an analysis based on sd model for energy-related co2 mitigation in the chinese household sector

Clicks: 236
ID: 135212
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #190 of 526 articles by views in acs combinatorial science

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 526 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Reducing carbon dioxide (CO2) emissions has become a global consensus in response to global warming and climate change, especially to China, the largest CO2 emitter in the world. Most studies have focused on CO2 emissions from the production sector, however, the household sector plays an important role in the total energy-related CO2 emissions. This study formulates an integrated model based on logarithmic mean Divisia index methodology and a system dynamics model to dynamically simulate household energy consumption and CO2 emissions under different conditions. Results show the following: (1) the integrated model performs well in calculating the contribution of influencing factors on household CO2 emissions and analyzing the options for CO2 emission mitigation; (2) the increase in income is the dominant driving force of household CO2 emissions, and as a result of the improved standard of living in China a sustained increase in household CO2 emissions can be expected; (3) with decreasing energy intensity, CO2 emissions will decrease to 404.26 Mt-CO2 in 2020, which is 9.84% lower than the emissions in 2014; (4) the reduction potential by developing non-fossil energy sources is limited, and raising the rate of urbanization cannot reduce the household CO2 emission under the comprehensive influence of other factors.
Reference Key
chen2016energiesan Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Xingpeng Chen;Guokui Wang;Xiaojia Guo;Jinxiu Fu
Journal acs combinatorial science
Year 2016
DOI
10.3390/en9121062
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.