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Green finance (GF) is a vital strategy implemented by China to minimize carbon emissions to achieve targets of carbon peak and carbon neutrality. Thus, the objective of this study is to reduce carbon emissions by developing green finance practices in China. This study identifies, evaluates, and ranks the factors and sub-factors of green finance because it is the core issue for sustainable development. In this regard, this study utilizes the Delphi and fuzzy Analytical Hierarchy Process (FAHP) method to analyze the main factors and sub-factors of green finance. The Delphi method finalizes the 6 factors and 26 sub-factors after a thorough investigation. The FAHP method was used to assess and rank the identified factors and sub-factors of green finance. The findings show that the political (POF) is the most crucial factor of green finance in the Chinese economy. The economic (ECF) and environmental (ENF) factors are ranked second and third important factors. The further results of the FAHP reveal that ecological and political identification (POF1), political stability (POF3), and climate commitments (POF2) are the top-ranked sub-factors of green finance. The results specify that green finance development is a very crucial strategy to minimize carbon emissions.

The growing environmental, economic, and social problems have forced governments and policymakers to ensure a sustainable energy future by deploying renewable energy technologies. However, the various barriers impede the development of renewable energy technologies. Therefore, this study identifies the seven-renewable energy barriers and twenty-nine sub-barriers, which obstruct the development of renewable energy technologies in Pakistan. Then, this study proposes various strategies to overcome these renewable energy barriers. First, the Analytical Hierarchy Process method assesses and prioritizes renewable energy barriers and sub-barriers. Then, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution method evaluates the strategies for sustainable implementation of renewable energy technologies. The results of the AHP method reveal that “Economic & Financial,” “Political & Policy,” and “Market” are ranked as the most critical barriers in the deployment of renewable energy technologies. Besides, the results of the Fuzzy TOPSIS method indicate that “Capital Subsidies,” “Feed-in Tariffs,” and “Direct, Enabling, & Integrating Policies,” are the most feasible strategies to overcome these barriers for the successful implementation of renewable energy technologies in Pakistan. This study shall assist the governments and policymakers in focusing their future efforts in deploying renewable energy technologies for sustainable energy planning and development.

The transition to a green economy for any country is crucial for the sustainability development of the economy, environment, society, and governance (EESG). A green economy is a sustainable approach to combating climate change and promoting sustainable development through the adoption of sustainable energy. This research utilizes the Delphi and fuzzy analytical hierarchy process (AHP) methodologies to assess and rank the EESG criteria and policy options for transitions to a green economy. The factors and policy choices are identified using the Delphi approach for further analysis. These factors and policy alternatives for switching to a green economy for sustainable development are determined using the fuzzy AHP technique. According to the fuzzy AHP approach, environmental, social, and economic factors are best suited for green economy transitions. The findings also show that the most crucial policy options for the switch to a green economy are research and development, carbon pricing, and renewable energy targets. The findings are useful to guide the creation of policies and the selection of options for the implementation of a green economy. Finally, the conclusion can guide actions to combat climate change and develop a sustainable energy future.

China has become a global leader in green infrastructure finance, investing heavily in renewable energy, sustainable transportation, and green buildings. However, there are multiple risks and challenges that impede the development of green infrastructure finance. Thus, this study analyzes and prioritizes the risks associated with green infrastructure finance in China and proposes policy plans to mitigate these risks. A Fuzzy analytical hierarchy process (AHP) is used to identify the main risks associated with green infrastructure finance. The main risks are further decomposed into sub-risks. After, the Fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is used to prioritize the key policy plans to mitigate risks and sub-risks. The results of Fuzzy AHP show that policy and regulations are the most significant risk associated with green infrastructure finance in China, followed by financial risks, and technical risks. The results of Fuzzy VIKOR reveal that increasing the availability of financing options is the most crucial policy plan to mitigate the risks and sub-risks for green infrastructure finance. The developed standardized technical guidelines and procedures and a legal and regulatory framework are ranked second and third are the most effective and feasible policy plans.

One of the challenging tasks for governments is to curtail the production and consumption of single-use plastic bags. Despite multiple advantages of plastic and its ubiquity, the environmental damage of single-use plastic bags is irreversible. However, policy intervention by the governments is also a need of the time to reduce its production and consumption. This study provides a strategic analysis of government policy options regarding the ban on single-use plastic production in Pakistan. A game-theoretic model is developed to examine the behavior of plastic bag producers vis-a-vis the government’s climate change policy. The study concludes that game theory is very effective in analyzing the efficient promulgation and productive implementation of environmental management policy regarding banning single-use plastic in Pakistan.

The historical megacities act as a catalyst for sustainable economic development. But the rampant urbanization and demand for the development of mass-transit infrastructure have put pressure on natural environment and heritage scape. Collaborative urban planning is essential especially in culturally and archaeologically rich cities. Megaprojects such as mass-transit systems, especially in developing countries, normally are encouraged for political point scoring. But the choices of the mod of mass-transit systems, their route selection, design and vertical alignment may have a devastating impact on cultural and historical heritage leading to serious conflicts during execution of mass-transit plans. This study employs system engineering decision analysis techniques to resolve urban planning issues of heritage sustainability while analysing metro-heritage conflict in Lahore. Realizing the fact that the attitude(s) of the Decision Makers (DMs) play important role in the decision–decision making, the authors use the attitudes of the DMs based on options in Graph Model for Conflict Resolution (GMCR) to resolve the metro-heritage conflict.

This research investigates the dynamic interactive associations among sustainable investment in the energy sector, air pollution, and sustainable development. To this end, it employs a “one-step” system-generalized method of moments (GMM) and “one-step” differential-GMM estimators, covering the period between 1996 and 2017. In this context, it utilizes the simultaneous equations of the dynamic panel data model for panel data of 27 Chinese provinces and municipalities. We have developed a new model of sustainable development, which incorporates sustainable investment in the energy sector and air pollution to offer a robust theoretical foundation for considering the underlying relations. The system-GMM estimator is used for the full data set; however, differential-GMM is utilized for the subsets of data, in order to tackle the small sample bias problem. The empirical outcomes provide several vital insights in that they yield mixed findings for the aggregated sample and subsets of data. For example, a two-way causal relationship occurs for all the panels, except the central part (medium development regions), between sustainable investment in the energy sector and sustainable development. Contrary to this, causality runs from air pollution to sustainable investment in the energy sector in a full data set and the central part (medium dev.). Nevertheless, the opposite is true in the case of the eastern part (most developed regions) of China. Still, the same relationship runs in either direction in the case of the western part (least developed regions). On the other way around, the feedback hypothesis of causality is confirmed, across all the samples, between air pollution and sustainable development. Hence, sustainable development and air pollution are overwhelmingly interdependent, in the country as well as the province and municipality level of the Chinese economy.

The establishment of Special Economic Zones (SEZs) is a lengthy, expensive, and long-term orientated endeavor. Proper selection of SEZs is indispensable to meet the objectives of export-led growth and value up-gradation. Consideration of sustainability issues in such planning under the Zone 3.0 paradigm is critical to achieve Sustainable Development Goals (SDGs) by 2030. Multiple key factors such as location, linkages, labor force, suitability of industries, incentives and facilitation, and market orientation are important in decision-making process of establishing SEZs. Furthermore, environmental conditions and resource availability need to be considered in the planning and policy making processes to keep symmetry in the natural environment and ecosystem of the areas under consideration for SEZs. The present study uses Multi-Criteria Decision Analysis (MCDA) methods in the perspectives of green industrial zone planning and development in Pakistan under the flagship project of China-Pakistan Economic Corridor (CPEC) of China&rsquo, s Belt and Road Initiative (BRI). This research uses Delphi method, Analytical Hierarchy Process (AHP), and the Fuzzy Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). The Delphi method has been used to identify the main criteria, sub-criteria, and their weights for 3 SEZs under consideration. The results of AHP analysis unfolded that the majority of the experts believe the location and land aspect is the most pivotal criteria in setting SEZs followed by linkages, subsidies, and facilities criteria. Finally, the results of Fuzzy VIKOR analysis considering environmental sustainability reveals that Faisalabad SEZ is the best suited under given criteria and sub-criteria.

Pakistan has an abundant solar power potential which can be effectively utilized for the electricity generation. There are various sites across the country which have sufficient solar irradiation across the year, and thus, suitable for the installation of solar photovoltaic (PV) power projects. This study, therefore, aims to undertake research on the establishment of solar power project site selection in Pakistan. In this context, 14 promising cities of Pakistan are considered as alternatives and studied in terms of economic, environmental, social, location, climate, and orography criteria and further supplemented with 20 sub-criteria. Initially, the analytical hierarchy process (AHP) method has been used to prioritize each of the main criteria and sub-criteria. Later, fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (F-VIKOR) method has been employed to prioritize the 14 alternatives. The present investigation reveals that Khuzdar (C2), Badin (C3), and Mastung (C7) are the most suitable cities for the installation of solar PV power projects in Pakistan. Finally, the outcome of the sensitivity analysis revealed that obtained results are reliable and robust for the installation of solar PV power projects in Pakistan. This study shall assist government, energy planners, and policymakers in making cities sustainable by establishing solar power projects in Pakistan.

In the wake of Paris agreement, global economies have been putting their full efforts in mitigation and adaption to limit the global temperature within 2 °C higher than the pre-industrial level. Redirection of investment flows to renewable energy technologies (RETs) is paramount to achieve the goals set in global climate agreement. The Turkish government is determined to attract investment in RETs for cleaner energy production and sustainable socio-economic development in Turkey. However, it is very challenging to substitute environmentally harmful traditional energy systems with renewable energy production and supply. Investing in and developing renewable energy projects (REPs) are posed to various inherent risks. Assessment and analysis of risk factors of renewable energy investments (REIs) are indispensable for a practical and profound policy guideline for mitigation. This study provides a Multi-Criteria Decision Methodology (MCDM) based three-stage decision framework to assess and examine the risk factors of REIs in Turkey. The first stage is the identification of risk factors of REI using the Delphi method. The second stage is the assessment of identified risk factors of REI by using the Analytical Hierarchy Process (AHP). The third stage is the evaluation and prioritization of strategies to overcome risk factors of REI projects by using Fuzzy Weighted Aggregated Sum Product Assessment (FWASPAS). The Delphi method unveiled 6 major risk factors with 23 sub-risk factors. Results of AHP analysis unfolded economic & business risk as a major risk factor. The FWASPAS analysis concluded a comprehensive and explicit explanation of the RET choices to be the most suitable of six strategies to deal with the investment risk factors for sustainable development in Turkey.

The world is facing the observable and direct impacts of climate change in the shape of extreme weather events, irregular precipitation, glacial melt, sea-level rise, an asymmetric average temperature trends, higher oceanic temperatures, damage to natural ecosystems, and biodiversity. In 2015, collective wisdom stirred the global community to agree upon two unprecedented milestones in recent human history—the Paris agreement and sustainable development goals (SDGs). The twin global agreements set a platform for collective efforts to secure socio-economic and climatic sustainability. Pakistan also joined the board to put forth policy interventions for the mitigation and adaption of climate change risks to maintain symmetry between the environmental quality and economic development. The government of Pakistan (GOP) formulated the National Climate Change Policy (NCCP (2012)) and passed the Pakistan Climate Change Act (PCCA (2017)) to provide an impetus for the implementation of the NCCP. Yet, an appropriate assessment and prioritization of the objectives of the NCCP are indispensable for productive and effective policies to achieve the targets. This study serves this purpose by prioritizing the climate change policy objectives (CCPOs) based on symmetric principles, i.e., energy, transport, urban and town planning, industry, and agriculture as criteria, with 17 sub-criteria in total. The fuzzy analytical hierarchy process (AHP) results show that the energy sector is the most pivotal while implementing the NCCP. Energy production is the most critical area that needs mitigation policy intervention for shifting the energy mix of the economy from high-carbon to low-carbon energy. The fuzzy AHP analysis further revealed the railway, population and urbanization, air pollution, crop growing practices and techniques as the most important related to transport, urban planning, industry, and agriculture sub-criteria, respectively. The fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis showed the ranking of the CCPOs from high to low through the integration of policies, institutional capacity building, water security, natural resource management, natural disaster management, environmental financial structure development, and social sector development. The findings of the present research would be helpful for experts and policymakers to re-examine the NCCP and put forth action plans to achieve sustainable climate and SDGs.

Global human pollutant activities have raised greenhouse gas (GHG) emissions, which have directly affected the climate. Fossil fuel-based energy has brought a negative impact on the environment and is considered one of the largest sources of GHG emissions. It is envisaged that GHG emissions will increase in the future due to rapid population growth and industrialization. Thus, it is imperative to mitigate climate variability and reduce GHGs by adopting renewable energy (RE) sources for electricity generation. In this regard, the multi-criteria decision analysis (MCDA) process would serve the purpose of framing out energy policy to analyze these environmentally friendly energy sources. This study uses an integrated decision methodology&mdash, a combination of Delphi, fuzzy analytical hierarchy process (FAHP), and the fuzzy weighted aggregated sum product assessment (FWASPAS)&mdash, for the adoption of RE sources for electricity generation in Turkey. Initially, the study identified five main criteria and seventeen sub-criteria using the Delphi method. Then, the FAHP method was used to evaluate and rank the main criteria and sub-criteria. Finally, the FWASPAS method was used to assess and prioritize five major RE sources for electricity generation. The FAHP analysis indicated that political criteria are the most influential, followed by economic and technical criteria. Further, the FWASPAS method revealed that wind energy is the most significant option for electricity generation. This decision-making process can help the energy planners to utilize RE sources for sustainable development.

Pakistan is facing a severe energy crisis since the last two decades, and yet the government has not been able to overcome this problem. Therefore, the various renewable energy resources of Sindh and Baluchistan province has been assessed to diversify the electricity generation from fossil fuels to renewable energy. In the study, Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis has been employed to assess the internal and external factors which affect the renewable energy technologies in Sindh and Baluchistan province. Then, the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) method is used from the multi-perspective approach (i.e., economic, environmental, technical, and socio-political criteria). Therefore in the study, four criteria, seventeen sub-criteria and three renewable energy resources (i.e., solar, wind, and biomass) have been assessed as alternatives in the decision model. It is identified that economic and socio-political are the two most important criteria. Further results reveal that wind has ample potential to generate electricity in both (Sindh and Baluchistan) provinces, whereas solar and biomass energy ranked second and third, respectively. It is, therefore, suggested that the government should exploit renewable resources to mitigate the current energy crisis and increase energy security for sustainable development of the country.