ArticleThe international journal of life cycle assessment2019
Integrating exposure to chemicals in building materials during use stage.
Article in The international journal of life cycle assessment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed, 30 citations in OpenAlex.
- Environmental Toxicity of Cement Nanocomposites Reinforced with Carbon Nanotubes.Materials (Basel, Switzerland) · 2025Article
- Exposure and Toxicity Characterization of Chemical Emissions and Chemicals in Products: Global Recommendations and Implementation in USEtox.The international journal of life cycle assessment · 2021Article
- Estimation of the Emission Characteristics of SVOCs from Household Articles Using Group Contribution Methods.Environmental science & technology · 2020Article
- Assessing Human Exposure to Chemicals in Materials, Products and Articles: The International Risk Management Landscape for Phthalates.Environmental science & technology · 2019Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
purposeThere do not currently exist scientifically defensible ways to consistently characterize the human exposures (via various pathways) to near-field chemical emissions and associated health impacts during the use stage of building materials. The present paper thus intends to provide a roadmap which summarizes the current status and guides future development for integrating into LCA the chemical exposures and health impacts on various users of building materials, with a focus on building occupants.
methodsWe first review potential human health impacts associated with the substances in building materials and the methods used to mitigate these impacts, also identifying several of the most important online data resources. A brief overview of the necessary steps for characterizing use stage chemical exposures and health impacts for building materials is then provided. Finally, we propose a systematic approach to integrate the use stage exposures and health impacts into building material LCA and describe its components, and then present a case study illustrating the application of the proposed approach to two representative chemicals: formaldehyde and methylene diphenyl diisocyanate (MDI) in particleboard products. RESULTS AND DISCUSSION: Our proposed approach builds on the coupled near-field and far-field framework proposed by Fantke et al. (Environ Int 94:508-518, 2016), which is based on the product intake fraction (PiF) metric proposed by Jolliet et al. (Environ Sci Technol 49:8924-8931, 2015), The proposed approach consists of three major components: characterization of product usage and chemical content, human exposures, and toxicity, for which available methods and data sources are reviewed and research gaps are identified. The case study illustrates the difference in dominant exposure pathways between formaldehyde and MDI and also highlights the impact of timing and use duration (e.g., the initial 50 days of the use stage vs. the remaining 15 years) on the exposures and health impacts for the building occupants.
conclusionsThe proposed approach thus provides the methodological basis for integrating into LCA the human health impacts associated with chemical exposures during the use stage of building materials. Data and modeling gaps which currently prohibit the application of the proposed systematic approach are discussed, including the need for chemical composition data, exposure models, and toxicity data. Research areas that are not currently focused on are also discussed, such as worker exposures and complex materials. Finally, future directions for integrating the use stage impacts of building materials into decision making in a tiered approach are discussed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.