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Publication Date: 2025
Journal of Urban and Regional Analysis (20674082) 17(2)pp. 177-193
The governance of smart cities is essential for addressing complex urban challenges, while advancing sustainability, and improving the quality of life for citizens. This study explores governance models for smart cities through a hybrid Analytical Hierarchy Process (AHP) – Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) framework, employing expert evaluations to prioritise and rank governance alternatives. The results showed Smart Urban Collaboration as the most effective governance framework, owing to its capacity to foster inclusivity and sustainability. The analysis also underlined the critical role of social inclusion in urban governance, emphasising the importance of involving diverse stakeholders in decision-making processes. Such participatory approaches are crucial for building citizens’ trust and collaboratively developing innovative solutions to urban challenges. Sustainability was identified as the next priority, highlighting the need for such urban governance frameworks to tackle environmental issues like climate change and resource scarcity. Smart cities can move towards sustainable development goals by strategically utilizing technology in stakeholders’ involvement. This work offers practical recommendations and insights for policymakers, urban planners, and academics aimed at creating urban environments that are resilient, inclusive, and sustainable. © 2025 Bucharest University Press. All rights reserved.
Publication Date: 2025
NPJ Ocean Sustainability (2731426X) 4(1)
Blue Carbon Projects conserve and restore degraded BCEs to mitigate climate change1, 2, 3–4, primarily funded through carbon markets2,4, 5–6, thereby delivering climate finance6, 7–8. Our assessment of 81 BCPs globally (2.0 million ha) shows annual emission reductions of 20.4 MtCO₂e/yr, targeting 5.8 GtCO₂e by 2075—≈2% of estimated potential4,9. Between 2014 and 2025, 6.96 million BCCs were issued and 3.65 million retired, mostly transferred from LDCs and developing to developed nations below real value. © The Author(s) 2025.
Publication Date: 2023
Ecological Economics (09218009) 211
Climate-induced projected range shifts of exploited species would lead to a redistribution of stocks. Evaluating the combined ecological and socio-economic consequences of projected changes in Mediterranean fisheries due to climate change has remained largely unexplored. This study aims to identify the most affected stocks by climate change and more vulnerable countries in the region. Thus, we calculated the species specific sensitivity per country for 17 harvested species of significant importance. Then, we evaluated the vulnerability index for Mediterranean countries. Results show that temperate-cold species, i.e., Sprattus sprattus and Solea solea appear the most sensitive species. In contrast, temperate-warm species like the bogue showed the lowest sensitivity. Egypt, Tunisia, and Libya are the most vulnerable countries due to their comparatively high exposure to global warming and low adaptive capacity. At the same time, Slovenia, France, and Croatia have the lowest vulnerability because of their low exposure and sensitivity and remarkably high adaptive capacity. The southern Mediterranean countries would be the most vulnerable to climate-induced effects on marine fisheries. The region seriously needs adequate and adopted on-time adaptation and mitigation policies to lessen potential risks to harvested species and stocks and guarantee the contribution of fisheries to the economy and food security in the long-term. © 2023 Elsevier B.V.
Publication Date: 2023
Frontiers in Climate (26249553) 5
The deep sea (below 200 m depth) is the largest carbon sink on Earth. It hosts abundant biodiversity that underpins the carbon cycle and provides provisioning, supporting, regulating and cultural ecosystem services. There is growing attention to climate-regulating ocean ecosystem services from the scientific, business and political sectors. In this essay we synthesize the unique biophysical, socioeconomic and governance characteristics of the deep sea to critically assess opportunities for deep-sea blue carbon to mitigate climate change. Deep-sea blue carbon consists of carbon fluxes and storage including carbon transferred from the atmosphere by the inorganic and organic carbon pumps to deep water, carbon sequestered in the skeletons and bodies of deep-sea organisms, carbon buried within sediments or captured in carbonate rock. However, mitigating climate change through deep-sea blue carbon enhancement suffers from lack of scientific knowledge and verification, technological limitations, potential environmental impacts, a lack of cooperation and collaboration, and underdeveloped governance. Together, these issues suggest that deep-sea climate change mitigation is limited. Thus, we suggest that a strong focus on blue carbon is too limited a framework for managing the deep sea to contribute to international goals, including the Sustainable Development Goals (SDGs), the Paris Agreement and the post-2020 Biodiversity Goals. Instead, the deep sea can be viewed as a more holistic nature-based solution, including many ecosystem services and biodiversity in addition to climate. Environmental impact assessments (EIAs), area-based management, pollution reduction, moratoria, carbon accounting and fisheries management are tools in international treaties that could help realize benefits from deep-sea, nature-based solutions. Copyright © 2023 Hilmi, Sutherland, Farahmand, Haraldsson, van Doorn, Ernst, Wisz, Claudel Rusin, Elsler and Levin.
Publication Date: 2021
Sustainability (Switzerland) (20711050) 13(19)
The objective of this study is to investigate the impacts of the environmental and socio-economic risks on the fisheries in the Mediterranean region from an economic point of view. A bal-anced panel of 21 Mediterranean countries for 2001–2018 has been estimated by the GLS method, considering heteroskedasticity and correlation among cross sections. The volume of fish landed and landed values have been considered in two models. The results show that increases in sea bottom and surface temperature, H+ ion concentration and salinity threaten the fisheries in the Mediterranean region for the volume of fish landed and that sea surface temperature and salinity negatively influence landed values. In addition, there is an inverse U-shaped relationship between human population and fisheries. Moreover, the Human Development Index (HDI), an indicator of countries’ adaptive capacity, has a positive impact on fisheries and indicates that countries can safeguard fisheries by improving their adaptive capacity. Finally, our results strongly show the risk of climate change for the fisheries in the Mediterranean region and that fisheries are adversely impacted by climate change as well as worsening socio-economic conditions in the absence of adaptation plans. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Publication Date: 2020
Gulf Studies (26624494) 1pp. 19-42
The Paris Agreement has identified climate change mitigation as a goal, aiming to hold “the increase in the global average temperature to well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels” (Paris Agreement, art. 2.1). The Agreement also recognizes that the current need for adaptation necessary to achieve the said goal “is significant and that greater levels of mitigation can reduce the need for additional adaptation efforts, and that greater adaptation needs can involve greater adaptation costs” (UNFCCC in Sendai framework for disaster risk reduction, 2015 Art 7.4). Climate change mitigation and climate-resilient development require energy transition away from fossil fuels to clean and renewable energy sources. Energy transition is happening in most countries, with different motivations and objectives. Adaptation measures, by contrast, are those changes that need to be introduced in response to the global adoption of climate change mitigation. This chapter examines how Kuwait can head toward energy transition and a larger economic diversification following a structural transformation of its economy. The energy transition from fossil fuels to renewables is necessary in order to reduce CO2 emissions and to free up hydrocarbon resources for export. Economic sustainability entails securing alternative sources of revenue to substitute for that generated by oil rents, which would be a solution to the intrinsically unsustainable nature of oil rents and the lack of diversification. Efficiency-enhancing structural change is required to achieve productivity growth in non-energy sectors that are also export-oriented—thereby achieving meaningful diversification. Policy reforms include competition and private sector reform. Moreover, energy pricing reform and revising energy subsidization are required in order to rationalize energy consumption, achieve energy efficiency, and encourage a more diversified growth while reducing greenhouse-gas emissions. © 2020, Springer Nature Singapore Pte Ltd.
Publication Date: 2020
Gulf Studies (26624494) 1pp. 89-109
Climate change is a global issue. According to an IPCC special report (IPCC, Global warming of 1.5 °C. An IPCC special report on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. World Meteorological Organization, Geneva, Switzerland, 32 p, 2018), if global warming is 1.5 °C above pre-industrial levels, this will increase the threat of climate change, challenge sustainable development and increase poverty in the world. All countries must reduce their greenhouse gas (GHG) emissions. The attention paid to countries that produce fossil fuels and export them to the rest of the world is evident in this context. Like other oil-producing countries, KSA faces two challenges for the 2020s: the consequences of the world’s low carbon energy transition and the changes associated with economic diversification and the growth of the low carbon economy at home. The country should diversify its economy and develop sustainable projects, like smart cities and sustainable tourism, in order to achieve the Agenda 30 aims and the UN Sustainable Development Goals. © 2020, Springer Nature Singapore Pte Ltd.
Publication Date: 2014
Iranian Economic Review (10266542) 18(1)pp. 81-101
The economic convergence concept arises from the Solow-Swan growth model. Accordingly, two hypotheses are considered: absolute and conditional convergence. The first implies the convergence of economies towards a steady-state. The second hypothesis is based on the convergence of each economy toward its own steady-state. Indeed, it refers to different structures of economies. In experimental studies, for testing the conditional hypothesis, different determinants are entered in the growth model to capture the differences in structures. However, one coefficient is estimated for β-convergence and one convergence speed is obtained. This paper examines the convergence hypotheses for Asian countries over the period of 1999-2009 using the geographically weighted regression (GWR) approach. GWR provides useful means for dealing with spatial variation in convergence speed. In this way, convergence coefficients can be computed for considered countries. The results show that, speed of convergence varies over different countries. Also, the spatial variation of steady- state incomes is significant. © 2014, University of Teheran. All rights reserved.
Publication Date: 2013
Iranian Economic Review (10266542) 17(1)pp. 69-91
Economic convergence is one of the important topics of new macroeconomics. It refers to tendency of income per capita of countries (regions) to converge to their steady-state value. There are two kinds of convergence: conditional and absolute convergence. This paper examines income convergence between 22 MENA countries during the period of 1970-2003 by using the neoclassical growth model of Barro-Salla-i-Martin for both kinds of convergence. Non-linearity of the underlying relationships, the restrictiveness of assumptions of functional forms and econometric problems in the estimation and application of theoretical models advocate for the use of Artificial Neural Networks (ANN) algorithms. We show that by changing the quantitative tools of analysis and using ANN, the results become more precise. Results show that absolute convergence and conditional convergence are significant but the rate of convergence is low.
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