A Probabilistic Dynamic Material Flow Analysis Model for Chinese Urban Housing Stock
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DOI: 10.1111/jiec.12579
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Citations
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Cited by:
- Bradley Kloostra & Benjamin Makarchuk & Shoshanna Saxe, 2022. "Bottom‐up estimation of material stocks and flows in Toronto's road network," Journal of Industrial Ecology, Yale University, vol. 26(3), pages 875-890, June.
- Zhou, Wei & O'Neill, Eoghan & Moncaster, Alice & Reiner, David M. & Guthrie, Peter, 2020.
"Forecasting urban residential stock turnover dynamics using system dynamics and Bayesian model averaging,"
Applied Energy, Elsevier, vol. 275(C).
- Wei Zhou & Eoghan O’Neill & Alice Moncaster & David Reiner & Peter Guthrie, 2020. "Forecasting Urban Residential Stock Turnover Dynamics using System Dynamics and Bayesian Model Averaging," Working Papers EPRG2016, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
- Zhou, W. & O’Neill, E. & Moncaster, A. & Reiner D. & Guthrie, P., 2020. "Forecasting Urban Residential Stock Turnover Dynamics using System Dynamics and Bayesian Model Averaging," Cambridge Working Papers in Economics 2054, Faculty of Economics, University of Cambridge.
- Ling Zhang & Qingqing Lu & Zengwei Yuan & Songyan Jiang & Huijun Wu, 2023. "A bottom‐up modeling of metabolism of the residential building system in China toward 2050," Journal of Industrial Ecology, Yale University, vol. 27(2), pages 587-600, April.
- Rafaela Tirado & Adélaïde Aublet & Sylvain Laurenceau & Mathieu Thorel & Mathilde Louërat & Guillaume Habert, 2021. "Component-Based Model for Building Material Stock and Waste-Flow Characterization: A Case in the Île-de-France Region," Sustainability, MDPI, vol. 13(23), pages 1-34, November.
- Qiance Liu & Litao Liu & Xiaojie Liu & Shenggong Li & Gang Liu, 2021. "Building stock dynamics and the impact of construction bubble and bust on employment in China," Journal of Industrial Ecology, Yale University, vol. 25(6), pages 1631-1643, December.
- Yang, Jingjing & Deng, Zhang & Guo, Siyue & Chen, Yixing, 2023. "Development of bottom-up model to estimate dynamic carbon emission for city-scale buildings," Applied Energy, Elsevier, vol. 331(C).
- Liang Yuan & Weisheng Lu & Yijie Wu, 2023. "Characterizing the spatiotemporal evolution of building material stock in China's Greater Bay Area: A statistical regression method," Journal of Industrial Ecology, Yale University, vol. 27(6), pages 1553-1566, December.
- Zhu, Chen & Li, Xiaodong & Zhu, Weina & Gong, Wei, 2022. "Embodied carbon emissions and mitigation potential in China's building sector: An outlook to 2060," Energy Policy, Elsevier, vol. 170(C).
- Yang, Xue & Zhang, Chao & Li, Xinyi & Cao, Zhi & Wang, Peng & Wang, Heming & Liu, Gang & Xia, Ziqian & Zhu, Dajian & Chen, Wei-Qiang, 2024. "Multinational dynamic steel cycle analysis reveals sequential decoupling between material use and economic growth," Ecological Economics, Elsevier, vol. 217(C).
- Xaysackda Vilaysouk & Savath Saypadith & Seiji Hashimoto, 2022. "Semisupervised machine learning classification framework for material intensity parameters of residential buildings," Journal of Industrial Ecology, Yale University, vol. 26(1), pages 72-87, February.
- Ruirui Zhang & Jing Guo & Dong Yang & Hiroaki Shirakawa & Feng Shi & Hiroki Tanikawa, 2022. "What matters most to the material intensity coefficient of buildings? Random forest‐based evidence from China," Journal of Industrial Ecology, Yale University, vol. 26(5), pages 1809-1823, October.
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