Abstract:With the increasing environmental awareness, apparel manufacturers have begun to consider environmental issues in supplier evaluation and selection. It is crucial to assess suppliers based on their environmental performance along with other criteria for supplier selection. This paper addresses the green supplier evaluation and selection problem in global apparel manufacturing by developing a methodological framework for green supplier evaluation and selection based on the triple bottom line principle and a fuzzy multi-criteria decision-making (MCDM) model. First, a green supplier evaluation criteria hierarchy based on the triple bottom line principle is established based on comprehensive literature review, on-site investigation and policy analysis. Then, a fuzzy MCDM model is presented to evaluate and select the best material supplier. Finally, a sensitivity analysis is conducted to verify the effectiveness of the proposed framework. Results show that the proposed framework can handle green supplier evaluation and selection in apparel manufacturing effectively.

Municipal solid waste (MSW) incineration has developed rapidly in China. However, the air pollution-related health risks attributable to MSW incinerators are still far from known. In this context, an MSW incineration emission inventory was compiled using plant-level activity data and localized emission factors. Subsequently, Gaussian Plume Model and Risk Quotients Model were utilized to calculate the spatialized hazard index (HI) and carcinogenic risk (CR). Altogether, 76449 tons (t) of NO X , 25725 t of SO 2 , 16937 t of CO, 9279 t of HCl, 5629 t of particulate matter, 33 t of Cr, 33 t of Pb, 20 t of Hg, 6 t of Cd, 4 t of Ni, 0.4 t of As, and 94 gtoxic equivalent quantity of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans were emitted in 2015. The national average HI was 1.88 × 10 −2 , which was far lower than the acceptable level (HI ≤ 1). However, the national average CR was 5.71 × 10 −6 , which was approximately five times higher than the acceptable level (CR ≤ 1 × 10 −6 ). The spatial heterogeneity of health risks was observed. The results enrich spatial dimensions of prior estimates and provide policy implications from the aspects of accelerating technology upgrades, strengthening emission standards, optimizing site selection and enhancing risk communication.

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