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<p>Household laundry activities generate substantial environmental pressures, particularly through carbon emissions and water-related impacts. In China, pronounced heterogeneity in climate, resource endowment, and socio-technical conditions leads to spatially differentiated laundry practices and environmental outcomes. To systematically capture this complexity, this study develops an integrated analytical framework based on an adapted multi-level perspective (MLP) of socio-technical transition theory, linking landscape-level contextual conditions, regime-level practices, and technological configurations to guide variable selection, empirical modelling, and result interpretation. Using survey data from 2,728 urban residents across China, the study integrates statistical analyses (descriptive statistics, chi-square tests with Cramer’s <i>V</i>, and logistic regression), environmental footprint accounting (carbon, direct water scarcity, and direct eutrophication footprints), and uncertainty and robustness assessments (bootstrap resampling, one-factor-at-a-time sensitivity analysis, and structural robustness tests). Results reveal statistically significant regional heterogeneity in laundry practices and appliance characteristics after controlling for socio-demographic factors, with Cramer’s <i>V</i> values suggesting small to moderate effect sizes. Northeast China, North China, and South Central China emerge as dominant hotspots for carbon emissions (55.716&#xa0;kg CO<sub>2</sub> eq/person), direct water scarcity footprint (3.958 m<sup>3</sup> H<sub>2</sub>O eq/person), and direct eutrophication potential (0.052&#xa0;kg PO<sub>4</sub><sup>3−</sup> eq/person), respectively. Uncertainty and robustness analyses indicate that regional hotspot patterns are robust to sampling variability and parameter perturbations, while structural robustness tests based on regional sample exclusion do not affect the interpretation of spatial patterns, despite minor variations in absolute values. Beyond baseline estimation, scenario analysis demonstrates that environmental outcomes are shaped by interactions between household practices, appliance efficiency, and regional contextual conditions rather than by isolated behavioral or technological drivers. These scenarios are explicitly framed as exploratory analytical tools rather than predictive forecasts. By integrating socio-technical theory with empirical footprint modelling and uncertainty quantification, this study demonstrates how similar household behaviors can generate divergent environmental impacts across regions and provides a robust analytical basis for context-sensitive sustainability strategies.</p>

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An adapted multi-level perspective on urban household laundry practices and regional environmental footprint disparities in China

  • 期刊论文

  • 发表日期：

    2026年8月4日

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  • Yan Luo,
  • Tian Xia,
  • Yimeng Chen,
  • Zhen Du,
  • Ming Tang,
  • Ye Tian,
  • Lei Shi,
  • Junming Zhu,
  • Xiongying Wu,
  • Xuemei Ding

摘要

Household laundry activities generate substantial environmental pressures, particularly through carbon emissions and water-related impacts. In China, pronounced heterogeneity in climate, resource endowment, and socio-technical conditions leads to spatially differentiated laundry practices and environmental outcomes. To systematically capture this complexity, this study develops an integrated analytical framework based on an adapted multi-level perspective (MLP) of socio-technical transition theory, linking landscape-level contextual conditions, regime-level practices, and technological configurations to guide variable selection, empirical modelling, and result interpretation. Using survey data from 2,728 urban residents across China, the study integrates statistical analyses (descriptive statistics, chi-square tests with Cramer’s V, and logistic regression), environmental footprint accounting (carbon, direct water scarcity, and direct eutrophication footprints), and uncertainty and robustness assessments (bootstrap resampling, one-factor-at-a-time sensitivity analysis, and structural robustness tests). Results reveal statistically significant regional heterogeneity in laundry practices and appliance characteristics after controlling for socio-demographic factors, with Cramer’s V values suggesting small to moderate effect sizes. Northeast China, North China, and South Central China emerge as dominant hotspots for carbon emissions (55.716 kg CO2 eq/person), direct water scarcity footprint (3.958 m3 H2O eq/person), and direct eutrophication potential (0.052 kg PO43− eq/person), respectively. Uncertainty and robustness analyses indicate that regional hotspot patterns are robust to sampling variability and parameter perturbations, while structural robustness tests based on regional sample exclusion do not affect the interpretation of spatial patterns, despite minor variations in absolute values. Beyond baseline estimation, scenario analysis demonstrates that environmental outcomes are shaped by interactions between household practices, appliance efficiency, and regional contextual conditions rather than by isolated behavioral or technological drivers. These scenarios are explicitly framed as exploratory analytical tools rather than predictive forecasts. By integrating socio-technical theory with empirical footprint modelling and uncertainty quantification, this study demonstrates how similar household behaviors can generate divergent environmental impacts across regions and provides a robust analytical basis for context-sensitive sustainability strategies.