0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessAgriculture, and its impact on land, contributes almost a third of total human emissions of greenhouse gases (GHG). At the same time, it is the only sector which has significant potential for negative emissions through offsetting via the supply of feedstock for energy and sequestration in biomass and soils. Perennial crops represent 30% of the global cropland area. However, the positive effect of biomass storage on net GHG emissions has largely been ignored. Reasons for this include the inconsistency in methods of accounting for biomass in perennials. In this study, we present a generic model to calculate the carbon balance and GHG emissions from perennial crops, covering both bioenergy and food crops. The model can be parametrized for any given crop if the necessary empirical data exists. We illustrate the model for four perennial crops – apple, coffee, sugarcane, and Miscanthus– to demonstrate the importance of biomass in overall farm GHG emissions.
Alicia Ledo, Richard Heathcote, Astley Hastings, Pete Smith, Jon Hillier (2018). Perennial-GHG: A new generic allometric model to estimate biomass accumulation and greenhouse gas emissions in perennial food and bioenergy crops. Environmental Modelling & Software, 102, pp. 292-305, DOI: 10.1016/j.envsoft.2017.12.005.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2018
Authors
5
Datasets
0
Total Files
0
Language
English
Journal
Environmental Modelling & Software
DOI
10.1016/j.envsoft.2017.12.005
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access