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DayCent data and results for "Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels"

Dataset ·
 [1]; ; ; ; ; ; ; ; ; ; ;
  1. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Bioenergy Innovation (CBI)

This zip file contains a UNIX-format DayCent model executable, input files, automation code, and associated directory structure necessary to re-produce the DayCent analysis underlying the manuscript. The main script 'autodaycent.py' (written for Python 2.7) opens an interactive command line routine that facilitates: * Calibrating the DayCent pine growth model. * Initializing DayCent for a set of case studies sites. * Executing an ensemble of model runs representing case study site reforestation, grassland restoration, or conversion to switchgrass cultivation. * Results analysis & generation of manuscript Fig. 3. Note that the interactive analysis code requires that all input files to be contained in the directory structure as uploaded, without modification. Executable versions of the DayCent model (https://www2.nrel.colostate.edu/projects/daycent/) compatible with other operating systems are available upon request.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Center for Bioenergy Innovation (CBI)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
DOE Contract Number:
AC05-00OR22725
OSTI ID:
3012650
Country of Publication:
United States
Language:
English

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Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels
Journal Article · Mon Aug 24 00:00:00 EDT 2020 · Proceedings of the National Academy of Sciences of the United States of America · OSTI ID:1650388