Belarus vs Qatar: Crude steelmaking capacity

Belarus
3 Tonnes
in 2025
Qatar
3.24 Tonnes
in 2025
Belarus rank
42nd
Qatar rank
40th

Crude steelmaking capacity over time

  • Belarus
  • Qatar
01234200020122025

How they compare

Qatar currently reports 3.24 Tonnes against 3 Tonnes in Belarus, a difference of 0.24 Tonnes.

That makes Qatar's figure about 1.1 times Belarus's.

The two have swapped places 1 time across 26 shared years of data; in 2000 it was Belarus ahead.

Belarus ranks 42nd and Qatar ranks 40th of 115 countries.

Across the 3 decades both report, Belarus averaged higher in 1 and Qatar in 2.

Head to head by decade

Decade Belarus Qatar Difference Ahead
2000s 2.8 Tonnes 2.02 Tonnes 0.775 Tonnes Belarus
2010s 2.92 Tonnes 3.12 Tonnes 0.204 Tonnes Qatar
2020s 3 Tonnes 3.24 Tonnes 0.24 Tonnes Qatar

Averages of every year both report within each decade.

Frequently asked questions

Which has higher crude steelmaking capacity, Belarus or Qatar?
Qatar, at 3.24 Tonnes against 3 Tonnes in Belarus as of 2025.
What is the difference in crude steelmaking capacity between Belarus and Qatar?
0.24 Tonnes, with Qatar ahead.
How many years of comparable data are there for Belarus and Qatar?
26 years are reported by both, from 2000 to 2025.
How do Belarus and Qatar rank globally for crude steelmaking capacity?
Belarus ranks 42nd and Qatar ranks 40th of 115 countries.
Where does this data come from?
Organisation for Economic Co-operation and Development, published as Crude steelmaking capacity. Statizoid refreshes it automatically from the source and publishes the full history for both places.

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Belarus vs Qatar: Crude steelmaking capacity. Statizoid, drawing on Organisation for Economic Co-operation and Development. Retrieved 22 August 2026, from https://urban.statizoid.com/compare/crude-steelmaking-capacity/belarus/qatar/

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About this data

Indicator
Crude steelmaking capacity
Unit
Tonnes
Source
Organisation for Economic Co-operation and Development
Licence
OECD Terms and Conditions (attribution required)
Coverage
132 places, 3,432 data points, 2000–2025
Last refreshed

This dataset provides information on crude steelmaking capacity for 132 OECD Member countries and non-OECD economies over the period 2000–2025. Definitions Steelmaking capacity Nominal crude steelmaking capacity is defined as the maximum theoretical output of installed steelmaking equipment. This definition does not account for yield losses, maintenance downtime, or other factors affecting actual production. As a result, the steelmaking capacity figures provided by the OECD should not be interpreted as effective capacity. Capacity is expressed in million metric tonnes (mmt). Annual capacity figures reflect all steelmaking capacity existing at the end of each calendar year. Steelmaking equipment Steelmaking equipment includes all equipment used to produce crude steel. The definition excludes ironmaking equipment, which is considered upstream, as well as casting, rolling, and finishing equipment, which are considered downstream. Specifically, crude steelmaking equipment includes electric arc furnaces (EAF), induction furnaces (IF) and LD basic oxygen furnaces (BOF). Methodology Steelmaking capacity developments are derived from data on existing capacity, investments, and closures. Capacity changes reflect new additions and permanent closures and therefore represent net changes. In some cases, capacity may be overestimated due to the assumption that projects classified as underway with expired start dates have become operational. Only permanent closures are included in capacity calculations, although some closures cannot be clearly classified due to limited available information. Data sources OECD calculations based on desk research, company websites, publicly available news sources and information exchanges within the OECD Steel Committee. Cite this dataset OECD (2025). Crude steelmaking capacity dataset. Accessed on [Day Month Year]. Further information OECD Steel Outlook 2025 OECD Steel Committee Global Forum on Steel Excess Capacity For questions or comments regarding this dataset, please contact Maika Sakamoto (Maika.SAKAMOTO@oecd.org) or Masanobu Nakamizu (Masanobu.NAKAMIZU@oecd.org).