The carbon footprint of household clothing washing in Shanghai during winter and spring based on empirical data.

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. [ABSTRACT FROM AUTHOR]