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Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City

Global warming has become the focus of attention of the international community, and the control of carbon dioxide emissions has become one of the necessary choices for the development strategies of countries around the world. Cities are places where carbon dioxide emissions are concentrated. The ke...

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Autores principales: Huang, Xianghua, Chen, Shidong, Xiong, Decheng, Xu, Chao, Yang, Zhijie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377890/
https://www.ncbi.nlm.nih.gov/pubmed/35978900
http://dx.doi.org/10.1155/2022/7546742
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author Huang, Xianghua
Chen, Shidong
Xiong, Decheng
Xu, Chao
Yang, Zhijie
author_facet Huang, Xianghua
Chen, Shidong
Xiong, Decheng
Xu, Chao
Yang, Zhijie
author_sort Huang, Xianghua
collection PubMed
description Global warming has become the focus of attention of the international community, and the control of carbon dioxide emissions has become one of the necessary choices for the development strategies of countries around the world. Cities are places where carbon dioxide emissions are concentrated. The key to controlling carbon emissions is to control the carbon emissions of cities. My country is currently in the process of rapid urbanization. Quantitative studies of the carbon cycle at the city level will help to take stock of carbon dioxide emissions in cities. On the other hand, it is helpful to understand the status and role of the urban carbon cycle in the process of the regional carbon cycle. Through the analysis and prediction of the elements influencing the carbon cycle of smart cities, this paper first determines the factors affecting smart cities in the carbon cycle process as industrial carbon emission strength factors, industrial structure effects, economic development factors, and population elements. It is found that the major positive factors affecting the significant add of CO2 emissions in smart cities from 2010 to 2019 are economic development factors and demographic factors, including economic development factors GDP/per capita GDP. The per capita contribution to CO2 emissions is higher than the model established by adjusting the affecting elements of overall CO2 emissions, except that the proportion of economic development factors in total CO2 emissions from 2013 to 2015 was lower than the increase in total CO2 emissions. The comparison can better reflect the relation between CO2 emissions and influencing elements. The main determinants affecting CO2 emissions are the expansion of the financial condition, the increase in the average daily population, and the increase in construction work. The adaptation index is judged to be consistent, indicating that the model adjustment effect is good; finally, the green computing in the smart city predicts the carbon cycle process, and the actual value trend line and the predicted value trend line are not much different from the practical value, the forecast error is small, and the prediction results are credible. Global warming has become the focus of attention of the international community, and carbon emission control has become one of the necessary options in the development strategies of countries around the world. Cities are the places where carbon emissions are concentrated. The key to controlling carbon emissions is to control urban carbon emissions. At present, my country is in the process of rapid urbanization. Quantitative research on the carbon cycle at the city level will help to establish an inventory accounting of urban carbon emissions. On the other hand, it is convenient to deeply understand the status and role of the urban carbon cycle in the process of the regional carbon cycle.
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spelling pubmed-93778902022-08-16 Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City Huang, Xianghua Chen, Shidong Xiong, Decheng Xu, Chao Yang, Zhijie Comput Intell Neurosci Research Article Global warming has become the focus of attention of the international community, and the control of carbon dioxide emissions has become one of the necessary choices for the development strategies of countries around the world. Cities are places where carbon dioxide emissions are concentrated. The key to controlling carbon emissions is to control the carbon emissions of cities. My country is currently in the process of rapid urbanization. Quantitative studies of the carbon cycle at the city level will help to take stock of carbon dioxide emissions in cities. On the other hand, it is helpful to understand the status and role of the urban carbon cycle in the process of the regional carbon cycle. Through the analysis and prediction of the elements influencing the carbon cycle of smart cities, this paper first determines the factors affecting smart cities in the carbon cycle process as industrial carbon emission strength factors, industrial structure effects, economic development factors, and population elements. It is found that the major positive factors affecting the significant add of CO2 emissions in smart cities from 2010 to 2019 are economic development factors and demographic factors, including economic development factors GDP/per capita GDP. The per capita contribution to CO2 emissions is higher than the model established by adjusting the affecting elements of overall CO2 emissions, except that the proportion of economic development factors in total CO2 emissions from 2013 to 2015 was lower than the increase in total CO2 emissions. The comparison can better reflect the relation between CO2 emissions and influencing elements. The main determinants affecting CO2 emissions are the expansion of the financial condition, the increase in the average daily population, and the increase in construction work. The adaptation index is judged to be consistent, indicating that the model adjustment effect is good; finally, the green computing in the smart city predicts the carbon cycle process, and the actual value trend line and the predicted value trend line are not much different from the practical value, the forecast error is small, and the prediction results are credible. Global warming has become the focus of attention of the international community, and carbon emission control has become one of the necessary options in the development strategies of countries around the world. Cities are the places where carbon emissions are concentrated. The key to controlling carbon emissions is to control urban carbon emissions. At present, my country is in the process of rapid urbanization. Quantitative research on the carbon cycle at the city level will help to establish an inventory accounting of urban carbon emissions. On the other hand, it is convenient to deeply understand the status and role of the urban carbon cycle in the process of the regional carbon cycle. Hindawi 2022-08-08 /pmc/articles/PMC9377890/ /pubmed/35978900 http://dx.doi.org/10.1155/2022/7546742 Text en Copyright © 2022 Xianghua Huang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Huang, Xianghua
Chen, Shidong
Xiong, Decheng
Xu, Chao
Yang, Zhijie
Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City
title Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City
title_full Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City
title_fullStr Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City
title_full_unstemmed Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City
title_short Analysis and Prediction of Influence Factors of Green Computing on Carbon Cycle Process in Smart City
title_sort analysis and prediction of influence factors of green computing on carbon cycle process in smart city
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377890/
https://www.ncbi.nlm.nih.gov/pubmed/35978900
http://dx.doi.org/10.1155/2022/7546742
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