Author(s)

Xiangyu Sun ¹

Affiliation(s)

¹ School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan, 114051, China

Corresponding Author

Xiangyu Sun

ABSTRACT

The aim of this paper is to develop a gray prediction model to predict climate impacts. Firstly, GGDP is accounted for through the asset-liability accounting method, i.e., resource depletion costs and environmental degradation costs are deducted from GDP. This is calculated by deducting the cost of environmental resources and the cost of environmental resource protection services from the current total GDP, i.e., GGDP = Traditional GDP - Resource Reduction Costs - Environmental Maintenance Costs. Second, to determine the use of carbon dioxide as a predictor, monthly global carbon dioxide emissions from 1959 to 2022 were collected from the National Bureau of Statistics of China. Then, based on the analysis of the intrinsic trend of the data and the series rank ratio test after the translation transformation, the use of the gray prediction model to predict carbon dioxide concentration was justified. Then, using the historical data fitting, the average relative error of the model is calculated to be 0.958%, which indicates that the model fits well and predicts that the carbon dioxide concentration in the coming year will increase from 411.372 ppm to 412.936 ppm on a monthly basis, paving the way for the prediction of global climate change. Finally, global temperature values were collected from NASA from 1992 to 2021. An exponential regression analysis was performed to analyze the temperature changes. The results show that the temperature shows a clear upward trend.

KEYWORDS

GGDP, GDP, SEEA, Gray predictive model, Exponential regression analysis

CITE THIS PAPER

Xiangyu Sun, Establishment of Relationship Model between GGDP and Climate Based on Grey Method. Environment, Resource and Ecology Journal (2023) Vol. 7: 49-57. DOI: http://dx.doi.org/10.23977/erej.2023.070707.

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