The impact of tourism on municipal solid waste generation: The case of Menorca Island (Spain)

Mateu-Sbert, Josep; Ricci‐Cabello, Ignacio; Villalonga-Olives, Ester; Cabeza-Irigoyen, Elena

doi:10.1016/j.wasman.2013.08.007

Cited by 131 publications

(90 citation statements)

References 15 publications

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“…The total number of experimental data runs generated from the CCD is 44, obtained according to Equation (2):…”

Section: Principle Of Central Composite Designmentioning

confidence: 99%

“…In fact, the sector accounts for 10-12% of the world's Gross Domestic Product (GDP) and approximately 14% of total employment [1]. Even though tourism can sustain high levels of employment, the sector is a source of environmental impacts with consequent public health concerns [2]. One of the most significant impacts of tourism is the generation of municipal waste, which increases as the seasonal population of tourists rises [3,4].…”

Section: Introductionmentioning

confidence: 99%

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Comparative Modelling and Artificial Neural Network Inspired Prediction of Waste Generation Rates of Hospitality Industry: The Case of North Cyprus

Azarmi

Oladipo²,

Vaziri³

et al. 2018

Sustainability

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This study was undertaken to forecast the waste generation rates of the accommodation sector in North Cyprus. Three predictor models, multiple linear regression (MLR), artificial neural networks (ANNs) and central composite design (CCD), were applied to predict the waste generation rate during the lean and peak seasons. ANN showed highest prediction performance, specifically, lowest values of the standard error of prediction (SEP = 2.153), mean absolute error (MAE = 1.378) and highest R 2 value (0.998) confirmed the accuracy of the model. The analysed waste was categorised into recyclable, general waste and food residue. The authors estimated the total waste generated during the lean season at 2010.5 kg/day, in which large hotels accounted for the largest fraction (66.7%), followed by medium-sized hotels (19.4%) and guesthouses (2.6%). During the peak season, about 49.6% increases in waste generation rates were obtained. Interestingly, 45% of the waste was generated by British tourists, while the least waste was generated by African tourists (7.5%). The ANN predicted that small and large hotels would produce 5.45 and 22.24 tons of waste by the year 2020, respectively. The findings herein are promising and useful in establishing a sustainable waste management system.

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“…The total number of experimental data runs generated from the CCD is 44, obtained according to Equation (2):…”

Section: Principle Of Central Composite Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparative Modelling and Artificial Neural Network Inspired Prediction of Waste Generation Rates of Hospitality Industry: The Case of North Cyprus

Azarmi

Oladipo²,

Vaziri³

et al. 2018

Sustainability

View full text Add to dashboard Cite

show abstract

“…Tourism may also have an impact on MSW generation [66,67]. For example, Pattaya (Thailand), a beach resort city approximately 160 km from Bangkok, has a much higher MSW generation per capita (1.00 kg day -1 ) [5] than the national average (0.64 kg day -1 ).…”

Section: Fig 2 Msw Generation Per Capita In East Asia and The Pacifimentioning

confidence: 99%

Revisiting estimates of municipal solid waste generation per capita and their reliability

Kawai

Tasaki

2015

J Mater Cycles Waste Manag

238

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Per capita municipal solid waste (MSW) generation, a core indicator of environmental pressure, is a useful measure for evaluating the intensity of waste generation over time and comparing the intensities among cities or countries. We provide an overview of global data on MSW generation per capita at the national and local levels. Although the legal definition of MSW varies from country to country, we conceptualize MSW simply as the waste managed by or for municipalities as a public service. We note the current challenges in estimating MSW generation per capita in developing countries, including a lack of equipment (e.g., weighbridges), lower rates of MSW collection efficiency, and rural-urban migration, all of which may have negative effects on data reliability. Incomplete data compilation systems at the national level also result in lower reliability and reduce the comparability of national data. We suggest technical solutions for estimating MSW generation per capita at the local and national levels to improve reliability and comparability of data.

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“…Firstly, the attention was put on the MSW management in islands [12,13] and only nowadays also tourist areas in specific regions were considered.…”

Section: Introductionmentioning

confidence: 99%

Municipal solid waste selective collection and tourism

Rada

Zatelli

Mattolin

2014

WIT Transactions on Ecology and the Environment

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This paper concerns the interaction between tourism and the selective collection of municipal solid waste (MSW). Data for an Italian province are shown, zooming in on five municipalities characterised by the high presence of tourists along the year. Information on the selective collection organisation is presented (also based on the presence of eco-centers). The highest tourist months are in winter and summer and their effect is seen in the increase of the factions connected with the tourists meals and also the increase of residual MSW. The monthly peaks of waste generation are very high, but the final results in terms of selective collection efficiency seem to not be affected (being even higher than 80%, a value that is better than the one obtained at provincial scale). Also the presence of decentralised landfills did not discourage the source separation that changed significantly in about a decade. Moreover, the trend of tourists towards shorter periods of holiday does not affect selective collection; possibly because they are used to coming back to the same municipality, where they have already learned the local principles of source separation.

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The impact of tourism on municipal solid waste generation: The case of Menorca Island (Spain)

Cited by 131 publications

References 15 publications

Comparative Modelling and Artificial Neural Network Inspired Prediction of Waste Generation Rates of Hospitality Industry: The Case of North Cyprus

Comparative Modelling and Artificial Neural Network Inspired Prediction of Waste Generation Rates of Hospitality Industry: The Case of North Cyprus

Revisiting estimates of municipal solid waste generation per capita and their reliability

Municipal solid waste selective collection and tourism

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