Prediction of the Path Level of Carbon Emission Reduction Based on the IPAT Model from the Computer Vision

Abstract

AbstractCurrently, global warming (GW) problems have become a hot spot that humans have to pay attention. Carbon dioxide is the most important greenhouse gas and the main cause of GW. In response to the huge environmental pressure, countries around the world have begun to explore the path of carbon emission reduction (CER) in order to control the excessive emission of carbon dioxide gas. IPAT model plays an important role in the research of CER field. This article starts from the computer perspective to study the CER path level prediction based on the IPAT model. This article introduces the expression and meaning of the classic IPAT model, selects the random model STIRPAT model of the IPAT model, and constructs the CER path level prediction model. This article takes the CER path of H province as the research object, predicts the CER effect of the province in different situations, and derives the CER path policy enlightenment. The survey data shows that under the balanced emission reduction scenario, the total carbon dioxide emissions of H province will reach a peak before 2029, with a peak of 525.23 million tons. This shows that H province should attach importance to the suppression of carbon dioxide emissions by technological innovation, energy structure adjustment, and industrial structure optimization to improve energy efficiency.KeywordsIPAT modelCarbon emission reductionCarbon emission forecastCarbon emission influencing factors