Global carbon intensity of crude oil production
Artikel i vetenskaplig tidskrift, 2018

Producing, transporting, and refining crude oil into fuels such as gasoline and diesel accounts for ∼15 to 40% of the “well-to-wheels” life-cycle greenhouse gas (GHG) emissions of transport fuels (1). Reducing emissions from petroleum production is of particular importance, as current transport fleets are almost entirely dependent on liquid petroleum products, and many uses of petroleum have limited prospects for near-term substitution (e.g., air travel). Better understanding of crude oil GHG emissions can help to quantify the benefits of alternative fuels and identify the most cost-effective opportunities for oil-sector emissions reductions (2). Yet, while regulations are beginning to address petroleum sector GHG emissions (3–5), and private investors are beginning to consider climate-related risk in oil investments (6), such efforts have generally struggled with methodological and data challenges. First, no single method exists for measuring the carbon intensity (CI) of oils. Second, there is a lack of comprehensive geographically rich datasets that would allow evaluation and monitoring of life-cycle emissions from oils. We have previously worked to address the first challenge by developing open-source oil-sector CI modeling tools [OPGEE (7, 8), supplementary materials (SM) 1.1]. Here, we address the second challenge by using these tools to model well-to-refinery CI of all major active oil fields globally—and to identify major drivers of these emissions.


Mohammad S. Masnadi

Stanford University

Hassan M. El-Houjeiri

Aramco Research Center

Dominik Schunack

Stanford University

Yunpo Li

Stanford University

Jacob G. Englander

Stanford University

Alhassan Badahdah

Aramco Research Center

Jean Christophe Monfort

Aramco Research Center

James E Anderson

Ford Motor Company

Timothy J Wallington

Ford Motor Company

J. Bergerson

University of Calgary

Deborah Gordon

Carnegie Endowment for International Peace

Jonathan Koomey

Koomey Analytics

Steven Przesmitzki

Aramco Research Center

Inês L. Azevedo

Carnegie Mellon University (CMU)

Xiaotao T. Bi

University of British Columbia (UBC)

James E. Duffy

State of California

Garvin A. Heath

National Renewable Energy Laboratory

Gregory A. Keoleian

University of Michigan

Christophe McGlade

International Energy Agency

D. Nathan Meehan

Baker Hughes

Sonia Yeh

Chalmers, Rymd-, geo- och miljövetenskap, Fysisk resursteori

Fengqi You

Cornell University

Michael Wang

Argonne National Laboratory

Adam R. Brandt

Stanford University


0036-8075 (ISSN) 1095-9203 (eISSN)

Vol. 361 6405 851-853


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