Journal of Statistical Theory and Applications

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Volume 19, Issue 1, March 2020, Pages 10 - 20

A Stochastic Approach in Modeling of Regional Atmospheric CO2 in the United States

Authors
Doo Young Kim1, *, Chris P. Tsokos2
1Department of Mathematics and Statistics, Sam Houston State University Box 2206, Huntsville, TX 77341-2206, USA
2Department of Mathematics and Statistics, University of South Florida 4202 East Fowler avenue, CMC 342, Tampa, FL 33620, USA
*Corresponding author. Email: dkim@shsu.edu
Corresponding Author
Doo Young Kim
Received 18 November 2018, Accepted 10 December 2018, Available Online 3 March 2020.
DOI
10.2991/jsta.d.200224.002How to use a DOI?
Keywords
Global Warming; Climate Change; Cluster Analysis; Transition Modeling
Abstract

Global warming is a function of two main contributable entities in the atmosphere, carbon dioxide, and atmospheric temperature. The objective of this study is to develop a statistical model using actual fossil fuel carbon dioxide emissions data from the United States to predict relative probability of rate of change in fossil fuels carbon dioxide emissions from nine US climate regions using transition modeling. The sensitivity of these transition probabilities to five sectors, that are the commercial, industrial, residential, transportation, and electric power sector, is also investigated for all nine US climate regions. The present study also suggests that the US government should be developing regional policies to control fossil fuel carbon dioxide emissions that will be more effective in addressing the subject problem.

Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Statistical Theory and Applications
Volume-Issue
19 - 1
Pages
10 - 20
Publication Date
2020/03/03
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
10.2991/jsta.d.200224.002How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Doo Young Kim
AU  - Chris P. Tsokos
PY  - 2020
DA  - 2020/03/03
TI  - A Stochastic Approach in Modeling of Regional Atmospheric CO2 in the United States
JO  - Journal of Statistical Theory and Applications
SP  - 10
EP  - 20
VL  - 19
IS  - 1
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.d.200224.002
DO  - 10.2991/jsta.d.200224.002
ID  - Kim2020
ER  -