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

There is currently a lack of studies on residential waste collection during COVID-19 in North America. SARIMA models were developed to predict residential waste collection rates (RWCR) across four North American jurisdictions before and during the pandemic. Unlike waste disposal rates, RWCR is relat...

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Autores principales: Mahmud, Tanvir Shahrier, Ng, Kelvin Tsun Wai, Hasan, Mohammad Mehedi, An, Chunjiang, Wan, Shuyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10225168/
https://www.ncbi.nlm.nih.gov/pubmed/37274541
http://dx.doi.org/10.1016/j.scs.2023.104685
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author Mahmud, Tanvir Shahrier
Ng, Kelvin Tsun Wai
Hasan, Mohammad Mehedi
An, Chunjiang
Wan, Shuyan
author_facet Mahmud, Tanvir Shahrier
Ng, Kelvin Tsun Wai
Hasan, Mohammad Mehedi
An, Chunjiang
Wan, Shuyan
author_sort Mahmud, Tanvir Shahrier
collection PubMed
description There is currently a lack of studies on residential waste collection during COVID-19 in North America. SARIMA models were developed to predict residential waste collection rates (RWCR) across four North American jurisdictions before and during the pandemic. Unlike waste disposal rates, RWCR is relatively less sensitive to the changes in COVID-19 regulatory policies and administrative measures, making RWCR more appropriate for cross-jurisdictional comparisons. It is hypothesized that the use of RWCR in forecasting models will help us to better understand the residential waste generation behaviors in North America. Both SARIMA models performed satisfactorily in predicting Regina's RWCR. The SARIMA D(CV) model's performance is noticeably better during COVID-19, with a 15.7% lower RMSE than that of the benchmark model (SARIMA B(CV)). The skewness of overprediction ratios was noticeably different between jurisdictions, and modeling errors were generally lower in less populated cities. Conflicting behavioral changes might have altered the residential waste generation characteristics and recycling behaviors differently across the jurisdictions. Overall, SARIMA D(CV) performed better in the Canadian jurisdiction than in U.S. jurisdictions, likely due to the model's bias on a less variable input dataset. The use of RWCR in forecasting models helps us to better understand the residential waste generation behaviors in North America and better prepare us for a future global pandemic.
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spelling pubmed-102251682023-05-30 A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19 Mahmud, Tanvir Shahrier Ng, Kelvin Tsun Wai Hasan, Mohammad Mehedi An, Chunjiang Wan, Shuyan Sustain Cities Soc Article There is currently a lack of studies on residential waste collection during COVID-19 in North America. SARIMA models were developed to predict residential waste collection rates (RWCR) across four North American jurisdictions before and during the pandemic. Unlike waste disposal rates, RWCR is relatively less sensitive to the changes in COVID-19 regulatory policies and administrative measures, making RWCR more appropriate for cross-jurisdictional comparisons. It is hypothesized that the use of RWCR in forecasting models will help us to better understand the residential waste generation behaviors in North America. Both SARIMA models performed satisfactorily in predicting Regina's RWCR. The SARIMA D(CV) model's performance is noticeably better during COVID-19, with a 15.7% lower RMSE than that of the benchmark model (SARIMA B(CV)). The skewness of overprediction ratios was noticeably different between jurisdictions, and modeling errors were generally lower in less populated cities. Conflicting behavioral changes might have altered the residential waste generation characteristics and recycling behaviors differently across the jurisdictions. Overall, SARIMA D(CV) performed better in the Canadian jurisdiction than in U.S. jurisdictions, likely due to the model's bias on a less variable input dataset. The use of RWCR in forecasting models helps us to better understand the residential waste generation behaviors in North America and better prepare us for a future global pandemic. Elsevier Ltd. 2023-09 2023-05-28 /pmc/articles/PMC10225168/ /pubmed/37274541 http://dx.doi.org/10.1016/j.scs.2023.104685 Text en © 2023 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Mahmud, Tanvir Shahrier
Ng, Kelvin Tsun Wai
Hasan, Mohammad Mehedi
An, Chunjiang
Wan, Shuyan
A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19
title A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19
title_full A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19
title_fullStr A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19
title_full_unstemmed A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19
title_short A cross-jurisdictional comparison on residential waste collection rates during earlier waves of COVID-19
title_sort cross-jurisdictional comparison on residential waste collection rates during earlier waves of covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10225168/
https://www.ncbi.nlm.nih.gov/pubmed/37274541
http://dx.doi.org/10.1016/j.scs.2023.104685
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