Prediction and Detection of Carbon Emission Trend Based on Big Data Analysis
大数据
计算机科学
数据挖掘
作者
Song Guo Cheng,Da Zhong,Feng Wen Lei
标识
DOI:10.1145/3632971.3633046
摘要
Abstract: With the rapid development of industrialization and urbanization, carbon emissions have become the main factor affecting global climate change, and Big data analysis technology is of great significance in this field. This paper used big data analysis technology to analyze historical and current carbon emission data, and predict and detect the future carbon emission trend. The experimental results indicated that the future carbon emissions would continue to rise, but the growth rate would gradually slow down. The predicted total carbon emissions in 2023 were 610, while the actual value was 600. In terms of carbon emissions reduction, measures such as increasing renewable energy and encouraging green travel can effectively reduce carbon emissions, while also having a positive impact on economic growth. Implementing carbon reduction measures such as carbon taxes would have an impact on economic growth. Carbon reduction measures should be continued in the future, and big data analytics should be used to monitor emissions and make accurate predictions, thus promoting environmental protection and sustainable development.