This study examines the relationship between Carbon Capture, Utilization, and Storage (CCUS) capacity and carbon emissions in the United States from 1972 to 2022. Using thirteen predictors and various econometric methods, including OLS, Lasso, Ridge, Elastic Net, Generalized Method of Moments, and Seemingly Unrelated Regression, the research aims to provide insights for policymakers to enhance CCUS capabilities and reduce carbon emissions. The Elastic Net model outperformed others in explaining CCUS capacity, while OLS was effective for carbon emissions. The study found that the number of projects and foreign direct investment positively impact CCUS capacity, but CCUS technology level had limited influence. The relationship between CCUS capacity and carbon emissions remained limited. The research highlights the importance of incentivizing projects to increase CCUS capabilities and the critical role of legal and regulatory frameworks in facilitating effective CCUS implementation in the US. It also emphasizes the need for affordable green alternatives to achieve decarbonization goals, noting that CCUS should be viewed as a complementary, rather than a sole, solution for emission reduction. The findings suggest that while CCUS has potential, its current capacity is limited, and its effectiveness in reducing emissions is not fully realized. The study underscores the importance of policy and economic factors in CCUS adoption and the need for robust legal and regulatory frameworks to ensure effective CCUS operations and CO2 storage. The results also indicate that renewable energy can reduce carbon emissions, while CCUS is not yet sufficient to significantly impact emissions due to its limited capacity. The study concludes that CCUS, when widely adopted and cost-effective, could play a significant role in reducing carbon emissions, but current challenges in policy and economics remain. The research contributes to the understanding of CCUS and carbon emissions, highlighting key factors driving or hindering progress in these areas.This study examines the relationship between Carbon Capture, Utilization, and Storage (CCUS) capacity and carbon emissions in the United States from 1972 to 2022. Using thirteen predictors and various econometric methods, including OLS, Lasso, Ridge, Elastic Net, Generalized Method of Moments, and Seemingly Unrelated Regression, the research aims to provide insights for policymakers to enhance CCUS capabilities and reduce carbon emissions. The Elastic Net model outperformed others in explaining CCUS capacity, while OLS was effective for carbon emissions. The study found that the number of projects and foreign direct investment positively impact CCUS capacity, but CCUS technology level had limited influence. The relationship between CCUS capacity and carbon emissions remained limited. The research highlights the importance of incentivizing projects to increase CCUS capabilities and the critical role of legal and regulatory frameworks in facilitating effective CCUS implementation in the US. It also emphasizes the need for affordable green alternatives to achieve decarbonization goals, noting that CCUS should be viewed as a complementary, rather than a sole, solution for emission reduction. The findings suggest that while CCUS has potential, its current capacity is limited, and its effectiveness in reducing emissions is not fully realized. The study underscores the importance of policy and economic factors in CCUS adoption and the need for robust legal and regulatory frameworks to ensure effective CCUS operations and CO2 storage. The results also indicate that renewable energy can reduce carbon emissions, while CCUS is not yet sufficient to significantly impact emissions due to its limited capacity. The study concludes that CCUS, when widely adopted and cost-effective, could play a significant role in reducing carbon emissions, but current challenges in policy and economics remain. The research contributes to the understanding of CCUS and carbon emissions, highlighting key factors driving or hindering progress in these areas.