Difference between revisions of "Country correction"

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=== Ecoscore approach ===
 
=== Ecoscore approach ===
The ecoscore is developed for France and favorises products from France. To achieve this a bonus is given to any product
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The ecoscore is developed for France and favorises products from France. To achieve this a bonus is given to any product produced in France of 15 points, which corresponds to a distance of 1000 km (?). This is much larger than the size of France by the way.
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So what to do with small countries, which have a much smaller transportation impact? Increase the bonus?

Revision as of 13:30, 9 March 2021

This page explores how the size of the country can be taken into account in the determination of the eco-score transport bonus.

Bonus approach

The eco-score approach intends to give a bonus to locally produced (and purchased) products. This bonus is +15, which is equal to a transport score of 100. This bonus is however now given to any product produced/purchased in France. No account has been taken of the very large size of France and impact of transport within the country.

Can this approach be adapted, so that the size of a country is taken into account?

Maximum bonus

It would be logic to give the maximum bonus (transport score if 100) only to very locally production and purchase. Ideally this will imply an area as small as possible, i.e. a city or very small country. Production and purchase that occurs in a country such as Andorra, Monaco, Liechtenstein or San Marino could be viewed as having a transportation score of 100.

No bonus

In the current calculation the no bonus (transportation score 0) is (arbitrarily) set at a distance of 2000 km. This distance covers roughly the size of Europe.

Centroids to the rescue

Is it possible to use the centroid calculations in determining the (transportation) size of a country?

The weighted sum for a country that consists of single city will be zero. This can then correspond to a transportation (bonus) score of 100. This means it is preferred to have no transportation.

The weighted sum of the major cities in the European Union (or larger area) could be used to define the transportation score of 0. This means a maximum transportation impact.

From Any weighted sum in between it is now possible to calculate a country transportation score. The larger the country, the lower the country transportation score. This country transportation score can be used to determine the maximum bonus for a country.

The centroid approach can also be used to calculate the country transportation size. We just have to add all cities, so that the entire population is covered. The resulting weighted distance is the size we are looking for.

In practice this approach is not feasible. It is just to much work to (to do by hand a least). So we need a way to get a reasonable approximation. For the calculation of the centroids a limited number of cities are used. We could try to extrapolate this data to get the transportation country size.

Approach

In the figure the results for the french departments are shown.

The population road-distance weighted size of France based on the departments

The cumulative population road-distance weighted distances are plotted against the cumulative population ratios. Each added city adds a point, increasing the cumulative population ratio and the cumulative distance. If the cumulative population ratio is 1, we have covered the entire population. And the corresponding cumulative distance is the value we are looking for.

Adding all the cities is to much work. Instead of adding all the cities, we could fit a line to the data of a few city points. The cumulative distance of the fit at a population ratio of 1, is then again the value we are looking for.

The function to fit must behave nicely with extrapolations. This excludes complex functions with many parameters. Or functions which behave not regular outside the fitted points (polynomials).

This leaves the following functions in Google Sheets:

  • linear - results in average values;
  • logarithmic - results in smaller values;
  • power functions - results in larger values, but goes through (0,0);

The results of France show that the logarithmic function does not fit the data. The best fit is provided by a power functions. However this works only if there is enough data above a population fraction of 25%. The data below 25% heavily influences the outcome of a power functions. As an approximation a linear fit, without using the data at low values gives a better estimate. For France in fact the results are the same.

Result

This approach has been applied on the following countries with a power function:

Country Centroid city size spreadsheet
Albania Tirana 100 link
Algeria Algers 370 link
Austria Vienna 230 link
Belgium Brussels 86 link
Bosnia and Herzegovina Zenica link
Croatia Zagreb 160 link
Czech Republic Prague link
Denmark Copenhagen 170 link
Estonia Tallinn 120 link
Finland Helsinki 220 link
France - cities Paris link
France - departments Paris 369 link
Germany Hannover 260 link
Greece Athens link
Hungary Budapest 120 link
Iceland Reykjavik 90 link
Ireland Dublin 100 link
Italy Rome 520 link
Latvia Riga 77 link
Lithuania Kaunas 120 link
Montenegro Bijelo Polje link
Morocco Temara 230 link
Netherlands Utrecht 72 link
Norway Skien 300 link
Poland Łódź 240 link
Portugal Lisboa 140 link
Romania Bucharest 300 link
Slovakia Banská Bystrica 78 link
Slovenia Ljubljana 66 link
Spain Madrid 430 link
Sweden Nörrköping 270 link
Switzerland Olten 120 link
Tunisia Tunis link
United Kingdom Coventry 210 link
European Union Munich link
Bouches du Rhône Marseille 22 link

Values in italic need more data.

Comments

Some observations on individual countries.

Conclusion

The graph below shows the size of each country based on population road-distance weighted transportation distance. The location of the circles is on the country centroid.

So what to do with this data? The idea is to extend the ecoscore to other countries. A consistent approach should allow comparison between countries and favorise local production and consumption.

How the transportation is incorporated depends on what the ecoscore wants achieve. There seem to be three approaches.

Real approach

Bonus approach

Ecoscore approach

The ecoscore is developed for France and favorises products from France. To achieve this a bonus is given to any product produced in France of 15 points, which corresponds to a distance of 1000 km (?). This is much larger than the size of France by the way.

So what to do with small countries, which have a much smaller transportation impact? Increase the bonus?