Choices in land representation materially affect modeled biofuel carbon intensity estimates

Plevin, RJ; Jones, J; Kyle, P; Levy, AW; Shell, MJ; Tanner, DJ

HERO ID

10367871

Reference Type

Journal Article

Year

2022

Language

English

PMID

35620117

HERO ID 10367871
In Press No
Year 2022
Title Choices in land representation materially affect modeled biofuel carbon intensity estimates
Authors Plevin, RJ; Jones, J; Kyle, P; Levy, AW; Shell, MJ; Tanner, DJ
Journal Journal of Cleaner Production
Volume 349
Page Numbers 1-10
Abstract Estimates of biofuel carbon intensity are uncertain and depend on modeled land use change (LUC) emissions. While analysts have focused on economic and agronomic assumptions affecting the quantity of land converted, researchers have paid less attention to how models classify land into broad categories and designate some categories as ineligible for LUC. To explore the effect of these land representation attributes, we use three versions of a global human and Earth systems model, GCAM, and compute the "carbon intensity of land-use change" (CI-LUC) from increased U.S. corn ethanol production. We consider uncertainty in model parameters along with the choice of land representation and find the latter is one of the most influential parameters on estimated CI-LUC. A version of the model that protects 90% of non-commercial land reduced estimated CI-LUC by an average of 32% across Monte Carlo trials compared to our baseline model. Another version that mimics the GTAP-BIO-ADV land representation, which protects all non-commercial land, reduced CI-LUC by an average of 19%. The results of this experiment demonstrate that land representation in biofuel LUC models is an important determinant of CI-LUC.
Doi 10.1016/j.jclepro.2022.131477
Pmid 35620117
Wosid WOS:000789583500003
Is Certified Translation No
Dupe Override No
Is Public Yes
Language Text English