S&P Global Launches Comprehensive Framework For Assessing Reliability Of Estimates Of Greenhouse Gas Intensity For Crude Oil


By Godson Umejiego, Senior Correspondent USA

A comprehensive new study by S&P Global (NYSE: SPGI) provides new guidance and methodology that improves comparability, consistency and confidence in assessing the life-cycle greenhouse gas (GHG) intensity of crude oil.

The study, entitled The Right Measure builds on existing literature, standards and practices to address some of the unique challenges that currently limit utility of life-cycle GHG emissions estimates of crude oil. It also proposes a new “Data Quality Metric”—a framework to improve the transparency around the reliability of estimates—developed in collaboration with the U.S. Department of Energy’s National Energy Technology Laboratory.

The study includes a demonstration of the new guidance and methodology by creating a benchmark representing the average intensity of crude oil consumed in North America. The results assess the crude oil pathways that comprise over 90 per cent of the volume processed in the United States in 2019 and represents the most current and comprehensive assessment to date.

 “Not all GHG emissions estimates of are created equal,” said director, GHG estimation and coordination, S&P Global and co-author of the study, Cathy Crawford. “Understanding GHG emissions can require data that may not have historically been gathered or reported across companies and regions, which affects the quality of estimates. This new comprehensive study builds on existing standards and practices to construct a guidebook that addresses some of the remaining sources of inconsistency with life-cycle GHG emissions that are unique to the estimation of crude oil.”

“Applying this new S&P Global method, S&P Global has created the most current and arguably the most comprehensive assessment of the average GHG intensity of crude oil processed in the United States,” said vice president, GHG estimation and coordination, S&P Global and the study co-author, Kevin Birn.

“What the market has been looking for is a credible and equitable yardstick when it comes to assessing oil and gas GHG emissions,” said vice chairman, S&P Global, Daniel Yergin. “This study advances several of the critical building blocks needed in the market while also being very transparent where some of the challenges that remain.”

For the study, S&P Global undertook a systematic review of existing GHG quantification guidance and identified four main remaining sources of differences between life-cycle crude oil estimates—System Boundaries, Coproducts, Units of Measurement and Data Quality.

Each source of inconsistency was systematically reviewed, and specific guidance was developed that addresses the core areas where differences continue to exist between estimates. These areas include Land-use Change, Fabrication and Construction, Purchased Fuels, Electrical Trade, Coproducts and Units.

To address the issue of data quality, the S&P Global study introduces the new Data Quality Metric (DQM). The DQM builds upon established principles of data quality and the existing Data Quality Indicator (DQI) framework to provide a quality metric that is more specific to oil and gas.

The S&P Global DQM was developed in accordance with three key principles:

  • Reliability. The degree to which an estimate can be depended on to be accurate (e.g. the comprehensiveness of underlying data)
  • Representativeness. To what degree can an estimate be expected to reflect reality (e.g. to what degree does the data represent the asset or assets in question).
  • Utility. The ease in assessing or assembling and interpreting the metric.

Emphasis was placed on ease of communication in the development of the DQM. A simple letter grade scoring system was devised with the ability to indicate if estimates have been verified by an independent, third party. The interpretation of the resulting DQM was designed to be consistent regardless of whether it is an assessment of individual stage or of a complete life cycle.

“Data quality really does matter, and it is a source of differentiation between estimates which has been unappreciated,” Birn said. “The creation of the Data Quality Metric has the potential to be a meaningful tool for GHG estimators, from companies to third parties, to allow users to assess the uncertainties and limitations of different GHG estimates. “Assessing and communicating estimate quality is absolutely critical for the market to have confidence in GHG estimates.”

To demonstrate the utility of the new S&P Global The Right Measure guidance, the study compiled a benchmark representing the average intensity of crude oil consumed in North America. The average represents a comprehensive assessment of the average product life-cycle GHG intensity of crude oil processed in the United States in 2019. This was done to demonstrate the utility of the guidance but also provide a public benchmark which others following a similar method may be comparative to.

S&P Global assessed the life-cycle stages for 48 distinct crude oil streams which collectively accounted for 90 per cent of volumes processed in the United States in 2019. The year 2019 was chosen as the most recent year of representative operations (2020 being the onset of the COVID-19 pandemic). Various tools and models were used while following The Right Measure method for consistency.

S&P Global estimates the volume-weighted average life-cycle GHG intensity of crude oil processed in the United States in 2019 was 84 gCO 2e/MJ or 457 kgCO2e/bbl of refined product. On a percentage basis the variation is somewhat contained because most emissions—69-88 per cent–occur from end-use. This is significantly lower than many other studies. While these prior analyses are incomparable for many reasons there was also reason to believe the US average may have declined naturally from improvements in shale extraction to Canadian oil sands which dominate the U.S. slate.

The average life-cycle GHG intensity for each of the 48 distinct crude streams against the volume consumed in 2019 that make up the US average, as well as detailed methodology of the S&P Global.

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