Comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary data
This study aims to quantify and probabilistically assess the environmental advantages of hot in-place recycling (HIPR) and hot in-plant recycling (HIR) technologies over traditional milling and filling (M&F) in the context of asphalt pavement recycling with the collected primary data. The study&...
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| Language: | English |
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Elsevier
2025-10-01
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| Series: | Developments in the Built Environment |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666165925001061 |
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| author | Xiaohua Liu Lu Deng Jiangmiao Yu |
| author_facet | Xiaohua Liu Lu Deng Jiangmiao Yu |
| author_sort | Xiaohua Liu |
| collection | DOAJ |
| description | This study aims to quantify and probabilistically assess the environmental advantages of hot in-place recycling (HIPR) and hot in-plant recycling (HIR) technologies over traditional milling and filling (M&F) in the context of asphalt pavement recycling with the collected primary data. The study's primary dataset served as the foundation for modeling the life cycle inventory (LCI) across various stages of pavement recycling, which is collected in the geographical context of China in 2024. Subsequently, an uncertainty analysis was conducted to evaluate the data quality of each inventory phase. The comparative analysis of environmental impacts, focusing on carbon emissions and energy demand, revealed that HIPR and HIR technologies offer substantial environmental benefits. Notably, M&F technology exhibited a wider uncertainty range, which is attributed to its greater reliance on secondary data sourced from public databases. In contrast, the HIR technology demonstrated the lowest uncertainty, suggesting a more reliable environmental impact assessment. The findings underscore the importance of considering uncertainty in LCA studies. |
| format | Article |
| id | doaj-art-b8848f8471024d5b916d14c7135b0da3 |
| institution | Kabale University |
| issn | 2666-1659 |
| language | English |
| publishDate | 2025-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Developments in the Built Environment |
| spelling | doaj-art-b8848f8471024d5b916d14c7135b0da32025-08-20T03:50:01ZengElsevierDevelopments in the Built Environment2666-16592025-10-012310070610.1016/j.dibe.2025.100706Comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary dataXiaohua Liu0Lu Deng1Jiangmiao Yu2College of Civil Engineering, Hunan University, Changsha, China; Shenzhen General Integrated Transportation and Municipal Engineering Design & Research Institute Co, Ltd, Shenzhen, ChinaCollege of Civil Engineering, Hunan University, Changsha, China; Key Laboratory of Damage Diagnosis for Engineering Structures of Hunan Province, Hunan University, Changsha, China; Corresponding author. College of Civil Engineering, Hunan University, Changsha, China.School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, China; Central Fortune Creation (Canton) Roadway Technology Co., Ltd., Guangzhou, ChinaThis study aims to quantify and probabilistically assess the environmental advantages of hot in-place recycling (HIPR) and hot in-plant recycling (HIR) technologies over traditional milling and filling (M&F) in the context of asphalt pavement recycling with the collected primary data. The study's primary dataset served as the foundation for modeling the life cycle inventory (LCI) across various stages of pavement recycling, which is collected in the geographical context of China in 2024. Subsequently, an uncertainty analysis was conducted to evaluate the data quality of each inventory phase. The comparative analysis of environmental impacts, focusing on carbon emissions and energy demand, revealed that HIPR and HIR technologies offer substantial environmental benefits. Notably, M&F technology exhibited a wider uncertainty range, which is attributed to its greater reliance on secondary data sourced from public databases. In contrast, the HIR technology demonstrated the lowest uncertainty, suggesting a more reliable environmental impact assessment. The findings underscore the importance of considering uncertainty in LCA studies.http://www.sciencedirect.com/science/article/pii/S2666165925001061Pavement engineeringPavement recyclingCarbon emissionEnergy demandUncertainty |
| spellingShingle | Xiaohua Liu Lu Deng Jiangmiao Yu Comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary data Developments in the Built Environment Pavement engineering Pavement recycling Carbon emission Energy demand Uncertainty |
| title | Comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary data |
| title_full | Comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary data |
| title_fullStr | Comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary data |
| title_full_unstemmed | Comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary data |
| title_short | Comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary data |
| title_sort | comparative analysis of carbon emission and energy demand of pavement recycling technologies based on primary data |
| topic | Pavement engineering Pavement recycling Carbon emission Energy demand Uncertainty |
| url | http://www.sciencedirect.com/science/article/pii/S2666165925001061 |
| work_keys_str_mv | AT xiaohualiu comparativeanalysisofcarbonemissionandenergydemandofpavementrecyclingtechnologiesbasedonprimarydata AT ludeng comparativeanalysisofcarbonemissionandenergydemandofpavementrecyclingtechnologiesbasedonprimarydata AT jiangmiaoyu comparativeanalysisofcarbonemissionandenergydemandofpavementrecyclingtechnologiesbasedonprimarydata |