Use of recycled construction and demolition waste in the landscape industry

Salman Shooshtarian1, Mohammad Reza Hosseini2

1RMIT University, School of Property, Construction and Project Management, Melbourne Australia,

2Deakin University, School of Architecture and Built Environment, Geelong, Australia

Increased construction activities around the world has led to the generation of excessive construction and demolition (C&D) waste annually. Hence, the C&D waste stream has become a national concern in many developed and developing nations in recent years. Several studies have provided solutions to improve current C&D waste systems. Among various solutions, the establishment of a domestic market has been highlighted as an effective and sustainable solution to this issue. The development of a domestic market largely hinges on unlocking new applications for valuable C&D waste materials. This review paper investigates the potential application of these materials in the landscape industry with a focus on boosting C&D waste resource recovery activities. Some past and new applications are identified (green roof substrate, green façade, sports surface construction, soil amendment,  vegetated surface mulch, vegetated permeable pavement) in this study, setting the scene for further inquiries into upcycling between the construction industry and the landscape industry. Also, the results provide a basis for policy development to encourage waste recovery and increase public and key stakeholders’ awareness and further incorporate the principles of the circular economy. 

  

Keywords: Circular economy; waste resource recovery; upcycling; market development; green infrastructure

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Comparison of regression methods for predicting soil water contents at field capacity and wilting point in Bas Sahara of Algeria

 Youcef ABDELHAFID1&3 *, Mohamed CHEBBAH2 and Milad Zohra RECHACHI3

 

1Department of Agronomic Sciences, Faculty of  Natural Sciences and Life Sciences, University of Biskra, Biskra 07000, Algeria

2 Laboratory of Natural Sciences and Materials, university of Mila, 43000, Algeria

3Center for scientific and technical research on arid regions, CRSTRA, BP N1682, Biskra, Algeria

* Correspondence: This email address is being protected from spambots. You need JavaScript enabled to view it.

 In arid regions, the rational management of available scare water ressources depends mainly on soil hydraulic properties (i.e., water retentionand hydraulic conductivity). knowledge of soil water content at field capacity (FC) and permanent wilting point (PWP) are very important parameters in biophysical modelling. However, direct measurement of these parameters are time consuminng and expensive. Using data mining methods enable accurate estimations and good generalisation of these parameters. 120 soils samples were collected from three  horizons of soil profils located in Biskra province, bas Sahara of Algeria. The pedologic parameters, such as clay, silt, sand, bulk density, and organic matter content were used as inputs. Three approachs were considered, multiple lineaire regression (MLR), multilayer perception (MLP) and support vector machine (SVM) for predicting soil water contents at field capacity (FC) and permanent wilting point (PWP). The model performance was evaluated and compared with coefficient of deternination (R2), root mean square error (RSME), and mean error (ME) indexes. The results obtained in our study show that both artificial intelligence algorithms MLP and  SVM are able to provide better performances than the conventinel MLR. Also, it was found that the MLP model performs somewhat better than SVM in the model prediction stage.

 

Keywords: Bas Sahara, Field capacity, Multilayer perception, Permanent wilting, point, Regression, Support vector machine

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