Comparison of decision-making approaches to prioritization of clean air action plans for sustainable development

Background: Clean air action plans have been prepared and are still being implemented in Turkey to control and prevent air pollution, and improve the air quality. The plans reveal a picture of the current situation and available inventory information. However, in order to implement the identified plans in real life, they need to be prioritized. This study aimed to identify and prioritize clean air action plans for Turkey using a framework of both fuzzy and crisp evaluations. Methods: In this study, priorities of the plans were identified and analyzed with a decision-making model. A three-step research methodology was provided. First, literature was reviewed regarding sustainable development and action plans. Second, in order to narrow and specify action plans, the nominal group technique (NGT) was implemented. Finally, fuzzy analytic hierarchy process (AHP) and best-worst method (BWM) surveys were applied to environmental engineers and experts working on sustainable development to prioritize the action plans. Results: It was revealed that heating dimension is considered as the most important criterion with the weight of 0.7469 in fuzzy AHP and 0.758 in BWM. AP1 with a weight of 0.3356 in fuzzy AHP and AP3 with a weight of 0.3289 in BWM were the most important sub-criteria, which are the plans for reducing coal use ranked at the forefront in reducing air pollution. Conclusion: According to the results, there is no significant difference in the priority ranking results. The results of fuzzy AHP and BWM are very similar. For example, traffic criterion has the best performance in both methods in the evaluation of decision makers. In addition, the main and sub-criteria with the lowest priority are the same in these two methods. Keywords: Air pollution, Cities, Decision making, Surveys and questionnaire

A data envelopment analysis based evaluation of sustainable energy generation portfolio scenarios

Generating secure, affordable, and clean energy requires careful evaluation of the costs and associated risks of different energy generation sources. Portfolio optimisation models are commonly used in this regard to help diversify risks associated with generation sources. In recent times, energy policies often require the consideration of the environmental and social effects of such activity. Consequently, sustainability has become a key factor in making energy mix planning decisions. To incorporate sustainability considerations in energy mix planning, the conventional approach has been to add indicators for environmental and social costs to the total generation cost for each available technology in a portfolio optimisation model. However, this approach to developing a sustainable generation mix may not effectively address all dimensions of sustainability. In most cases, the economic dimension is prioritised over social and environmental factors. We examine how various aggregation methods impact the preference among the sources and the optimal portfolio mix and propose aggregation methods that effectively incorporate all sustainability dimensions. We observed that technology ranking based on multiplicative, pairwise interaction, and multilinear aggregation options aligns better with our sustainability goals than additive aggregation. By adopting these methods of aggregation, we were able to include more renewable and clean energy sources in our optimal portfolios

A data envelopment analysis based evaluation of sustainable energy generation portfolio scenarios

Generating secure, affordable, and clean energy requires careful evaluation of the costs and associated risks of different energy generation sources. Portfolio optimisation models are commonly used in this regard to help diversify risks associated with generation sources. In recent times, energy policies often require the consideration of the environmental and social effects of such activity. Consequently, sustainability has become a key factor in making energy mix planning decisions. To incorporate sustainability considerations in energy mix planning, the conventional approach has been to add indicators for environmental and social costs to the total generation cost for each available technology in a portfolio optimisation model. However, this approach to developing a sustainable generation mix may not effectively address all dimensions of sustainability. In most cases, the economic dimension is prioritised over social and environmental factors. We examine how various aggregation methods impact the preference among the sources and the optimal portfolio mix and propose aggregation methods that effectively incorporate all sustainability dimensions. We observed that technology ranking based on multiplicative, pairwise interaction, and multilinear aggregation options aligns better with our sustainability goals than additive aggregation. By adopting these methods of aggregation, we were able to include more renewable and clean energy sources in our optimal portfolios

Hesitant Fuzzy Linguistic Multicriteria Decision-Making Method Based on Generalized Prioritized Aggregation Operator

Based on linguistic term sets and hesitant fuzzy sets, the concept of hesitant fuzzy linguistic sets was introduced. The focus of this paper is the multicriteria decision-making (MCDM) problems in which the criteria are in different priority levels and the criteria values take the form of hesitant fuzzy linguistic numbers (HFLNs). A new approach to solving these problems is proposed, which is based on the generalized prioritized aggregation operator of HFLNs. Firstly, the new operations and comparison method for HFLNs are provided and some linguistic scale functions are applied. Subsequently, two prioritized aggregation operators and a generalized prioritized aggregation operator of HFLNs are developed and applied to MCDM problems. Finally, an illustrative example is given to illustrate the effectiveness and feasibility of the proposed method, which are then compared to the existing approach

A linguistic Neutrosophic Multi-Criteria Group Decision-Making Method to University Human Resource Management

Competition among different universities depends largely on the competition for talent. Talent evaluation and selection is one of the main activities in human resource management (HRM) which is critical for university development. Firstly, linguistic neutrosophic sets (LNSs) are introduced to better express multiple uncertain information during the evaluation procedure. We further merge the power averaging operator with LNSs for information aggregation and propose a LN-power weighted averaging (LNPWA) operator and a LN-power weighted geometric (LNPWG) operator. Then, an extended technique for order preference by similarity to ideal solution (TOPSIS) method is developed to solve a case of university HRM evaluation problem. The main contribution and novelty of the proposed method rely on that it allows the information provided by different decision makers (DMs) to support and reinforce each other which is more consistent with the actual situation of university HRM evaluation. In addition, its effectiveness and advantages over existing methods are verified through sensitivity and comparative analysis. The results show that the proposal is capable in the domain of university HRM evaluation and may contribute to the talent introduction in universities

Sustainability assessment of energy production: A critical review of methods, measures and issues

Sustainable operations of energy production systems have become an increasingly important policy agenda globally because of the massive pressure placed on energy resources needed to support economic development and population growth. Due to the increasing research interest in examining the operational impacts of energy production systems on the society and the environment, this paper critically reviews the academic literature on the clean, affordable and secure supply of energy focussing on methods of assessments, measures of sustainability and emerging issues in the literature. While there have been some surveys on the sustainability of energy production systems they have either tended to focus on one assessment approach or one type of energy generation technology. This study builds on previous studies by providing a broader and comprehensive examination of the literature across generation technologies and assessment methods. A systematic review of 128 scholarly articles covering a 20-year period, ending 2018, and gathered from ProQuest, Scopus, and manual search is conducted. Synthesis and critical evaluation of the reviewed papers highlight a number of research gaps that exist within the sustainable energy production systems research domain. In addition, using mapping and cluster analyses, the paper visually highlights the network of dominant research issues, which emerged from the review

Renewable Energy in the Context of Sustainable Development

Historically, economic development has been strongly correlated with increasing energy use and growth of greenhouse gas (GHG) emissions. Renewable energy (RE) can help decouple that correlation, contributing to sustainable development (SD). In addition, RE offers the opportunity to improve access to modern energy services for the poorest members of society, which is crucial for the achievement of any single of the eight Millennium Development Goals. Theoretical concepts of SD can provide useful frameworks to assess the interactions between SD and RE. SD addresses concerns about relationships between human society and nature. Traditionally, SD has been framed in the three-pillar model—Economy, Ecology, and Society—allowing a schematic categorization of development goals, with the three pillars being interdependent and mutually reinforcing. Within another conceptual framework, SD can be oriented along a continuum between the two paradigms of weak sustainability and strong sustainability. The two paradigms differ in assumptions about the substitutability of natural and human-made capital. RE can contribute to the development goals of the three-pillar model and can be assessed in terms of both weak and strong SD, since RE utilization is defined as sustaining natural capital as long as its resource use does not reduce the potential for future harvest. The relationship between RE and SD can be viewed as a hierarchy of goals and constraints that involve both global and regional or local considerations. Though the exact contribution of RE to SD has to be evaluated in a country specifi c context, RE offers the opportunity to contribute to a number of important SD goals: (1) social and economic development; (2) energy access; (3) energy security; (4) climate change mitigation and the reduction of environmental and health impacts. The mitigation of dangerous anthropogenic climate change is seen as one strong driving force behind the increased use of RE worldwide. The chapter provides an overview of the scientific literature on the relationship between these four SD goals and RE and, at times, fossil and nuclear energy technologies. The assessments are based on different methodological tools, including bottom-up indicators derived from attributional lifecycle assessments (LCA) or energy statistics, dynamic integrated modelling approaches, and qualitative analyses. Countries at different levels of development have different incentives and socioeconomic SD goals to advance RE. The creation of employment opportunities and actively promoting structural change in the economy are seen, especially in industrialized countries, as goals that support the promotion of RE. However, the associated costs are a major factor determining the desirability of RE to meet increasing energy demand and concerns have been voiced that increased energy prices might endanger industrializing countries’ development prospects; this underlines the need for a concomitant discussion about the details of an international burden-sharing regime. Still, decentralized grids based on RE have expanded and already improved energy access in developing countries. Under favorable conditions, cost savings in comparison to non-RE use exist, in particular in remote areas and in poor rural areas lacking centralized energy access. In addition, non-electrical RE technologies offer opportunities for modernization of energy services, for example, using solar energy for water heating and crop drying, biofuels for transportation, biogas and modern biomass for heating, cooling, cooking and lighting, and wind for water pumping. RE deployment can contribute to energy security by diversifying energy sources and diminishing dependence on a limited number of suppliers, therefore reducing the economy’s vulnerability to price volatility. Many developing countries specifically link energy access and security issues to include stability and reliability of local supply in their definition of energy security. Supporting the SD goal to mitigate environmental impacts from energy systems, RE technologies can provide important benefits compared to fossil fuels, in particular regarding GHG emissions. Maximizing these benefits often depends on the specific technology, management, and site characteristics associated with each RE project, especially with respect to land use change (LUC) impacts. Lifecycle assessments for electricity generation indicate that GHG emissions from RE technologies are, in general, considerably lower than those associated with fossil fuel options, and in a range of conditions, less than fossil fuels employing carbon capture and storage (CCS). The maximum estimate for concentrating solar power (CSP), geothermal, hydropower, ocean and wind energy is less than or equal to 100 g CO2eq/kWh, and median values for all RE range from 4 to 46 g CO2eq/kWh. The GHG balances of bioenergy production, however, have considerable uncertainties, mostly related to land management and LUC. Excluding LUC, most bioenergy systems reduce GHG emissions compared to fossil-fueled systems and can lead to avoided GHG emissions from residues and wastes in landfill disposals and co-products; the combination of bioenergy with CCS may provide for further reductions. For transport fuels, some first-generation biofuels result in relatively modest GHG mitigation potential, while most next-generation biofuels could provide greater climate benefits. To optimize benefits from bioenergy production, it is critical to reduce uncertainties and to consider ways to mitigate the risk of bioenergy-induced LUC. RE technologies can also offer benefits with respect to air pollution and health. Non-combustion-based RE power generation technologies have the potential to significantly reduce local and regional air pollution and lower associated health impacts compared to fossil-based power generation. Impacts on water and biodiversity, however, depend on local conditions. In areas where water scarcity is already a concern, non-thermal RE technologies or thermal RE technologies using dry cooling can provide energy services without additional stress on water resources. Conventional water-cooled thermal power plants may be especially vulnerable to conditions of water scarcity and climate change. Hydropower and some bioenergy systems are dependent on water availability, and can either increase competition or mitigate water scarcity. RE specific impacts on biodiversity may be positive or negative; the degree of these impacts will be determined by site-specific conditions. Accident risks of RE technologies are not negligible, but the technologies’ often decentralized structure strongly limits the potential for disastrous consequences in terms of fatalities. However, dams associated with some hydropower projects may create a specific risk depending on site-specific factors. The scenario literature that describes global mitigation pathways for RE deployment can provide some insights into associated SD implications. Putting an upper limit on future GHG emissions results in welfare losses (usually measured as gross domestic product or consumption foregone), disregarding the costs of climate change impacts. These welfare losses are based on assumptions about the availability and costs of mitigation technologies and increase when the availability of technological alternatives for constraining GHGs, for example, RE technologies, is limited. Scenario analyses show that developing countries are likely to see most of the expansion of RE production. Increasing energy access is not necessarily beneficial for all aspects of SD, as a shift to modern energy away from, for example, traditional biomass could simply be a shift to fossil fuels. In general, available scenario analyses highlight the role of policies and finance for increased energy access, even though forced shifts to RE that would provide access to modern energy services could negatively affect household budgets. To the extent that RE deployment in mitigation scenarios contributes to diversifying the energy portfolio, it has the potential to enhance energy security by making the energy system less susceptible to (sudden) energy supply disruption. In scenarios, this role of RE will vary with the energy form. With appropriate carbon mitigation policies in place, electricity generation can be relatively easily decarbonized through RE sources that have the potential to replace concentrated and increasingly scarce fossil fuels in the building and industry sectors. By contrast, the demand for liquid fuels in the transport sector remains inelastic if no technological breakthrough can be achieved. Therefore oil and related energy security concerns are likely to continue to play a role in the future global energy system; as compared to today these will be seen more prominently in developing countries. In order to take account of environmental and health impacts from energy systems, several models have included explicit representation of these, such as sulphate pollution. Some scenario results show that climate policy can help drive improvements in local air pollution (i.e., particulate matter), but air pollution reduction policies alone do not necessarily drive reductions in GHG emissions. Another implication of some potential energy trajectories is the possible diversion of land to support biofuel production. Scenario results have pointed at the possibility that climate policy could drive widespread deforestation if not accompanied by other policy measures, with land use being shifted to bioenergy crops with possibly adverse SD implications, including GHG emissions. 712 Renewable Energy in the Context of Sustainable Development Chapter 9 The integration of RE policies and measures in SD strategies at various levels can help overcome existing barriers and create opportunities for RE deployment in line with meeting SD goals. In the context of SD, barriers continue to impede RE deployment. Besides market-related and economic barriers, those barriers intrinsically linked to societal and personal values and norms will fundamentally affect the perception and acceptance of RE technologies and related deployment impacts by individuals, groups and societies. Dedicated communication efforts are therefore a crucial component of any transformation strategy and local SD initiatives can play an important role in this context. At international and national levels, strategies should include: the removal of mechanisms that are perceived to work against SD; mechanisms for SD that internalize environmental and social externalities; and RE strategies that support low-carbon, green and sustainable development including leapfrogging. The assessment has shown that RE can contribute to SD to varying degrees; more interdisciplinary research is needed to close existing knowledge gaps. While benefi ts with respect to reduced environmental and health impacts may appear more clear-cut, the exact contribution to, for example, social and economic development is more ambiguous. In order to improve the knowledge regarding the interrelations between SD and RE and to fi nd answers to the question of an effective, economically effi cient and socially acceptable transformation of the energy system, a much closer integration of insights from social, natural and economic sciences (e.g., through risk analysis approaches), refl ecting the different (especially intertemporal, spatial and intra-generational) dimensions of sustainability, is required. So far, the knowledge base is often limited to very narrow views from specifi c branches of research, which do not fully account for the complexity of the issue