Exploring the use of astronomical seasons in municipal solid waste disposal rates modeling

Adusei, Kenneth K.; Ng, Kelvin Tsun Wai; Mahmud, Tanvir Shahrier; Karimi, Nima; Lakhan, Calvin

doi:10.1016/j.scs.2022.104115

Cited by 17 publications

(4 citation statements)

References 66 publications

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“…Consistency in waste generators’ behaviors appears to improve both the accuracy and precision of the SARIMA B CV . The seasonal variations in waste generation behaviors are also reported in Adusei et al. (2022b) .…”

Section: Resultsmentioning

confidence: 99%

“…Seasonal variations of MSW generation characteristics and recycling behaviors have been well documented and discussed ( Denafas et al., 2014 ; Edjabou et al., 2018 ), and various numerical models have been proposed ( Adusei et al., 2022a , 2022b ; Sarmento et al., 2022 ). Many waste researchers have applied Seasonal Autoregressive Integrated Moving Average (SARIMA) models in quantitative forecasting due to the model's ability to capture seasonal and non-stationary behaviors of time series.…”

Section: Introductionmentioning

confidence: 99%

“…The key study objectives are to [i] predict residential waste collection rate (RWCR) during COVID-19 period in a Canadian capital city using SARIMA models, and [ii] compare the SARIMA models’ performance across the jurisdictions in North America. Unlike most waste modeling studies with a focus on MSW disposal rates ( Adusei et al., 2022b ; Vu et al., 2022a ; Jassim et al., 2023 ), this study focused solely on the RWCR derived from municipal programs. Conventional modeling of MSW disposal rates during the pandemic may be less applicable for cross-jurisdictional comparisons, given their sensitivity to COVID-19 regulatory and administrative measures and diverse climatic conditions.…”

Section: Introductionmentioning

confidence: 99%

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A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19

Mahmud

Hasan

et al. 2023

Sustainable Cities and Society

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19

Mahmud

Hasan

et al. 2023

Sustainable Cities and Society

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“…Similarly, the average recycling rate for municipal waste in Europe in 2017 was reported to be 46% [13]. The factors contributing to the prevalence of frequent landfilling practices and the existence of numerous landfills can be attributed to urban growth, population expansion, available land resources, and public attitudes, such as the "Not In My Backyard" (NIMBY) approach [14][15][16].…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Assessing Global Waste Management: Alternatives to Landfilling in Different Waste Streams—A Scoping Review

Karimi

2023

Sustainability

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This scoping review examines global strategies and enterprises for sustainable solid waste management, with a focus on alternative landfilling approaches. The study collected and analyzed a significant number of documents from different regions, revealing Asia as the major contributor (for the collected documents) (48.7%), followed by North America (24.3%) and Europe (15.8%). Recycling emerged as the most effective alternative waste treatment method, representing 52.3% of the documented approaches, with industrial recycling (22.6%) and residential/nonresidential recycling (20.2%) as prominent categories. Food waste was a significant concern across regions, constituting 21.4% of the collected documents. Composting was widely adopted (15.4%) due to its simplicity and benefits for gardening and soil improvement. Other methods like biogas extraction, reusing, raising awareness, incinerating, redistributing, reducing, and fermentation accounted for 13.1% cumulatively. The study highlights the need for adopted waste management solutions based on regional challenges and successful practices. Promoting recycling infrastructure, composting, and waste reduction approaches are crucial to achieving sustainable waste management aligned with SDGs. Collaboration and knowledge sharing between regions are essential to improve inefficient waste management mechanisms. Integrating the findings into policymaking and industry practices can lead to a more sustainable future with reduced environmental impact.

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Filter Method Feature Selection Techniques for Solid Waste Prediction Based on GRU Deep Learning Model

Batool,

Arbain,

Ghazali

et al. 2024

Lecture Notes in Networks and Systems

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Exploring the use of astronomical seasons in municipal solid waste disposal rates modeling

Cited by 17 publications

References 66 publications

A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19

A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19

Assessing Global Waste Management: Alternatives to Landfilling in Different Waste Streams—A Scoping Review

Filter Method Feature Selection Techniques for Solid Waste Prediction Based on GRU Deep Learning Model

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