USEtox human exposure and toxicity factors for comparative assessment of toxic emissions in life cycle analysis: sensitivity to key chemical properties

Rosenbaum, Ralph K.; Huijbregts, Mark A. J.; Henderson, Andrew; Margni, Manuele; McKone, Thomas E.; Meent, Dik van de; Hauschild, Michael Zwicky; Shaked, Shanna; Li, Ding Sheng; Gold, Lois Swirsky; Jolliet, Olivier

doi:10.1007/s11367-011-0316-4

Cited by 197 publications

(184 citation statements)

References 56 publications

Supporting

Mentioning

182

Contrasting

Unclassified

Order By: Relevance

“…Additionally, in an LCA study containing several substances in the inventory, there is not only one type of non-cancer human toxicity effects covered. For example, the CF can reflect severe chronic damage to foetus development as well as temporary skin irritation (Rosenbaum et al 2011). For cancer human toxicity effects, the CF can likewise reflect different cancer causes including both substances that induce tumours and that increase their incidence.…”

Section: Best-estimate Approach For Datamentioning

confidence: 99%

“…The models selected were ECOSAR (US EPA 2012) for ecotoxicity and QSAR Toolbox (OECD 2016a) for mammalian toxicity. To fill as many data gaps as possible, the acuteto-chronic extrapolation, as suggested by Rosenbaum et al (2011), was used as a complementary method to estimate cancer (if indicated to be mutagenic) and non-cancer ED 50 based on acute LC 50 values as predicted with the US EPA T.E.S.T. model (US EPA 2017).…”

Section: Evaluation Of Data Sources For Inclusion In the Strategymentioning

confidence: 99%

“…HSDB was used in Rosenbaum et al (2011) and therefore considered prioritised d Data from the REACH registration database is subject to copyright laws and may require the permission of the owner of the information had to fulfil the criteria as defined in Table 1, and the non-MDQ experimental data had to point in the same direction (cf. WoE approach in REACH Annex XI).…”

Section: Proposed Data Source Selection Strategymentioning

confidence: 99%

See 2 more Smart Citations

USEtox characterisation factors for textile chemicals based on a transparent data source selection strategy

Roos

Holmquist

Jönsson³

et al. 2017

Int J Life Cycle Assess

View full text Add to dashboard Cite

Purpose Life cycle assessments (LCAs) of textile products which do not include the use and emission of textile chemicals, such as dyes, softeners and water-repellent agents, will give non-comprehensive results for the toxicity impact potential. The purpose of this paper is twofold: (1) to provide a set of characterisation factors (CFs) for some of the most common textile chemicals and (2) to propose a data source selection strategy in order to increase transparency when calculating new CFs. Methods A set of 72 common textile-related substances was matched with the USEtox 2.01, USEtox 1.01 and the COSMEDE databases in order to investigate coverage and coherence. For the 25 chemicals that did not already have established CFs in any of these databases, new CFs were calculated. A data source selection strategy was developed and followed in order to ensure consistency and transparency, and USEtox 2.01 was used for calculations. The parameters that caused the most uncertainty were identified during the modelling and strategies for handling them were developed. Results and discussion Of the 72 textile-related substances, 48 already had calculated recommended or indicative CFs in existing databases, which showed good coherence. The main uncertainty identified during the calculation of 25 new CFs was the selection of input data regarding toxicity and degradation in water. However, for substances such as per-and polyfluoroalkyl substances (PFAS), the acid dissociation constant (pK a ) and partitioning coefficients (K ow and K OC ) also require special considerations. Other input parameters had less than one order of magnitude impact on the CF result for essentially all substances. Conclusions The paper presents a strategy for how to provide a complete set of toxicity CFs for a given list of substances. In addition, such a set of CFs for common textile-related substances is presented. The data source selection strategy provides a structured and transparent way of calculating additional CFs for textile chemicals with USEtox. Consequently, this study can help future LCA studies to provide relevant guidance towards environmentally benign chemical management in the textile industry.

show abstract

Section: Best-estimate Approach For Datamentioning

confidence: 99%

Section: Evaluation Of Data Sources For Inclusion In the Strategymentioning

confidence: 99%

Section: Proposed Data Source Selection Strategymentioning

confidence: 99%

See 1 more Smart Citation

USEtox characterisation factors for textile chemicals based on a transparent data source selection strategy

Roos

Holmquist

Jönsson³

et al. 2017

Int J Life Cycle Assess

View full text Add to dashboard Cite

show abstract

“…USEtox is a consensus model developed within the Life Cycle Initiative led by the United Nations Environmental Program and the Society of Environmental Toxicology and Chemistry (UNEP-SETAC) (Hauschild et al, 2008;Henderson et al, 2011;Rosenbaum et al, 2008Rosenbaum et al, , 2011. This parsimonious and transparent model can screen thousands of chemicals and is widely used, but only provides continent-generic characterisation factors and impact scores for a generic unknown continent.…”

Section: Introductionmentioning

confidence: 99%

“…Humbert et al (2011) showed that intake fractions from inhalation of primary particulate matter can be modelled based on emission release height and "archetypal" environment (indoor versus outdoor; urban, rural, or remote locations) and vary by orders of magnitude among conditions considered. Several other authors have used the archetype approach to estimate human toxicity impacts from air emissions, including Hellweg et al (2009) and Wenger et al (2012) for indoor air and Rosenbaum et al (2011) for urban emissions by continent. However, a similar archetypal approach has not yet been developed for related fate and exposure for water emissions.…”

Section: Introductionmentioning

confidence: 99%

Spatial analysis of toxic emissions in LCA: A sub-continental nested USEtox model with freshwater archetypes

Kounina

Margni

Shaked

et al. 2014

Environment International

Self Cite

View full text Add to dashboard Cite

This paper develops continent-specific factors for the USEtox model and analyses the accuracy of different model architectures, spatial scales and archetypes in evaluating toxic impacts, with a focus on freshwater pathways. Inter-continental variation is analysed by comparing chemical fate and intake fractions between sub-continental zones of two life cycle impact assessment models: (1) the nested USEtox model parameterized with sub-continental zones and (2) the spatially differentiated IMPACTWorld model with 17 interconnected sub-continental regions. Substance residence time in water varies by up to two orders of magnitude among the 17 zones assessed with IMPACTWorld and USEtox, and intake fraction varies by up to three orders of magnitude. Despite this variation, the nested USEtox model succeeds in mimicking the results of the spatially differentiated model, with the exception of very persistent volatile pollutants that can be transported to polar regions. Intra-continental variation is analysed by comparing fate and intake fractions modelled with the a-spatial (one box) IMPACT Europe continental model vs. the spatially differentiated version of the same model. Results show that the one box model might overestimate chemical fate and characterisation factors for freshwater eco-toxicity of persistent pollutants by up to three orders of magnitude for point source emissions. Subdividing Europe into three archetypes, based on freshwater residence time (how long it takes water to reach the sea), improves the prediction of fate and intake fractions for point source emissions, bringing them within a factor five compared to the spatial model. We demonstrated that a sub-continental nested model such as USEtox, with continent-specific parameterization complemented with freshwater archetypes, can thus represent inter-and intra-continental spatial variations, whilst minimizing model complexity.

show abstract

Life Cycle Impact Assessment

2014

Life Cycle Assessment (LCA)

View full text Add to dashboard Cite

This chapter is dedicated to the third phase of an LCA study, the Life 6 Cycle Impact Assessment (LCIA) where the life cycle inventory's information on 7 elementary flows is translated into environmental impact scores. In contrast to the 8 three other LCA phases, LCIA is in practice largely automated by LCA software, 9 but the underlying principles, models and factors should still be well understood by 10 practitioners to ensure the insight that is needed for a qualified interpretation of the 11 results. This chapter teaches the fundamentals of LCIA and opens the black box of 12 LCIA with its characterisation models and factors to inform the reader about: (1) the 13 main purpose and characteristics of LCIA, (2) the mandatory and optional steps of 14 LCIA according to the ISO standard, and (3) the science and methods underlying 15 the assessment for each environmental impact category. For each impact category, 16 the reader is taken through (a) the underlying environmental problem, (b) the 17 underlying environmental mechanism and its fundamental modelling principles, 18 (c) the main anthropogenic sources causing the problem and (d) the main methods 19 available in LCIA. An annex to this book offers a comprehensive qualitative 20 comparison of the main elements and properties of the most widely used and also 21 the latest LCIA methods for each impact category, to further assist the advanced 22practitioner to make an informed choice between LCIA methods. 25After studying this chapter, the reader should be able to: 26• Explain and discuss the process and main purposes of the LCIA phase of an 27 LCA study. 28• Distinguish and explain the mandatory and optional steps according to inter-29 national standards for LCA. 30• Differentiate and describe each of the impact categories applied in LCIA 31 regarding: 32the underlying environmental problem. 33the environmental mechanism and its fundamental modelling principles. 34the main anthropogenic sources causing the problem. 35the main methods used in LCIA. 36 37 38 39 10.1 Introduction 40 In practice, the LCIA phase is largely automated and essentially requires the 41 practitioner to choose an LCIA method and a few other settings for it via menus and 42 buttons in LCA software. However, as straightforward as that may seem, without 43 understanding a few basic, underlying principles and the meaning of the indicators, 44 neither an informed choice of LCIA method nor a meaningful and robust inter-45 pretation of LCA results is possible. However, the important extent of science and 46 its inherent multidisciplinarity frequently result in a perceived opacity of this phase. 47 This chapter intends to open the black box of LCIA with its characterisation models 48 and factors, and to accessibly explain (1) its main purpose and characteristics, 49(2) the mandatory and optional steps according to ISO and (3) the meaning and 50 handling of each impact category. While this chapter is a pedagogical and focused 51 introduction into the complex and broad aspects of LCIA, a more profound a...

show abstract

USEtox human exposure and toxicity factors for comparative assessment of toxic emissions in life cycle analysis: sensitivity to key chemical properties

Cited by 197 publications

References 56 publications

USEtox characterisation factors for textile chemicals based on a transparent data source selection strategy

USEtox characterisation factors for textile chemicals based on a transparent data source selection strategy

Spatial analysis of toxic emissions in LCA: A sub-continental nested USEtox model with freshwater archetypes

Life Cycle Impact Assessment

Contact Info

Product

Resources

About