of the following steps:

Open MS Excel and create a new empty sheet
Go to the “Data” menu and select “import external data” and then “import data”
Open the *.csv file
The text import wizard opens. Proceed as follows during the different windows:
- Step 1: Just click “next”
- Step 2: Select as delimiter the “Comma”. Click “finish”
In the import data window just click “OK”

Now you imported the *.csv file. If Excel uses dots to separate decimals, your sheet is ready for use. If Excel uses comma's to separate decimals, it will not recognise most of the measurements as numbers, because a dot has been used to separate the decimals. In this case Excel will see it as text and will align it to the left in the cells. To change them into numbers, you have to replace the dots with comma's. Go to the menu “Edit” and choose “Replace”. At “Find what” fill in a dot. At “Replace with” fill in a comma. Then click “Replace All”. Dit kan simpeler binnen Excel door binnen de import functie bij Advanced aan te geven dat de decimalen door een punt gescheiden worden.

Correlation between wind speed and CO₂ levels

As an example I downloaded the same data as displayed in figure 3. These are the data of the Carl-Zeiss-Gymnasium from the 10^th until the 14^th of November. As I mentioned before, the CO2 levels rise during the night as a result of the inversion, unless there is plenty of wind to mix the atmospere. So you expect that the CO2 levels decrease when the wind speed increases. In the video tutorial called “Tutorial 02 - Correlation between CO2 concentration and wind speed” I show how you can make a graph to visualize the correlation between CO2 levels and average wind speed.

Determining the average CO2 levels

To get a good picture of the average CO2 levels of the atmosphere, it is important to just take those measurements when the atmospere is well mixed. The atmosphere is well mixed during the day because of turbulence. Secondly, the atmosphere is well mixed when the wind speed is high. So we will determine the average CO2 level just on the basis of the measurements taken between 13 – 17 h and at an average wind speed above 2.5 m/s.

How do we do this in Excel? The first step is to filter the data, to get just the measurements between 13-17 h and at an average wind speed above 2.5 m/s. The video tutorial called “Filtering CO2 levels in well mixed atmosphere” explains how to do this. For this tutorial I downloaded the following data with the SchoolCO2web tool: “NL CIO” from the 3^rd of June until the 5^th of September.

The second step is to calculate the average CO2 level for all the data and for just the filtered data. Our hypothesis is that the CO2 levels for the filtered data are lower, because the measurements are taken in a well mixed atmosphere. The video tutorial “Tutorial 04 – Calculation of the average CO2 levels” shows how to calculate the average CO2 levels. Although not statistically proved, you can see that the average CO2 level for a mixed atmosphere is indeed higher (370 ppm) than for all the measurements (377 ppm).

Weerfronten en CO2

Kijk op www.ready.noaa.gov/ready/open/hysplit4.html om te berekenen waar de wind vandaan gekomen is. Volg de volgende stappen:

Compute trajectories
GDAS (global, 2005-present)
Weekselectie
Coördinaten van 1 locatie
Typ de volgende dingen in het scherm
- Backward
- Runtime

4 CROSSWALK FRICTION TESTS (ATTACHMENT) FIGURE 1 AN INTERSECTION
7 BILDER OG UTKIPPSFIGURER I PRIMÆR 3 –
AIR CARGO FIGURES FOR THE MAIN UK FREIGHT AIRPORTS

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