The consumer use phase of textiles and fashion contributes one-third to the carbon and water footprint, which is the highest for the life cycle assessment technique. However, it is only estimated by questionnaire or estimated data. We carried out a 180-day direct data tracking for three volunteer families with different demographic characteristics. The results show that consumer behaviors significantly influence the carbon and water scarcity footprint. Moreover, the uncertainty between the test data and the energy label estimated data is revealed. For family 1, the energy label-based electricity consumption carbon footprint is 0.57 kgCO₂e, while the empirical data result is 2.79 kgCO₂e. We proposed an improved carbon footprint evaluation method with the correction parameters, which can be estimated using the sampling data from the customers. The results show that applying actual data collection and building a database is necessary to reduce the astonishing errors, making error analysis possible and meaningful.

The family use garment steamers with superheated steam have several advantages but lead natural fiber fabrics whiteness reduction. This study explored the four kinds of natural fiber fabric whiteness reduction both experimentally and theoretically. We first built a temperature controllable 1 atm superheated steam generator, and recorded the whiteness and decrease percentages of cotton, flax, silk and wool fabrics at 150°C, 175°C, and 200°C separately. Then we calculated the monotonically increases thermal diffusivity(α) as a function of fiber volume fraction( ${\phi }_f$), and the α is divided into three regions based on the ${\phi }_f$: average region( ${\phi }_f$ <0.3), transition region(0.3 < ${\phi }_f$ <0.9) and fiber region( ${\phi }_f$ >0.9). The ${\phi }_f$ of studied samples are all in the average region, and the whiteness reduction percentage value sequence is opposite with the α, which are a reflection of the samples average properties, which means the design of superheated fabric steamers should depend on the structures or garment types of fabrics rather than fiber types.