Literature DB >> 33762626

Regression analysis and driving force model building of CO2 emissions in China.

Yi Zhou1, Jinyan Zhang2, Shanying Hu3.   

Abstract

In recent years, global warming has become increasingly devastating, leading to severe consequences, such as extreme weather events and sea-level rise. To reduce carbon dioxide emissions, it is essential to recognize different emission sources and key driving factors. Three main carbon emission sources from the period between 1990 and 2017 were identified in China: the energy industry, fuel combustion in other industries, and industrial process. For each source, a driving force model was developed via multiple linear regression. Based on these models, forecasts of the carbon intensity and total CO2 emissions were obtained from 2018 to 2030. The results demonstrate that the CO2 emission intensity and total emissions will continue to decrease but more effort will be required to achieve the goal of Paris Agreement.

Entities:  

Year:  2021        PMID: 33762626     DOI: 10.1038/s41598-021-86183-5

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  1 in total

1.  Impact and mechanism of digital economy on China's carbon emissions: from the perspective of spatial heterogeneity.

Authors:  Haijing Yu; Qin Zhu
Journal:  Environ Sci Pollut Res Int       Date:  2022-09-03       Impact factor: 5.190

  1 in total

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