This paper focuses on a closed-loop supply chain that deals with disruptions in the distribution centers, and optimizes the network in two dimensions of sustainability: economic and environmental. Avenues for cost minimization are designed for the customer by adding the warranty periods, the reworking options, and the incentives for returning the used items. Nondominated solutions via the Reservation Level-driven Tchebycheff procedure are found by appropriate choice of facility establishment and suitable allocation links considering the disruption in the distribution centers. The concept of primary and supporting allocations are introduced to address the disruptions and ensure an uninterrupted flow of service. Environmentally, the model adopts a zero-waste strategy by embedding various return-segmentation policies and a secondary chain. The backward flow depends on the customers' choice of reworking, the validity of the warranty contract, and the quality of the returns. The test results indicate that the manufacturing and distribution centers prefer returns with medium-range quality, while due to the incentives offered for the recyclable items, the customers benefit the most from returning the items with the lowest quality. The tests on probability of disruptions indicate that establishing a minimum number of the manufacturing and/or distribution sites without disruption leads to better overall performance.

Background: Particulate matter air pollution is one of the most important risk factors for cardiovascular and respiratory diseases. By increasing the number of mineral industries in the two past decades, workers in these industries are exposed to pathogenic respirable particulate matter pollutants. Cluster analysis is a multivariate statistical analysis method. Clustering creates groups or classes that the difference between the sub-groups samples is less than the difference between the groups. Therefore, this study assigns the cluster analysis to air sampling data collected from the various units of a tile factory. Methods: In this observational study, sampling from the respiratory zone of 93 workers in a tile and ceramic factory for both respirable and inhalable particles were performed. Sampling of inhalable particle based on NIOSH_0500 protocol and respirable particles based on NIOSH_0600 was conducted. Data were analyzed by both R 3.2.2 software and hierarchical cluster analysis with Ward link. Results: 92.47% of Workers were exposed to respirable particles less than TLV and 39.8% of them were exposed to inhalable particles more than TLV. The maximum average exposure for respirable particles 13.04 mg/m3 and inhalable particles 84.88 mg/m3 is respectively reported for crusher unit. The lowest average exposures to respirable (0.41 mg/m3) and inhalable (min=1.74 mg/m3) particles were observed in the glaze line division. Conclusion: Since the workers are exposed to concentrations more than the threshold limit value of respirable particles, and especially inhalable particles in some units, appropriate control measures must be considered to prevent possible consequences