Future projections expect a growing biobased economy (BBE) in the next decades [1
]. This is characterised by an increasing use of biomass for energy purposes, like biofuels and a growing demand for biobased materials [2
]. The latter comprise i.e., bioplastics, biochemicals, biolubricants, biosolvents, and biosurfactants [3
]. For the manufacturing of these products, feedstocks obtained from the use of agricultural land are of essential importance [4
]. This might increase the demand for land to cultivate those feedstocks [5
]. To meet that growing demand, the cultivated area, on the one hand, might expand to currently uncultivated land and on the other hand might occupy cultivated area, worldwide [7
]. That could result in higher pressure on land, which was not cultivated before, with increasing impacts on biodiversity and carbon stock [8
]. Land use change (LUC) could be one of the consequences. Land use change can be categorised into direct land use change (dLUC) and indirect land use change (iLUC). According to the Intergovernmental Panel on Climate Change (IPCC), dLUC is defined as a change in the use or management of land by humans, which may lead to a change in land cover. Whereas iLUC refers to shifts in land use induced by a change in the production level of an agricultural product somewhere else in the world. This change can be the consequence of market mechanisms or political measures inducing additional demand for biomass or land [10
]. Therefore, the decision to change agricultural land use activities of a particular location could also change land use activities globally or locally. The particular characteristic of iLUC is that the displacement of other land use activities, which could for example be caused by an increase in biomass production for the manufacture of biobased products, is decoupled from the production of the biobased product itself. For example, if soybeans from existing soybean farmland originally used for food and feed production are used to produce soybean-based biodiesel, the cultivation of soybeans for food and feed purposes could be shifted to previously unused land somewhere in the world. This displacement could take place across national borders, which in turn could make it more difficult to trace LUC, and thus increase the decoupling of feedstock production of biobased products from its impact [11
]. While dLUC is easy to monitor and quantify, iLUC effects are more complex, because it is influenced by many different factors, such as (i) an increasing demand for biomass, worldwide, (ii) an increase in the price of food crops, (iii) environmental policies lead to leakage effects like unintended land use displacements, (iv) spatially varying crop yields, (v) and the globalised trade of biobased products [12
]. Therefore, iLUC could occur worldwide, with significant time lags and might be strongly influenced by global trade [16
]. The dilemma with iLUC was recognised under the EU Renewable Energy Directive (RED) [17
], when sustainability criteria for biofuels guaranteed the origin from established cultivation areas, but came along with the expansion of cultivation areas for food, feed, and material purposes [18
]. Figure 1
shows the interconnection between EU policies dealing with iLUC and relevant iLUC modelling studies. The results of the modelling had a significant impact on the development of the respective EU policies. The results of the MIRAGE (Modelling International Relationship in Applied General Equilibrium) study [19
] and the GLOBIOM (Global Biosphere Management) study [20
] played an important role in the further development of the RED. As already mentioned, the RED introduced the certification of biofuels that are produced in compliance with sustainability criteria. Nevertheless, with the RED 2 there was a change in focus towards an approach whose goal is to reduce the iLUC risk [21
]. For this purpose, the RED 2 is supplemented by a delegated regulation, which names so-called additionality measures. According to this, low iLUC risk biomass must be produced in compliance with these additionality measures in order to be certified [22
1.1. Approaches to Quantify the iLUC Effects of Biofuel Policies
An assessment of indirect impacts caused by the production of biofuels from US corn conducted by Searchinger et al. [26
] in the year 2008 is one of the first attempts to quantify the effects of iLUC. This analysis was complemented by other iLUC quantification approaches, mostly related to policy targets (e.g., the target for the share of renewables in the EU transport sector as defined by the RED) [27
]. Most of these quantification approaches use models to estimate the contribution of iLUC to the overall Green House Gas (GHG) emissions balance of biofuels [29
]. In this sense, the respective iLUC modelling approaches take into account emissions caused by the conversion of land to cropland due to the loss of existing above and below ground biomass [23
According to De Rosa et al. [30
], the models can be grouped into Economic Equilibrium Models (EEM), Causal-Descriptive Models (CDM), and Normative Models (NM). Whereas, the EEM base on economic equilibrium theory and include Computable General Equilibrium (CGE) models and Partial Equilibrium (PE) models [30
]. A recently conducted review of iLUC assessment and quantification approaches distinguish between four modelling types, as Figure 2
]. Panichelli and Gnansounou [32
] identify several other LUC modelling approaches, e.g., optimisation models, biophysical models, and system dynamics models for the estimation of LUC GHG emissions from biofuels production. Henders and Ostwald [33
] highlight strengths and weaknesses of several EEM and CDM approaches. A comprehensive overview of different iLUC modelling activities can be found in [34
The models estimate the annualised iLUC GHG emissions intensity, expressed in g CO2
biofuel, also known as iLUC emission factor [48
]. Figure 3
shows exemplarily the iLUC emission factors of several biofuels made from different feedstock. For each biofuel path, the results of different modelling approaches are shown. The results underline that iLUC is a key issue for the implementation of policies aimed at increasing the use of biofuels as a tool to mitigate climate change. However, due to the different modelling results, it is not possible to provide clear information on the exact level of GHG emissions caused by iLUC for each biofuel. The results of the modelling approaches (e.g., CGE, PE, or CDM) differ considerably due to several factors as follows (taken from [15
Structural components of the models: CGE models are developed for the whole economy, whereas PE models are developed only for specific sectors. There are differences in the geographical and commodity-level resolution. Furthermore, additional reasons for uncertainties could be to model trade of biofuels and the expansion of cultivated land into different land use types. The focus of many studies is on first-generation biofuels. Furthermore, the analysis of indirect effects focus on biofuels only, without considering indirect effects of fossil fuels. Many studies conduct no comprehensive sensitivity and uncertainty analysis.
Input data and assumptions: Many analyses take into account different policies and the use of different start and end-points in time. However, many studies do not take into account the effect of sustainability criteria and national land use policies. Furthermore, many models choose different ratios for biodiesel and ethanol. In addition, some models assume different amounts of harvest levels and feedstock use per MJ of biodiesel as well as the amount and value of byproducts. Assumptions in the demand for different commodities as well as differences in assumed land prices and costs for land conversion can differ between the models. Due to its dynamic nature, iLUC of a specific feedstock can change over time.
Treatment of carbon stock changes: To determine LUC related GHG emissions different additional carbon stock and emission databases are used to be added to economic modelling. Many models mainly focus on CO2 emissions, without taking into account other GHG emissions highly relevant as potential impacts of agricultural production, like N2O and CH4.
1.2. A Brief Review of the EU iLUC Policy Framework Development
The topic of iLUC has become a prominent aspect in the debate about biofuels after the definition of ambitious policy targets for the use of bioenergy, mostly in the EU and US transport sector (e.g., [19
]). Within the EU, the introduction of the RED [17
] in 2009 defined a 10% target for renewable energies in the transport sector, along with a set of sustainability criteria set out in Article 17. The sustainability criteria concern not to obtain the feedstock for biofuels and bioliquids from land with high biodiversity value and high-carbon stock. Biofuels sold in the EU that are to count towards the 10% target must demonstrate compliance with the sustainability criteria through sustainability certification (compare Figure 4
]. It has to be noted, that especially this combination of a target for renewable energy in the transport sector, which created a market or increasing the market volumes for biofuels in EU member states and the definition of sustainability criteria (including a criteria on direct land use change) has led to the complex problem of indirect land use change. The reason is that, whilst the RED has created an additional demand for biofuels and at the same time introduced a criterion, prohibiting the direct conversion of natural land. Since the latter is a criterion that is exclusive for this regulated market of biofuels, it can create spillover effects into other sectors of biomass production [52
Consequently, different researchers conducted assessments, flagging the high risks for increasing pressure on natural areas because of a policy induced additional demand for biofuels (compare [19
In the year 2012, the EC published an impact assessment of different policy options on how to deal with iLUC. The aim of the assessment was to investigate the effectiveness of several policy options aimed at the reduction of iLUC impacts. The following policy options were considered within the assessment:
Take no action for the time being, while continuing to monitor.
Increase the minimum GHG saving threshold for biofuels.
Introduce additional sustainability requirements on certain categories of biofuels.
Attribute a quantity of GHG emissions to biofuels reflecting the estimated indirect land-use impact.
Limit the contribution from conventional biofuels to the RED targets to current production levels.
The assessment concluded, that a balanced approach based on the option E accompanied by aspects of the options B and D, complemented by additional incentives for advanced biofuels, would be the best way to reduce the potential impact of EU biofuel policies [24
]. The option B aimed to exclude biofuels with large estimated iLUC emissions. The objective of option D was to incorporate the estimated iLUC emissions values in the reporting of the existing GHG methodology of biofuels. However, the estimated iLUC emissions cannot be determined clearly (compare Section 1.1
). The EC rejected the option C at that time, because criteria and compliance indicators for low iLUC risk practices were insufficiently developed [24
Based on the results of the impact assessment, the so-called iLUC Directive 2015/1513 was published in the year 2015 [25
]. This directive amended the RED and the Directive 98/70/EC [54
]. Among other things, it stipulated that the share of energy from biofuels, produced from food and feed crops, should be limited to 7% of final energy consumption in the transport sector in 2020. Furthermore, the directive presented a methodology for how to calculate the annualised emissions from carbon stock changes caused by LUC. The directive also included a definition of low iLUC risk biofuels and bioliquids. That “means biofuels and bioliquids, the feedstocks of which were produced within schemes which reduce the displacement of production for purposes other than for making biofuels and bioliquids and which were produced in accordance with the sustainability criteria for biofuels and bioliquids set out in Article 17” [25
] (p. 14).
In 2018, the Renewable Energy Directive 2 (RED 2) [21
] came into force. The RED 2 stipulates the repeal of the RED for the year 2021. Within the RED 2, the 7% limit for biofuels produced from food or feed crops is maintained. In addition, for biofuels classified as high iLUC risk produced from feedstocks for which a significant expansion of the production area into land with high-carbon stock is observed, e.g., palm oil, a cap and phase-out to 0% from 2023 to 2030 is set. To determine high iLUC risk biofuels, the RED 2 committed the EC to publish a report on the status of worldwide production expansion of relevant feedstock crops by February 2019 (for the report see [55
]). However, a biofuel classified as potentially high iLUC risk may be exempted from the phase-out if the biofuels are certified as low iLUC risk in the context of a specific project [21
]. In example, biodiesel produced from palm oil can be sold on the European market, if the biodiesel is certified as low iLUC risk. Thus, with the adoption of the RED 2, the focus of the sustainability certification of biofuels has changed to a risk-based approach.
The RED 2 is supplemented by the Commission Delegated Regulation (EU) 2019/807, published in March 2019. The regulation includes criteria for the identification of feedstock with high iLUC risk and general criteria for the certification of biofuels with a low iLUC risk. In addition, the regulation proposes specific criteria for determining so-called additionality measures. The purpose of the additionality measures is to produce an additional amount of biomass without jeopardizing existing users. On the one hand, these include improvements in the efficiency of existing uses, especially the increase in agricultural crop yields. On the other hand, there is the possibility of the planned change in use of previously unused areas. One focus is here on the conversion of abandoned land [22