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Methodology

Open Assets builds each company's emissions from the bottom up: every plant, its technology and output, and its emissions, attributed to companies by ownership. The same rules apply to every company, so companies can be compared with each other.

Why build emissions from assets and ownership?

Reported emissions cannot be compared across companies. Each company draws its own boundary (operational control or equity share, Scope 1 or Scope 1 and 2, own plants or contracted supply), uses its own reporting year and methods, and many companies do not report at all.

We instead start from the physical assets, using public plant-level data, and attribute each plant to its owners by their equity share. One method for every company makes them comparable, shows which plants drive a company's emissions, and lets us project emissions forward from announced closures and retirements, independently of what companies disclose.

Reported and modelled figures from others (company reports, the Transition Pathway Initiative, Climate TRACE) are shown next to ours for context, clearly marked as not directly comparable.

The Asset-based Planning Approach (APA)

Our method is the production Asset-based Planning Approach, published in Nature Communications:

Kampmann, D., Rekker, S., Ruan, M. & Shrimali, G. (2026). Assessing corporate transition plans using a production asset-based planning approach. Nature Communications 17, 6410. doi.org/10.1038/s41467-026-72703-2

Plant emissions = plant output × emission factor (technology, country, year)

Company emissions = Σ plant emissions × company's ownership share

Each sector applies this with its best plant-level data: in steel, plant capacity and technology with company production; in power, plant emissions and generation reported to regulators. The sector tabs below give the details.

Two ownership bases: equity share and operational control
  • Equity share (default): each plant is split between its owners by their equity share (Global Energy Monitor ownership data), including stakes in plants others operate. This is the basis for comparing companies.
  • Operational control: each plant counts 100% to the company that operates it, as regulators record it (e.g. Australia's NGER). Companies often set targets on this boundary, so target lines are compared on it.

Steel company emissions from Global Energy Monitor's steel plants and Kampmann's production data, following APA. Steel data →

Data: plants, owners and production

Data Source: GEM GIST December 2025

Three standalone Excel files from the Global Energy Monitor's Global Iron and Steel Tracker, covering 800+ plant-status entries:

  • • Plant-level data — plant_id, country, parent, owner, status, start_year
  • • Iron unit data — BF and DRI unit capacities (technology, capacity_ttpa)
  • • Steel unit data — BOF and EAF unit capacities (technology, capacity_ttpa)

26 Companies Tracked

The original 14 companies from Kampmann's paper plus 12 expanded companies, resulting in 229 company-year APA pairs covering 2014–2024.

Emission factors

Based on Koolen & Vidovic (2022) JRC129297 — country-specific emission factors for the steel industry and its trading partners.

BF-BOF (Scope 1 + Upstream)

Country-specific, time-varying with 0.5%/year compound improvement from 2020 reference:

EF(country, year) = EF_base(country) × (1 - 0.005)^(year - 2020)
Region Base EF (2020) 2014 EF 2024 EF
EU 1.770 1.824 1.735
China 1.760 1.814 1.725
India 3.720 3.834 3.646
Japan 2.050 2.113 2.009
United States 1.940 1.999 1.902
Brazil 2.190 2.257 2.147
South Korea 2.000 2.061 1.960
Russia 2.790 2.875 2.735
Global (fallback) 2.314 2.385 2.268

Rationale: Worldsteel Sustainability Indicators show global BF-BOF intensity is largely flat over 2014-2024 (<5% total change). IEA assumes 0.3-0.7% annual improvement. We use 0.5% as a middle estimate.

EAF (Scope 1 only) — Static

EAF scope 1 emissions are very small (0.02-0.12 tCO2/t) and kept constant across all years.

DRI — Static (technology-specific)

Coal-based DRI: 3.10 tCO2/t (India, China, South Africa). Gas-based DRI: 1.05 tCO2/t (all others). Hydrogen DRI: 0.04 tCO2/t (future technology).

Production data hierarchy

Five sources, prioritised (lower number = higher priority):

Priority Source Coverage
0 Kampmann BAU (reported) 14 companies, 2020-2023
1 Annual report extraction Varies by company
2 Curated reports CSV 26 companies, 2014-2024
3 Kampmann ALD data 14 companies, 2020-2023
4 GEM plant production Variable (50% coverage floor)
Which plants count in each year

Plants are filtered per year based on GEM status and start_year, meaning the plant set changes over time. New plants come online and the technology mix shifts — this is the first-order effect on weighted emission factors.

Status Rule
Operating / Pre-retirement Include if start_year ≤ year
Construction Include if start_year ≤ year (came online)
Retired / Mothballed Include for all historical years
Announced / Cancelled Always exclude
What APA is not
NOT TPI intensity benchmarks (those are sector-wide, not asset-level)
NOT corporate target tracking (that’s NZT — useful for comparison only)
NOT satellite emissions estimates (that’s ClimateTrace — useful for validation)
NOT scenario pathway alignment (that’s the PCP/SDA/ACA analysis that uses APA as input)

APA is purely: Assets → Emission Factors → Baseline Emissions, driven by physical plant data and reported production.