estimation of passenger car co2 emissions with urban population density scenarios for low carbon transportation in japan
Clicks: 375
ID: 174307
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.
Reader Engagement
Popular Article
30.0
/100
375 views
36 readers
AI Quality Assessment
Not analyzed
Readership in this journal
PopularRanked #6 of 61 articles by views in computers and education
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate 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
The aim of this study is to quantify the potential reduction of CO2 emissions by passenger vehicles over the long term through the introduction of compact cities. We determined the correlation between population distribution and passenger car CO2 emissions from 1980 to 2005 and simulated passenger car CO2 emissions in 2030 under both compact and dispersed scenarios. We conducted correlation analysis and scenario analysis with the data sets of municipal CO2 emissions of passenger cars, national population census figures, and future population distribution scenarios. Then, we estimated the annual CO2 emissions of passenger cars per capita by mesh cell density category. The results show that the difference in emissions per capita between the compact and dispersed scenarios is roughly 5% in Japanese municipalities as a whole.
| Reference Key |
matsuhashi2016iatssestimation
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Keisuke Matsuhashi;Toshinori Ariga |
| Journal | computers and education |
| Year | 2016 |
| DOI |
10.1016/j.iatssr.2016.01.002
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.