Literature DB >> 29706481

Estimating solid waste generation by hospitality industry during major festivals: A quantification model based on multiple regression.

Muhammad Abdulredha1, Rafid Al Khaddar2, David Jordan2, Patryk Kot2, Ali Abdulridha3, Khalid Hashim2.   

Abstract

Major-religious festivals hosted in the city of Kerbala, Iraq, annually generate large quantities of Municipal Solid Waste (MSW) which negatively impacts the environment and human health when poorly managed. The hospitality sector, specifically hotels, is one of the major sources of MSW generated during these festivals. Because it is essential to establish a proper waste management system for such festivals, accurate information regarding MSW generation is required. This study therefore investigated the rate of production of MSW from hotels in Kerbala during major festivals. A field questionnaire survey was conducted with 150 hotels during the Arba'een festival, one of the largest festivals in the world, attended by about 18 million participants, to identify how much MSW is produced and what features of hotels impact on this. Hotel managers responded to questions regarding features of the hotel such as size (Hs), expenditure (Hex), area (Ha) and number of staff (Hst). An on-site audit was also carried out with all participating hotels to estimate the mass of MSW generated from these hotels. The results indicate that MSW produced by hotels varies widely. In general, it was found that each hotel guest produces an estimated 0.89 kg of MSW per day. However, this figure varies according to the hotels' rating. Average rates of MSW production from one and four star hotels were 0.83 and 1.22 kg per guest per day, respectively. Statistically, it was found that the relationship between MSW production and hotel features can be modelled with an R2 of 0.799, where the influence of hotel feature on MSW production followed the order Hs > Hex > Hst.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Hotels; Kerbala; Major festivals; Multiple linear regression; Solid waste generation

Mesh:

Substances:

Year:  2018        PMID: 29706481     DOI: 10.1016/j.wasman.2018.04.025

Source DB:  PubMed          Journal:  Waste Manag        ISSN: 0956-053X            Impact factor:   7.145


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Journal:  MethodsX       Date:  2018-10-31
  4 in total

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