Municipal Solid Waste Landfill Site Selection Based on Fuzzy-AHP and Geoinformation Techniques in Asir Region Saudi Arabia

Integrating fuzzy-AHP and GIS for solid waste disposal site selection in Kenitra province, NW Morocco

Selecting an optimal solid waste disposal site is one of the decisive waste management issues because unsuitable sites cause serious environmental and public health problems. In Kenitra province, northwest Morocco, sustainable disposal sites have become a major challenge due to rapid urbanization and population growth. In addition, the existing disposal sites are traditional and inappropriate. The objective of this study is to suggest potential suitable disposal sites using fuzzy logic and analytical hierarchy process (fuzzy-AHP) method integrated with geographic information system (GIS) techniques. For this purpose, thirteen factors affecting the selection process were involved. The results showed that 5% of the studied area is considered extremely suitable and scattered in the central-eastern parts, while 9% is considered almost unsuitable and distributed in the northern and southern parts. Thereafter, these results were validated using the area under the curve (AUC) of the receiver operating characteristics (ROC). The AUC found was 57.1%, which is a moderate prediction's accuracy because the existing sites used in the validation's process were randomly selected. These results can assist relevant authorities and stakeholders for setting new solid waste disposal sites in Kenitra province.

Evaluating sustainable municipal solid waste management scenarios: A multicriteria decision making approach

Due to increasing urbanization and population growth, municipal solid waste management (MSWM) is a significant environmental concern in developing countries. Inadequate waste management systems lead to environmental pollution, health hazards, and economic losses. While considering the challenges and limitations, policymakers and authorities need to opt for such waste management scenarios that are environmentally friendly and resolve energy issues. Ten MSWM scenarios were developed and evaluated using seven different criteria. Four multi-criteria decision-making (MCDM) techniques, namely fuzzy logic, AHP, TOPSIS, and PROMETHEE II, were employed to rank the scenarios and identify the most appropriate option for solid waste management in Lahore. This study highlights that the optimal waste management approach comprises a composition of 54% anaerobic digestion, 37% gasification, and 9% landfill technologies. These percentages collectively represent the most suitable and effective strategies for the city's waste management needs. All the MCDM techniques consistently produce similar results. These scenarios have broader applicability across cities in Central Asia and beyond. The study's findings are aligned to promote sustainable and environmentally friendly MSWM practices. These findings endorse implementing strategies and measures aimed at fostering environmental sustainability and the responsible handling of waste, serving as a valuable reference for various regions.

Assessment of inorganic solid waste management techniques using full consistency and extended MABAC method

Population and industrial growth have spiked product consumption, which in turn have caused an abrupt rise in municipal solid waste (MSW) production. Due to the lack of resources allocated to waste management, municipal inorganic solid waste (ISW) has increased exponentially, posing a significant strain on the environment and health. To mitigate these issues, sustainable waste management strategies need to be implemented to reduce environmental impacts and improve waste collection and disposal efficiency. The objective of our work was to analyse and identify the most effective techniques for disposing of ISW in India by employing multi-criteria decision-making (MCDM). This technique entails selecting the most suitable alternative based on a variety of competing and interactive criteria. A fusion decision model named the FULL COnsistency Method (FUCOM) and Multi-Attributive Border Approximation area Comparison (MABAC) based on the interval-valued q-rung orthopair fuzzy (IV q-ROF) was developed. Finally, a comparative analysis was performed to demonstrate the system's robustness.

Application of high-dimensional uniform manifold approximation and projection (UMAP) to cluster existing landfills on the basis of geographical and environmental features

Due to extreme conditions, which are influenced by the location of landfills, the release of pollutants has been recently proven to be more severe in estuary landfills, as these landfill locations are affected by both sea-water and river-water interactions. To identify geographic and environmental features linked to the extreme conditions of certain landfills, a high-dimensional clustering method combining Uniform Manifold Approximation and Projection (UMAP) with the Louvain algorithm is proposed. A case study was conducted using 17 noteworthy features that transform to Landfill Suitability Index (LSI) applied to hundreds of landfill sites in Taiwan. This study clustered landfills into 10 clusters and identified several clusters with significant extreme locations, including estuary landfills (7.9 %), fault-water-body landfills (8.2 %), and densely-populated-water-body landfills (17.6 %). Furthermore, a critical discovery of endangered Platalea minor habitats near these estuary landfills was made. Additionally, this work identified "healthy" landfills (11.2 %) that are minimally affected by the considered features. These findings demonstrate the promising potential of our framework for managers to systematically improve landfill management strategies. Moreover, our framework was tested by incorporating rainfall and flooding features in relation to climate change scenarios. To address the demand for land release from occupied landfills in Taiwan, there is a pressing need to expedite the transition to a circular economy, and our framework can provide further assistance in this regard. This approach is promising, as it provides a new method to evaluate the environmental risks linked to landfills and also identifies potential opportunities related to landfill mining. Finally, this work was extended to include a case study in England, which has 19,801 landfills and a dataset containing 15 relevant landfill features; in this case study, our framework identified 110 landfill clusters, and several placed in extreme locations, demonstrating that our framework is flexible for use in other regions outside of Taiwan.

QGIS-based weighted linear combination plugin for landfill site selection: a case study in Tokat Province, Turkey

Proper disposal of solid waste is crucial for the protection of natural resources and human health. However, increasing population and changes in consumption habits have led to a global increase in solid waste production. Therefore, a site selection process for solid waste management that takes into account environmental, economic, and social factors is needed. The number of open-source GIS (geographic information system) software programs used in site selection analysis is increasing day by day. QGIS software is an open-source GIS software developed by free software developers, with its popularity increasing with each new version and allowing for the development of plugins with the Python programming language. The shareability of plugins developed with QGIS software brings together open-source GIS users around the world for common goals. In this study, a plugin called "LANDFILL SITE SELECTION (LFSS)" was developed in the QGIS software environment for solid waste landfill site selection and a suitability map was created for solid waste landfill site selection in Tokat, Turkey, using this plugin. For this purpose, 14 evaluation criteria and 8 exclusion criteria were selected, the importance levels of criteria and sub-criteria were determined using the AHP method, and a solid waste landfill site selection suitability map was created using the developed plugin.

Site suitability analysis for sanitary landfills using geospatial methods in a part of southern Peninsular Malaysia

Globally, around 1.3 billion tonnes of waste are generated annually, and solid waste management has thus become a major concern worldwide. There are projections of a 70% increase in waste generation from 2016 to 2050 owing to urbanization and the rapid growth of the global population. Estimates indicate that around 38,200 tonnes of waste are generated per day in Malaysia, and this volume of waste is significantly shortening the planned life spans of operating sanitary landfills in the country. Batu Pahat is a district in the state of Johor, Malaysia, with a relatively large population of 495,000 and with no record of an operational sanitary landfill. This study was conducted to identify and classify the most suitable sites for sanitary landfill developments in southern Peninsular Malaysia by means of the Analytical Hierarchy Process (AHP), which is recognized as a competent technique for multicriteria decision-making. The resulting landfill site suitability index map established 33.88 km2 of area coverage as very highly suitable for landfill development, while 353.86 km2 of area coverage was classified as unsuitable. Sites 1-6 were identified as the most suitable for landfill activities. Sites 1-5 are situated in agricultural land areas, while site 6 is in a forested land area; this implies public participation and the adoption of compensatory measures in the event of landfill development in these areas, given their socioeconomic importance. The six suitable sites are all at least 2000 m from rivers: 2000-3000 m for sites 1, 3, and 5 and > 3000 m for sites 2, 4, and 6. The six sites are all > 3000 m from fault zones and > 1000 m from flood-prone areas, meaning that occurrences such as fault movements and flooding will have minimal impact on the operational activities of landfills at these sites. The selection of sites 1-6 as very suitable for landfill development was associated with an overall accuracy rating of 93.33% and kappa coefficient score of 0.92 based on accuracy assessment analysis of all sites. This study will guide the actions of policymakers, city planners, and local authorities toward sustainable and environment-friendly landfill development and operation in Batu Pahat and other districts in the state of Johor.

Satellite Data Potentialities in Solid Waste Landfill Monitoring: Review and Case Studies

Remote sensing can represent an important instrument for monitoring landfills and their evolution over time. In general, remote sensing can offer a global and rapid view of the Earth's surface. Thanks to a wide variety of heterogeneous sensors, it can provide high-level information, making it a useful technology for many applications. The main purpose of this paper is to provide a review of relevant methods based on remote sensing for landfill identification and monitoring. The methods found in the literature make use of measurements acquired from both multi-spectral and radar sensors and exploit vegetation indexes, land surface temperature, and backscatter information, either separately or in combination. Moreover, additional information can be provided by atmospheric sounders able to detect gas emissions (e.g., methane) and hyperspectral sensors. In order to provide a comprehensive overview of the full potential of Earth observation data for landfill monitoring, this article also provides applications of the main procedures presented to selected test sites. These applications highlight the potentialities of satellite-borne sensors for improving the detection and delimitation of landfills and enhancing the evaluation of waste disposal effects on environmental health. The results revealed that a single-sensor-based analysis can provide significant information on the landfill evolution. However, a data fusion approach that incorporates data acquired from heterogeneous sensors, including visible/near infrared, thermal infrared, and synthetic aperture radar (SAR), can result in a more effective instrument to fully support the monitoring of landfills and their effect on the surrounding area. In particular, the results show that a synergistic use of multispectral indexes, land surface temperature, and the backscatter coefficient retrieved from SAR sensors can improve the sensitivity to changes in the spatial geometry of the considered site.

Sustainable assessment of plastic and mixed waste disposal problem during COVID-19 pandemic: an integrated multi-criteria decision-making approach

This article focuses on India's inorganic solid waste disposal problem, with a particular emphasis on plastic and mixed waste. It aims to identify the current COVID-19 pandemic situation as well as provide a suitable disposal technique for wastes that are specifically related to municipal solid waste management. We propose an integrated approach to disposing of paper and plastic and mixed wastes in an interval-valued q-rung orthopair fuzzy (IVq-ROF) environment for this problem. In this case, we use the FUCOM method to calculate the weight values of the criteria and the MABAC method to rank the alternatives based on the chosen criteria. To confirm the effectiveness of the proposed method, a numerical illustration is provided, and validation of the suggested method is also shown.

Geospatial alternatives for quantification of bio-thermal influence zone in the vicinity of a solid waste dump

Owing to the release of toxic gases, leachate and thermal emissions that originate from waste dumps, these sites significantly impact environmental sustainability. The study attempts to assess the deleterious impact of municipal solid waste (MSW) dump on surrounding forested landscape by employing geospatial technologies, which are cost and time-effective. For this purpose, temporal period ranging from 2015 to 2020, having 41 valid satellite observations has been selected for study. Firstly, the radii of intense hazardous zone and hazardous zone have been measured, as two separate parameters, which are 580 ± 30 m and 1260 ± 30 m, respectively. Secondly, average spatial extent of bio-influence zone is measured to be 1262 m while the average thermal influence zone extends up to 530 m around the MSW dumping site. A detailed analysis of influence zone variations reveals that the bio-influence zone depends on multitude of meteorological parameters, whereas the thermal influence zone relies mainly on seasonal temperature fluctuations. Moreover, the level of severity of emissions from MSW decomposition directly depends upon temperature. The long-term variability analysis of these hazardous zones reveals the stationarity of their spatial extents, signifying forest resilience. This study has proved significance of geospatial techniques as an alternate of expensive and time intensive assessment methods involving in situ measurements. So the proposed technique is beneficial for environmentalists, decision-makers and municipal authorities for analysing the extent and severity of MSW pollutants for forest community to address the problem of ecological degradation.

Integration of LCSA and GIS-based MCDM for sustainable landfill site selection: a case study

The paper aims at developing a framework for decision-support to select a sustainable landfill site in Bardaskan City (Iran) by combining life cycle sustainability assessment (LCSA) concepts and geographic information system (GIS)-based multi-criteria decision-making (MCDM). Overall, 13 criteria were chosen (three constraints and 10 factors) and classified into three main aspects of sustainability (i.e., environmental, social, and economic) to achieve the research goals. Boolean and fuzzy logic were employed to standardize the classified constraints and factors, respectively. Analytic hierarchy process (AHP) was used to calculate the factors' weights and then suitability maps were produced using the GIS analysis. The layers were combined using simple additive weighting (SAW). Next, the most sustainable sites were obtained. The results indicated that distance from city backline, groundwater depth, and distance from rural areas were the most significant factors with the weight of 0.338, 0.141, and 0.129, respectively. The final map of suitable sites was created by classifying the SAW layer according to 75, 80, and 85% of suitability to show the high, medium, and low priority areas for landfill site selection, respectively. Therefore, integration of LCSA and GIS-based MCDM to select the sustainable landfill site for municipal solid waste (MSW) is highly important, which can be effectively employed in regional and urban planning to select the location of appropriate and sustainable landfills.

Sanitary landfill site selection using GIS-based on a fuzzy multi-criteria evaluation technique: a case study of the City of Kraljevo, Serbia

Adequate disposal of municipal solid waste (MSW) is one of Serbia's most complex environmental challenges. The problem is more serious in urban areas, since large amounts of waste are disposed of in locations that do not comply with environmental, technical, and socio-economic standards. Such is the case for the city of Kraljevo, where about 116,000 inhabitants do not have a sanitary landfill facility. This research includes a multi-criteria analysis, conducted with the help of geographic information systems, to find a suitable landfill site location. After data collection, the first step was to process 15 environmental and socio-economic factors utilizing the fuzzy analytic-hierarchy process method. The second step comprised the visual analysis and selection of the ten most suitable locations from the synthetic convenience map. The third step involved the final ranking of sites by means of the fuzzy multi-objective analysis by ratio, plus the full multiplicative form method, based on four additional beneficial and non-beneficial criteria. The results show that sanitary landfill candidate site A4 is the most suitable location for constructing a sanitary landfill site due to its large area (569 ha) and relatively short distance from the urban zone (8 km). This study is the first to integrate geographic information systems and the fuzzy analytic-hierarchy process, multi-objective analysis by ratio, and the full multiplicative form algorithm for sanitary landfill selection. The results of the research can be used as a reference for safe waste disposal in the city of Kraljevo.

Identification and selection of suitable landfill sites using GIS-based multi-criteria decision analysis in the Peshawar District, Pakistan

Managing municipal solid waste (MSW) is indispensable for public health and quality living standards in urban and rural environments. Suitable landfill site selection (LSS) requires the consideration of many diverse criteria. This study uses various environmental, social and economic criteria in a sophisticated multi-criteria decision analysis (MCDA) within the geographical information system (GIS) and aims to provide a scientific basis for the identification of suitable landfill sites which can efficiently be used for MSW in one of the most urbanized cities (Peshawar district) in Pakistan. The methodology involves pairwise comparisons of the selected and ranked criteria using the analytical hierarchy process (AHP). A weighted linear combination (WLC) was applied to generate the most suitable landfill site for MSW disposal within the study area. The results show that approximately 11.4% (14,485.15 ha) and 16.6% (21,211.95 ha) of the total study area are either very highly suitable or highly suitable, 20.8% (26,525.56 ha) area is unsuitable and the remaining areas are either low (27.3%; 34,834.84 ha) or moderately suitable (23.8%; 30,356.84 ha) for the construction of landfill sites. It is recommended that using the proposed landfill sites would have the least consequences of public health risks and environmental degradation.

MCA and geospatial analysis-based suitable dumping site selection for urban environmental protection: A case study of Shambu, Oromia Regional State, Ethiopia

A lack of suitable dumping sites in a town or city can have an impact on the health of the residents as well as the quality of the urban environment. There are no identified dumping sites in this study area that meet scientific or urban standards. Residents are dumping solid waste into ditches, roads, public water sources, and small streams. The solid and liquid wastes generated by residential areas, state prisons, religious areas, public markets, and business centers have a negative impact on the town. The purpose of this study is to demonstrate the novelty of using Multi-Criteria Analysis (MCA)-based geospatial analysis to select suitable dumping sites in Shambu town. Key factors for dumping site selection, such as LULC, road networks, private well locations, slope, geomorphology, geology, soil texture, drainage density, and lineament density, were confirmed as geospatial analysis criteria. In the Analytical Hierarchy Process (AHP), the importance of the key factors was weighted and prioritized, and thematic maps were created using weighted overlay analysis. The suitable dumping sites were identified using qualitative classifications such as ^“highly suitable^” (13.84%), ^“moderately suitable^” (7.35%), ^“less suitable^” (30.41%), and ^“not suitable^” (48.40%). The consistency of AHP was determined to be CI = 0.012, indicating that the weights assigned to each factor were correct. As a result, the use of geospatial and MCA analysis for dumping site suitability analysis was successful, and the findings of this study will be useful in taking action to reduce the impacts of solid waste by developing dumping plants on the identified sites.

Optimal Waste-to-Energy Strategy Assisted by Fuzzy MCDM Model for Sustainable Solid Waste Management

In Vietnam, rapid population and economic growth are responsible for the recent increase in solid waste. Energy production from waste is now becoming an effective solution around the world, especially in Vietnam, to solve environmental challenges while contributing to the country’s sustainable energy production. Waste-to-energy production has become a solution to the municipal solid waste problem, which is projected to increase by 10–16%. In this study, the author proposed a fuzzy MCDM model to assess and select a solid-waste-to-energy plant location in Vietnam. In the first stage, the fuzzy analytic hierarchy process (FAHP) technique is utilized to analyze the relative weight of the primary and secondary evaluation elements, and a combined compromise solution (CoCoSo) model is used to rank the candidates in the final stage. This is the first solid-waste-to-energy plant location evaluation and selection model used in a renewable energy project in Vietnam based on expert interviews and a literature review. This study’s contribution can be a significant guide in analyzing and selecting appropriate locations for solid-waste-to-energy projects, as well as for decision makers and investors in other renewable energy projects in Vietnam and throughout the world.

Identifying and Ranking Landfill Sites for Municipal Solid Waste Management: An Integrated Remote Sensing and GIS Approach

Disposal of municipal solid waste (MSW) is one of the significant global issues that is more evident in developing nations. One of the key methods for disposing of the MSW is locating, assessing, and planning for landfill sites. Faisalabad is one of the largest industrial cities in Pakistan. It has many sustainability challenges and planning problems, including MSW management. This study uses Faisalabad as a case study area and humbly attempts to provide a framework for identifying and ranking landfill sites and addressing MSW concerns in Faisalabad. This method can be extended and applied to similar industrial cities. The landfill sites were identified using remote sensing (RS) and geographic information system (GIS). Multiple datasets, including normalized difference vegetation, water, and built-up areas indices (NDVI, NDWI, and NDBI) and physical factors including water bodies, roads, and the population that influence the landfill site selection were used to identify, rank, and select the most suitable site. The target area was distributed into 9 Thiessen polygons and ranked based on their favorability for the development and expansion of landfill sites. 70% of the area was favorable for developing and expanding landfill sites, whereas 30% was deemed unsuitable. Polygon 6, having more vegetation, a smaller population, and built-up areas was declared the best region for developing landfill sites and expansion as per rank mean indices and standard deviation (SD) of RS and vector data. The current study provides a reliable integrated mechanism based on GIS and RS that can be implemented in similar study areas and expanded to other developing countries. Accordingly, urban planning and city management can be improved, and MSW can be managed with dexterity.

A GIS-based novel approach for suitable sanitary landfill site selection using integrated fuzzy analytic hierarchy process and machine learning algorithms

Disposal of waste without treatment is the least preferable way of sustainable solid waste management (SWM). But most cities in developing nations still use open dumps, causing negative impacts on the environment and human health. This study offered a novel approach for selecting landfill sites and sustainable SWM in Aligarh city, India. This was done through data collection, selecting models for criterion weighting, and validation. In order to prepare a landfill site suitability map, a geographic information system (GIS)-based ensemble fuzzy analytic hierarchy process-support vector machine (FAHP-SVM) and fuzzy analytic hierarchy process-random forest (FAHP-RF) models were implemented. Considering the previous studies and the study area characteristics, eighteen thematic layers were selected. The result revealed that land value; distance from residential roads, hospitals and clinics, and waste bins; and normalized difference built-up index (NDBI) have a fuzzy weight greater than 0.10, indicating significant factors. In contrast, land elevation, land slope, surface temperature, soil moisture index, normalized difference vegetation index (NDVI), and urban classification have a zero fuzzy weight, indicating these criteria have no importance. The result further revealed that FAHP-RF with an area under curve (AUC) value of 0.91 is the more accurate model than FAHP-SVM. According to the final weight-based overlay result, seven potential landfill sites were identified, out of which three were determined as most suitable by considering current land cover, public opinions, and environmental and economic concerns. This research proposed a zonal division model based on landfill sites location for sustainable SWM in Aligarh city. However, the findings may provide a guideline to the decision-makers and planners for optimal landfill site selection in other cities of developing countries.

Sustainability Assessment of Municipal Solid Waste in Riyadh, Saudi Arabia, in the Framework of Circular Economy Transition

Life cycle assessment (LCA) tools can be used for the environmental assessment of municipal solid waste management (MSWM) systems. The present study aims to evaluate the impact of an MSWM system in Riyadh, Saudi Arabia, under three different scenarios based on the Strategy for 2045 of Riyadh. The current scenario (S0) considers that municipal solid waste (MSW) is landfilled, scenario one (S1) considers waste to energy (WtE) as the main treatment while dry recyclables and organic waste collection schemes are introduced, and scenario two (S2) considers dry recyclables and organic waste collection schemes at the maximum level while the residual portion is treated as WtE. The system boundaries include MSW treatment and disposal by recycling, incineration, composting, and landfilling methods. The scenarios were compared using SimaPro 9.1.1.1 software, and the ReCiPe 2016 Midpoint (H) V1.04/World (2010) H method was used to assess global warming, ozone formation (human health), fine particulate matter formation, terrestrial acidification, freshwater eutrophication, mineral resource scarcity, and fossil resource scarcity. S0 was found to be the scenario with the least impact if considering just the waste treatment. However, S1 and S2 allow material and energy recovery that avoids the impact of obtaining primary resources. S1 and S2 reduced greenhouse gases (GHG) emissions by 55% and 58%, respectively, compared to S0. According to the SV2030, 2% of the electricity generated by the Kingdom would have to come from WtE, but based on the calculations, the maximum electricity from waste would be obtained with S1 fully implemented and would contribute a maximum of 1.51% to Saudi Arabia’s electricity demand. This study contributes by providing useful insights that could help decision-makers to understand the potential environmental impacts by assessing each step considered by the Strategy for 2045 for Riyadh along with the consequences on material and energy supply by using the material and energy potential of MSW.

Qualitative and Quantitative Characterization of Municipal Waste in Uncontrolled Dumpsites and Landfills Using Integrated Remote Sensing, Geological and Geophysical Data: A Case Study

The conducted research offers an environmental assessment of municipal waste (MW) using remote sensing (RS), geological, and geophysical datasets. As a test site, the present study aims to characterize one of the largest uncontrolled dumpsites in Egypt. RS data analysis indicates that high temperature values are concentrated at the MW and landfill site allocations as a result of the decomposition process, leading to fire risks. Moreover, the geological and structural data draw attention to the structural-controlled old topography role on MW distributions. Consequently, the dumpsite MW has larger surface quantities near the downthrows of the mapped faults. For MW characterization, geophysical data are acquired to produce2D/3D resistivity models. Because MW has the ability to become soft clay, the municipal organic waste and landfill leachate resistivities are lower than that of municipal solid waste and sandy soils. The geophysical inversion results indicate that the maximum thickness of MW calibrating with the drilled borehole data is 60 m. Furthermore, the estimated MW dumpsite volume is about 42.32 MCM. Accordingly, the MW can be characterized in an accurate qualitative and quantitative manner. Our findings, therefore, help the efforts of uncontrolled dumpsite development and thus contribute to sustainability plans.

A GIS-Based Method for Identification of Blindness in Former Site Selection of Sewage Treatment Plants and Exploration of Optimal Siting Areas: A Case Study in Liao River Basin

With regard to environmental facilities, blindness and the subjectivity of site selection lead to serious economic, engineering and social problems. A proper siting proposal often poses a challenge to local governments, as multiple factors should be considered, such as costs, construction conditions and social impact. How to make the optimal siting decision has become a topical issue in academic circles. In order to enrich the framework of site selection models, this study combined GIS, AHP and Remote Sensing (RS) technologies to conduct siting suitability analysis of sewage treatment plants, and it was first applied in the Liao River basin in Jilin Province in China. The enriched model is able to reveal blindness in the former site selection of sewage treatment plants and explore optimal siting areas, involving an effective quantification method for summer dominant wind direction and urban stream direction. In a case study, it was found that local governments need to be cautious of the distance of sites from rivers and residential areas and the impact of these sites on downwind and downstream residents. Additionally, siting suitability has obvious regional characteristics, and its distribution varies significantly between towns. Huaide Town shows the largest optimal siting areas and can be given priority for the construction of new sewage treatment plants. This paper developed a more scientific approach to site selection, and the outcome can provide a robust reference for local governments.

Factors Determining Suitable Landfill Sites for Energy Generation from Municipal Solid Waste: A Case Study of Jabodetabek Area, Indonesia

Most municipal solid waste (MSW) is found to be dominated by organic debris, which has excellent potential as an energy source. However, the main problems of this material are poor planning, urban expansion, and lack of management skills. All these problems are presently being encountered by the regional governments of Jakarta, Bogor, Depok, Tangerang, and Bekasi city (known locally as Jabodetabek), Indonesia. In the MSW management system, a vital planning protocol is reportedly assessing suitable landfill sites for energy generation, although this selection process is still a complex task that should consider various factors, such as environmental, social and safety, and economic variables. Therefore, this study aims to examine various factors in determining a suitable location for landfills. It also aims to identify the various factors required for MSW energy generation. Based on this study, a multicriteria decision analysis (MCDA) approach was applied to weigh the factors determining the appropriate location. This approach is popular in decision-making due to evaluating the complexity of multidimensionality factors. The results showed that 3 factors and 14 subfactors were formulated and structured in the MCDA hierarchy, with their information obtained to create pairwise comparisons by 10 involved experts. In this study, the MCDA output was the weight value associated with a systematic priority level, indicating that the environment was the highest factor in determining a suitable landfill site for energy generation. In addition, the weight factors were used for overlay analysis, in determining the suitable site for future energy generation studies.

What Influences Consumers to Recycle Solid Waste? An Application of the Extended Theory of Planned Behavior in the Kingdom of Saudi Arabia

This extant study attempts to present a comprehensive predictive model for solid waste recycling behavior. Solid waste is a major environmental concern globally. Particularly, the kingdom of Saudi Arabia (KSA), being the larger gulf country in the Middle East is a major contributor to solid waste. Consequently, this study was carried out to identify the motivational factors that consumers consider important for recycling their household waste. We extended the theory of planned behavior (TBP) and utilized actual behavioral variables such as resell, reuse, and donation. A structured questionnaire was carried out with 365 purposively selected respondents in the KSA. Among several other noteworthy findings consistent with previous studies, we found that reselling was the most significant factor of recycling behavior followed by donation. Further, the multi-group analysis (MGA) results reveal significant group differences in gender and age variables; the significance test indicates that the male group has much better pro-environmental behavior than the female group. In terms of age, our results showed that recycling intention and reselling behavior passed a significant test in the elderly group when compared to a younger group. This study has unique contributions and findings leading to practical implications for government authorities, businesses, and non-governmental organizations. The findings will particularly aid in increasing the recycling intention and behavior among household consumers. This research will guide in making laws and policies that can help to embrace the green challenges and boost recycling activities for a sustainable environment.

GIS-Based Decision Support System for Safe and Sustainable Building Construction Site in a Mountainous Region

The site selection process for a building entails evaluating a variety of factors with varying degrees of importance or percentage influence. In order to ensure that critical site selection factors are not overlooked, a methodology for calculating a building’s safe site selection must be developed. The study identified three broad aspects widely considered in site selection, namely environmental, physical, and socioeconomic criteria. To assess the safest site selection of residential building construction for sustainable urban growth, we used GIS-based multi-criteria decision-making approach that combined Fuzzy-AHP and weighted linear combination (WLC) aggregation method used to calculate the SSPZ. The final safe site suitability map was generated by aggregating all aspects such as geophysical, socio-economic and Geo-environmental thematic layers and their associated Fuzzy-AHP weights using the weighted linear combination method. The sites potential index’s mean value of 0.513 with standard deviation of 0.340, minimum and maximum GeoPhySSSI are 0.0 and 0.91, respectively, SSS index is classified into zones by histogram profile using natural breaks (jenks)” Subsequently, safe sites identified and divided into six classes namely no construction, very low suitable site low suitable site, moderate suitable site, high suitable site, and very high suitable site.“ According to the statistical analysis, 3.64% and 32.12% of the total area were under very high and high SSSZ, while 26.40% and 6.22% accounted to the moderate and low suitable potential, respectively” Our findings suggest that integrating the fuzzy collection with AHP is highly desirable in terms of alternative and decision-making effectiveness. The study reveals that the areas of high and moderate suitability are located near existing habitant area, major roads, and educational and health services; they are not located in restricted/protected areas or are vulnerable to natural hazards. The findings indicate that unsuitable and less-suitable land uses such as vegetation, protected areas, and agriculture lands cover nearly one-third area of Abha-Khamis Mushyet regions, implying that using Fuzzy-AHP and GIS techniques will significantly aid in the conservation of the environment. This would significantly mitigate adverse effects on the ecosystem and climate.

A GIS-based multi-criteria decision-making method for the selection of potential municipal solid waste disposal sites in Mersin, Turkey

Due to rapid urbanization and the resulting rapid population increases, an important problem for cities today is the elimination of solid waste or finding suitable places for waste storage. Municipal solid waste disposal (MSWD) site selection is one of the most important steps in urban waste management. Many criteria political, economic, social, and technological should be considered in this process. Geographic information systems (GIS) and multi-criteria decision-making (MCDM) are tools that are superior to traditional methods in the planning phase of site selection studies. In this study, suitable MSWD sites were determined in Mersin (a Turkish province) based on GIS and the analytic hierarchy process, an MCDM method. Unsuitable areas in the study were removed at the beginning of the analysis. Eleven evaluation criteria were selected: elevation, slope, permeability, distance from lineaments, groundwater level, distance from rivers and water surfaces, distance from roads, distance from settlements, distance from protected areas, and land cover. Considering the evaluation and exclusion criteria, 19.12% of the study area was deemed suitable, and 80.88% was determined unsuitable for an MSWD site. An MSWD suitability map was created as a result of the study. The outcomes indicate that 80,377 ha and 83,022 ha of the study area were classified as high and very high suitability, respectively. Based on these results, we evaluate whether the locations of existing solid waste landfills are appropriate and propose alternative solid waste landfills for each district.

Artificial Intelligence in Geospatial Analysis for Flood Vulnerability Assessment: A Case of Dire Dawa Watershed, Awash Basin, Ethiopia

This study presents the novelty artificial intelligence in geospatial analysis for flood vulnerability assessment in Dire Dawa, Ethiopia. Flood-causing factors such as rainfall, slope, LULC, elevation NDVI, TWI, SAVI, K-factor, R-factor, river distance, geomorphology, road distance, SPI, and population density were used to train the ANN model. The weights were generated in the ANN model and prioritized. Initial values were randomly assigned to the NN and trained with the feedforward processes. Ground-truthing points collected from the historical flood events of 2006 were used as targeting data during the training. A rough flood hazard map generated in feedforward was compared with the actual data, and the errors were propagated back into the NN with the backpropagation technique, and this step was repeated until a good agreement was made between the result of the GIS-ANN and the historical flood events. The results were overlapped with ground-truthing points at 88.46% and 89.15% agreement during training and validation periods. Therefore, the application of the GIS-ANN for the assessment of flood vulnerable zones for this city and its catchment was successful. The result of this study can also be further considered along with the city and its catchment for practical flood management.

Multi-Criteria Decision-Making Methods in Fuzzy Decision Problems: A Case Study in the Frozen Shrimp Industry

The European Union (EU) is the largest shrimp consumer market in the world in terms of requirements for shrimp product imports. Therefore, other enterprises that export frozen shrimp to the EU must consider many criteria when choosing suppliers of raw shrimp. The difficulty of choosing suppliers of raw shrimp makes selecting raw material suppliers in the fisheries sector a multi-criteria decision-making problem. In such problems, the decision makers must review and evaluate many criteria—including qualitative and quantitative factors—to achieve an optimal result. While there have been multiple multi-criteria decision making models developed to support supplier selection processes in different industries, none of these have been developed to solve the particular problems facing the shrimp industry, especially as it concerns a fuzzy decision-making environment. In this research, the authors propose a Multi-Criteria Decision Making model (MCDM) including the Fuzzy Analytical Network Process (FANP) and Weighted Aggregated Sum Product Assessment (WASPAS) for the evaluation and selection process of shrimp suppliers in the fisheries industry. The model is applied to a real-world case study and the results show that Supplier 3 (SA3) is the most optimal supplier of raw shrimp. The contribution of this work is the employment of FANP and WASPAS to propose an MCDM for ranking potential suppliers in the fisheries industry in a fuzzy environment. The proposed approach can also be modified to support complex decision-making processes in fuzzy environments in different industries.