Promoting sustainable management of hazardous waste-to-wealth practices: An innovative integrated DPSIR and decision-making framework.

Sustainable valorization of tannery sludge (TS) is vital for achieving several sustainable development goals (SDGs) in the tannery industry. TS is considered a hazardous waste by-product posing a significant environmental challenge. However, TS can be utilized for energy or resource recovery by considering it as biomass and implementing the circular economy (CE) concept. Therefore, this study aims to develop an innovative DPSIR (Driver, Pressure, State, Impact, and Response) framework for promoting sustainable valorization of TS. Further, the study extends to quantify the importance of subjective DPSIR factors by offering interval-valued intuitionistic fuzzy number-based best worst method (IVIFN-BWM), which is relatively new in the literature and able to deal with the uncertainty, inconsistency, imprecise, and vagueness in the decision-making process. The study also investigates the most appropriate TS valorization technologies concerning identified DPSIR factors using a novel IVIFN-combined compromise solution (CoCoSo) approach. This research contributes to the literature by developing a comprehensive solution approach that combines the DPSIR framework, IVIFN-BWM, and IVIFN-CoCoSo method in addressing sustainability and resource recovery challenges for the tannery industry. The research findings highlight the potential of sustainable valorization of TS in reducing the waste amount and promoting sustainability and CE practices in the tannery industry. The findings indicated that response factors 'creation of national-level policies and awareness campaign' and 'facilitating financial support to adopt waste valorization technologies' received the highest priority among other DPSIR factors for managing and fostering sustainable valorization of TS. The IVIFN-CoCoSo analysis confirmed that the most promising TS valorization technology is 'gasification', which is followed by pyrolysis, anaerobic digestion, and incineration. The study's implications extend to policymakers, industrial practitioners, and researchers, who can leverage the research findings to develop more sustainable TS management practices in the tannery industry.

Consumption-based emissions at city level in China and the spatial heterogeneity analysis of the influential factors.

It is of great significance to identify the critical influential factors of pollutant emissions for emission mitigation. However, city disparity implies different priorities for regional mitigation. This study aims to estimate the consumption-based emissions of 309 prefecture-level cities in China based on the multi-region input-output table and the sectoral NOx emission inventory and investigate the emission transfer phenomenon among cities and sectors. In addition, a geographically weighted regression method is used to analyze the spatial heterogeneity in the driving factors of regional consumption-based emissions. The results reveal that the top 10 cities in consumption-based emissions account for 25.2% of emissions and contribute 22.6% to GDP. The consumption-based emissions are mainly driven by local demand (72.79%) at the regional level and by construction activities (94.43%) at the sectoral level. Besides, the results also show the spatial variances in contributions of driving forces to consumption-based emissions. Economic growth has been identified as the most important factor which promotes consumption-based emissions. However, disposable personal income, per capita road area, urbanization, and percentage of tertiary industry GDP are conducive to reduce consumption-based emissions in some cities of China. It could be concluded that policies without consideration of the emissions from a consumption perspective are difficult to achieve effective emission reduction.

Multi-criteria decision making for sustainability assessment of boxboard production: A life cycle perspective considering water consumption, energy consumption, GHG emissions, and internal costs.

Papermaking is a capital-intensive industry that requires a high consumption of plant fibers, energy, and water. Previous sustainability assessments of papermaking industry primarily focused on separate evaluations for multiple criteria without the integration for criteria and could not compare the overall priority of the production alternatives. The life cycle sustainability for the most representative boxboard production is analyzed as a case study in this work. Life cycle water consumption, energy consumption, greenhouse gas emissions, and internal costs are selected as the assessment criteria. The two multi-criteria decision-making methods are applied to integrate the above criteria to obtain the sustainability sequence under different production pathways. When the papermaking enterprises are regarded as decision-makers, the alternative using waste paper as raw material to manufacture boxboard is the most sustainable, following by mixed fiber. The sustainability sequence of the alternatives using wood and straw as raw materials is controversial due to the different calculation models. Changing the proportion of raw materials and the criteria weights might adjust sustainability sequence of the alternatives.

Technology selection for ballast water treatment by multi-stakeholders: A multi-attribute decision analysis approach based on the combined weights and extension theory.

This objective of this study is to develop a generic multi-attribute decision analysis framework for ranking the technologies for ballast water treatment and determine their grades. An evaluation criteria system consisting of eight criteria in four categories was used to evaluate the technologies for ballast water treatment. The Best-Worst method, which is a subjective weighting method and Criteria importance through inter-criteria correlation method, which is an objective weighting method, were combined to determine the weights of the evaluation criteria. The extension theory was employed to prioritize the technologies for ballast water treatment and determine their grades. An illustrative case including four technologies for ballast water treatment, i.e. Alfa Laval (T1), Hyde (T2), Unitor (T3), and NaOH (T4), were studied by the proposed method, and the Hyde (T2) was recognized as the best technology. Sensitivity analysis was also carried to investigate the effects of the combined coefficients and the weights of the evaluation criteria on the final priority order of the four technologies for ballast water treatment. The sum weighted method and the TOPSIS was also employed to rank the four technologies, and the results determined by these two methods are consistent to that determined by the proposed method in this study.

Life cycle cost optimization of biofuel supply chains under uncertainties based on interval linear programming.

The aim of this work was to develop a model for optimizing the life cycle cost of biofuel supply chain under uncertainties. Multiple agriculture zones, multiple transportation modes for the transport of grain and biofuel, multiple biofuel plants, and multiple market centers were considered in this model, and the price of the resources, the yield of grain and the market demands were regarded as interval numbers instead of constants. An interval linear programming was developed, and a method for solving interval linear programming was presented. An illustrative case was studied by the proposed model, and the results showed that the proposed model is feasible for designing biofuel supply chain under uncertainties.