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The environmental costs of intensive farming activities are often underestimated or not traded by the market, even though they play an important role in addressing future society's needs. The estimation of nitrogen (N) dynamics is thus an important issue which demands detailed simulation based methods and their integrated use to correctly represent complex and nonlinear interactions into cropping systems. To calculate the N 2 O flux and N leaching from European arable lands, a modeling framework has been developed by linking the CAPRI agro-economic dataset with the DNDC-EUROPE bio-geo-chemical model. But, despite the great power of modern calculators, their use at continental scale is often too computationally costly. By comparing several statistical methods this paper aims to design a metamodel able to approximate the expensive code of the detailed modeling approach, devising the best compromise between estimation performance and simulation speed. We describe the use of two parametric (linear) models and six nonparametric approaches: two methods based on splines (ACOSSO and SDR), one method based on kriging (DACE), a neural networks method (multilayer perceptron, MLP), SVM and a bagging method (random forest, RF). This analysis shows that, as long as few data are available to train the model, splines approaches lead to best results, while when the size of training dataset increases, SVM and RF provide faster and more accurate solutions.

Graphical abstract Integrative and collaborative process adopted to design the EU Bioeconomy Monitoring System

No abstract

The Brazilian government’s decision to open the Amazon biome to sugarcane expansion reignited EU concerns regarding the sustainability of Brazil’s sugar sector, hindering the ratification of the EU-Mercosur trade agreement. Meanwhile, in the EU, certain conventional biofuels face stricter controls, whilst uncertainty surrounding the commercialisation of more sustainable advanced-biofuels renders bioethanol as a short- to medium-term fix. This paper examines Brazil’s land-use changes and associated greenhouse gas emissions arising from an EU driven ethanol import policy and projections for other 13 biocommodities. Results suggest that Brazil’s sugarcane could satisfy growing ethanol demand and comply with EU environmental criteria, since almost all sugarcane expansion is expected to occur on long-established pasturelands in the South and Midwest. However, expansion of sugarcane is also driven by competition for viable lands with other relevant commodities, mainly soy and beef. As a result, deforestation trends in the Amazon and Cerrado biomes linked to soy and beef production could jeopardize Brazil’s contribution to the Paris agreement with an additional 1 ± 0.3 billion CO2eq tonnes above its First NDC target by 2030. Trade talks with a narrow focus on a single commodity could thus risk unsustainable outcomes, calling for systemic sustainability benchmarks, should the deal be ratified.