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Daily transportation of wastes due to its environmental, financial, and social aspects has been considered a challenging issue in developing countries' municipal solid waste management systems. The location of transfer stations as intermediate nodes in municipal solid waste management network affects optimal collection frequency. A sustainable multi-period and multi-trip vehicle routing problem integrated with relocation models was developed to redesign the intermediate transfer stations and find optimal vehicle routes and the best collection frequency for each municipal solid waste generation point. Regarding the social aspects of a sustainable solid waste management system, an extended social life cycle assessment methodology for redesign and routing operations was developed based on the UNEP guidelines. The social life cycle assessment methodology evaluated the probable social effects of the system throughout the entire life cycle using an iterative policy. In this study, selected impact subcategories and inventory indicators for the routing and redesign system were utilized to quantify the system social score. Besides, the developed model was solved for different problem instances. The results indicated that system social score was affected by collection frequencies decisions, redesign policy, and the number of demand nodes. Furthermore, the model was applied to a real-world case study resulting in a total cost reduction of 66% that occurred by a 86% reduction in weekly traveled distance and a 12% decrease in routing social score., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Location-routing problem is a combination of facility location problem and vehicle routing problem. Numerous logistics problems have been extended to investigate greenhouse issues and costs related to the environmental impact of transportation activities. The green capacitated locating-routing problem (LRP) seeks to find the best places to establish facilities and simultaneously design routes to satisfy customers' stochastic demand with minimum total operating costs and total emitted carbon dioxide. In this paper, features that make the problem more practical are: considering time windows for customers and drivers, assuming city traffic congestion to calculate travel time along the edges, and dealing with capacitated warehouses and vehicles. The main novelty of this study is to combine the mentioned features and consider the problem closer to the real-world case uses. A mixed-integer programming model has been developed and scenario production method is used to solve this stochastic model. Since the problem belongs to the class of NP-hard problems, a combination of the progressive hedging algorithm (PHA) and genetic algorithm (GA) is considered to solve large-scale problems. It is the first time, as per our knowledge, that this combination is implemented on a green capacitated location routing problem (G-CLPR) and resulted in satisfactory solutions. Nondominating sorting genetic algorithm II (NSGA-II) and epsilon constraints methods are used to face with the bi-objective problem. Finally, sensitivity analysis is performed on the problem's input parameters and the efficiency of the proposed method is measured. Comparing the results of the proposed solution approach with those of the exact method indicates that the solution approach is computationally efficient in finding promising solutions., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: Air pollution is a global phenomenon which invariably leads to a serious environmental and health related sequalae. "Black carbon" (BC), a subset of fine particulate matter ≤2.5 μm (PM 2.5 ), is a fossil fuel emission by-product and has more recently been recognized as a major health hazard. The objective of this study is to statistically analyze the BC concentration and its correlation with cardiorespiratory related mortality and to estimate the benefits of BC reduction on the health of the population in the capital city of Tehran., Methods: We analyzed the ambient air BC concentration and its correlation with cardiorespiratory related mortality and conducted health impact assessment of BC in Tehran (Jan 2018-Jan 2019). The data pertaining to BC concentration was obtained from Tehran's four major pollution monitoring stations. The mortality data was obtained from Tehran's cemetery registry. We calculated and analyzed BC concentration statistics including the mean, standard deviation, coefficient of variation, skewness, and kurtosis. We then assessed the cross-correlation and temporal relationship (0-7 days) between the daily mean concentration of BC for the entire city and cardiorespiratory related mortality. The BenMAP software was utilized to estimate the potential reduction in cardiorespiratory related mortality rates if BC concentration is reduced. Three hypothetical scenarios were employed in the analysis, utilizing the BenMAP software: (I) BC concentration was completely removed from the ambient air; (II) BC concentration was eliminated, and the remaining (non-BC portion of) PM 2.5 concentration was reverted to the United States Environmental Protection Agency (EPA)'s standard level (i.e., 35 μg/m 3 ); and (III) The BC emission during the night (22:00 h-6:00 h, when heavy-duty vehicles (HDVs) are allowed to commute in the city) was distributed throughout the whole day. Since the planetary boundary layer during daytime is much higher than that of nighttime, with the same rate of emission, lower concentrations are spread during the whole day., Results: The trend of BC concentration variation revealed a persistently higher emission of BC during the nighttime, which is consistent with the large-scale operation of HDVs during these hours in the city of Tehran. We observed a direct correlation between BC concentration and cardiorespiratory related mortality. Analysis also showed a 1.4-day lag period from the time of exposure to BC polluted air and respiratory related deaths, and 2 days for cardiovascular related deaths. As a result, the reduction in BC has significant beneficial effects in reducing potentially preventable cardiorespiratory related mortality. The aforementioned three scenarios for age groups of 30 and above yielded the following results: (I) 11,369 (126 per 100,000 population), (II) 15,386 (171 per 100,000 population), and (III) 2552 (28 per 100,000 population) potentially preventable all-cause (including cardiorespiratory) related deaths annually., Conclusions: The BC concentration is relatively high in Tehran and HDVs have a major role in emission of this pollutant. A direct correlation between BC concentration and cardiorespiratory related mortality is observed. There are considerable health benefits in reducing BC concentration in this city. Our findings highlight the urgent need to actively curtail emissions of this harmful pollutant. This can be achieved through utilizing control mechanisms such as particulate filters or amending traffic laws., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

The excessive expansion of cities and the consequent increase in urban population, especially in recent years, have led to a significant increase in consumptions and generations of different types of municipal solid waste (MSW). In this research, a robust green location-allocation-inventory problem (LAIP) is investigated to design an efficient MSW management system. Since the exact amount of MSW composition in different regions is not known and is uncertain, robust optimization technique is applied to formulate the problem as a mixed-integer linear programming (MILP) model. The objective is to minimize the total cost including fixed locational costs of collection and processing/disposal facilities, operational costs of facilities, transportation costs, penalty costs of non-collected waste and costs arising from pollution emissions. The validation of the proposed model is performed by different problems based on real-life data in deterministic and uncertain conditions using CPLEX solver of GAMS software. Then, the effects of greenness are evaluated by performing a sensitivity analysis on the parameter of pollution cost. Finally, the concept of robustness worthiness threshold (RWT) under budget constraint is introduced and discussed., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Nowadays, urban solid waste management is one of the most crucial activities in municipalities and their affiliated organizations. It includes the processes of collection, transportation and disposal. These major operations require a large amount of resources and investments, which will always be subject to limitations. In this paper, a chance-constrained programming model based on fuzzy credibility theory is proposed for the multi-trip capacitated arc routing problem to cope with the uncertain nature of waste amount generated in urban areas with the aim of total cost minimization. To deal with the complexity of the problem and solve it efficiently, a hybrid augmented ant colony optimization algorithm is developed based on an improved max-min ant system with an innovative probability function and a simulated annealing algorithm. The performance of hybrid augmented ant colony optimization is enhanced by using the Taguchi parameter design method to adjust the parameters' values optimally. The overall efficiency of the algorithm is evaluated against other similar algorithms using well-known benchmarks. Finally, the applicability of the suggested methodology is tested on a real case study with a sensitivity analysis to evolve the managerial insights and decision aids.

Although rainwater harvesting (RWH) schemes have gradually gained more credibility and popularity in recent times, efficient utilisation and larger scale implementation of multi-purpose RWH are still a challenging task. This paper aims to explore the potential of using smart RWH schemes and their impact on the efficiency improvement in integrated urban water systems (UWS). The smart RWH scheme analysed here is capable of proactively controlling the tank water level to ensure sufficient spare storage is maintained at all times that accommodates the runoff from storm events. The multi-purpose RWH tank can mitigate local floods during rainfall events and supply harvested rainwater to non-potable residential water consumption. Optimal design parameters of the smart RWH scheme are also identified to achieve the best operational performance of the UWS. WaterMet 2 model is used to assess the performance of the UWS with smart RWH schemes. The efficiency of the proposed methodology is demonstrated through modelling a real case of integrated UWS. The results obtained indicate that utilisation of smart RWH with an optimally sized tank, compared to the corresponding conventional RWH, is able to significantly improve the UWS efficiency in terms of mitigation of local flooding and reliability of water supply from harvested rainwater.