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Experts have been searching for ways to mitigate the impacts of climate change on resources since the early 20th century. In response, the World Economic Forum introduced the concept of a “nexus”, which involves the simultaneous, systematic collaboration of multiple individuals or sectors, such as water, energy, and food, in order to create an integrated approach to reducing resource scarcity through a multi-disciplinary framework. In contrast, a circular economy (CE) involves restructuring material flows from a linear economic system and closing the loop on resource exploitation. Both the nexus and CE have been developed to address the overexploitation of resources, but they also contribute to the Sustainable Development Goals (SDGs) and decouple carbon emissions from economic growth. This study explores the potential of combining the nexus and CE to pursue the SDGs on a global scale. Our findings reveal significant research gaps and policy implementation challenges in developing countries, as well as the potential consequences of adopting integrative scenarios. Finally, we propose a system dynamics model as a way to address the difficulties of coupling policies and to better understand the interdependencies between different parts of the economy.

The Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6) forecasts a sea level rise (SLR) of up to 2 m by 2100, which poses significant risks to regional geomorphology. As a country with a rapidly developing economy and substantial population, Bangladesh confronts unique challenges due to its extensive floodplains and 720 km-long Bay of Bengal coastline. This study uses nighttime light data to investigate the demographic repercussions and potential disruptions to economic clusters arising from land inundation attributable to SLR in the Bay of Bengal. By using geographical information system (GIS)-based bathtub modeling, this research scrutinizes potential risk zones under three selected shared socioeconomic pathway (SSP) scenarios. The analysis anticipates that between 0.8 and 2.8 thousand km2 of land may be inundated according to the present elevation profile, affecting 0.5–2.8 million people in Bangladesh by 2150. Moreover, artificial neural network (ANN)-based cellular automata modeling is used to determine economic clusters at risk from SLR impacts. These findings emphasize the urgency for land planners to incorporate modeling and sea inundation projections to tackle the inherent uncertainty in SLR estimations and devise effective coastal flooding mitigation strategies. This study provides valuable insights for policy development and long-term planning in coastal regions, especially for areas with a limited availability of relevant data.

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The Red Sea, lying between Asia and Africa, is a significant eco-region and the habitat of many marine species. It is an essential route for marine transportation, and it also provides many ecosystem services. Therefore, assessing the spatial and temporal distributions of air quality parameters over the Red Sea and assess temporal trends is important. This study investigated observations of multiple satellites to collect different meteorological and tropospheric columns of aerosols, trace gas including carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3), and meteorological data. The tropospheric columns of trace gases and aerosol index exhibit seasonal and regional characteristics over the Red Sea. The correlation coefficient for air pollutants (NO2, SO2, and O3) and meteorological parameters showed a positive medium and low correlation, whereas a negative correlation was found between O3, Aerosol Index (AI), and wind speed. The back trajectory transport of air mass component using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model showed long-range trajectory pattern. AI, trace gases concentrations, and meteorological data were investigated through Principal Component Analysis (PCA) with varimax rotation to find a discerning relationship and co-variance between air pollutants and meteorological data. This showed a relationship between meteorological data and CO and O3. Although the satellite observations have some inherent limitations compared to in-situ measurements, this study provides an overall landscape of air pollution over the Red Sea, which will benefit policymakers and researchers.