Analysis of mean bin weight data to monitor best practice at HWRCs
Analysis of mean bin weight data to monitor best practice at HWRCs
This paper describes a modelling approach used to investigate the significance of key factors (vehicle type, compaction type, site design, temporal effects) in influencing the variability in observed nett amenity bin weights produced by Household Waste Recycling Centres (HWRC). Understanding such variability is a prerequisite to achieving best operational practices, to minimise the number of vehicle movements between each HWRC and disposal sites, and achieve consequential environmental and traffic benefits. The method described can help to quickly identify sites that are producing significantly lighter bins, enabling detailed back-end analyses to be efficiently targeted and best practice in HWRC operation identified. Tested on weigh ticket data obtained from nine HWRCs across West Sussex, the model suggested that compaction technique, vehicle type, month and site design explained 76% of the variability in the observed nett amenity weights. For each factor, a weighting coefficient was calculated to generate a predicted nett weight for each bin transaction and Bognor Regis, Crawley and East Grinstead were identified as having similar characteristics but returning significantly different mean nett bin weights. Waste and site audits were then conducted at the three sites to try and determine the possible sources of the remaining variability. Significant differences were identified in the proportions of contained waste (bagged), wood, and dry recyclables entering the amenity waste stream with significantly less contained waste and dry recyclables observed in the amenity waste bins at Bognor Regis.
Maynard, S.
a6cb202f-0090-4095-9c62-a5abe1469c26
Cherrett, T.J.
e5929951-e97c-4720-96a8-3e586f2d5f95
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
January 2008
Maynard, S.
a6cb202f-0090-4095-9c62-a5abe1469c26
Cherrett, T.J.
e5929951-e97c-4720-96a8-3e586f2d5f95
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Maynard, S., Cherrett, T.J. and Waterson, Ben
(2008)
Analysis of mean bin weight data to monitor best practice at HWRCs.
40th Annual Conference of the Universities' Transport Study Group, Portsmouth, UK.
03 - 05 Jan 2008.
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Conference or Workshop Item
(Paper)
Abstract
This paper describes a modelling approach used to investigate the significance of key factors (vehicle type, compaction type, site design, temporal effects) in influencing the variability in observed nett amenity bin weights produced by Household Waste Recycling Centres (HWRC). Understanding such variability is a prerequisite to achieving best operational practices, to minimise the number of vehicle movements between each HWRC and disposal sites, and achieve consequential environmental and traffic benefits. The method described can help to quickly identify sites that are producing significantly lighter bins, enabling detailed back-end analyses to be efficiently targeted and best practice in HWRC operation identified. Tested on weigh ticket data obtained from nine HWRCs across West Sussex, the model suggested that compaction technique, vehicle type, month and site design explained 76% of the variability in the observed nett amenity weights. For each factor, a weighting coefficient was calculated to generate a predicted nett weight for each bin transaction and Bognor Regis, Crawley and East Grinstead were identified as having similar characteristics but returning significantly different mean nett bin weights. Waste and site audits were then conducted at the three sites to try and determine the possible sources of the remaining variability. Significant differences were identified in the proportions of contained waste (bagged), wood, and dry recyclables entering the amenity waste stream with significantly less contained waste and dry recyclables observed in the amenity waste bins at Bognor Regis.
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Published date: January 2008
Venue - Dates:
40th Annual Conference of the Universities' Transport Study Group, Portsmouth, UK, 2008-01-03 - 2008-01-05
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Local EPrints ID: 53006
URI: http://eprints.soton.ac.uk/id/eprint/53006
PURE UUID: 426a1387-ee81-459a-a901-5391f119a1ca
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Date deposited: 24 Jul 2008
Last modified: 03 Mar 2023 02:34
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Author:
S. Maynard
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