Siting and ranking municipal landfill sites in regional scale using nighttime satellite imagery

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

doi:10.1016/j.jenvman.2019.109942

Cited by 40 publications

(21 citation statements)

References 37 publications

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“…However, alternative approaches that break down such administrative constructs can also be achieved by using methods, such as Thiessen polygons ( Karimi et al, 2020 , Richter et al, 2019 ; Richter, Ng, Karimi, & Li, 2021; Zhang et al, 2015 ) or Standard Deviational Ellipses (Richter, Ng, Karimi, & Chang, 2021).…”

Section: Introductionmentioning

confidence: 99%

Impact of COVID-19 lockdown measures on waste production behavior in Lisbon

et al. 2022

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The recent restrictions on mobility and economic activities imposed by governments due to the COVID-19 pandemic have significantly affected waste production and recycling patterns in cities worldwide. This effect differed both between cities and within cities as the measures of confinement adopted by governments had diverse impacts in different areas of cities, depending on their characteristics (e.g., touristic, or residential). In the present work, mixed waste collection areas were created, based on waste collection points, that define spatial units in which contextual data such as tourism and residential characteristics were aggregated. The difference in mixed waste collected compared with previous years was analyzed along with the impacts on recycling due to the modification in operations regarding waste collection during the lockdown. The results showed that despite the suspension of the door-to-door recycling system during the lockdown, this did not translate into an increase in the production of mixed waste, and the recycling levels of previous years have not been reached after the lockdown, indicating a possible change in recycling habits in Lisbon. The touristic and non-residential mixed waste circuits presented significantly reduced mixed waste production compared to the non-pandemic context. Also, tourist, mobility, and economic activity were measured to understand which factors contributed to waste production changes during the COVID-19 pandemic. While little evidence of a relationship with these exogenous variables was found at the citywide level, evidence was found at the waste collection circuit level.

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Section: Introductionmentioning

confidence: 99%

Impact of COVID-19 lockdown measures on waste production behavior in Lisbon

et al. 2022

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“…According to Statistics Canada, 24.9 million tons of solid waste was disposed in Canadian landfills in 2016 [15]. The three Canadian Prairie provinces (Alberta, Saskatchewan, and Manitoba) had an estimated 7.9 landfills per hundred thousand people in 2017 [16,17]. In comparison, the United States had an estimated 0.5 landfills per hundred thousand people in 2015 [18].…”

Section: Introductionmentioning

confidence: 99%

Temporal and Spatial Distributions of Waste Facilities and Solid Waste Management Strategies in Rural and Urban Saskatchewan, Canada

Ghosh

2021

Sustainability

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Saskatchewan has the highest number of landfills per capita in Canada. Given the lower population density and the skewed spatial population distribution, comprehensive analysis of municipal solid waste management systems in Saskatchewan is inherently difficult. Most of the published waste studies however focus on city-level waste management, and there is a lack of literature with respect to the rural areas. In this study, landfills and transfer stations are examined temporally and spatially using Geographic Information System. Landfills and transfer stations from 2017 and 2020 were plotted against census division land area, annual budget, and population density to study temporal changes. Saskatchewan witnessed a 54% reduction in the number of landfills and a 55% increase in number of transfer stations between 2017 and 2020. The replacement of landfills with transfer stations are more noticeable in divisions 8, 9, and 16. Regression analysis is conducted, and landfill closure operation show no obvious correlation to division land area, annual budget, or population density. Rural division 18, representing Northern Saskatchewan, has approximately 45% of the land area in the province and has the lowest population density. The findings suggest different waste management strategies are required for urban and rural areas. The results of this study will help policy makers to better implement solid waste management strategies in urban and rural areas.

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“…Siting MSW landfills often requires the engagement of multiple stakeholders encompassing government, municipalities, industries, experts, and the general public, where numerous criteria must be considered. Assuming no political or administrative boundaries as inputs, Karimi et al (2020) proposed a data-driven GIS-based method that considers spatial, environmental, and economic constraints using study regions derived from nighttime light data. Based on the Analytic Hierarchy Process(AHP) and GIS technology Sener et al (2010) combined social, environmental, and technical parameters to identify two candidate landfill sites for Konya, Turkey.…”

Section: Introductionmentioning

confidence: 99%

Siting MSW landfills via the integration of DEMATEL-ANP and clustering algorithm in a fuzzy logic environment (Case Study: Lanzhou, China)

Liu¹,

Li²,

Xiao³

et al. 2021

Preprint

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The siting of Municipal Solid Waste (MSW) landfills is a complex decision based process that involves multiple hydrogeological, morphological, environmental, climatic, and socio-economic criteria. In a fuzzy logic environment, DEMATEL and ANP methods were employed to comprehensively consider uncertainty, fuzziness of data and the subjective scoring and stability of results to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30m resolution, criteria weights were determined via the integration of DEMATEL and ANP, and seven sets of membership functions were simulated to obtain the best fuzzy logic environment. Combining GIS spatial analysis and the three clustering algorithms (DBSCAN, HDBSCAN, and OPTICS), candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics and reachability were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This paper focuses on a flexible and novel framework for the selection of MSW landfill sites for Lanzhou, which is a semi-arid valley basin city in China. In contrast to common techniques, this model not only made the best recommendation scientifically and efficiently but could also provide accurate assessment data for decision makers in landfill construction and high-quality urban development.

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Siting and ranking municipal landfill sites in regional scale using nighttime satellite imagery

Cited by 40 publications

References 37 publications

Impact of COVID-19 lockdown measures on waste production behavior in Lisbon

Impact of COVID-19 lockdown measures on waste production behavior in Lisbon

Temporal and Spatial Distributions of Waste Facilities and Solid Waste Management Strategies in Rural and Urban Saskatchewan, Canada

Siting MSW landfills via the integration of DEMATEL-ANP and clustering algorithm in a fuzzy logic environment (Case Study: Lanzhou, China)

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