{"title":"利用灰色断点预测模型预测金砖国家二氧化碳排放量","authors":"Huiping Wang, Xinge Guo","doi":"10.1186/s13021-025-00301-8","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, three novel grey breakpoint prediction models are proposed based on calculating the development coefficient and grey action of grey prediction models after fuzzy breakpoints, unifying the calculation methods for parameter estimation and the relevant time-response equations, and using the particle swarm optimisation algorithm to optimise the two-stage background values. Finally, the novel grey breakpoint prediction models are used to simulate and forecast the CO<sub>2</sub> emissions in BRICS countries. We can see that by setting time breakpoints and fuzzy breakpoint intervals, the novel methods successfully detect abrupt changes in the system and achieve accurate predictions, thus improving the accuracy and applicability of the grey model. The new grey breakpoint prediction models demonstrate better estimation in all cases in CO<sub>2</sub> emissions forecasting. The projections show that between 2022 and 2025, CO<sub>2</sub> emissions in Brazil and South Africa will decrease each year, while CO<sub>2</sub> emissions in China, Russia and India will increase each year, but the upwards trend in India shows signs of slowing.</p></div>","PeriodicalId":505,"journal":{"name":"Carbon Balance and Management","volume":"20 1","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-025-00301-8","citationCount":"0","resultStr":"{\"title\":\"Forecasting CO2 emissions in BRICS countries using the grey breakpoint prediction models\",\"authors\":\"Huiping Wang, Xinge Guo\",\"doi\":\"10.1186/s13021-025-00301-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In this paper, three novel grey breakpoint prediction models are proposed based on calculating the development coefficient and grey action of grey prediction models after fuzzy breakpoints, unifying the calculation methods for parameter estimation and the relevant time-response equations, and using the particle swarm optimisation algorithm to optimise the two-stage background values. Finally, the novel grey breakpoint prediction models are used to simulate and forecast the CO<sub>2</sub> emissions in BRICS countries. We can see that by setting time breakpoints and fuzzy breakpoint intervals, the novel methods successfully detect abrupt changes in the system and achieve accurate predictions, thus improving the accuracy and applicability of the grey model. The new grey breakpoint prediction models demonstrate better estimation in all cases in CO<sub>2</sub> emissions forecasting. The projections show that between 2022 and 2025, CO<sub>2</sub> emissions in Brazil and South Africa will decrease each year, while CO<sub>2</sub> emissions in China, Russia and India will increase each year, but the upwards trend in India shows signs of slowing.</p></div>\",\"PeriodicalId\":505,\"journal\":{\"name\":\"Carbon Balance and Management\",\"volume\":\"20 1\",\"pages\":\"\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://cbmjournal.biomedcentral.com/counter/pdf/10.1186/s13021-025-00301-8\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Carbon Balance and Management\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s13021-025-00301-8\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Carbon Balance and Management","FirstCategoryId":"89","ListUrlMain":"https://link.springer.com/article/10.1186/s13021-025-00301-8","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Forecasting CO2 emissions in BRICS countries using the grey breakpoint prediction models
In this paper, three novel grey breakpoint prediction models are proposed based on calculating the development coefficient and grey action of grey prediction models after fuzzy breakpoints, unifying the calculation methods for parameter estimation and the relevant time-response equations, and using the particle swarm optimisation algorithm to optimise the two-stage background values. Finally, the novel grey breakpoint prediction models are used to simulate and forecast the CO2 emissions in BRICS countries. We can see that by setting time breakpoints and fuzzy breakpoint intervals, the novel methods successfully detect abrupt changes in the system and achieve accurate predictions, thus improving the accuracy and applicability of the grey model. The new grey breakpoint prediction models demonstrate better estimation in all cases in CO2 emissions forecasting. The projections show that between 2022 and 2025, CO2 emissions in Brazil and South Africa will decrease each year, while CO2 emissions in China, Russia and India will increase each year, but the upwards trend in India shows signs of slowing.
期刊介绍:
Carbon Balance and Management is an open access, peer-reviewed online journal that encompasses all aspects of research aimed at developing a comprehensive policy relevant to the understanding of the global carbon cycle.
The global carbon cycle involves important couplings between climate, atmospheric CO2 and the terrestrial and oceanic biospheres. The current transformation of the carbon cycle due to changes in climate and atmospheric composition is widely recognized as potentially dangerous for the biosphere and for the well-being of humankind, and therefore monitoring, understanding and predicting the evolution of the carbon cycle in the context of the whole biosphere (both terrestrial and marine) is a challenge to the scientific community.
This demands interdisciplinary research and new approaches for studying geographical and temporal distributions of carbon pools and fluxes, control and feedback mechanisms of the carbon-climate system, points of intervention and windows of opportunity for managing the carbon-climate-human system.
Carbon Balance and Management is a medium for researchers in the field to convey the results of their research across disciplinary boundaries. Through this dissemination of research, the journal aims to support the work of the Intergovernmental Panel for Climate Change (IPCC) and to provide governmental and non-governmental organizations with instantaneous access to continually emerging knowledge, including paradigm shifts and consensual views.