Land use and land-use changes (LULUC) information is essential to determine the environmental impacts of anthropogenic land-use and conversion. However, existing data sets are either local-scale or they quantify land occupation per land-use type rather than providing information on land-use changes. Here we combined the strengths of the remotely sensed MODIS land cover data set and FAOSTAT land-use data to obtain a database including a collection of 231 country-specific LULUC matrixes, as suggested by the IPCC. We produced two versions of each matrix: version 1, identifying forestland based on canopy cover criteria; version 2, distinguishing primary, secondary, planted forests and permanent crops. The outcome was a first country-based, consistent set of spatially explicit LULUC matrixes. The database facilitates a more holistic assessment of land-use changes, quantifying changes that occur between land classes from 2001 to 2012, providing crucial information for assessing environmental impacts caused by LULUC. The data allow global-scale land-use change analyses, requiring a distinction between land types based not only on land cover but also on land uses. The spatially explicit data set may also serve as a starting point for further studies aiming at determining the drivers of land-use change supported by spatial statistical modeling.
The assessment of Land Uses and Land-use Changes (LULUC) impacts has become increasingly complex. Sophisticated modelling tools such as Life Cycle Assessment (LCA) are employed to capture both direct and indirect damages. However, quantitative assessments are often incomplete, dominated by environmental aspects. Land uses are a multidisciplinary matter and environmental and sustainable development policies intertwine. Yet, LCAs mostly focus on environmental impacts excluding socioeconomic implications of land occupation. This paper investigates the limitations of current LULUC modelling practices in LCA. Common LCA assumptions harbor value choices reflect a post-positivist epistemology that are often non-transparent to e.g. policymakers. They particularly influence the definition of the functional unit, the reference system and system boundaries, among other LCA methodological choices. Consequently, results informing land policies may be biased towards determined development strategies or hide indirect effects and socioeconomic damages caused by large-scale land acquisitions, such as violation of tenure rights, speculation and displacement. Quantitative assessments of LULUC impacts are certainly useful but should holistically encompass both direct and indirect impacts concerning the environmental and the social science dimension of LULUC. An epistemological shift towards a dialectic approach would facilitate the integration of multiple tools and methods and a critical interpretation of results.
In this paper, we summarize the discussion and present the findings of an expert group effort under the umbrella of the United Nations Environment Programme (UNEP)/Society of Environmental Toxicology and Chemistry (SETAC) Life Cycle Initiative proposing natural resources as an Area of Protection (AoP) in Life Cycle Impact Assessment (LCIA).
As a first step, natural resources have been defined for the LCA context with reference to the overall UNEP/SETAC Life Cycle Impact Assessment (LCIA) framework. Second, existing LCIA methods have been reviewed and discussed. The reviewed methods have been evaluated according to the considered type of natural resources and their underlying principles followed (use-to-availability ratios, backup technology approaches, or thermodynamic accounting methods).
The project assessed the climate impacts of different biofuels including indirect land use changes (iLUC), time dependency of greenhouse gas (GHG) emissions and manipulation of the carbon in biomass and soil carbon. The project resulted in a project report that acted as a the scientific background for Concito's own report "Klimapåvirkningen fra biomasse og andre energikilder" (in Danish).
Around 9% of global CO2 emissions originate from land use changes. Often, these emissions are not appropriately addressed in Life Cycle Assessment. The link between demand for crops in one region and impacts in other regions is referred to here as indirect land use change (iLUC) and includes deforestation, intensification and reduced consumption. Existing models for iLUC tend to ignore intensification and reduced consumption, they most often operate with arbitrary amortisation periods to allocate deforestation emissions over time, and the causal link between land occupation and deforestation is generally weakly established. This paper presents the conceptual framework required for a consistent modelling of iLUC in Life Cycle Assessment. It reports on a novel and biophysical iLUC model, in which amortisation is avoided by using discounted Global Warming Potentials (GWPs). The causal link between demand for land and land use changes is established through markets for land's production capacity. The iLUC model presented is generally applicable to all land use types, crops and regions of the world in typical LCA decision-making contexts focusing on the long-term effects of small-scale changes. The model's strengths and weaknesses are discussed.
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.
Assessing the effects of land use change (LUC) at the product level, as it is done in life cycle assessment(LCA) and carbon footprinting (CF), has been and still is subject to debate, especially when the focus is on so-called indirect land use change(iLUC). It is in this context that Prof. Matthias Finkbeiner recently published a report titled ‘Indirect land use change (iLUC) within life cycle assessment (LCA) – scientific robustness and consistency with international standards’, where he addressed whether iLUC “can be included in the LCA or CF calculations of biofuels in a scientifically robust and consistent way” (Finkbeiner 2013a, p. 7). Finkbeiner´s conclusion to this core question is a ‘no’. The arguments for this conclusion are concisely summarised in seven bullet points in a 1-page document shared with the European Parliament (Finkbeiner 2013b), where we find statements such as ‘...there is no fact-based support for a scientifically robust and consistent inclusion of iLUC factors into LCA and carbon footprints (CF) assessments’.
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* see also the document: Avoiding the streetlight effect - a longer version of the rebuttal.
Food consumption is a major driver of global environmental impacts. This paper presents an analysis of the life cycle impacts caused by global food consumption based on the newly completed input-output model; Exiobase v2. Exiobase v2 is a multi-regional input-output database covering 43 countries plus five rest-of-world regions for 2007. The data in the model includes all global product, emission and waste flows related to food consumption, i.e. a global mass flow analysis of all food related flows. The functional unit of the study was the global consumption of food in 2007. The included life cycle stages were cultivation/husbandry, processing, retail, preparation in households/restaurants and food waste disposal. The impact assessment focused on GHG-emissions and land-use. In this respect it should be noted that a model of indirect land-use changes is integrated in the Exiobase v2 model used in this study, to account for GHG- emissions caused by the use of land.
Land use and total (or gross) land use change data were analysed with focus on UNFCCC national inventory data and CORINE land cover data, and in comparison with FAO data and specific national data. For the European countries for which CORINE data are available this data base represents in most cases the preferable one with regard to land use change. The data quality and comprehensiveness however differs a lot between the individual countries. Due to restricted or unclear data availability other global or international data bases could not be used to derive data for gross land use change. Data from FAO and in particular the Global Forest Resources Assessment could be used to indirectly estimate net land use changes such as cropland expansion as a result of deforestation. This was not further elaborated here but specific studies on the issue exist. Allocation of land use (occupation) to industry sectors in SUTs can be done following the common approach for environmental extension data (see report to WP 7: Provision of data on land use by country and category).
Alignment of land use / land cover accounts with SEEA 2012 is currently hampered due to different classification systems. Further, available data do not fit with proposed SEEA categories which are characterised as being provisional.
With regard to land use change, our proposal is to keep it in a separate account by country/region which might be aggregated to a global account once comprehensive, harmonised data sets were available. The effects on land use change could then be included by linking the land occupation (as above) to the global market for land (the global LUC matrix).
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