Abstract

Climate change and global warming are among the most important environmental issues and require sufficient and urgent global action to protect the Earth for future generations. One of the main approaches used to reduce CO2 emissions and mitigate the worst impacts of climate change is carbon capture technology. Carbon capture technologies have the potential to capture carbon from the atmosphere and convert it into fuels that can be used in environmentally friendly energy production. Innovative technologies can increase the potential for carbon capture, which can play an important role in combating climate change. A better understanding of the mechanisms that extract, store and release carbon from the atmosphere will allow us to make more accurate predictions for assessing carbon capture potentials. There have been many efforts by scientists, industry sectors and policy makers in the search for new technologies to reduce greenhouse gas emissions and achieve net zero emissions targets. Research and development work to create new technology involves complex processes and requires a digital system to optimize big data forecasting as well as reduce production time. A mathematical and statistical approach such as machine learning plays an important role in solving research problems, providing fast results and cost-effective tools for predicting big data. Effective policies and international cooperation for carbon capture can increase the potential for carbon capture. New policies and cooperation models can incentivize investment in carbon capture projects, which can increase potential. These new approaches can be used to better understand the potential for carbon capture and develop effective solutions to tackle climate change. However, work in this area is still ongoing and more research and development is needed in the future.

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