Blue carbon has made significant contributions to climate change adaptation and mitigation while assisting in achieving co-benefits such as aquaculture development and coastal restoration, winning international recognition. Climate change mitigation and co-benefits from blue carbon ecosystems are highlighted in the recent Intergovernmental Panel on Climate Change Special Report on Ocean and Cryosphere in a Changing Climate. Its diverse nature has resulted in unprecedented collaboration across disciplines, with conservationists, academics, and politicians working together to achieve common goals such as climate change mitigation and adaptation, which need proper policy regulations, funding, and multi-prong and multi-dimensional strategies to deal with. An overview of blue carbon habitats such as seagrass beds, mangrove forests, and salt marshes, the critical role of blue carbon ecosystems in mitigating plastic/micro-plastic pollution, as well as the utilization of the above-mentioned blue carbon resources for biofuel production, are critically presented in this research. It also highlights the concerns about blue carbon habitats. Identifying and addressing these issues might help preserve and enhance the ocean’s ability to store carbon and combat climate change and mitigate plastic/micro-plastic pollution. Checking out their role in carbon sequestration and how they act as the major carbon sinks of the world are integral parts of this study. In light of the global frameworks for blue carbon and the inclusion of microalgae in blue carbon, blue carbon ecosystems must be protected and restored as part of carbon stock conservation efforts and the mitigation of plastic/micro-plastic pollution. When compared to the ecosystem services offered by terrestrial ecosystems, the ecosystem services provided by coastal ecosystems, such as the sequestration of carbon, the production of biofuels, and the remediation of pollution, among other things, are enormous. The primary purpose of this research is to bring awareness to the extensive range of beneficial effects that can be traced back to ecosystems found in coastal environments.

In marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types of ships. Most traditional statistical methods do not consider these factors when predicting marine vessel fuel consumption. With technological development, different statistical models have been developed for estimating fuel consumption patterns based on ship data. Artificial Neural Networks (ANN) are some of the most effective artificial methods for modelling and validating marine vessel fuel consumption. The application of ANN in maritime transport improves the accuracy of the regression models developed for analysing interactive relationships between various factors. The present review sheds light on consolidating the works carried out in predicting ship fuel consumption using ANN, with an emphasis on topics such as ANN structure, application and prediction algorithms. Future research directions are also proposed and the present review can be a benchmark for mathematical modelling of ship fuel consumption using ANN.