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Emission reduction planning for carbon footprint in rural residential life cycle under the low-carbon background.
- Source :
- Energy Informatics; 9/27/2024, Vol. 7 Issue 1, p1-18, 18p
- Publication Year :
- 2024
-
Abstract
- In the context of global low-carbon development, reducing rural residential carbon emissions is the key to implementing emission reduction policies. In order to reduce carbon emissions from rural housing, a carbon emission classification method based on residential life cycle assessment is proposed based on the characteristics of rural housing in China. Its innovation lies in achieving precise analysis of carbon emissions from multiple stages of residential design, construction, and use. Secondly, introducing a lifecycle based emission reduction planning strategy to achieve a new pattern of low-carbon emission reduction in rural residential areas. Taking a rural residential building as a case study, in the early stage of implementing emission reduction, the mean values of the initial carbon emissions corresponding to building energy consumption, energy consumption, and resident living habits were 689, 691, and 683, with standard deviations of 81, 79, and 84. After implementing emission reduction plans, the values decreased to 686, 674, and 631, respectively, with standard deviations reduced to 28, 32, and 13. It was evident that emission reduction planning not only significantly reduced the mean carbon emissions but also substantially decreases their variability, enhancing the stability of carbon emissions. This research contributed to a deeper understanding of the carbon emissions from rural residential life cycles and provides theoretical support and data references for the formulation and implementation of more scientific and effective emission reduction planning. Simultaneously, it promoted low-carbon development in rural areas of China, achieving a harmonious coexistence of economic and social development with environmental protection and contributing to global low-carbon development. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 25208942
- Volume :
- 7
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Energy Informatics
- Publication Type :
- Academic Journal
- Accession number :
- 179970417
- Full Text :
- https://doi.org/10.1186/s42162-024-00389-1