Modeling the Carbon Cycle Dynamics and the Greenhouse Effect

Soo Hyoung Choi; Vasilios I. Manousiouthakis

doi:10.1016/j.ifacol.2022.07.480

Modeling the Carbon Cycle Dynamics and the Greenhouse Effect

Soo Hyoung Choi
, Vasilios I. Manousiouthakis

Division of Chemical Engineering

University of California at Los Angeles

Research output: Contribution to journal › Conference article › peer-review

9 Scopus citations

Abstract

A carbon cycle model is proposed that predicts changes in the atmospheric CO₂concentration, and provides a global temperature estimate from an empirical correlation of the two variables. The model is validated by simulating the anthropogenic carbon emissions and deforestation since the industrial revolution, and comparing the predicted and measured atmospheric CO₂concentration and global temperature data. The temperature data are also compared with those predicted by a greenhouse effect model based on the effective emission temperature hypothesis. The result suggests that radiative forcing by CO₂alone can account for only about half of the measured global warming. The model requires further elaboration for the other half, in order to be applicable to simulation of potential climate control.

Original language	English
Pages (from-to)	424-428
Number of pages	5
Journal	IFAC-PapersOnLine
Volume	55
Issue number	7
DOIs	https://doi.org/10.1016/j.ifacol.2022.07.480
State	Published - 2022
Event	13th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, DYCOPS 2022 - Busan, Korea, Republic of Duration: 2022.06.14 → 2022.06.17

Keywords

carbon cycle dynamics
carbon neutrality
climate control
global warming
greenhouse effect

Quacquarelli Symonds(QS) Subject Topics

Computer Science & Information Systems

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10.1016/j.ifacol.2022.07.480

Cite this

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title = "Modeling the Carbon Cycle Dynamics and the Greenhouse Effect",

abstract = "A carbon cycle model is proposed that predicts changes in the atmospheric CO2concentration, and provides a global temperature estimate from an empirical correlation of the two variables. The model is validated by simulating the anthropogenic carbon emissions and deforestation since the industrial revolution, and comparing the predicted and measured atmospheric CO2concentration and global temperature data. The temperature data are also compared with those predicted by a greenhouse effect model based on the effective emission temperature hypothesis. The result suggests that radiative forcing by CO2alone can account for only about half of the measured global warming. The model requires further elaboration for the other half, in order to be applicable to simulation of potential climate control.",

keywords = "carbon cycle dynamics, carbon neutrality, climate control, global warming, greenhouse effect",

author = "Choi, \{Soo Hyoung\} and Manousiouthakis, \{Vasilios I.\}",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier B.V.. All rights reserved.; 13th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, DYCOPS 2022 ; Conference date: 14-06-2022 Through 17-06-2022",

year = "2022",

doi = "10.1016/j.ifacol.2022.07.480",

language = "English",

volume = "55",

pages = "424--428",

journal = "IFAC-PapersOnLine",

issn = "2405-8963",

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TY - JOUR

T1 - Modeling the Carbon Cycle Dynamics and the Greenhouse Effect

AU - Choi, Soo Hyoung

AU - Manousiouthakis, Vasilios I.

PY - 2022

Y1 - 2022

N2 - A carbon cycle model is proposed that predicts changes in the atmospheric CO2concentration, and provides a global temperature estimate from an empirical correlation of the two variables. The model is validated by simulating the anthropogenic carbon emissions and deforestation since the industrial revolution, and comparing the predicted and measured atmospheric CO2concentration and global temperature data. The temperature data are also compared with those predicted by a greenhouse effect model based on the effective emission temperature hypothesis. The result suggests that radiative forcing by CO2alone can account for only about half of the measured global warming. The model requires further elaboration for the other half, in order to be applicable to simulation of potential climate control.

AB - A carbon cycle model is proposed that predicts changes in the atmospheric CO2concentration, and provides a global temperature estimate from an empirical correlation of the two variables. The model is validated by simulating the anthropogenic carbon emissions and deforestation since the industrial revolution, and comparing the predicted and measured atmospheric CO2concentration and global temperature data. The temperature data are also compared with those predicted by a greenhouse effect model based on the effective emission temperature hypothesis. The result suggests that radiative forcing by CO2alone can account for only about half of the measured global warming. The model requires further elaboration for the other half, in order to be applicable to simulation of potential climate control.

KW - carbon cycle dynamics

KW - carbon neutrality

KW - climate control

KW - global warming

KW - greenhouse effect

UR - https://www.scopus.com/pages/publications/85137049090

U2 - 10.1016/j.ifacol.2022.07.480

DO - 10.1016/j.ifacol.2022.07.480

M3 - Conference article

AN - SCOPUS:85137049090

SN - 2405-8963

VL - 55

SP - 424

EP - 428

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

IS - 7

T2 - 13th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, DYCOPS 2022

Y2 - 14 June 2022 through 17 June 2022

ER -

Modeling the Carbon Cycle Dynamics and the Greenhouse Effect

Abstract

Keywords

Quacquarelli Symonds(QS) Subject Topics

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