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INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social- economic indicators and packaging waste selectively collection

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Page 1: INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social-economic indicators and packaging waste selectively collection

INE / Portugal EUROSTAT / 9 – 10 April 2003 /

Waste WG Meeting1

Social-economicindicators and packaging waste selectively collection

Page 2: INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social-economic indicators and packaging waste selectively collection

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Waste WG Meeting2

Prime goal.

What questions look for an answer?

Page 3: INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social-economic indicators and packaging waste selectively collection

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Waste WG Meeting3

Questions to be answered. Do households contribute at a

maximum level on sorting packaging waste at home?

Have we reach a high rate of packaging waste selectively collected?

Page 4: INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social-economic indicators and packaging waste selectively collection

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Waste WG Meeting4

Questions to be answered. Is there a significant difference

between households in terms of social-economic conditions and respective contribution on sorting/select packaging waste at home?

Which is the best solution door-to-door collection or specific containers placed on strategic sites on streets?

Page 5: INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social-economic indicators and packaging waste selectively collection

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Prime objectives.

Evaluate families behaviour about waste sorting at home – social-economic conditions explain differences?

Is all packaging waste proper for selectively collection being sorted and sended for recycling – how high is the rate? can it be improved?

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Who is looking for this answers? Instituto Nacional de Estatística –

Statistical Office. Universidade Nova de Lisboa -

New University of Lisbon Environment Engineering Department

Valorlis S.A. – Waste Management Scheme – Private business participated by municipalities from West Region.

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Work phases.

(1) Characterization of study area – door-to-door areas; eco-points; households.

(2) Collection of data on packanging waste selectively collected and mixed household waste; quality of materials sorted out on transfer facilities.

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Work phases.

(3) Data treatment; social-economic characterization of population; basic statistics and analysis; data aggregations.

(4) Symbolic Object Data Analysis – Relation between waste collected and neighbourhood main characteristics.

Page 9: INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social-economic indicators and packaging waste selectively collection

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Waste WG Meeting9

INE – Census 2001 Data – statistics on households – statistical work and data analysis.

Valorlis – Identify eco-points subject to the study – avoiding commercial areas and small businesses.

NUL/EED – Develop questionnaires on families and define types of packaging to study.

Back office work.

Page 10: INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social-economic indicators and packaging waste selectively collection

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Field work.

INE – Organize field work on households questionnaires – interviews preparation and lead collection of data.

Valorlis – Weight packaging waste collected by eco-point and door-to-door areas – weight of packaging waste sorted out from containers for mixed waste.

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Field work.

NUL/EED – Students teams to collect data on households and identify obstacles and barriers on the field which limit access of people in order to identify the significant buildings and houses under a 100 meters influence buffers of eco-points to be surveyed.

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# EcopontosConcelhos

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POMBAL (77)

OURÉM (77)

BATALHA (29)PORTO DE MÓS (43)

MARINHA GRANDE (118)

LEIRIA (292)

Municipalities.

Page 13: INE / Portugal EUROSTAT / 9 – 10 April 2003 / Waste WG Meeting 1 Social-economic indicators and packaging waste selectively collection

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Data collection / treatment. Special questionnaires on families

to evaluate if they contribute, how they contribute and amounts perceived – if not … why they don’t?

Data on waste and households characteristics constitute agreggates based on geographic areas.

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Data collection / treatment. Data aggregates constitute

symbolic objects to be analysed with Symbolic Objects Data Analysis Software.

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Main results.

Rates on packaging waste selectively collected.

Indicators on waste separately collected in order to validate data over similar areas in terms of social-economic conditions.

Factors influencing households behaviour on sorting packaging waste.

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Conclusions.

What can be done to improve packaging waste sorting by households and consequent separately collection.

Which system (door-to-door vs. eco-points) get better results.

Stereotype household best contribute to packaging waste sorting at home.