Conflicts are socio-political pressures that alter wellbeing, social structure, and economic sustenance. However, very limited studies have assessed the long-term impact of conflicts on environmental sustainability. This study investigates the role of internal and external conflicts on ecological footprint in the Middle East and North African countries (MENA) over the period 1995–2016. Here, we test whether the environmental Kuznets curve (EKC) hypothesis is valid for MENA countries during the period of internal and external conflicts—characterized by energy disasters and deteriorating income levels. Using robust econometric tools based on 12 MENA countries, the results show that income growth has negative impact with evidence of inherent heterogeneity across quantile distribution of ecological footprint. However, the positive impact of the square term of income decreases ecological footprint, thus, confirming U-shaped relationship between income and environmental indicator across MENA countries. The results further show that excessive energy consumption is attributed to a rising level of urbanization, while increase in conflicts stimulates environmental degradation. These findings are essential for effective conflict resolution and environmental policies across conflict-prone countries.

Air pollution has caused huge losses of life and property. So, how to choose a practically effective scheme to m.itigate air pollution is of great significance. However, such a selection problem of treatment schemes represents really a group negotiation process of many decision makers (DMs), involving a variety of fuzzy information and preferences. To successfully address this selection problem, this paper proposes a novel group negotiation decision model by jointly employing various approaches, such as hesitant fuzzy set, grey target, grey incidence analysis, and graph model for conflict resolution (GMCR). Then, this model is used to determine the equilibrium schemes for treating air pollution. It is expected that this work provides a method for Chinese government to introduce programs to target air pollution control.

This paper develops a multi-objective conflict resolution simulation-optimization model based on a leader-follower game to resolve conflicts between different water users while optimizing water quality in the river through selective depth water withdrawal from the reservoir. Iran Water Resources Management Company (IWRMC), given the nature of the power distribution in this region, is selected as leader, and agricultural, domestic, and industrial water users are selected as followers. Nash-Harsanyi bargaining theory is used as a nested model in this general framework to model competition between followers. The proposed selective withdrawal approach considers four reservoir outlets, located at 120, 145, 163, and 181 m above sea level. Water withdrawal from multiple outlets addresses reservoir thermal stratification and water quality. Temperature and water quality are simulated based on different possible scenarios of reservoir inflow and release using a calibrated CE-QUAL-W2 model. Five artificial neural network (ANN) surrogate/meta models are then trained and validated based on CE-QUAL-W2 model results for each water quality variable. Subsequently, these validated surrogate models are coupled with the NSGA-II optimization model, which along with the utility functions of different stakeholders, constitute the building blocks of our conflict resolution multi-objective optimization model. Finally, three decision-making methods, namely AHP, PROMETHEE, and TOPSIS, are utilized to choose the superior compromise solution. Our results show that water withdrawal from multiple reservoir outlets ensures optimal water allocation to different stakeholders while satisfying the desired water quality criteria. In this study, the top outlet (181 m) has desirable quality, and the IRWQISC water quality criterion at the top and deepest outlets are highest and lowest, respectively.