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      Integrating effects of overheating on human health into buildings’ life cycle assessment

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          Abstract

          Purpose

          Due to climate change, the severity and length of heat waves are increasing, and this trend is likely to continue while mitigation efforts are insufficient. These climatic events cause overheating inside buildings, which increases mortality. Adaptation measures reduce overheating but induce environmental impacts, including on human health. This study aims to integrate the overheating-related effects on human health in building LCA to provide a design aid combining mitigation and adaptation.

          Methods

          In a novel approach, an existing building LCA tool is utilised to evaluate life cycle impacts, including damage to human health expressed in DALYs. The overheating risk is then evaluated using an existing dynamic thermal simulation (DTS) tool and prospective climatic data. Overheating is expressed as a degree-hour (DH) indicator, which integrates both the severity (temperature degrees over a comfort threshold) and the duration (hours). By assuming proportionality between DALYs and DH × area in a first step, the 2003 heat wave mortality data, 2003 climatic data, and a simplified model of the national residential building stock were used to identify a characterisation factor, which can then be used to evaluate DALYs corresponding to any building using DH obtained by thermal simulation.

          Results

          The proposed overheating model not only allows to derive a characterisation factor for overheating to be used in building LCA but also provides practical insights. The first estimation of the characterisation factor is 1.35E-8DALY. DH-1.m-2. The method was tested in a case study corresponding to a social housing apartment building in France built in 1969 without insulation. The thickness of insulation implemented in the renovation works was varied. For this specific case study, the contribution of overheating is significant, ranging from 1.1E-5DALY.m-2.y-1 to 2.2E-5DALY.m-2.y-1, comparable to the contribution of heating. DTS and LCA results found an optimal thickness, minimising the human health indicator in DALYs. This underscores the potential of active cooling to reduce human health impacts, especially if it consumes electricity produced by a photovoltaic system integrated in the building.

          Conclusion

          Combining DTS and LCA makes it possible to evaluate damage indicators on human health, including building life cycles (e.g., material and energy) and overheating-related impacts. An application on a case study shows this method’s feasibility and gives a first order of magnitude of overheating health impacts induced by buildings. A more sophisticated model could replace the assumed proportionality between DALYs and DH.

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          Most cited references67

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          Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

          Summary Background Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk–outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk–outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk–outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95% uncertainty interval [UI] 9·51–12·1) deaths (19·2% [16·9–21·3] of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12–9·31) deaths (15·4% [14·6–16·2] of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253–350) DALYs (11·6% [10·3–13·1] of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0–9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10–24 years, alcohol use for those aged 25–49 years, and high systolic blood pressure for those aged 50–74 years and 75 years and older. Interpretation Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding Bill & Melinda Gates Foundation.
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            ReCiPe2016: a harmonised life cycle impact assessment method at midpoint and endpoint level

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              The CNRM-CM5.1 global climate model: description and basic evaluation

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                Author and article information

                Contributors
                (View ORCID Profile)
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                Journal
                The International Journal of Life Cycle Assessment
                Int J Life Cycle Assess
                Springer Science and Business Media LLC
                0948-3349
                1614-7502
                November 2024
                August 20 2024
                November 2024
                : 29
                : 11
                : 2137-2150
                Article
                10.1007/s11367-024-02353-3
                6a2acbf0-9f4e-48f7-87e1-445bdc002232
                © 2024

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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