The Global Burden of Disease (GBD) study for the year 2016 reports a global disease burden of 0.32 DALY/person-year, given in disability-specific DALYs per country for 188 countries. However, the human health impacts from all LCIA categories included in the ReCiPe global normalisation reference for the year 2012 together account for <0.02 DALY/person-year. The difference of 0.30 DALY/person-year represents mortality and morbidity that to a large extent are caused by human activities and for which we identify the corresponding elementary flows and unit processes that should be included in product life cycle inventories. In total, we attribute 37% of the GBD to one or more of 79 specific risk factors (e.g. air pollution or dietary risks). The remaining GBD, not attributable to specified risk factors, we then divide in two parts: The ‘Unavoidable GBD’ (19%) and the residual (44%) that we find attributable to an ‘insufficient health care system’.
Land demand is driven by an increasing population and changing consumption patterns. When land is required Land Use Changes (LUC) are triggered, causing several environmental and social impacts. Particularly topical is the assessment of indirect LUC effects. Several methodological approaches have been proposed for carrying out the assessment. In this paper we classified LUC models for Life Cycle Assessment (LCA) applications into three main categories: Economic, Causal–Descriptive and Normative models. Six models were selected as representative of these three categories and compared according to fifteen criteria covering: modeling framework, impact categories assessed and model transparency. The results show that, progresses have been made in the Economic General Equilibrium Models and the Causal–Descriptive Models compared. Causal–Descriptive models appear more suitable for long-term assessments in the LCA context while the compared economic models are more suitable for short/medium-term assessments of LUC consequences. As LUC dynamics involve interdisciplinary knowledge, a combination of economic, biophysical and statistical data is however required to achieve a robust assessment of complex LUC dynamics.
There is still considerable scope for improving current LUC models. In particular, there is room for improving precision of data, identification of marginal land and inclusion of a broader range of impact categories. Current models mainly focus on GHG emission-related impacts and rarely on other environmental impacts such as nutrient leaching, biodiversity impacts and water resource depletion. Socio-economic analyses of LUC patterns are currently excluded from LCA analysis, preventing a holistic assessment of land occupation impacts.
This article describes the algorithm that has been developed within the European Union (EU) FP7 project DESIRE for the construction of the EXIOBASE multiregional hybrid supply and use tables (MR-HSUTs) version 3. The tables include 43 countries plus five rest-of-the-world regions and are built for the period 2000–2011. MR-HSUTs are compiled in mixed units, that is, tangible goods in mass units, intangible energy flows in terajoules, and, finally, services in euros. The article summarizes the various steps of the developed procedure, from data collection until the final supply and use tables. It will be shown how several disconnected data sets with varying quality are harmonized so as to build an effective analytical database that can be used for several types of analyses, such as life cycle assessment, total material requirement, material intensity per product service, carbon footprint, and so on.
Results of Life Cycle Assessment (LCA) are critically dependent on the system boundaries, notably the choice of attributional or consequential modelling. Published LCA studies rarely specify and justify their modelling choices. Since LCA studies are typically performed within the context of social responsibility and product life cycle management, this article investigates the relationship between social responsibility paradigms and the system modelling choices in LCA. We identify three different social responsibility paradigms: Value chain responsibility, Supply chain responsibility and Consequential responsibility. We point out that while there is no generally right or wrong choice of system model, each responsibility paradigm implies a specific matching system model. We then argue that all responsibility paradigms ultimately imply a consequential perspective, namely that of responding to the concerns of the system stakeholders. Although value or supply chains are systems defined without concern for consequences, and thus may include activities that the decision maker cannot influence, the chosen system is still analysed and assessed by accounting for its social consequences, and it is for these consequences that social responsibility is then taken. We argue that it is inconsistent to exclude consequences of own actions (i.e. the consequential system) while including consequences from actions of others in value chain or supply chain. We thus conclude that a consistent socially responsible decision-maker must always take responsibility for the activities in the consequential product life cycle and may additionally take responsibility for the consequences of other activities in the value chain or supply chain. We end the article with recommendations on reporting on LCA system models that are more specific than those of the current LCA standards.
We investigate how the boundary between product systems and their environment has been delineated in life cycle assessment and question the usefulness and ontological relevance of a strict division between the two.
We consider flows, activities and impacts as general terms applicable to both product systems and their environment and propose that the ontologically relevant boundary is between the flows that are modelled as inputs to other activities (economic or environmental)—and the flows that—in a specific study—are regarded as final impacts, in the sense that no further feedback into the product system is considered before these impacts are applied in decision-making. Using this conceptual model, we contrast the traditional mathematical calculation of the life cycle impacts with a new, simpler computational structure where the life cycle impacts are calculated directly as part of the Leontief inverse, treating product flows and environmental flows in parallel, without the need to consider any boundary between economic and environmental activities.
Our theoretical outline and the numerical example demonstrate that the distinctions and boundaries between product systems and their environment are unnecessary and in some cases obstructive from the perspective of impact assessment, and can therefore be ignored or chosen freely to reflect meaningful distinctions of specific life cycle assessment (LCA) studies. We show that our proposed computational structure is backwards compatible with the current practice of LCA modelling, while allowing inclusion of feedback loops both from the environment to the economy and internally between different impact categories in the impact assessment.
Our proposed computational structure for LCA facilitates consistent, explicit and transparent modelling of the feedback loops between environment and the economy and between different environmental mechanisms. The explicit and transparent modelling, combining economic and environmental information in a common computational structure, facilitates data exchange and re-use between different academic fields.
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.
Life cycle assessment (LCA) is broadly applied to assess the environmental impact of products through their life cycle. LCA of bio-based products is particularly challenging due to the uncertainties in modeling the natural biomass production process. While uncertainties related to inventory data are often addressed in LCA by performing sensitivity analyses, the sensitivity of results to LCA methodologies chosen is seldom addressed. This work investigates the influence of common methodological choices on LCA climate impact results of forestry products.
Performing a consequential LCA, the study compares results obtained through different choices concerning four methodological aspects: the modeling of land use change effects, the choice of climate metric for impact assessment, the choice of time horizon applied, and the completeness of the forest carbon stock modeled. Eight scenarios were tested, applied to the same case study to ensure the full comparability of the results. A dynamic life cycle inventory of annual forest biomass production and degradation was obtained through a methodology accounting dynamically for the annual carbon fluxes in a forest plot.
The results obtained for the eight scenarios showed a great variability of the estimated climate effect, ranging from a net carbon sequestration of 24 kg CO2 equivalents to a net carbon emission of 3220 kg CO2 equivalents, though seven out of eight scenarios resulted in a net carbon emission. The results are particularly sensitive to the choice of time horizon, especially when combined with the choice of static or dynamic climate indicator and different climate metrics as GWP and GTP. The case study showed a lower variability of results to the choice of forest carbon stock compared to the effect of the other tested assumptions.
LCA results of forestry products were highly sensitive to the tested methodological choices. A description and motivation of these choices is required for a clear and critical interpretation of the results. The choice of climate indicator and TH applied depends on the goal and scope of the study and strongly affects the contribution to climate impact results of all LCA processes. Those choices need to be carefully discussed and should be in accordance with the goal of the study, since different climate metric and TH have distinct interpretations. The interpretation of different climate indicators and their time horizons should be linked with the considered endpoints of climate change.
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).
This paper has been prepared for the Nordic PEF project as an input to the discussion on recommendations for the development of the European PEF scheme. The paper includes the responses from a group discussion in Copenhagen 2016-04-26.
Valuation covers the terms normalisation and weighting, as used in the LCA community.
