Regional or global?: the question of low-emission food sourcing addressed with spatial optimization modelling

Does producing staple food locally cause fewer greenhouse gas emissions than food sourced through imports from another continent? To address this question we used a spatial optimization approach that minimized greenhouse gas emissions from production and transport of five food commodities (barley, m...

Full description

Saved in:
Bibliographic Details
Main Authors: Kreidenweis, Ulrich (Author) , Lautenbach, Sven (Author) , Köllner, Thomas (Author)
Format: Article (Journal)
Language:English
Published: 30 April 2016
In: Environmental modelling & software
Year: 2016, Volume: 82, Pages: 128-141
ISSN:1873-6726
DOI:10.1016/j.envsoft.2016.04.020
Online Access:Verlag, Volltext: http://dx.doi.org/10.1016/j.envsoft.2016.04.020
Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S1364815216301153
Get full text
Author Notes:Ulrich Kreidenweis, Sven Lautenbach, Thomas Koellner
Description
Summary:Does producing staple food locally cause fewer greenhouse gas emissions than food sourced through imports from another continent? To address this question we used a spatial optimization approach that minimized greenhouse gas emissions from production and transport of five food commodities (barley, maize, oil, sugar and wheat) and compared this to a setting of local production where distances between production and consumption were minimized. We focused on the example of two countries - Brazil and Germany - in order to allow modelling at high spatial resolution. In the model, a minimization of greenhouse gas emissions led to an allocation of large shares of production to locations abroad. In contrast, the local production case, optimized on distance only, resulted in higher greenhouse gas emissions. Our findings show that despite additional transport needs for imports, specialization of countries on the production of specified crops can represent a low climate impact strategy.
Item Description:Gesehen am 06.12.2018
Physical Description:Online Resource
ISSN:1873-6726
DOI:10.1016/j.envsoft.2016.04.020