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What can and can't we say about indirect land‐use change in Brazil using an integrated economic – land‐use change model?

Authors: Verstegen, J.A.; van der Hilst, Floor; Woltjer, Geert; Karssenberg, Derek; de Jong, S.M.; Faaij, André P.C.;

What can and can't we say about indirect land‐use change in Brazil using an integrated economic – land‐use change model?

Abstract

AbstractIt is commonly recognized that large uncertainties exist in modelled biofuel‐induced indirect land‐use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this study, we demonstrate a general methodology to stochastically calculate direct and indirect land‐use change (dLUCandiLUC) caused by an increasing demand for biofuels, with an integrated economic – land‐use change model. We use the global Computable General Equilibrium model MAGNET, connected to the spatially explicit land‐use change modelPLUC. We quantify important uncertainties in the modelling chain. Next,dLUCandiLUCprojections for Brazil up to 2030 at different spatial scales and the uncertainty herein are assessed. Our results show that cell‐based (5 × 5 km2) probabilities ofdLUCrange from 0 to 0.77, and ofiLUCfrom 0 to 0.43, indicating that it is difficult to project exactly wheredLUCandiLUCwill occur, with more difficulties foriLUCthan fordLUC. At country level,dLUCarea can be projected with high certainty, having a coefficient of variation (cv) of only 0.02, whileiLUCarea is still uncertain, having a cv of 0.72. The latter means that, considering the 95% confidence interval, theiLUCarea in Brazil might be 2.4 times as high or as low as the projected mean. Because this confidence interval is so wide that it is likely to straddle any legislation threshold, our opinion is that threshold evaluation foriLUCindicators should not be implemented in legislation. For future studies, we emphasize the need for provision of quantitative uncertainty estimates together with the calculatedLUCindicators, to allow users to evaluate the reliability of these indicators and the effects of their uncertainty on the impacts of land‐use change, such as greenhouse gas emissions.

Country
Netherlands
Keywords

BIOFUELS, UNCERTAINTY, Sugar cane, Renewable energy sources, land-use change, valorisation, AGRICULTURAL LAND, uncertainty, Waste Management and Disposal, Monte Carlo, error propagation, indirect land-use change, SDG 15 - Life on Land, land‐use change, Uncertainty, Forestry, EXPANSION, biofuel, HD9502-9502.5, Brazil, sugar cane, Land-use change, TJ807-830, TIME-SERIES, Indirect land-use change, Energy industries. Energy policy. Fuel trade, SUGARCANE, Modelling, modelling, CHANGE SCENARIOS, FUTURE, Biofuel, SDG 7 - Affordable and Clean Energy, Renewable Energy, Sustainability and the Environment, Renewable Energy, Sustainability and the Environment, AVAILABILITY, spatio-temporal, CROP, indirect land‐use change, Error propagation, Spatio-temporal, Agronomy and Crop Science

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    48
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
48
Top 10%
Top 10%
Top 10%
Green
gold