Excise duty on diesel (units of national currency per 1000 litres) - Poland - European Commission - Weekly
This series is part of the dataset: Retail diesel prices (EU)
Download Full Dataset (.xlsx)Latest updates. In Poland, the excise duty on diesel (automotive gasoil) was 1,413.52 units of national currency per 1000 litres on 12 October 2026, as on 5 October.
Sample. There are 1,088 observations overall in the weekly time series presented in the graph above. The series covers the time span stretching from January 2005 to October 2026.
History. Have a look at some statistics calculated on the entire sample: the excise duty peaked at 1,693.52 national-currency units on 5 January 2026; it hit a trough of 1,144.00 national-currency units on 5 January 2009; it averaged 1,406.47 national-currency units.
Latest values
| Date | Value - Units of national currency per 1000 litres |
|---|---|
| 2026-09-28 | 1,693.52 |
| 2026-10-05 | 1,413.52 |
| 2026-10-12 | 1,413.52 |
Suggestion. Our metadata often include references to the sources of the data series we publish. You can use these references to discover more details.
Not for investment purposes. Information collected and published on this web site is not supposed to be used for investment purposes or as a basis for financial-decision making. Users should seek professional advice and do their own independent due diligence before pledging money to any investment.
Series Metadata
| Field | Value |
|---|---|
| Description | Excise duty on automotive gasoil |
| Country | Poland |
| Economic concept | Tax |
| Data type | Nominal amount |
| Seasonally adjusted | No |
| Deflation method | Current prices |
| Rescaling | None |
| Measure type | Level |
| Frequency | Weekly |
| Unit | Units of national currency per 1000 litres |
| Source | European Commission (Weekly Oil Bulletin) |
| Source type | International institution |
| Data licence | Reuse allowed under EU legal notice (with attribution) |
| Other information | Not available |
| FSR temporal aggregation code | LW1 |
Series in the same data set
Discover the other time series included in this data set.