A data driven technique applying GIS, and remote sensing to rank locations for waste disposal site expansion

Richter, Amy; Ng, Kelvin Tsun Wai; Karimi, Nima

doi:10.1016/j.resconrec.2019.06.013

Cited by 41 publications

(14 citation statements)

References 43 publications

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“…In this context, we highlight the importance of conducting future risk assessment studies of landfills [38]. e use of the integrated methodology MCDA-AHP and GIS-RS has been a successful tool for finding the optimal landfill site location [13,21,26,30,32,41,74]. Unfortunately, in Peru, there is a serious lack of this type of methodology [51] and an adequate location of landfills [12].…”

Section: Discussionmentioning

confidence: 99%

“…Methodologies have arisen that incorporate geographic information systems (GISs), remote sensing (RS), and multicriteria decision analysis (MCDA) through the analytic hierarchy process (AHP) [13,[23][24][25][26][27][28]. GISs are efficient in collecting, manipulating, interacting, and analyzing spatial data (many of which come from RS) that apply to the criteria for the selection of the ideal site [29][30][31][32], while the AHP is one of the most commonly used MCDA techniques for determining the relative importance of the criteria [26,[33][34][35]. ese tools have been integrated into several studies [9,36,37] because they are effective in simplifying the selection of the optimal landfill sites [7,28,[38][39][40][41].…”

Section: Introductionmentioning

confidence: 99%

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Analytic Hierarchy Process (AHP) for a Landfill Site Selection in Chachapoyas and Huancas (NW Peru): Modeling in a GIS‐RS Environment

López

Briceño

et al. 2022

Advances in Civil Engineering

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The evaluation of suitable landfill sites is a complex process and requires various legislative, technical, social, and environmental criteria. Therefore, this study provides a management tool for identifying suitable sites for landfills through the integrated use of the analytic hierarchy process (AHP), geographic information systems (GISs), and remote sensing (RS). Accordingly, fourteen subcriteria were identified and grouped into physical (7), environmental (3), and socioeconomic (4) criteria and were weighed using pairwise comparison matrices (PCMs). The weighted linear combination (WLC) approach of maps allowed us to generate models and submodels of land suitability. From the territory of the districts of Chachapoyas and Huancas, 0.9% (1.71 km2), 71.1% (141.89 km2), 21.0% (41.86 km2), 0.0%, and 7.7% (14.21 km2) have highly suitable, moderately suitable, marginally suitable, unsuitable, and restricted conditions, respectively, for a landfill site. Twelve highly suitable sites were identified, of which three were selected based on their shape and the minimum area required for the operation of the landfill until 2040. In fact, this study proposes a management tool for decision-makers (DMs) that improve the process of selecting landfill sites, supported by engineering and its applications for territorial sustainability.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analytic Hierarchy Process (AHP) for a Landfill Site Selection in Chachapoyas and Huancas (NW Peru): Modeling in a GIS‐RS Environment

López

Briceño

et al. 2022

Advances in Civil Engineering

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“…Data accuracy and reliability is a key challenge in the development of an evidence-based waste management system (Richter et al 2019;Ghosh and Ng, 2021), especially during the pandemic. For example, different modeling approaches such as the uses of lagged inputs and distinct time series (Vu et al 2021a) and separated waste fractions (Vu et al 2021b) were attempted to minimize uncertainties in data and variations in waste recycling behaviors during the COVID pandemic.…”

Section: Data-driven Waste Policy On Medical and Healthcare Wastesmentioning

confidence: 99%

Hospital waste generation during the first wave of COVID-19 pandemic: a case study in Delhi

Singh

Karimi

et al. 2022

Environ Sci Pollut Res

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In this study, the hospital waste generation rates and compositions in Delhi were examined temporally and spatially during the first COVID-19 wave of April 2020. A total of 11 representative hospitals located in five districts were considered. The pre-COVID hospital waste generation rates were relatively consistent among the districts, ranging from 15 to 23 tonne/ month. It is found that the number of hospital beds per capita may not be a significant factor in the hospital waste quantity. Strong seasonal variations were not observed. All districts experienced a drastic decrease in generation rates during the 1-month lockdown. The average rates during the COVID period ranged from 12 to 24 tonne/month. Bio-contaminated and disposable medical product wastes were the most common waste in Delhi's hospitals, representing 70-80% by weight. The changes in waste composition were however not spatially consistent. The lockdown appeared to have had a higher impact on hospital waste generation rate than on waste composition. The findings are important as the design and operation of a waste management system are sensitive to both waste quantity and quality. Waste records at source helped to minimize waste data uncertainties and allowed a closer examination of generation trends.

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“…Baiocchi et al (2014) utilised Boolean logic, index overlay and fuzzy gamma decision support methodologies to perform landfill site suitability analysis for waste disposal in urban regions of Italy. Richter et al (2019) combined remote sensing and vector data to rank the suitability of current landfill sites and their area of influence for expansion. Shi et al (2019) integrated a genetic algorithm with probabilistic robust optimisation to select a suitable site for the recycling of construction waste.…”

Section: Literature Reviewmentioning

confidence: 99%

Application of ArcGIS and QFD-based model for site selection for bio-medical waste disposal

2021

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With the increasing formalisation of the health sector in India, the bio-medical waste (BMW) disposal regulations are getting stringent and its implementation is being enforced strictly. The coronavirus disease 2019 (COVID-19) created a healthcare crisis because of the highly contagious nature of the novel virus. Measures employed for the prevention and management of COVID-19 resulted in the generation of an unprecedented amount of BMW in Indian medical history. This BMW needs to be disposed of safely at a suitable site to prevent secondary infection and the potential spread of the virus in the environment. The selection of an appropriate site for BMW disposal requires comparing a wide range of social, economic and environmental factors corresponding to different site locations, which makes it a multi-criteria decision-making (MCDM) problem. This study aims to solve the BMW site selection problems using a quality function deployment-based model that can consider both the subjective and the objective criteria, and evaluate them as per the user’s requirements. The proposed model is applied to evaluate the suitability of waste disposal sites in the city of Bilaspur in Chhattisgarh, India. At first, eight possible locations for BMW disposal are identified, while utilising geographical information system (GIS). Consequently, the developed model is applied to evaluate the identified sites, taking 18 relevant criteria into consideration. A software prototype is developed in Visual BASIC 6 to automate the entire decision-making process, further adding to the novelty of the work.

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A data driven technique applying GIS, and remote sensing to rank locations for waste disposal site expansion

Cited by 41 publications

References 43 publications

Analytic Hierarchy Process (AHP) for a Landfill Site Selection in Chachapoyas and Huancas (NW Peru): Modeling in a GIS‐RS Environment

Analytic Hierarchy Process (AHP) for a Landfill Site Selection in Chachapoyas and Huancas (NW Peru): Modeling in a GIS‐RS Environment

Hospital waste generation during the first wave of COVID-19 pandemic: a case study in Delhi

Application of ArcGIS and QFD-based model for site selection for bio-medical waste disposal

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