PERKOULIDIS

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Estimation of packaging and residual waste generation pattern of a geographic information system for PAYT implementation in a municipality of Greece

G. Perkoulidis, T. Kasampalis and A. Karagiannidis 15th Panhellenic Logistics Conference

PAYT


Municipality of Elefsina and Pilot area

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PAYT •Solid waste is one of the largest outlays in the urban area and associated with serious consequences to the living quality and considerable cost burdens for the communities. •The approach of PAYT (also known as variable rate pricing, unit pricing, differentiated tariff system) in waste management is: •to realise the polluter pays principle in a fair manner by charging people in accordance •to the amount of waste which they actually generate.

15th Panhellenic Logistics Conference

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SWOT Analysis (1/5)

•SWOT is an acronym for strengths, weaknesses, opportunities and threats. •SWOT is a tool designed to be used in the preliminary stages of decision-making on the one hand and as a precursor to strategic management planning on the other. •It should be performed by the individual user and also in groups.

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SWOT Analysis (2/5) •This PAYT scheme-based SWOT analysis was performed to develop a part of a strategic action plan of different PAYT concepts for Greece. •It aimed at identifying the positive and negative factors, as well as internal and external factors, that might have an impact on the proposed PAYT concept. •SWOT analysis of this project was intended to maximize both strengths and opportunities, minimize the external threats, and transform the identified weaknesses into strengths and to take advantage of opportunities along with minimizing both internal weaknesses and external threats. 15th Panhellenic Logistics Conference

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SWOT Analysis (3/5) •In the SWOT analysis, available resources and their potential utilization are going to be studied from the viewpoints of •economic, •ecological and •social sustainability. •However, its main purpose in the planning process is to obtain decision support that is to be utilized in the choice of the strategy to be followed.

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SWOT Analysis (4/5)

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SWOT Analysis (5/5) • A SWOT analysis needs to be flexible. •Situations change with the time and an updated analysis should be made frequently. •The intention is to develop strategy action plans for improving PAYT through SWOT analysis

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SWOT Analysis in PAYT

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Location of the Municipality of Elefsina and study area outline

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System for MSW monitoring

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Components of MSW collection system

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Data from global position system satellite (10 January 2010 – 11 December 2010) Database matrix: 7,998 rows x 29 lines - Bin identification number - Collection day - Typology of bin (blue, green) - Weight of bin (blue, green) - Time between collection points (sec) - Bin location (street names, crossroads, squares) 15th Panhellenic Logistics Conference

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Data elaboration and development of GIS system (1/2)

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Data elaboration and development of GIS system (2/2)

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Bins’ location identification

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Location of blue and green bins

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Household’s identification in GIS and part of its fields

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Identification of green bin

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Weight of blue bins and served households on the 10th of December 2010

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Weight of green bins and served households on the 10th of December 2010

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Identification of green bin and served household

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Collection time for green bins collection

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Daily mean value of weighted packaging and mostly organic waste

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Mean value analysis of weighted waste

Mostly organic waste: 62.5 % by weight/month

Packaging waste: 37.5 % by weight/month

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Daily estimated packaging and mostly organic waste production (in kg)

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Statistical analysis for the weight in blue bins

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Statistical analysis for the weight of green bins

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Conclusions (1/2) . • The designed and developed geographic information system can monitor and implement the pay as you throw system in any case study area. • The location of bins should be improved; there are many ‘transactions’ (30%) in the 8,000 x 29 database matrix. • The weight mean value of waste in blue bin is 60 kg and in green bin is 104 kg. These values increase on Mondays (18% for blue bin and 3% for green bin) due to high waste production during weekend. • From Tuesdays – Thursdays a 6% reduction of green bins weight has been observed.

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Conclusions (2/2) • The standard deviation of weight is 48.8 kg for packaging waste and 60.3 kg for organic waste due to possible wrong location of bins. • Organic waste and packaging waste collection was calculated to 82 % and 18 % respectively. • The geographic information system could be utilized for the future collection of selected waste streams.

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Thank you for your attention For more information: Dr. George Perkoulidis, Τel.: +302310-994181, e-mail: gperk@aix.meng.auth.gr Themistoklis Kasampalis, Tel.: +302310-994167, e-mail: thekas@aix.meng.auth.gr

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