In agriculture and forestry, an important means for mitigating impacts on biodiversity and climate change is nature conservation. However, this is seldom included in life cycle assessment (LCA) and most LCA and footprint guidelines prescribe that such off-setting shall be excluded from the system (e.g. ISO 14067; PEF guideline; ILCD guideline; PAS2050; the GHG protocol). Obviously, there are good reasons for excluding off-setting in the guidelines, however in some cases the distance between the studied product system and a mitigation option (offset) is very short, and the industry managing the product system may be the (only) one who is able to conserve high value biodiversity and carbon stock areas. This is the case of companies operating in countries where the frontier between product systems and high conservation value nature is moving.
The purpose of this paper is to describe how the most recent research within indirect land use changes (iLUC) can be used to creating a cause-effect based method for quantifying the life cycle implications of nature conservation. The application of the method is demonstrated with a case study LCA of palm oil production at United Plantations Berhad in Malaysia and Indonesia. With their recent expansion of the plantation area into Central Kalimantan Indonesia, United Plantations has voluntarily set-aside more than 8000 ha of high value conservation and high carbon stock land for permanent nature conservation. The findings are used to recommend how LCA and footprint guidelines should be revised in order to enable for the inclusion of important mitigation options.
Chapter 4.12 on "Dispersal of invasive species and GMO": Increased dispersal of invasive species, alien to the local ecosystems, may happen as a result of intentional introductions or as an unintentional side-effect of creating new corridors or dispersal vectors. The largest impact is due to transport vectors, such as ballast water of freighters, soil sticking to trucks and souvenirs brought home by tourists or business travellers. Intentional introductions is mainly relevant for agri-, silvi- and aquaculture. The dispersal of genes introduced via genetically modified organisms is generally a more limited problem due to stricter legal approval procedures, but its potential impact can be modelled in the same way as dispersal of natural species.
Chapter 4.12 on "Use of Natural Resources": In this section a general proposal on the way to handle different types of natural resources, including water, minerals, energy carriers, soil and biotic resources is presented first. Secondly, more detailed considerations are provided for subcategories water use, minerals, soil erosion and soil salination and dessication are presented.
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.
New definitions are provided of intensive and extensive forestry in version 3 of the ecoinvent database. These definitions are based on explicit and easily measured indicators for the most important aspects of forestry management for biodiversity. Unfortunately, many certified forestry products come from what would be classified as intensive forestry in the ecoinvent classification. The real challenge is to develop forest management systems that have a neutral or positive biodiversity impact relative to that of plantation forestry. Such truly extensive, biodiversity-managed forestry is very challenging and not very common today. Ample options exist for increasing yields in intensive and plantation forests, which can be recommended as having lower biodiversity impact than similar products from other management systems, certified or not.
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.
