It is arguably beyond controversy that shifting to a global bio-based economy, with an increased demand for food, fuel and fibre will put more pressure on land resources. However, when it comes to measuring this pressure at the product level, as it is done in life cycle assessment (LCA) and carbon footprinting (CF), this has been and still is subject to debate, especially regarding the modelling/estimation of indirect land use change (iLUC). In order to understand the concept of iLUC, it must be realised that there are two types of land use change (LUC) i.e. direct land use change (dLUC) and indirect land use change (iLUC). LUC as a whole can be defined as a change in the purpose for which land is used by humans. We talk about dLUC when the change takes places directly within the land that is being used, whereas we talk about iLUC when the change takes place elsewhere, as a consequence of our using the land
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* see also the GCB Bioenergy, Letter to editor (2014)
This is the final report from the sub-project “Quantitative environmental assessment of land use in relation to the product life cycle” of the EUREKA project EU-1296 entitled “Development and application of major missing elements in the existing detailed Life Cycle Assessment methodology (LCAGAPS),” which was funded by the Danish EUREKA- secretariat at the Danish Agency for Industry and Trade. Through the Danish funding it was possible to involve a Dutch expert in the field, Erwin Lindeijer, to participate in the work.
The original concepts upon which this report is based were presented to the international scientific community in 1996 (Weidema & Mortensen 1996, Blonk et al. 1996), and within the field of biodiversity assessment some key ideas were developed in the report by Schmidt (1997). Several of the scientific topics related to environmental assessment of land use have been in rapid development during the scheduled period of the LCAGAPS project, especially in the fields of assessment of biodiversity and biogeochemical substance cycles. The finalisation of the project was postponed to take advantage of this concurrent and still ongoing development, and in the following years we focused on contributing to the conceptual development, especially in the SETAC working group on impact assessment (as documented e.g. in Lindeijer et al. 1998). In view of the rapid advancement in modelling and data availability, we have placed emphasis on assessment indicators that can function at the current level of available information, while being amenable for refinement as more data become available. For the same reason, not all aspects of the topic have been treated in equal detail. The final results of the project are presented with the present report.
In order to improve the knowledge of Denmark’s “carbon footprint”, the Danish Energy Agency (DEA) has commissioned a study on the national consumption-related greenhouse gas (GHG) emissions. Besides providing new results, this study does also provide a critical review of previous studies. The focus of the review is highlighting methodological differences and any other aspects causing differences in the results obtained.
The main goal of this project is to provide the best possible estimate of Denmark’s consumption-related “carbon footprint”. By carbon footprint is meant GHG-emissions, expressed as carbon dioxide equivalents (CO2-eq.). Consumption-related is defined as GHG-emissions from the Danish economy including imports, while emissions associated with exports are excluded. In this respect, the limitations of the traditional geographical approach to account for national emissions are addressed by taking into account the full life cycle of imported products to Danish economy. Data on production, imports, and exports of goods and services are obtained from environmentally-extended input-output (IO) tables. An additional goal of the project is to provide an overview of the products and services imported to and exported from Denmark, and their embedded GHG-emissions.
More than 10% of global GHG emissions are related to land use changes (LUC). This is almost the same as global GHG emissions from transport and around half of global GHG emissions from electricity produced from coal. The magnitude of LUC emissions clearly indicates that excluding this from LCA is highly problematic. In addition, several LCIA methods suggest that land use related impacts are much more important than GHG emissions (Weidema 2015). This makes the exclusion of LUC from LCA even more problematic.
Often, the impacts from indirect land use change (iLUC) are lacking in LCA studies – or at the best, it is modelled without reasonable considerations on cause-effect relationships between the use of land and the induced effects. If iLUC impacts are not included properly in the LCA results, there is a great risk of producing misleading results. Therefore, there is an urgent need for a good generic way of modelling iLUC. This should not be limited to biofuels or some certain crops in a certain region. There is a need for a generic model that can be applied to all kinds of land using LCA processes (cultivation of crops, cattle grassland, forestry, and land for buildings and infrastructure).
In order to make such a model available, we established the iLUC Club in 2011, which now has more than 20 universities and companies as members. We are currently working on the fifth version of the model which makes use of global land use change matrices and satellite data. The model framework is documented in a peer reviewed scientic article: A framework for modelling indirect land use changes in life cycle assessment. The model has been compared with other iLUC models in a scientific paper, where it was ranked as the best performing with regard to several criteria. Further, we actively contribute to the ongoing scientific debate on iLUC.
The model strives towards establishing a cause-effect relationship between, on the one side:
and on the other side:
The model has been tested and applied in several studies:
Subscription to the iLUC Club gives access to:
An important open source output from the project is a file with the needed information for obtaining iLUC GHG emission data for any land use (arable, forest, grassland) in any country in the world (download file).
The current members include:
On occasion of the 10th anniversary of our engagement with iLUC (15th Nov. 2017) we held a free webinar - the recording from this webinar can be seen here (youtube video) and the slides here (pdf).
For subscription (or questions), please contact us. To go to the club click here.
Biofuels were given an important role in the Danish government’s energy and climate-change mitigation strategy (Energiaftale 2012). However, following a report questioning the carbon neutrality of different biofuels (Concito 2011), Concito is interested in assessing further the climate impacts of different biofuels. The current report includes Life Cycle Assessment (LCA) screenings for calculating the carbon footprint (CF) of six different biofuels: wood pellets, wood chips, straw, biogas, ethanol and biodiesel. Critical sources of emissions in the product systems of the biofuels, which are often excluded from LCA studies, are addressed in the current study. These include indirect land use changes (iLUC), time dependency of greenhouse gas (GHG) emissions, manipulation of the carbon in biomass and soil carbon.
To assess the diverse environmental impacts of land use, a standardization of quantifying land use elementary flows is needed in life cycle assessment (LCA). The purpose of this paper is to propose how to standardize the land use classification and how to regionalize land use elementary flows.
In life cycle inventories, land occupation and transformation are elementary flows providing relevant information on the type and location of land use for land use impact assessment. To find a suitable land use classification system for LCA, existing global land cover classification systems and global approaches to define biogeographical regions are reviewed.
A new multi-level classification of land use is presented. It consists of four levels of detail ranging from very general global land cover classes to more refined categories and very specific categories indicating land use intensities. Regionalization is built on five levels, first distinguishing between terrestrial, freshwater, and marine biomes and further specifying climatic regions, specific biomes, ecoregions and finally indicating the exact geo-referenced information of land use. Current land use inventories and impact assessment methods do not always match and hinder a comprehensive assessment of land use impact. A standardized definition of land use types and geographic location helps to overcome this gap and provides the opportunity to test the optimal resolution of land cover types and regionalization for each impact pathway.
The presented approach provides the necessary flexibility to providers of inventories and developers of impact assessment methods. To simplify inventories and impact assessment methods of land use, we need to find archetypical situations across impact pathways, land use types and regions, and aggregate inventory entries and methods accordingly.
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The land use required in order to meet the increasing demand for biodiesel has significant impacts. New methodological developments within environmental life cycle assessment (LCA) establish a cause–effect relationship between the demand for biodiesel and its impacts on biodiversity. The objective of this article is to assess and compare the impacts of rapeseed oil (RSO) production in the EU and palm oil (PO) production in Southeast Asia. The functional unit of the LCA is 20.8 Mtoe (million tons oil equivalents) biodiesel equalling the EU25 goals for biodiesel in 2020. Land occupation and transformation are quantified for the two alternative vegetable oils, and losses throughout the product chain from cultivation over crushing to refining are inventoried. Market mechanisms and land which is indirectly affected by product substitutions from co-products are included in the modelling. Land occupation and transformation are evaluated by the use of life cycle impact assessment (LCIA) models on land use and biodiversity. Three basic scenarios are evaluated: (1) RSO-based biodiesel is produced from rapeseed grown on fields which were previously grown by other crops (barley, BL) – the displaced BL is imported from abroad; (2) RSO-based biodiesel is produced from rapeseed grown on former set-aside land in the EU; and (3) PO-based biodiesel produced in Southeast Asia is imported to the EU. It is concluded that the new EU policies on using set-aside land for energy crops cannot cover the European demand for biodiesel and crops must thus be imported from outside the EU. This means that land use outside the EU is affected. The modelling shows that the use of PO affects the land use in Malaysia or Indonesia and that Canadian land use for BL cultivation is affected when rapeseed is produced in the EU. The impacts on land use and biodiversity are presented for all three scenarios. Finally, it is discussed how an LCA perspective like the one applied here can contribute to the assessment of environmental impacts within land use science.
The UNEP/SETAC life cycle initiative has recently proposed a framework for life cycle impact assessment (LCIA) of land use. Still, a lack of appropriate LCIA-methods for assessing land use impacts exist in life cycle assessment (LCA). Most existing methods are either too coarse-grained regarding the differentiation between different land use types (e.g. conventional farming versus organic farming), or they are too narrow regarding spatial coverage (e.g. only part of Europe). Therefore, the purpose of this article is to develop a method that overcomes these problems. A secondary goal is to develop a method for which it is possible to determine characterisation factors for any land use type in any region without the need for overwhelming data and data manipulation requirements. The developed method for LCIA of biodiversity focuses on species richness of vascular plants which can be determined from species–area curves. The category indicator is calculated as the multiplication of occupied area, the number of species affected per standard area (100 m2), the duration of occupation and renaturalisation from transformation, and a factor for ecosystem vulnerability. The main uncertainties of the method are related to the determination of renaturalisation times and the establishment species–area curves. The intention of the study presented in this article, i.e. to develop an applicable model with global coverage and no constraints on resolution regarding spatial and land use type differentiation, has widely been met. The limiting factor for applicability is the access to species richness surveys for the relevant regions and land use types. But still, the method shows that, with limited efforts, it is possible to calculate characterisation factors for a large range of land use types in different parts of the world.
This study has been commissioned by AB TetraPak, Global Environment.
The objective of the study is to review existing proposals for biodiversity indicators for forest management, placing the indicators within a common framework.
