nach oben

Erschienen in:

2023 | OriginalPaper | Buchkapitel

A Bibliometric Review of the Carbon Emissions and Machine Learning Research in the Post-COVID-19 Era

verfasst von : Peiyi Liao, Dan Chong

Erschienen in: Proceedings of the 27th International Symposium on Advancement of Construction Management and Real Estate

Verlag: Springer Nature Singapore

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

The COVID-19 pandemic has dramatically changed people’s lives and had a major impact on the field of research. In this study, bibliometrics was used to analyze 783 articles in the field of the post-COVID-19 era, among which 55 articles were the most popular management directions. Based on this background, carbon emissions and machine learning are selected for further analysis, which are the current hot research directions. There were only 22 and 12 related articles. This shows that management direction is a hot research topic in the post-COVID-19 era, while carbon emissions and machine learning are relatively few. This study sorted out and analyzed the specific research content of these 34 literatures. It is found that there are few literatures that apply machine learning to the study of carbon emission. But it also found that machine learning methods can be applied to carbon emissions even in the post-COVID-19 era. This not only provides scholars with new ideas and directions for their research, but also provides a theoretical basis for enterprises and governments to formulate corresponding carbon emission management policies.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Life Cycle Carbon Emission Assessment of Prefabricated Buildings: A Case Study in Nantong, China

Nächstes Kapitel Job Stress of Chinese Construction Project Management Personnel in Project Overall Implementation Process

Ray, R.L., Singh, V.P., Singh, S.K., et al.: What is the impact of COVID-19 pandemic on global carbon emissions? Sci. Total Environ. 816, 151503 (2022). https://doi.org/10.1016/j.scitotenv.2021.151503CrossRef

Li, Z., Wang, J., Che, S.: Synergistic effect of carbon trading scheme on carbon dioxide and atmospheric pollutants. Sustainability 13(10), 5403 (2021). https://doi.org/10.3390/su13105403CrossRef

Naderipour, A., Abdul-Malek, Z., Ahmad, N.A., et al.: Effect of COVID-19 virus on reducing ghg emission and increasing energy generated by renewable energy sources: a brief study in Malaysian context. Environ. Technol. Innov. 20, 101151 (2020). https://doi.org/10.1016/j.eti.2020.101151CrossRef

Filonchyk, M., Hurynovich, V., Yan, H., et al.: Impact assessment of COVID-19 on variations of SO₂, NO₂, CO and AOD over east china. Aerosol Air Qual. Res. 20(7), 1530–1540 (2020). https://doi.org/10.4209/aaqr.2020.05.0226CrossRef

Nguyen, X.P., Hoang, A.T., Ölçer, A.I., et al.: Record decline in global co 2 emissions prompted by COVID-19 pandemic and its implications on future climate change policies. Energy Sources Part A Recovery Utilization Environ. Effects 1–4 (2021). https://doi.org/10.1080/15567036.2021.1879969

Magazzino, C., Mele, M., Schneider, N.: A machine learning approach on the relationship among solar and wind energy production, coal consumption, GDP, and CO₂ emissions. Renew. Energy 167, 99–115 (2021). https://doi.org/10.1016/j.renene.2020.11.050CrossRef

Kurniawan, R., Managi, S.: Forecasting annual energy consumption using machine learnings: case of Indonesia. IOP Conf. Ser. Earth Environ. Sci. 257, 012032 (2019). https://doi.org/10.1088/1755-1315/257/1/012032CrossRef

Mele, M., Magazzino, C.: Pollution, economic growth, and COVID-19 deaths in India: a machine learning evidence. Environ. Sci. Pollut. Res. 28(3), 2669–2677 (2020). https://doi.org/10.1007/s11356-020-10689-0CrossRef

Mardani, A., Liao, H., Nilashi, M., et al.: A multi-stage method to predict carbon dioxide emissions using dimensionality reduction, clustering, and machine learning techniques. J. Clean. Prod. 275, 122942 (2020). https://doi.org/10.1016/j.jclepro.2020.122942CrossRef

10.

Aria, M., Cuccurullo, C.: Bibliometrix : an R-tool for comprehensive science mapping analysis. J. Informet. 11(4), 959–975 (2017). https://doi.org/10.1016/j.joi.2017.08.007CrossRef

11.

Zhang, X., Li, Z., Wang, J.: Impact of COVID-19 pandemic on energy consumption and carbon dioxide emissions in China’s transportation sector. Case Stud. Therm. Eng. 26, 101091 (2021). https://doi.org/10.1016/j.csite.2021.101091CrossRef

12.

Han, S., Roy, P.K., Hossain, M.I., et al.: COVID-19 pandemic crisis and food safety: implications and inactivation strategies. Trends Food Sci. Technol. 109, 25–36 (2021). https://doi.org/10.1016/j.tifs.2021.01.004CrossRef

13.

Gössling, S., Scott, D., Hall, C.M.: Pandemics, tourism and global change: a rapid assessment of COVID-19. J. Sustain. Tour. 29(1), 1–20 (2021). https://doi.org/10.1080/09669582.2020.1758708CrossRef

14.

Tian, J., Yu, L., Xue, R., et al.: Global low-carbon energy transition in the post-COVID-19 era. Appl. Energy 307, 118205 (2022). https://doi.org/10.1016/j.apenergy.2021.118205CrossRef

15.

Yang, M., Chen, L., Msigwa, G., et al.: Implications of COVID-19 on global environmental pollution and carbon emissions with strategies for sustainability in the COVID-19 era. Sci. Total Environ. 809, 151657 (2022). https://doi.org/10.1016/j.scitotenv.2021.151657CrossRef

16.

Chen, T., Peng, L., Yang, J., et al.: Evolutionary game of multi-subjects in live streaming and governance strategies based on social preference theory during the COVID-19 pandemic. Mathematics 9(21), 2743 (2021). https://doi.org/10.3390/math9212743CrossRef

17.

Choe, J.Y. (Jacey), Kim, J.J., Hwang, J.: Perceived risks from drone food delivery services before and after COVID-19. Int. J. Contemp. Hospitality Manage. 33(4), 1276–1296 (2021). https://doi.org/10.1108/IJCHM-08-2020-0839

18.

Cobo, M.J., López-Herrera, A.G., Herrera-Viedma, E., et al.: An approach for detecting, quantifying, and visualizing the evolution of a research field: a practical application to the fuzzy sets theory field. J. Informet. 5(1), 146–166 (2011). https://doi.org/10.1016/j.joi.2010.10.002CrossRef

19.

Yang, C., Hao, Y., Irfan, M.: Energy consumption structural adjustment and carbon neutrality in the post-COVID-19 era. Struct. Chang. Econ. Dyn. 59, 442–453 (2021). https://doi.org/10.1016/j.strueco.2021.06.017CrossRef

20.

Yan, Y., Liang, W., Wang, B., et al.: Spillover effect among independent carbon markets: evidence from China’s carbon markets. Econ. Change Restruct. (2022). https://doi.org/10.1007/s10644-022-09431-2

21.

Wei, R., Ayub, B., Dagar, V.: Environmental benefits from carbon tax in the Chinese carbon market: a roadmap to energy efficiency in the post-COVID-19 era. Front. Energy Res. 10, 832578 (2022). https://doi.org/10.3389/fenrg.2022.832578CrossRef

22.

Liu, J., Tian, J., Lyu, W., et al.: The impact of COVID-19 on reducing carbon emissions: from the angle of international student mobility. Appl. Energy 317, 119136 (2022). https://doi.org/10.1016/j.apenergy.2022.119136CrossRef

23.

Li, M., Yao-Ping Peng, M., Nazar, R., et al.: How does energy efficiency mitigate carbon emissions without reducing economic growth in post COVID-19 era. Front. Energy Res. 10, 832189 (2022). https://doi.org/10.3389/fenrg.2022.832189CrossRef

24.

Chong, C.T., Fan, Y.V., Lee, C.T., et al.: Post COVID-19 energy sustainability and carbon emissions neutrality. Energy 241, 122801 (2022). https://doi.org/10.1016/j.energy.2021.122801CrossRef

25.

Strielkowski, W., Zenchenko, S., Tarasova, A., et al.: Management of smart and sustainable cities in the post-COVID-19 era: lessons and implications. Sustainability 14(12), 7267 (2022). https://doi.org/10.3390/su14127267CrossRef

26.

Masmoudi, N., Jaafar, W., Cherif, S., et al.: UAV-based crowd surveillance in post COVID-19 era. IEEE Access 9, 162276–162290 (2021). https://doi.org/10.1109/ACCESS.2021.3133796CrossRef

27.

Li, R., Li, Z., Guo, L.: What determine the corporate tax rates during the COVID-19? evidence from 113 countries. Front. Public Health 9, 816561 (2022). https://doi.org/10.3389/fpubh.2021.816561CrossRef

28.

Kerdvibulvech, C., Dong, Z.Y.: Roles of artificial intelligence and extended reality development in the post-COVID-19 era. In: Stephanidis, C., et al., (eds.) HCI International 2021 - Late Breaking Papers: Multimodality, eXtended Reality, and Artificial Intelligence. HCII 2021. Lecture Notes in Computer Science, vol. 13095, pp. 445–454. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-90963-5_34

29.

Kawakami, N., Imamura, K., Watanabe, K., et al.: Effectiveness of an internet-based machine-guided stress management program based on cognitive behavioral therapy for improving depression among workers: protocol for a randomized controlled trial. JMIR Res. Protoc. 10(9), e30305 (2021). https://doi.org/10.2196/30305CrossRef

30.

Imam, T., Ananda, J.: Machine learning for characterizing growth in tourism employment in developing economies: an assessment of tourism employment in Sri Lanka. Curr. Issue Tour. 25(16), 2695–2716 (2022). https://doi.org/10.1080/13683500.2021.1991895CrossRef

31.

Giri, C., Cleaves, H.J., Meringer, M., et al.: The post-COVID-19 era: interdisciplinary demands of contagion surveillance mass spectrometry for future pandemics. Sustainability 13(14), 7614 (2021). https://doi.org/10.3390/su13147614CrossRef

32.

Brahim, G.B.: Predicting student performance from online engagement activities using novel statistical features. Arab. J. Sci. Eng. 47(8), 10225–10243 (2022). https://doi.org/10.1007/s13369-021-06548-wCrossRef

33.

Antani, S., Kun, L., Carey, C., et al.: Life science and its implications for society—(in addition to COVID-19). In: 2021 IEEE International Symposium on Technology and Society (ISTAS). Waterloo, ON, Canada: IEEE 2021, p. 1 (2022).https://doi.org/10.1109/ISTAS52410.2021.9629200. https://ieeexplore.ieee.org/document/9629200/

34.

Andreou, A., Mavromoustakis, C.X., Mastorakis, G., et al.: Evaluation of the COVID-19 era by using machine learning and interpretation of confidential dataset. Electronics 10(23), 2910 (2021). https://doi.org/10.3390/electronics10232910CrossRef

Titel: A Bibliometric Review of the Carbon Emissions and Machine Learning Research in the Post-COVID-19 Era
verfasst von: Peiyi Liao
Dan Chong
Verlag: Springer Nature Singapore
Buch: Proceedings of the 27th International Symposium on Advancement of Construction Management and Real Estate
Print ISBN: 978-981-9936-25-0

Electronic ISBN: 978-981-9936-26-7

Copyright-Jahr: 2023
DOI: https://doi.org/10.1007/978-981-99-3626-7_99

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"