The Earth offers a finite amount of coal. Theses coal stocks take different forms and according to the coal kind and the region it comes from, the price changes. The first model takes into account two coal families : * Anthracite and bituminous family is the most expensive stock and so it's the most fill stock (753639 million tons left) * Lignite and sub-bituminous family is the less expensive stock and so the less fill stock (320469 million tons left) [^3]
In order to find these parameters we need to find the past production data per year from the beginning of the production The used data are taken from 1950 to 2020 there are several categories of coal which represent a percentage of the total production. These proportions change with the production year but in this model we take the repartition at year 2020.
production data sources : [^2] and [^3]
Coal data
|Year |sub-bituminous and lignite (Mt)|anthracite and bituminous (Mt) | | :------- | :---------- | :-----------: | |1950|540|1260| |...|...|...|...|...|...| |2020|2272.5|5302.5|
Fitting [^3]
To fit the curve with the maximum reserve estimate by BP we adjust the beginning year of the regression in order to take the year start at the beginning of the current peak and get realistic values for maximal stock.
Extraction Price [^4]
We use the mean price according to the proportion of each coal types.
Other data [^3]
The following identified stocks are integrated into the model :
| Region |Coal type | Current reserve | Reserve unit | | :------- | :--------:| ---------: | :-----------------: | | World | anthracite and bituminous | 753639 | million tonnes | | world | lignite and sub-bituminous | 320469 | million tonnes |
Next we calculate the reserve left each year and the price evolution associate. In this model we use all the cheaper resources before extracting the more expensive ones. The resource price also depends on the world region we are living in. Here the price corresponds to the US market price. So, for more precision, we have to make a model based on the world region price.
Sector using coal [^5]
| |proportion of the global demand per year in % |demand in tonnes| | :------- | :---------------------------------:| :--------------: | |global|100|7921| |service, fishing, agriculture|4.6|364.366| |residential|7.5|594.075| |Iron steel|32.5|2574.325| |chemical, petrochemichal|9.7|768.337| |Non metallic mineral|21.2|1679.252| |Other sector|24.5|1940.645|
Data implemented in the coal demand csv.
References
[^2]: Höök, M., Zittel, W., Schindler, J. & Aleklett, K. - "Global coal production outlooks based on a logistic model" (2010) Fuel, Vol. 89, Issue 11: 3546-3558 - Published online at 'http://dx.doi.org/10.1016/j.fuel.2010.06.013' - Retrieved from: 'https://www.diva-portal.org/smash/get/diva2:329110/FULLTEXT01.pdf' [^3]: BP - Statistical Review of World Energy (2021) - Retrieved from: 'https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review-2021-full-report.pdf' [^4]: U.S. Energy Information Administration - "Coal explained" (2021) - Retrieved from: 'https://www.eia.gov/energyexplained/coal/prices-and-outlook.php' [^5]: IEA 2022; World Energy Balances, https://www.iea.org/data-and-statistics/charts/world-coal-final-consumption-by-sector-2018, License: CC BY 4.0.