A spatial interaction model for the representation of user access to household waste recycling centres

Zaharudin, Zati Aqmar; Brint, Andrew; Genovese, Andrea; Piccolo, Carmela

doi:10.1016/j.resconrec.2021.105438

Cited by 8 publications

(7 citation statements)

References 43 publications

(43 reference statements)

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“…Sheffield City Council currently provides and manages five HWRCs. The Local Authority has experienced financial pressures, which have also led to contentious relationships with the contractor managing the entire waste management cycle; such tensions have resulted in service disruptions and labour disputes [52] which have damaged the reputation of the contractor and resulted in inconveniences for citizens [53]. On the one hand, constant cuts to the Council budget have posed a serious challenge to the operations of the centre; on the other hand, the current HWRC system experiences very high levels of demand and frequent queueing problems [54].…”

Section: A Real-life Case Study: Reorganising Hwrc In Sheffield Ukmentioning

confidence: 99%

“…Therefore, to capture the distributions of users at each HWRC, a spatial interaction model (originally formulated by Ref. [53] is adopted.…”

Section: Data Collection and Parameters Settingmentioning

confidence: 99%

“…where d it is the number of users in ward i during time period t, Q j is the attractiveness of each HWRC, dist ij is the distance between user in ward i and facility j, and the value of n is chosen to minimise the difference between the actual and the estimated (survey-based) distribution of users at the HWRCs (see also [53].…”

Section: Data Collection and Parameters Settingmentioning

confidence: 99%

“…Such a survey was utilised in order to calibrate the functioning of the spatial interaction model. Details of the survey, of the designed spatial interaction model and of its reliability are discussed in the following (for an extensive discussion, see also [53].…”

Section: Allocation Of Users To Hwrc Facilitiesmentioning

confidence: 99%

See 3 more Smart Citations

A multi-period model for reorganising urban household waste recycling networks

Zaharudin

Brint²,

Genovese³

2022

Socio-Economic Planning Sciences

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Section: A Real-life Case Study: Reorganising Hwrc In Sheffield Ukmentioning

confidence: 99%

“…Therefore, to capture the distributions of users at each HWRC, a spatial interaction model (originally formulated by Ref. [53] is adopted.…”

Section: Data Collection and Parameters Settingmentioning

confidence: 99%

Section: Data Collection and Parameters Settingmentioning

confidence: 99%

Section: Allocation Of Users To Hwrc Facilitiesmentioning

confidence: 99%

See 2 more Smart Citations

A multi-period model for reorganising urban household waste recycling networks

Zaharudin

Brint²,

Genovese³

2022

Socio-Economic Planning Sciences

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“…Proper reuse and recycling of waste materials can save energy, reduce CO2 emissions (Umar et al, 2021), directly reduce the amount of waste sent to landfills, and induce the government financially (Razali et al, 2020). Besides being the key to fostering the circular economic transition (Zaharudin et al, 2021), recycling reflects the zerowaste principles while complying with two important Sustainable Development Goals (SDGs), i.e., SDG 11 (make cities inclusive, safe, resilient, and sustainable) and SDG 12 (responsible consumption and production).…”

Section: Introductionmentioning

confidence: 99%

Establishing Recycling Bins Location and Allocation for Sustainable Urban Municipalities of Johor Bahru in Malaysia

Jamiron¹,

Sarif²,

Rahman³

et al. 2021

IJAREMS

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Recycling helps reduce the amount of waste sent to landfills besides being one of the most crucial components of the circular economy system. This good practice is carried out through reverse and forward logistic systems and is in line with two Sustainable Development Goals (SDGs), namely SDG 11 (make cities inclusive, safe, resilient, and sustainable) and SDG 12 (responsible consumption and production). Since the 1970s, Malaysia's government has been committed to strengthening recycling systems, but public support has been lacking. In fact, most recyclable waste is sent to the landfill. A high degree of participation in recycling practices by the highest municipal waste generators, i.e., the household level, is critical. Encouraging waste separation at the household level, as well as providing appropriate locations for recycling facilities (such as drop-off recycling bins), could attract public participation in recycling programmes, resulting in higher recycling rates, and lowering waste sent to landfills. For this reason, this study determines the location and allocation of recycling bins within the selected household areas of Johor Bahru, an urban municipality in Malaysia, by using a mathematical model. The model was found to be capable of determining the optimal location-allocation for recycling bins to cover the study area.

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Selectively closing recycling centers in Bavaria: Reforming waste‐management policy to reduce disparity

Schmidt,

Singh

2024

Networks

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Recycling centers sort and process collected waste in the interest of the environment, but also lead to damaging climate effects via released emissions and pollutants in their operation. Consequently, governments are closing such centers to fulfill climate and carbon neutrality goals. However, such closures risk populations being forced to travel further to facilities that collect waste, and can cause an unfair burden on the remaining open centers, thereby reducing participation in recycling. Using a facility location optimization model and mobility survey data within the state of Bavaria in Germany, we show how selective closures of these centers can still lead to high levels of recycling access. Our analysis ensures that even when 20% of facilities are closed smartly, the median travel distance by residents to their assigned recycling center increases by only 450 m. Additionally, we find Bavaria suffers from disparity in recycling patterns in rural and urban regions, both in terms of motivation to recycle and the locations of the facilities. We promote a policy that favors retention of recycling centers in rural regions by reserving 75% of open facilities to be in rural areas, while selectively closing facilities in urban regions, to remove these regional differences. Success of recycling campaigns depends on public perception of closures of such facilities and also on their ease of access. As policymakers gradually implement further closures, such data‐driven strategies can assist in being more transparent to the public thereby increasing the willingness to participate in such recycling programs.

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A spatial interaction model for the representation of user access to household waste recycling centres

Cited by 8 publications

References 43 publications

A multi-period model for reorganising urban household waste recycling networks

A multi-period model for reorganising urban household waste recycling networks

Establishing Recycling Bins Location and Allocation for Sustainable Urban Municipalities of Johor Bahru in Malaysia

Selectively closing recycling centers in Bavaria: Reforming waste‐management policy to reduce disparity

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