Explore the vast range of titles available.

PurposeAn insufficient amount of available domestic water can lead to an increase in the occurrence of water-related diseases. No LCIA consensus has been reached on how to model the potential impacts on human health resulting from water use implying domestic water deprivation. Building on Boulay et al. (2011), this research work provides an updated and revisited characterization model and factors assessing the potential impact on human health induced along this impact pathway.MethodThis work consolidates the cause-effect chain linking water use to domestic impacts on human health. The revised fate factor aligns current water use assessment methods and includes information not only on the physical water scarcity but also on the level of population access to water in a region. Building on Boulay et al. (2011), the global effect factor is revised. The data source is updated, and a novel approach is developed estimating the domestic water deficit. Country-scale exposure factors are updated, building on Boulay et al. (2011)’s proposal to rely on the gross national income per capita as a proxy for a country’s capacity to adapt to water shortages.Results and discussionCompared to Boulay et al. (2011), the revised fate and exposure factors show lower values as a result of different methodological choices and of the overall increase of GNI per capita, respectively. The revised value of the effect factor is equal to 3.13E-3DALY/m3 which compares to the value of 3.11E-3 in Boulay et al. (2011). Revised characterization factors (CF) range from 0 DALY/m3 (the potential impact on human health due to water use is null with respect to domestic water deprivation) to 3.13E-3 DALY/m3. The distribution of the new CFs shows an order of magnitude decrease compared to the previous model. These CFs assess the consequences on human health induced by water use leading to short-term water deprivation.Conclusion and recommendationsThis research work helps to better account for the impacts of water use at the endpoint level. However, it underlines significant limitations in the current calculation of the effect factor, in particular regarding current quantification of domestic water deprivation. These shortcomings prevent the model from considering a difference in vulnerability to health damages from the deprivation of 1 m3 of domestic water. This research work argues for additional research efforts aimed at developing an alternative calculation method for this factor.

Purpose The consumption of freshwater can increase local competition among ecosystems needs, agriculture, and domestic users. This competition can lead to reduced domestic water availability and subsequent inadequate hygiene practices leading to water-related diseases. Among the few attempts to develop endpoint-oriented characterization models and factors to assess this impact pathway, limitations still need to be addressed to improve the effect factor (EF) representing the marginal increase in health damage associated with 1 m 3 of water consumed. This research proposes a revised country-scale effect model assessing diarrheal diseases due to domestic water deprivation, considering different levels of water availability within a country. Methods The calculation of the EF is based on the principle that the probability of negative health consequences associated with depriving a domestic user of 1 m 3 of water depends on the quantity used daily by this user. Three classes of domestic water users are defined based on their range of daily water use. EFs are calculated for each class of domestic users building on a comparative risk assessment methodology and households’ levels of access to drinking water and sanitation from the Joint Monitoring Program. Country-specific EFs are computed as the weighted sum of class-specific EF proportionally to the population within each class. Revised country-specific EFs are used to overwrite the generic constant EF used in previous characterization models and to compute new characterization factors (CFs). Results and discussion Class-specific effect factors equal to 1.35e − 3, 3.44e − 4, and 7.53e − 5 DALY/m 3 for the three classes of users, showing a 57, 89, and 98% reduction compared to previous characterization models. Country-specific EF values range from 7.5e − 05 to 8.7e − 04 DALY/m 3 deprived ( M : 2.5e − 04; SD: 1.8e − 04), representing a reduction of 72.2 to 97.6% compared to previous models. New 11987 CFs were compiled ranging from 0 to 7.63e − 04 DALY/m 3 consumed ( M : 1.9e − 6; SD: 2.1e − 5). The global potential impact induced by water consumption over the year 2019 computed with our model reaches 2.77e + 7 DALYs, corresponding to 50% of the water-related burden of diarrheal disease calculated by a recent epidemiology study, which confirms the plausibility of our results. Conclusions Unlike previous methods, our revised EFs acknowledge inequalities in domestic water consumption within a country. Revised EFs are calculated by country, going beyond the global resolution of previous models, compared to which they show a reduction of 72 to 98%. A sanity check confirms the plausibility of our CFs but does not rule out a potential overestimation. Future research is needed to provide empirical evidence supporting a causal link between water deprivation and diarrheal diseases and to assess uncertainties of the model results.

Life Cycle Assessment (LCA) is a key tool for sustainable management. This standardized methodology is structured into four main steps. The third step, called Life Cycle Impact Assessment (LCIA), aims to translate inventory data (e.g., emissions of toxic substances) into potential environmental impacts. This translation relies on characterization factors, which are derived from characterization models representing the involved environmental mechanisms. Characterization models are structured within an “LCIA framework”, which is a coherent and comprehensive conceptual structure that identifies and organizes pathways of potential impact and relevant indicators for decision-making.Over time, the LCIA framework and its associated characterization models have evolved. However, the current framework still insufficiently addresses the pathways by which human activities affect the benefits provided by nature, known as ecosystem services. Such services are essential to human well-being, and their omission from LCA impact profiles represents a significant blind spot for decision-making. Bridging this gap requires the development of appropriate impact models and characterization factors assessing pathways of impacts on ecosystem services. Yet, such developments must remain consistent with existing LCIA models, which typically address other impact categories such as human health or ecosystem quality. Many of these existing models implicitly integrate concepts closely related to ecosystem services, such as ecosystem functions. Therefore, to ensure conceptual coherence and avoid double counting, it is important to identify and make explicit the interactions between ecosystem services concepts and traditional LCIA pathways. In this context, the present article-based thesis proposes a revision of the LCIA framework through the lens of ecosystem services. Building on the revised framework, models and characterization factors are developed for two specific impact pathways.The first article presents a critical literature review, combining two research works: a review of the fundamental concepts relating to ecosystem services and an analysis of attempts to integrate ecosystem services into LCIA. The review highlights both the relevance and the challenges of incorporating ecosystem services into LCIA. It identifies inconsistencies and a lack of conceptual clarity in several existing proposals and advocates for a more suitable LCIA framework for ecosystem services integration.In response, the second article introduces a revised LCIA framework built on the “cascade model” developed by the ecosystem services research community. This new framework reveals strong conceptual linkages between ES-related concepts and most existing LCIA models. To illustrate its comprehensiveness and applicability, all characterization models from the IMPACT World+ methodology are mapped onto this revised framework.On the basis of this new structure, models and CFs are being developed for two impact pathways. The third study of this thesis develops a model and associated characterization factors to assess the impacts of sea-level rise and the intensification of extreme events on coastal ES. The characterization factors are calculated as the ratio between (1) the loss of ecosystem service supply potential in coastal zones projected to be flooded between 2015 and 2100, and (2) the cumulative greenhouse gas emissions over the same period. Depending on the scenario, characterization factors values range from 16.7 to 66.1 $/tCO2,eq, aligning with the social cost of carbon (estimated at 185$ /tCO2,eq), thus validating their order of magnitude. Nevertheless, limitations are acknowledged, including the challenges of modeling the capacity of coastal ecosystems to adapt to flooding and of quantifying global ecosystem services demand.A second impact pathway of the revised framework explored in this thesis addresses the potential human health impacts from freshwater use and deprivation, expressed in DALYs/m3 consumed. Two articles are dedicated to this topic. The fourth article of this thesis revisits and consolidates a characterization model developed in 2011, updating its fate, exposure, and effect factors to produce a new set of characterization factors. However, the work reveals a significant limitation of the effect factor, which estimates health impacts due to water deprivation. Being global in scope, the effect factor does not account for disparities in water access within populations.To address this shortcoming, the fifth article proposes a new effect factor calculation method, based on the premise that health consequences of losing 1 m3 of water depend on the user’s typical daily consumption. By distinguishing user classes, new country-scale effect factors are developed and integrated with the updated characterization factors components, yielding a consolidated set of characterization factors. Despite these improvements, the empirical demonstration of the causal chain from water deprivation to health outcomes remains a key research need. The application of the revised LCIA framework across these two impact pathways demonstrates both its relevance and practical utility. However, the case study on sea-level rise also highlights a key limitation in operationalizing the framework: the complexity of modeling demand for ecosystem services.The proposed framework is designed to be flexible and adaptable to different cause-effect chains. Rather than offering strict guidelines, this work aims to provide a coherent and comprehensive structure for methodological developments, ultimately enabling the creation of meaningful indicators for decision support. However, it is important to emphasize that the selection of relevant impacts is inherently subjective; differing value systems can lead to the development of alternative frameworks.The revised LCIA framework proposed in this thesis serves as a conceptual tool for LCA modelers, supporting consistency and completeness in characterization models development. The characterization factors derived from it are intended for LCA practitioners, helping to generate more comprehensive and robust information for decision-making. More broadly, this work contributes to advancing and consolidating the field of LCIA.