4.7 Article

Analysis of carbon emissions in urban building sector using multi-influence model

期刊

JOURNAL OF CLEANER PRODUCTION
卷 426, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2023.139130

关键词

Urban building; Renewable energy; Carbon emission; Carbon neutral; Heilongjiang

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This study proposes a comprehensive and versatile carbon emission prediction system for the urban building industry, aiming to reduce carbon emissions. The application of the model in a case study in Heilongjiang Province, China suggests that early peak carbon emissions in urban buildings can be achieved before 2030, with a potential reduction of approximately 78% by 2060 compared to 2020 levels. The scalability of the model allows for its future implementation in larger regions of China and its potential use in assessing CO2 emissions in urban buildings. With quantitative data, the model offers valuable support to policymakers implementing low-carbon strategies in the building sector.
The building industry is a major energy-consumer and carbon-emitter worldwide. Energy with low carbon emissions is critical for decarbonizing the urban building sector. Early studies often showed how one or more factors affected carbon emissions, but frequently ignored how diverse urban building subsystems varied in integrity, dynamism, and complexity. This study created a comprehensive and versatile carbon emission pre-diction system for the urban construction industry using the proposed Multi-influence Model of Urban Building Carbon-emission (MMUBC). Application of the model is demonstrated through a case study in Heilongjiang Province, China. The modeling results indicate that carbon emissions from urban buildings are projected to reach their peak before 2030, with a potential reduction of approximately 78% by 2060 compared with 2020 levels. Achieving early peak carbon emissions in the power generation and heating sectors appears to be feasible through increased use of renewable energy for heating. The scalability of the model allows for future implementation in larger regions of China and potential use for assessing CO2 emissions in urban buildings. With quantitative data, the model offers valuable support to policymakers implementing low-carbon strategies in the building sector.

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