Related Experiment Video
Updated: Mar 9, 2026

Design and Use of a Full Flow Sampling System FFS for the Quantification of Methane Emissions
Published on: June 12, 2016
Estimating firms' emissions from asset level data helps revealing (mis)alignment to net zero targets
Hamada Saleh1, Stefano Battiston2,3, Irene Monasterolo4,5,6
1Institut Louis Bachelier, Paris, France.
None:
We develop a bottom-up methodology to estimate companies' (mis)alignment to net-zero scenarios. The approach relies on asset-level data for individual production units, enabling a detailed estimation of corporate emissions trajectories. We apply the methodology to the steel sector globally and find that companies' projected emissions for 2030 exceed those implied by the International Energy Agency's (IEA) Net Zero Emissions (NZE) scenario by between 10% and 22%, depending on the assumptions about the future evolution of emission factors of steel production. Further, we find that projected emissions for 2030 exceed companies' aggregate stated targets, even under the optimistic assumption of electricity supply decarbonization rate following the net-zero scenario, with the gap primarily driven by the largest steel companies. Our results show that a bottom-up asset-level approach allows for a reality check of companies' contributions to national decarbonization plans. This, in turn, is crucial to inform more targeted industrial policies for decarbonization, and regulatory disclosure.
Related Concept Videos
Estimation of the Physical Quantities
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Energy Budgets
Emission Spectra

