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Traditional GDP accounting only pursues the development of economic aggregate, ignoring the loss of energy resources and the destruction of natural environment, thus triggering a new upsurge of green GDP research in the theoretical circle. Compared with traditional GDP, green GDP is a more sustainable economic evaluation index, considering resource cost and environmental cost when calculating national economy. Based on the internationally accepted green Gross Domestic Product (GGDP) calculation method and scholars' research, a new GGDP calculation model is proposed in this paper, which is mainly divided into two parts: natural resource loss and environmental pollution loss, which are respectively divided into two primary factors. The portfolio of sub-criteria reflecting sustainable development capacity was reduced to 13 factors. Principal component analysis was used to find out the representative principal factors. On this basis, the relationship between the main factors, gdp and global mean temperature, and the influence of each factor on the temperature forecast in 2020-2040 are analyzed. Based on IESI and BP neural network model, a global temperature mitigation prediction model considering the sea temperature and land temperature of each climate country is established. The results show that there is a 74% probability that the GGDP growth rate is positively correlated with temperature change over 50 years. Using the computational model GGDP, the differences between development patterns and global GDP and green GDP are analyzed, and the relationship between environmental efficiency and global mean temperature is examined. All factors are proportional to global temperature, indicating that natural resource utilization and pollution emissions have significant effects on economic growth and temperature rise. Finally, it evaluates the global sustainable development level from the perspective of economy and environment, and establishes the sustainable development evaluation method.
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