A spatio-temporal life cycle assessment framework for building renovation scenarios at the urban scale

Reducing the energy consumption of buildings is a priority for carbon emissions mitigation in urban areas. Building stock energy models have been developed to support decisions of public authorities in renovation strategies. However, the burdens of renovation interventions and their temporal distribution are mostly overlooked, leading to potential overestimation of environmental benefits. Life Cycle Assessment (LCA) provides a holistic estimation of environmental impacts, but further developments are needed to correctly consider spatio-temporal aspects. We propose a spatio-temporal LCA framework to assess renovation scenarios of urban housing stocks, integrating: 1) a geospatial building-by-building stock model, 2) energy demand modelling, 3) product-based LCA, and 4) a scenario generator. Temporal aspects are considered both in the lifecycle inventory and the lifecycle impact assessment phases, by accounting for the evolution of the existing housing stock and applying time-adjusted carbon footprint calculation. We apply the framework for the carbon footprint assessment of housing renovation in Esch-sur-Alzette (Luxembourg). Results show that the renovation stage represents 4%–16% of the carbon footprint in the residual service life of existing buildings, respectively after conventional or advanced renovations. Under current renovation rates, the carbon footprint reduction would be limited to 3–4% by 2030. Pushing renovation rates to 3%, enables carbon reductions up to 28% by 2030 when combined with advanced renovations. Carbon reductions in the operational stage of buildings are offset by 8–9% due to the impacts of renovation. Using time-adjusted emissions results in higher weight for the renovation stage and slightly lower benefits for renovation

Stochastic and epistemic uncertainty propagation in LCA

Purpose: When performing uncertainty propagation, most LCA practitioners choose to represent uncertainties by single probability distributions and to propagate them using stochastic methods. However the selection of single probability distributions appears often arbitrary when faced with scarce information or expert judgement (epistemic uncertainty). Possibility theory has been developed over the last decades to address this problem. The objective of this study is to present a methodology that combines probability and possibility theories to represent stochastic and epistemic uncertainties in a consistent manner and apply it to LCA. A case study is used to show the uncertainty propagation performed with the proposed method and compare it to propagation performed using probability and possibility theories alone. Methods: Basic knowledge on the probability theory is first recalled, followed by a detailed description of hal-00811827, version 1- 11 Apr 2013 epistemic uncertainty representation using fuzzy intervals. The propagation methods used are the Monte Carlo analysis for probability distribution and an optimisation on alpha-cuts for fuzzy intervals. The proposed method (noted IRS) generalizes the process of random sampling to probability distributions as well as fuzzy intervals, thus making the simultaneous use of both representations possible

Uncertainty analysis in agent-based modelling and consequential life cycle assessment coupled models: a critical review

The evolution of life cycle assessment (LCA) from a merely comparative tool for the assessment of products to a policy analysis tool proceeds by incorporating increasingly complex modelling approaches. In more recent studies of complex systems, such as the agriculture sector or mobility, agent-based modelling (ABM) has been introduced as tool for life cycle inventory modelling. The promises of such ABM/LCA coupled models include the consideration of human behaviour and local variabilities in the studied system as well as scenario modelling for emerging systems. The acceptance of this new approach depends, among other things, on the handling of uncertainty and variability forthcoming from various sources. As the complexity of a methodology increases, it also becomes increasingly challenging to adequately handle uncertainty and variability, and be confident about an inference. In the case of ABM/LCA coupled models, the different nature of both parts (non-linear computational ABM and linear deterministic LCA) poses an additional challenge. The sources of uncertainty and variability and the preferable propagation methods differ for both parts and clear guidance is needed. Yet no study, to our best knowledge, has addressed this issue, although its need has been expressed by several authors. In this paper, to make uncertainty analysis of ABM/LCA coupled models operational, the different uncertainty sources in both models are identified and a systematic classification is proposed. The efforts in both fields to propagate these uncertainty sources are reviewed and discussed against three criteria (applicability, accuracy and computational effort). Using ABM within LCA adds new uncertainty sources to the LCI and limits the number of applicable propagation methods, as the coupled model can no longer be expressed as an explicit formula. The context of uncertainty sources (e.g. nature of uncertainty and available information) determines which propagation method is the most appropriate and promises high accuracy, while the choice might be constraint by the computational effort

Uncertainty analysis in agent-based modelling and consequential life cycle assessment coupled models:a critical review

\u3cp\u3eThe evolution of life cycle assessment (LCA) from a merely comparative tool for the assessment of products to a policy analysis tool proceeds by incorporating increasingly complex modelling approaches. In more recent studies of complex systems, such as the agriculture sector or mobility, agent-based modelling (ABM) has been introduced as tool for life cycle inventory modelling. The promises of such ABM/LCA coupled models include the consideration of human behaviour and local variabilities in the studied system as well as scenario modelling for emerging systems. The acceptance of this new approach depends, among other things, on the handling of uncertainty and variability forthcoming from various sources. As the complexity of a methodology increases, it also becomes increasingly challenging to adequately handle uncertainty and variability, and be confident about an inference. In the case of ABM/LCA coupled models, the different nature of both parts (non-linear computational ABM and linear deterministic LCA) poses an additional challenge. The sources of uncertainty and variability and the preferable propagation methods differ for both parts and clear guidance is needed. Yet no study, to our best knowledge, has addressed this issue, although its need has been expressed by several authors. In this paper, to make uncertainty analysis of ABM/LCA coupled models operational, the different uncertainty sources in both models are identified and a systematic classification is proposed. The efforts in both fields to propagate these uncertainty sources are reviewed and discussed against three criteria (applicability, accuracy and computational effort). Using ABM within LCA adds new uncertainty sources to the LCI and limits the number of applicable propagation methods, as the coupled model can no longer be expressed as an explicit formula. The context of uncertainty sources (e.g. nature of uncertainty and available information) determines which propagation method is the most appropriate and promises high accuracy, while the choice might be constraint by the computational effort.\u3c/p\u3

Emergy evaluation vs. life cycle-based embodied energy (solar, tidal and geothermal) of wood biomass resources

Several environmental accounting methods exist to evaluate the rate of ecosystems resource exploitation and to strengthen the comparison among human production systems in terms of renewability and sustainable use of resources. However, their application rarely refers to the environmental work that is necessary to produce natural resources. The aim of this research is to advance the characterization of different wood biomass species by using the emergy principles and thus to estimate the geobiosphere work required to generate wood resources. The analysis has been conducted applying the classical emergy methodology and a recently developed life cycle-based embodied energy approach. This latter is implemented with the support of Life Cycle Assessment (LCA) principles and tools to disclose as a result vectors of Unit Embodied Energy Value ((UEEV) over right arrow), composed by three components: the Embodied Solar, Tidal and Geothermal Energy. Differently from emergy evaluation, the life cycle-based embodied energy approach does not consider the baseline concept and the emergy algebra, but the Solar, Geothermal and Tidal sources are independently quantified, keeping them separated and not weighted. The present paper shows that the latter method can provide a consistent framework to trace and evaluate the primary provision of energy throughout the formation of resources. Regionalized UEVs (Unit Emergy Values) and ((UEEVs) over right arrow) have been obtained and compared with regard to Fagus spp., Quercus spp., Picea spp., Pinus spp., Pseudotsuga spp., Fraxinus spp., Populus spp., Castanea spp., and other grouped conifers (Larix spp., Cupressus spp. and Abies spp.) and other deciduous species (Carpinus spp., Betulus spp., Alnus spp. and Robinia spp.). The trend of output values per unit of resource species obtained by means of the two methods was very similar when looking at the Solar Embodied Energy contribution, meaning that this flow has the main direct (with the life cycle-based embodied energy approach) and indirect (with the emergy one) influence on the generation of wood biomass. Results obtained by means of both methods can fill out the life cycle of products based on wood biomass, providing the natural contribution to wood species formation and thus embedding this information in the technosphere processes. (C) 2013 Elsevier Ltd. All rights reserved

Implications of a consumer-based perspective for the estimation of GHG emissions. The illustrative case of Luxembourg

The Kyoto protocol has established an accounting system for national greenhouse gas (GHG) emissions according to a geographic criterion (producer perspective), such as that proposed by the IPCC guidelines for national GHG inventories. However, the representativeness of this approach is still being debated, because the role of final consumers (consumer perspective) is not considered in the emission allocation system. This paper explores the usefulness of a hybrid analysis, including input-output (IO) and process inventory data, as a complementary tool for estimating and allocating national GHG emissions according to both consumer- and producer-based perspectives. We assess the historical GHG impact profile (from 1995 to 2009) of Luxembourg, which is taken as a case study. The country's net consumption over time is estimated to generate about 28,700 Gg CO(2)e/year on average. Compared to the conventional IPCC inventory, the IO-based framework typically shows much higher emission estimations. This relevant discrepancy is mainly due to the different points of view obtained from the hybrid model, in particular with regard to the contribution of imported goods and services. Detailing the GHG inventory by economic activity and considering a wider system boundary make the hybrid IO method advantageous as compared to the IPCC approach, but its effective implementation is still limited by the relatively complex modeling system, as well as the lack of coordination and scarce availability of datasets at the national level

Emergy-based mid-point valuation of ecosystem goods and services for life cycle impact assessment

Ecosystem goods and services (EGSs) are of crucial importance for the economic and social development of human communities. The well-established life cycle assessment (LCA) method is facing a number of challenging improvements to define new Characterization factors (CFs) for life cycle impact assessment (LCIA) of EGSs. Very recently, extensive work conducted under the UNEP/SETAC Life Cycle initiative has been completed with the goal of providing new LCIA methods and spatially differentiated mid-point CFs for land use and land use change impacts on biodiversity and ecosystem services. However, the implemented models do not enable one to assess the actual damage to ecosystem functionality, and thus the relationship among EGSs and related areas of protection (e.g. AoP of "Natural Resources") remains undefined. This paper aims at investigating the potential characterization ability of the Emergy method for LCIA of EGSs. The goal is to use the extensive libraries of Unit Emergy Values (UEVs) of primary services and resources as CFs for LCIA to evaluate the physical contribution of EGSs in supporting life cycle processes. Having its roots in thermodynamics and systems ecology, Emergy can appraise a larger and more diversified (than LCA) number of EGSs through a common physical denominator, i.e. the solar emjoule or seJ, which measures the solar energy embodied in natural products. Emergy thus has a typical Nature-oriented perspective, accounting for the available energy that is used up by the natural cycles, directly and indirectly, to generate biotic and abiotic resources. A library of selected UEVs (more than 100) for biophysical EGS valuation has been framed including values collected from the Emergy literature and formulated on the latest planetary baseline (i.e. 15.2E + 24 seJ/yr). Advantages and limitations for future application of these values toward an LCIA mid-point impact characterization of Emergy are discussed. UEVs may represent mid-point LCIA factors for ecological contribution analysis, enabling one to account for the memory of energy previously required to produce EGSs, which can be used as a proxy to assess the future environmental work necessary to regenerate the used EGSs. However, the added value of Emergy for LCA is still debated, mainly because of the low accuracy and unclear meaning of the UEVs in relation to the availability of resources. Therefore, Emergy can be conceived as a suitable physical measure complementary to the economic valuations and current "user-side" tools applied in LCA

Legislative Documents

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Towards prospective life cycle sustainability analysis: exploring complementarities between social and environmental life cycle assessments for the case of Luxembourg’s energy system

Sustainability typically relies on the durable interaction between humans and the environment. Historically, modelling tools such as environmental-life cycle assessment (E-LCA) have been developed to address the mitigation of environmental impacts generated by human activities. More recently, social-life cycle assessment (S-LCA) methods have been proposed to investigate the social sustainability sphere, looking at the life cycle effects generated by positive or negative pressures on social endpoints (i.e. well-being of stakeholders). Despite this promising added value, however, S-LCA methods still show limitations and challenges to be faced, e.g. regarding the lack of high quality datasets and the implementation of consensual social impact assessment indicators. This paper discusses on the complementarity between S-LCA and E-LCA towards the definition of prospective life cycle sustainability analysis (LCSA) approaches. To this aim, a case study is presented comparing (i) E-LCA results of business-as-usual (BAU) scenarios of energy supply and demand technology changes in Luxembourg, up to 2025, based on economic equilibrium modeling and hybrid life cycle inventories, with (ii) a monetary-based input-output estimation of the related changes in the societal sphere. The results show that environmental and social issues do not follow the same impact trends. While E-LCA outputs highlight contrasting patterns, they do generally underlie a relatively low decrease in the aggregated environmental burdens curve (around 20% of decrease over the single-score impact trend over time). In contrast, social hotspots (identified in S-LCA by specific risk indicators of human rights, worker treatment, poverty, etc.) are typically increasing over time according to the growth of the final energy demand. Overall, the case study allowed identifying possible synergies and tradeoffs related to the impact of projected energy demands in Luxembourg. Despite the studied approach does not fully adopt a consequential perspective, it can be considered as a basis to develop a prospective LCSA approach, combining consequential E-LCA and S-LCA. Accordingly, we introduced the concept of “anticipatory experiences” on energy transition towards a low carbon society as drivers for change, observing that societal phenomena characterizing the transition of the energy systems towards lower carbon-related emissions seem to facilitate the identification of actual and potential changes that may take place within these upcoming transition processes. Such phenomena, which are somehow typical, may be used as inputs for S-LCA, so as to better defining the most likely developments of certain intervention/policies in the energy sector and eventually contribute to the definition of prospective and consequential LCSA modelling tools