Desirability Function Approach to Response Surface Optimization Analysis of Atmospheric Carbon Dioxide CO2 Emissions in Africa
The continuous growing worlds’ impact of climate change (global warming), including frequent natural disasters such as earthquakes, wildfires, etc.; rising food insecurity, infectious diseases, etc.; among others, causing economic, political, and civil unrest cannot be downplayed. Carbon dioxide (CO2) is the most significant contributor to climate change, mainly generate through human-induced industrial and techno logical advancement activities. Africa is most vulnerable to the impact of climate change in the world. Hence, any effort to combat climate change in Africa will be an outstanding achievement towards mitigating the excessive effect of climate change globally. We proposed a surface response optimization method to optimize (mini mize) the CO2 emissions in Africa. We utilized the desirability function approach to obtain the optimum value of the risk factors that minimize Africa’s CO2 emissions. The minimum value of the CO2 was obtained along with a 95% confidence region. Also, the bivariate interaction effect of the risk factors on the CO2 was obtained. The optimization process is well-validated to satisfies the necessary conditions, achieving a desirability function of 0.99. The proposed method provides a robust mitigating approach towards combating CO2 emission, limiting the impact of climate change in Africa and its impact on the world. The subject of essential findings is based on the very high quality of a predictive real data-driven statistical model developed by the authors that identify the significant risk factors and interactions that produce CO2 emissions in the atmosphere.
