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Causal cross-modal effects between odor and temperature on occupants' perception in a single-person office environment.

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Title: Causal cross-modal effects between odor and temperature on occupants' perception in a single-person office environment.
Authors: Pan, Jian1 (AUTHOR) jpan@ukaachen.de, Bertram, Jens2 (AUTHOR), Rengelshausen, Jens2 (AUTHOR), Kraus, Thomas2 (AUTHOR), Mahdavi, Ardeshir3 (AUTHOR), Martínez-Muñoz, Irene3 (AUTHOR), Mino-Rodriguez, Isabel4 (AUTHOR), Wagner, Andreas4 (AUTHOR), Berger, Christiane5 (AUTHOR), Christoforou, Rania1 (AUTHOR), Müller, Irene Elisabeth1 (AUTHOR), Schweiker, Marcel1,6 (AUTHOR)
Source: Building & Environment. Jun2026, Vol. 297, pN.PAG-N.PAG. 1p.
Subject Terms: *Temperature effect, *Indoor air quality, Olfactory perception, Causal inference, Satisfaction, Perceptual learning, Bayesian analysis
Abstract: • Manipulated room odor and temperature in a 2 × 2 office perception experiment. • Warmth reduced olfactory satisfaction; marginal temperature × odor interactions. • Supports negativity bias: negative experiences in one domain can affect another. • Applied causal inference, adjustment criterion, and Bayesian ROPE frameworks. • Offers a replicable methodological template for causal occupant-centric research. Both odor and temperature have been suggested to shape occupants' perception of indoor environment, yet quantitative evidence regarding their interdependence remains limited. This study investigated their cross-modal effects on human responses in office environments, theoretically based on negativity bias, revenge effect, and One-Vote Veto effect. A single-blind 2 × 2 within-subject experiment was conducted in the Aachen Workplace Simulation Lab. 23 healthy, mostly young participants experienced room atmospheres with pleasant (0.7 ppm pentyl acetate) and unpleasant (5 ppm 1-butanol) odors at neutral (24 °C) and slightly warm (28.5 °C) temperatures. Standardized questionnaires assessed subjective satisfaction and sensation across sensory domains before and after olfactory adaptation. Modern statistical advancements—including causal inference, adjustment criterion, and Bayesian region of practical equivalence—were leveraged to address existing methodological limitations in multi-domain research. Results revealed cross-modal main effects, with increased warmth reducing olfactory satisfaction. Marginal temperature x odor interactions were found for thermal and overall satisfaction, while other cross-modal effects remained inconclusive. Substantial inter-individual variability was observed in odor valence ratings. These findings highlight the interdependence of thermal and olfactory perception and partially support the notion that negative experiences from one domain can influence another; however, One-Vote Veto effects were not confirmed. The study underscores the need for holistic indoor environmental quality assessments and follow-up multi-domain research. Methodologically, it showcases application of modern statistical tools to improve transparency and rigor in causal human-centric building science. Challenges related to odor selection and concentration manipulation are highlighted as key areas for improvement in related future research. [ABSTRACT FROM AUTHOR]
Copyright of Building & Environment is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Causal cross-modal effects between odor and temperature on occupants' perception in a single-person office environment.
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  Data: <searchLink fieldCode="AR" term="%22Pan%2C+Jian%22">Pan, Jian</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jpan@ukaachen.de</i><br /><searchLink fieldCode="AR" term="%22Bertram%2C+Jens%22">Bertram, Jens</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Rengelshausen%2C+Jens%22">Rengelshausen, Jens</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kraus%2C+Thomas%22">Kraus, Thomas</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mahdavi%2C+Ardeshir%22">Mahdavi, Ardeshir</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Martínez-Muñoz%2C+Irene%22">Martínez-Muñoz, Irene</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mino-Rodriguez%2C+Isabel%22">Mino-Rodriguez, Isabel</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wagner%2C+Andreas%22">Wagner, Andreas</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Berger%2C+Christiane%22">Berger, Christiane</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Christoforou%2C+Rania%22">Christoforou, Rania</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Müller%2C+Irene+Elisabeth%22">Müller, Irene Elisabeth</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schweiker%2C+Marcel%22">Schweiker, Marcel</searchLink><relatesTo>1,6</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Building+%26+Environment%22">Building & Environment</searchLink>. Jun2026, Vol. 297, pN.PAG-N.PAG. 1p.
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  Data: *<searchLink fieldCode="DE" term="%22Temperature+effect%22">Temperature effect</searchLink><br />*<searchLink fieldCode="DE" term="%22Indoor+air+quality%22">Indoor air quality</searchLink><br /><searchLink fieldCode="DE" term="%22Olfactory+perception%22">Olfactory perception</searchLink><br /><searchLink fieldCode="DE" term="%22Causal+inference%22">Causal inference</searchLink><br /><searchLink fieldCode="DE" term="%22Satisfaction%22">Satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Perceptual+learning%22">Perceptual learning</searchLink><br /><searchLink fieldCode="DE" term="%22Bayesian+analysis%22">Bayesian analysis</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: • Manipulated room odor and temperature in a 2 × 2 office perception experiment. • Warmth reduced olfactory satisfaction; marginal temperature × odor interactions. • Supports negativity bias: negative experiences in one domain can affect another. • Applied causal inference, adjustment criterion, and Bayesian ROPE frameworks. • Offers a replicable methodological template for causal occupant-centric research. Both odor and temperature have been suggested to shape occupants' perception of indoor environment, yet quantitative evidence regarding their interdependence remains limited. This study investigated their cross-modal effects on human responses in office environments, theoretically based on negativity bias, revenge effect, and One-Vote Veto effect. A single-blind 2 × 2 within-subject experiment was conducted in the Aachen Workplace Simulation Lab. 23 healthy, mostly young participants experienced room atmospheres with pleasant (0.7 ppm pentyl acetate) and unpleasant (5 ppm 1-butanol) odors at neutral (24 °C) and slightly warm (28.5 °C) temperatures. Standardized questionnaires assessed subjective satisfaction and sensation across sensory domains before and after olfactory adaptation. Modern statistical advancements—including causal inference, adjustment criterion, and Bayesian region of practical equivalence—were leveraged to address existing methodological limitations in multi-domain research. Results revealed cross-modal main effects, with increased warmth reducing olfactory satisfaction. Marginal temperature x odor interactions were found for thermal and overall satisfaction, while other cross-modal effects remained inconclusive. Substantial inter-individual variability was observed in odor valence ratings. These findings highlight the interdependence of thermal and olfactory perception and partially support the notion that negative experiences from one domain can influence another; however, One-Vote Veto effects were not confirmed. The study underscores the need for holistic indoor environmental quality assessments and follow-up multi-domain research. Methodologically, it showcases application of modern statistical tools to improve transparency and rigor in causal human-centric building science. Challenges related to odor selection and concentration manipulation are highlighted as key areas for improvement in related future research. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
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  Data: <i>Copyright of Building & Environment is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.buildenv.2026.114504
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      – Code: eng
        Text: English
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        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Temperature effect
        Type: general
      – SubjectFull: Indoor air quality
        Type: general
      – SubjectFull: Olfactory perception
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      – SubjectFull: Causal inference
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      – SubjectFull: Satisfaction
        Type: general
      – SubjectFull: Perceptual learning
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      – SubjectFull: Bayesian analysis
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              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
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