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Go to Editorial ManagerMunicipal solid waste management in Syria remains primitive in many cases, both in terms of waste collection and disposal methods, particularly in areas that have experienced severe population density due to the war. Waste recycling processes are neglected, and waste is often disposed of in specific plots of land, often far from residential areas. This research aims to identify criteria related to decision-making for selecting the optimal site for a landfill, in line with the local context and Syrian conditions. This was achieved by reviewing several previous studies and interviewing local experts interested in this type of research. (21) criteria were identified and divided into (6) main groups: (environmental criteria, site-related criteria, external and weather conditions, economic and social criteria, and criteria related to sustainable transportation). The relative importance of these criteria was then calculated using the Fuzzy Hierarchy Process (FAHP). After obtaining the weights, these criteria were used to evaluate the current site of the Safita landfill using the Fuzzy Inference System (FIS). The evaluation results were very weak due to decision makers' neglect of many factors and conditions that must be met at the selected site. A set of recommendations and proposals were identified for consideration when selecting the optimal site for a landfill, consistent with the local context of the study area (Syria), and for improving existing sites.
The Light Falling Weight Deflectometer (LFWD) was developed to estimate the in-situ elastic modulus directly to the layers near the base as subgrade and subbase layers. The field tests were carried out on selected sections from landfill project within Anbar Province. Furthermore, Forty test sections have been constructed and tested at the Civil Engineering Department- University of Anbar. All sections were tested using the ZFG 3000 model - LFWD in companion with the Plate Load Test (PLT) which were used as reference measures. Regression analyzes were performed to determine the best correlation between the elastic modulus obtained from LFWD and PLT tests. ANN model was used to calculate Evd and compare the regression statistical model. It was found that the ANN model showed a higher performance than regression analysis in predicting Evd. Satisfactory correlations were obtained, which showed that LFWD could be a promising device for in-situ characterizing of subsurface and subgrade layers.