Model collaboration for the improved assessment of biomass supply, demand and impacts

Wicke, B., van der Hilst, F., Daioglou, V., Banse, M., Beringer, T., & Valin, H. ORCID: https://orcid.org/0000-0002-0618-773X (2015). Model collaboration for the improved assessment of biomass supply, demand and impacts. GCB Bioenergy 7 (3) 422-437. 10.1111/gcbb.12176.

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Abstract

Existing assessments of biomass supply and demand and their impacts face various types of limitations and uncertainties, partly due to the type of tools and methods applied (e.g. partial representation of sectors, lack of geographical details, aggregated representation of technologies involved). Improved collaboration between existing modeling approaches may provide new, more comprehensive insights, especially into issues that involve multiple economic sectors, different temporal and spatial scales or various impact categories. Model collaboration consists of aligning and harmonizing input data and scenarios, model comparison and/or model linkage. Improved collaboration between existing modeling approaches can help assess (i) the causes of differences and similarities in model output, which is important for interpreting the results for policy-making, and (ii) the linkages, feedbacks and trade-offs between different systems and impacts (e.g. economic and natural), which is key to a more comprehensive understanding of the impacts of biomass supply and demand. But, full consistency or integration in assumptions, structure, solution algorithm, dynamics and feedbacks can be difficult to achieve. And, if it is done, it frequently implies a tradeoff in terms of resolution (spatial, temporal, structural) and/or computation. Three key research areas are selected to illustrate how model collaboration can provide additional ways for tackling some of the shortcomings and uncertainties in the assessment of biomass supply and demand and their impacts. These research areas are livestock production, agricultural residues and greenhouse gas emissions from land use change. Describing how model collaboration might look like in these examples, we show how improved model collaboration can strengthen our ability to project biomass supply, demand and impacts. This in turn can aid in improving the information for policy-makers and in taking better-informed decisions.

Item Type:	Article
Uncontrolled Keywords:	Model collaboration; Integrated assessment; Biomass supply and demand; Impacts; bottom-up modeling; Top-down modeling
Research Programs:	Ecosystems Services and Management (ESM)
Bibliographic Reference:	GCB Bioenergy; 7(3):422-437 (May 2015) (Published online 7 February 2014)
Depositing User:	IIASA Import
Date Deposited:	15 Jan 2016 08:53
Last Modified:	27 Aug 2021 17:25
URI:	https://pure.iiasa.ac.at/11474

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