Developing a Green GGDP Calculation Model to Predict the Impact of Global Climate Mitigation

In recent years, with global greenhouse gas emissions increasing year on year and the destruction of the natural environment and ecosystems, a climate crisis has arrived upon us, and a global campaign to protect the betterment of humanity seems urgent. As a consequence, a green GDP conversion action was opened up. We simulated the replacement of GDP by green GDP as a key indicator of a country's economic health, integrated global considerations of the expected impacts of climate mitigation. We first choose the GGDP as the basic calculation model. Further, we propose a direct loss cost (M1) and an indirect loss cost (M2) for climate impacts, making improvements to the GGDP calculation model. Further, because M1 and M2 contribute differently to climate impacts, we attribute different weights to each. Finally, we use entropy weighting method for the solution of the weights, the weights for M1 and M2 were found to be 0.5464 and 0.4536 respectively. We first choose CO2 emissions and annual average temperature change as indicators to evaluate the global impact of climate mitigation. Further, we use a improved BP neural network for the training of the model and optimize the threshold and connection weights of the BP neural network based on a genetic algorithm. Finally, temperature changes and CO2 emissions are simulated and forecast for four countries.