Transcript Municipal Waste Generation Prognostic Model for Cities and

Life Cycle Assessment Tools for the Development
of Integrated Waste Management Strategies for
Cities and Regions with Rapid Growing
Economies
LCA-IWM
Prof. Johannes Jager, Emilia Szpadt, Jan den Boer
Technische Universität Darmstadt
Institute WAR
(Institute for Water Supply and Groundwater Protection,
Wastewater Technology, Waste Management, Industrial
Material Flows and Environmental Planning)
1
Agenda
• Introduction of the project
• Current waste management in the EU
Accession States
• Proposed tools for waste management planning
• State of work
2
LCA-IWM within EU research
Programme
EU 5th Framework Programme
1998-2002
Research Programme: Environment and
Sustainable Development (EESD)
Key-action “The City of Tomorrow
and Cultural Heritage”
4.1 Sustainable city planning and rational
resource management
LCA-IWM
4.1.2 Improving the quality of urban life 3
Consortium
8 University Partners and 4 SMEs:
1.
Darmstadt University of Technology, 7.
Germany
De Straat Milieu adviseurs, the
Netherlands
2.
Universitat Rovira i Virgili (URV)
Grup AGA , Spain
8.
Infrastruktur & Umwelt, Germany
9.
Servei de Tecnologia Quimica,
Universitat Rovira i Virgili, Spain
10.
Wameco, Consulting company,
Poland
11.
Kaunas University of Technology,
Lithuania
12.
Slovak University of Technology,
Slovakia
3.
4.
5.
6.
Universität für Bodenkultur Wien,
Austria
Wrocław University of Technology,
Poland
Democritus University of Thrace,
Greece
novaTec, Luxemburg
Involved Municipalities:
Barcelona, Reus (Spain)
Nitra (Slovakia)
Kaunas (Lithuania)
Wroclaw (Poland)
Xanthi (Greece)
4
Objectives of LCA-IWM:
Develop decision support for:
•
•
Planning of new
Optimisation of existing waste manag. systems
Two tools are proposed:
•
•
Waste Prognostic model
Criteria and quantitative indicators
for assessment of the
(i) environmental,
(ii) economic
(iii) social performance
of integrated waste management strategies
Targeted user:
waste management decision maker (planner) in EU Accession5
Countries and South European Regions
Project milestones
Prognostic
model
Assessment model
•
glass
•
metals
•
plastics
•
organic waste
•
residual waste
•
WEEE
•
bulky waste
•
hazardous waste
Waste
pre-treatment
& treatment
• Composting
• Digestion
• Mech.-Biol.
Pre-treatment
• Incineration
• Recycling:
(paper, glass,
metals, plastics,
WEEE)
Environmental
Final disposal
paper &
cardboard
Temporary storage
•
Collection systems, transport
Waste quantity &
composition
Economi
c
Social
Credits:
Energy
Compost Secondary materials
6
Why waste prognostic model
is needed
United Kingdom
Poland
100%
Other
Mineral
80%
Plastics
60%
Glass
Metals
40%
Paper
20%
Textiles
Organics
0%
1879
1925
1965
1978
1995
1998
Data sources: Williams, P.T., Szpadt, R., 1999
Underlying factors:
Socio-economic development, consumption patterns,
environmental awareness etc.
7
Data collection on waste generation
and socio-political developments
• Waste Quantities
• Factors of Influence
– general (temp., area, population)
– economic (GDP)
– social (education, housing equipment)
– environment (CO2 emission)
– waste management (waste treatment capacity)
time series: 1970 – 2001
32 states, 55 cities
over 33.000 data sets 8
Delivery: Prognostic model
Waste generation
analysis
W=f(A,B)
Prognosis of
influencing factors
A
B
W
A
B
1980
1990
2000
2010
Waste prognosis
W
W ... Waste quantity
A,B ... Influencing
factors (e.g.
population,
average size of
households)
B
A
1980
1990
2000
2010
9
Why waste management
planning tools are needed
Example: Poland
selective collection –
app. 2% of MSW;
the rest landfilled
bottom lining
5% accord. EU standards
25% - one layer lining
70% no isolation
leachate collection
20% of all landfills
gas installation
10% of landfills
10 plants – el. engine
10
Why waste management
planning tools are needed
Case study: Poland
Polish Waste Law:
(...) the next urgent step is to develop waste management
plans:
• at regional level:
• at the county level
• at the commune level
by June 2003
by December 2003
by June 2004
Potential to develop optimal waste management
systems !!!
• lack of experience on advance waste management technology
• lack of data for impact assessment
• lack of public acceptance
11
Waste management assessment
model
Scenario 1
Landfill
Energy
Scenario 2
Incineration
Scenario 3
Landfill
Energy
Compost
Incineration
Landfill
Mech.-Biol.
Composting
Pretreatment
Scenario 4
Energy
Mech.-Biol.
Pre-treatment
Landfill
Cement kiln
Scenario 5
Energy
Materials
Recycling
Compost
Mech.-Biol.
Composting
Pretreatment
Incineration
12
Landfill
Assessment tool structure
Prognostic
model
INVENTORY
Waste
generation
economic
indicators
Temporary
storage
module 1
Temporary
storage
module n
Collection
module 1
Collection
module n
Transport
module 1
Transport
module n
Treatment
module 1
Treatment
module n
Products:
energy and secondary materials
Credit
module 1
Credit
module n
Material / energy flow
LEGEND (waste, products
environm.
indicators
social
indicators
ASSESSMENT
economic
criteria
environm.
criteria
social criteria
AGGREGATION
Im
pa
ct
I
m
p
a
ct
Im
pa
ct
reference
reference
reference
scenario 1
scenario 1
scenario 1
scenario n
scenario n
scenario n
Information flow
(emissions, costs)
13
Sources of criteria selection for
waste management assessment
2) Specific targets of the European Waste Policy (landfill
directive, packaging directive, WEEE)
Social
3) Targets of the European 6th Environment Programme
4) Consortium understanding of sustainability in waste
management
14
Economic
5) Targets of the selected municipalities
6) Expertise of involved partners
Environmental
1) General objectives of waste management
according to Framework Directive on Waste (74/442/EEC
as amended by 91/156/EEC)
Environmental criteria
for WM assessment - examples
– global warming potential
– health impact (toxic emissions)
– resources consumption
LCIA approach
- reduction of landfilling of organic waste
- recovery & recycling targets for glass, paper,
plastics
EU Recovery/
recycling quotas
15
Waste valorisation
minimisation
Local employment
creation
Social equity
Waste minimisation
Quality of
employment
Benefits distribution
Social acceptance
Costs allocation
Private and urban
space consumption
Perceived risk
Visual impact
Odour, Noise
Social criteria and
indicators for WM assessment examples
Social sustainability
Social function
16
Problems & Further work
• European dimension
• Prognosis model development – data availability
• Level of detail of the assessment criteria and
indicators
• Quantification of standard module inventory data
• Verification phase in the involved municipalities
• Tools and Handbook
17