Predicting Renovation Waste Generation Based on Grey System Theory: A Case Study of Shenzhen

Ding, Zhikun; Shi, Mengjie; Chen, Lu; Wu, Zezhou; Chong, Dan; Gong, Wenyan

doi:10.3390/su11164326

Cited by 15 publications

(4 citation statements)

References 31 publications

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“…Therefore, the GM is the most suitable tool for applications in this field. Currently, the GM(1,1) model, with a proper predictive accuracy and a relatively simple calculation, is typically adopted to predict the generation of C&D waste [18]. Zhao et al [19] applied the GM(1,1) model to predict the quantity of building decoration waste in Shenzhen, China.…”

Section: Short-term and Medium-term Prediction Methodsmentioning

confidence: 99%

Quantity Prediction of Construction and Demolition Waste Using Weighted Combined Grey Theory and Autoregressive Integrated Moving Average Model

Fang,

Shi,

Chen

et al. 2024

Sustainability

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With rapid urban development, the “waste-free city” concept has emerged. Therefore, the accurate prediction of the amount of C&D waste is of great importance. However, many countries and regions, including China, have not yet established C&D waste databases and standard prediction methods. This study proposed a method using a weighted combination of the grey theory model (GM) and the autoregressive integrated moving average (ARIMA) model to predict the quantity of urban C&D waste in the future. Based on a case study in Guangzhou, this study compared the prediction results of three prediction models, namely the GM, the ARIMA, and the proposed weighted combined model of the GM and the ARIMA (GM-ARIMA). The results of this study proved that the proposed combined GM-ARIMA model had a better predictive performance than both the separated models. The mean absolute percentage errors (MAPE) of the GM and ARIMA models were 12.11% and 14.26%, respectively, whereas the proposed GM-ARIMA model had a lower MAPE (8.5%). This study found that the generation of C&D waste in Guangzhou will continue to grow steadily. From 2024 to 2035, the quantity of C&D waste is expected to reach 850 million tons cumulatively, with an annual growth rate of 7.1%.

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Section: Short-term and Medium-term Prediction Methodsmentioning

confidence: 99%

Quantity Prediction of Construction and Demolition Waste Using Weighted Combined Grey Theory and Autoregressive Integrated Moving Average Model

Fang,

Shi,

Chen

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…The grey model, which is constructed from the grey system theory, focuses on the insufficient information available, or the uncertainty of information that is [ 29 ]. It has been extensively utilized in the industries of finance, economics and the quantification of construction waste generation [ 30 ]. A major advantage of this method is that it can help predict problems with less data [ 29 ], which is extremely suitable for the current study.…”

Section: Methodsmentioning

confidence: 99%

Estimating the Carbon Emission of Construction Waste Recycling Using Grey Model and Life Cycle Assessment: A Case Study of Shanghai

Wang

Liu

et al. 2022

IJERPH

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Great efforts have been exerted in reducing carbon emissions in design, construction and operation stages. However, little attention is paid to the quantification of carbon emissions in construction waste recycling at the end-of-life stage. This study aims to quantitatively analyze the carbon emission of construction waste in Shanghai City, PR China. A grey model is used to forecast the generation amount of construction waste, and a life cycle assessment is performed to estimate the carbon emission of construction waste. In this study, both the carbon emission of recycling activities (environmental costs), and the equivalent amount of carbon generated from alternative materials (environmental benefit) are considered. Here, recycling 1 ton (t) of construction waste in Shanghai can save 100.4 kg CO2−e. The total carbon-emission-saving potential can be increased from 0.31 million t CO2−e (2022) to 0.35 million t CO2−e (2031). The carbon emission of recycling concrete, brick, steel, wood and mortar, identified as the key components of construction waste, is investigated. This research can help to reduce carbon emissions and further achieve carbon neutrality for Shanghai City. The proposed methods can also be applied to other regions, especially when the data for construction waste are insufficient.

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“…Shenzhen), C&D waste is transferred to less-developed neighbouring regions in China (Zheng et al, 2017). Even worse, waste producers may illegally dump waste at unpermitted areas, such as farmlands, abandoned residential lands, borrow pits, river sides and low-lying areas in nearby cities (Ding et al, 2019b).…”

Section: Overseas Policies and Strategies In Randr Waste Managementmentioning

confidence: 99%

Minimisation and management strategies for refurbishment and renovation waste in Hong Kong

Mok

Wong

2021

ECAM

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PurposeThe capacity of landfills will reach saturation in the 2020s. There are more than 50,000 buildings in Hong Kong over 30 years old and which may require extensive refurbishment under the Mandatory Building Scheme. Additionally, most new owners/tenants tend to renovate their premises before moving in. Hence, there is an urgent need in Hong Kong, to explore strategies and measures to enable the development of effective refurbishment and renovation (R&R) waste management for such projects. The objectives of this paper are to investigate the process of R&R for identifying the perceived barriers and thereby the strategies for minimisation and management of R&R waste in Hong Kong.Design/methodology/approachDesktop study, semi-structured interviews, site observations and document reviews were used as the data collection methods to achieve the objectives of this research. Considering the nature and characteristics of the industry structure, the snowball sampling process was deployed for data collection. Thematic analysis and content analysis were used for data analysis. Waste minimisation and management strategies for R&R projects were then discussed and developed by the research team and a focus group meeting was held to validate the research findings. Six strategies were then proposed to the government.FindingsR&R projects contribute 10–20% of the construction and demolition waste. The barriers to recycling of R&R waste can be grouped into six major categories: (1) lack of sorting and storage spaces, (2) high cost, (3) insufficient government supporting policy, (4) complicated recycling processes, (5) immature recycling market and (6) insufficient public education. Also, six strategies are proposed in this study, which include (1) pre-refurbishment audit, (2) development of recycling market, (3) sea reclamation, (4) incineration, (5) government support and (6) education and research.Originality/valueThe strategies and measures proposed in this research could most adequately serve as reference for the government officials, building professionals and academic researchers. Such knowledge would make possible the development of effective strategies and measures for minimising and managing R&R waste.

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Predicting Renovation Waste Generation Based on Grey System Theory: A Case Study of Shenzhen

Cited by 15 publications

References 31 publications

Quantity Prediction of Construction and Demolition Waste Using Weighted Combined Grey Theory and Autoregressive Integrated Moving Average Model

Quantity Prediction of Construction and Demolition Waste Using Weighted Combined Grey Theory and Autoregressive Integrated Moving Average Model

Estimating the Carbon Emission of Construction Waste Recycling Using Grey Model and Life Cycle Assessment: A Case Study of Shanghai

Minimisation and management strategies for refurbishment and renovation waste in Hong Kong

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