Transcript Quantifying releases of Priority Pollutants from Urban Sources

Preliminary Results
From the ScorePP Project
Hans-Christian Holten Lützhøft and Eva Eriksson
DTU Environment, Technical University of Denmark, Kgs. Lyngby, Denmark
SOCOPSE Final Conference
Maastricht (NL)
24 June 2009
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
The ScorePP project
A Specific Targeted
Research Project (STREP)
Funded by the European
Commission under the 6th
Framework Programme
(4th Call), sub-priority
1.1.6.3 ”Global Change
and Ecosystems”
Duration: 01OCT2006 to
30SEP2009 +6 months
Budget: 3.6 M EUR, 2.6
M EUR from the EC
9 partners
4 case cities
www.scorepp.eu
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
The ScorePP approach
Limiting release through:
- Substitution
- Minimising release from products
- Legislation and regulations
- Voluntary use reductions
Example: Combined system:
D+T
R+T
D+T
Treatment options:
- Stormwater BMPs
- Household treatment & reuse of WW
- On-site industrial treatment
- WWTPs
- Sludge disposal
Sinks:
- Primary: Surface water (WFD)
ELV ...  
- Secondary: Sediments,
soils/gr., water, humans, ...
T
O +T
T
T
EQS ...  ?
D+T
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Aim
The main project aim is to develop comprehensive and appropriate
Source Control Options that authorities, cities, water utilities and
chemical industry can employ to Reduce Emissions of Priority
Pollutants from urban areas
which will be pursued through




identifying potential sources and to quantify releases of priority
pollutants
identifying emission barriers that can be implemented at appropriate
stages in the priority pollutant release process
defining archetype cities in order to define emission control strategies
studying the pollutant flows in society to be able to assess the
important stocks and pathways
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Approach
Establish Source Classification Framework
Compile data on sources & releases
Classifying using ESs
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Source Classification Framework
Requirements
Content should be structured and organised in a harmonised way
Ensure that the different sources could be distinguished from each other
To be valid EU wide
Dynamic and to be used after this project ends
Inspiration
US EPA SCC
TGD
Harmonised codes like CN, NACE and NOSE
EINECS, CAS#
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Source Classification Framework –
the Emission String concept
CAS #: unique identification of each substance
NOSE: unique identification of emission processes
NACE: unique identification of economic activities related with the source
ES_Type: a ScorePP defined urban structure descriptor
Agriculture
Construction sites
Facilities; e.g. factories, dentists, slaughter houses (legal entities)
Households
Railways
Rivers
Roads
Waste sites/landfills
and more
All data are stored in a database
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Compiling data
Risk Assessment Reports from EU
Hazardous Substance Data Bank and Household Product Database from
US NLM
Handbooks and electronic compilations, e.g. the Merck Index, Rippen, the
e-Pesticide Manual, Kirk-Othmer’s Encyclopedia of Chemical Technology
Research articles
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Classifying sources using the ES concept
Evaporation
Evaporation
NOSE
Wear & tear
NACE
Waste
ES_Type
Disposal
Plasticiser, by-products, impurities
CAS#
Release factor
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
SCF tested on a selection of WFD substances
Substance
Major use/function
Representing
Anthracene
Atrazine
Benzene
B(a)P
Cl-alkanes
Cadmium
Chlorpyrifos
DEHP
Diuron
Endosulfan
Endrin
HCB
HCBD
HCH
Lead
Mercury
DCM
Nickel
NPs
DDT
PBDE
PeCB
TEL
TBTs
TCE
Trifluralin
Intermediate (lower PAH)
Pesticide, triazine
Intermediate
Combustion product (higher PAH)
Flame-retardant/metal working fluid
Metal. Wide variety of functions
Pesticide, organophosphate
Plasticizer
Pesticide, urea
Pesticide, cyclodiene organochlorine
Pesticide, cyclodiene
Impurity/by-product
Impurity/by-product
Pesticide, cyclodiene organochlorine
Metal. Wide variety of functions
Metal. Wide variety of functions
Solvent, chlorinated methane
Metal. Wide variety of functions
Intermediate
Pesticide
Flame-retardant
Impurity/by-product
Alkyllead anti knocking agent
Pesticide/stabilizer in plastics
Solvent, chlorinated ethane
Pesticide, selective soil herbicide
Naphthalene; fluoranthene
Alachlor; simazine
trichlorobenzenes
Higher PAHs
Chlorfenvinphos
Isoproturon
Alfa-endosulfan; partly PeCP
Aldrin; dieldrin; isodrin
Lindane; partly PeCP
Alkyl mercury
Cl-methanes
Alkyl phenols
DDT derivatives
Alkyl lead
Alkyl tin
Cl-ethylenes
Partly isoproturon
hr
a
At cen
Be
nz Beraz e
C o(a nz ine
hl )p e
or y ne
oa re
C lka ne
C ad ne
hl m s
or iu
py m
rif
D os
D CM
E
En D HP
do iur
su on
En lfan
dr
H in
H CB
C
BD
H
C
H
M Lea
er d
cu
N
Tr ic ry
ifl ke
ur l
al
i
N n
PB Ps
PeDE
C
B
TE
TB L
T
TC s
E
An
t
ESs with ...
Introduction
100
Sources
Visualisation
Strategies
Substance
Substance flows
Number of ESs for each PP
(ab 900 ESs in total)
150
RF
Load
Miscellaneous
No data
50
0
Conclusions
Ag
r
Ai icu
r t ltu
ra re
n
C
on B sp
st ui ort
ru ld
D cti ing
iff on s
u
W se s site
as o s
te urc
di es
sp
El os
ec al
tr
Fa icit
ci y
li
Fo ties
re
G stry
H ard
ou e
se ns
ho
ld
s
M
O in
th in
er g
R use
ai
lro s
ad
R s
iv
Se R ers
a oa
t
W ran ds
at sp
er o
s u rt
pp
ly
ESs with ...
Introduction
Sources
Visualisation
Strategies
600
400
200
150
ES_Type
Substance flows
Number of ESs in each urban structure
(ab 900 ESs in total)
RF
Load
Miscellaneous
No data
100
50
0
Conclusions
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Environmental releases due to
vehicular transport on roads
Anthracene
Combustion: 5,2-28 µg/kg fuel burned, depending on vehicle and fuel type
Benzene
Combustion: 4-10 mg/km driven, depending on vehicle type
Benzo(a)pyrene
Combustion: 1-8 µg/km driven, without and with catalyst
Cadmium (from both break linings, tyres, fuel and asphalt)
7 kg/year is released in Stockholm with 780.000 inhabitants
DEHP (from undercoating)
200 kg/year is released in Stockholm with 780.000 inhabitants
Mercury
Tyres: 4-240 µg/km depending on vehicle type
Roads: 3-17 µg/km depending on vehicle type
Nickel
Combustion: 21-107 and 3,2-2310 ng/km driven, for gasoline and diesel,
respectively
Brake-linings, tyres and asphalt: 91-182 ng/km
Introduction
Sources
Visualisation
Strategies
Substance flows
Statistics for Denmark year 2007
Data on driven km and use of fuel (Danish Statistics, 2009)
Person cars (both diesel and gasoline)
35·109 km
Taxis (both diesel and gasoline)
51·107 km
Motorbikes
76·107 km
Mopeds
90·106 km
Total
36·109 km
Vans (both diesel and gasoline)
79·108 km
Lorries
14·108 km
Semi-trailers
92·107 km
Busses
62·107 km
Total
11·109 km
Fuel used for vehicle engines
2,4·109 kg
Conclusions
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Environmental releases due to
vehicular transport on roads
Depending on fuel and
vehicle type:
Release of nickel from Danish
highways: 108 kg
Anthracene: 12-67 kg
Nickel: 4,4-117 kg
Benzene from
busses, lorries etc:
105 tonnes
Benzene from cars:
154 tonnes
Cadmium: 49 kg
Benzo(a)pyrene:
360 tonnes
Mercury:
0,3-12 tonnes
DEHP: 1,41 tonnes
Plus releases of anthracene from wear & tear of tyres and asphalt and
release of anthracene, benzene, benzo(a)pyrene due to leakage & spillage
Thomas Ruby Bentzen, PhD thesis (2008)
Introduction
Sources
Visualisation
Strategies
Example of source mapping
Substance flows
Conclusions
Introduction
Sources
Visualisation
Strategies
Emission barriers using GIS
Substance flows
Conclusions
Introduction
Sources
Visualisation
Strategies
Emission barriers using GIS
Substance flows
Conclusions
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Potential emission barriers for a specific source
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Potential emission barriers for a specific area
Introduction
Sources
Visualisation
Strategies
Substance flows
Potential sites for an emission barrier
Conclusions
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Case cities and ’Semi-hypothetical case city
archetypes’
Case cities : Vastly different with respect to
climate, industry, treatment technologies
and environmental awareness.
+ Real-life monitoring, existing industries and
release patterns etc
- Limited by confidential or missing
information
SHCCA: Designed to represent different
geographical and urban systems
All data available which is needed for further
work (modelling, visualisation, multi-criteria
analysis, evaluation of emission control
strategies).
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Archetypes
Geographical system
Climate; Size; Rainfall; Population etc
Urban system
Urban structures; Financial and activity systems;
Technical systems and consumption; Pollution
level; Local authorities and households
Emission control strategies
Generic and city specific
Emission control
strategies
Urban
system
Geographical
system
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Limiting release and emissions
Pre-Application Control: Voluntary and
regulatory initiatives, legislation,
Limiting release through:
preventative measures, phasing out,
- Substitution
substitutions- Minimising
etc
release from produtcs
D+T
- Legislation and regulations
- Voluntary use reductions
Pre-Environmental Release
Treatment: municipal and industrial
Treatment options:
WWTPs and -greywater
as well as
Stormwater BMPs
& reuse of WW etc
treatment treatment
- Household
combined sewer
overflows
D+T
T
- On-site industrial treatment
- WWTPs
- Sludge disposal
Post-Environmental
Release
Control
and Treatment: structural and nonSinks:
structural stormwater
best management
(WFD)etc
water
- Primary: Surfaceof
practices, management
sinks
- Secondary: Sediments,
soils/gr.water, humans, ...
O+T
T
T
D+T
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
An example of Pre-Application Control
Case city Stockholm
Pre-application control campaigns in the period 1995-2003
Stricter EU and national legislations
New technologies (batteries)
Voluntary initiatives e.g., artists paint (Cd), anglers (Pb) also dentists
(Hg)
Substance flow analyses showed a reduction in the stocks of Cd and Hg
by approximately 25 % to 30 %. Cd and Hg inflow was substantially
reduced, but Pb inflow increased.
Individual campaigns cannot be quantified due to the lack of field data
Månsson et al (2008) Phasing Out Cadmium, Lead, and Mercury Effects on Urban Stocks and Flows. Journal of
Industrial Ecology
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Emission control strategies
Emission control strategies are combination of individual barriers
(source control or treatment units)  individual barriers should also
be evaluated.
Initial test-set:
1: Baseline
2: Implementation of relevant EU directives
3: 2 + Household voluntary initiatives and on-site treatment
4: 2 + Industrial Best Available Technologies
5: 2 + Post-Environmental Release Control and Treatment
(stormwater and CSO)
6: 2 + Advanced end-of-pipe treatment
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Tool for assessing effects of emission control
strategies
Inflow
STOCK
Outflow
Substance flow analysis:
Test the framework for a selected substance: Di(2-etylhexyl) phthalate
(DEHP)
Utilise the Emission String DB
Compare estimated environmental loads with monitoring data
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Size and distribution of stock
Roofings
25000
Undersealing paste
20000
tonnes
Shoe soles
15000
Coated textiles
10000
Films, sheets, coated
products
Tubes and profiles
Floor and wall coverings
5000
Cables
0
Stock 2002
Stock 2009
Introduction
Sources
Visualisation
Strategies
16
14
tonnes/year
12
10
8
6
4
Printing ink
Lacquers and paint
Sealants and adhesives
Combustion
Release during transport
Roofings
Car wash
Undersealing paste
Shoe soles
Coated textiles
Films, sheets, coated products
Tubes and profiles
Floor and wall coverings
Cables
Substance flows
Conclusions
Fate of
emissions
2
0
Surface water
Air
Urban surface
WWTP sludge
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Comparing SFA results with measured data
Loads (in
tonnes/year)
WWTP sludge
SFA
Measured
0.7
1
WWTP effluent
0.1
0.07-0.12
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Conclusions
SCF established – based on literature knowledge about sources
About 900 ESs established for the 25 WFD substances
Overall 16% with concrete knowledge about release quantity
Overall 65% without any quantitative data on release into the technosphere
WFD substances occur in a wide variety of sources and activities in urban
settings and are released to all studied compartments
Most sources are related to production activities
Other large categories are households, waste disposal, agriculture, construction
and transport
Linking the urban descriptor/the ESs with GIS enables good visualisation
tools
Sources can be plotted on a map
Substances can be plotted on a map
Source control options, e.g. waste water and stormwater treatment units can
be shown on a map
Introduction
Sources
Visualisation
Strategies
Substance flows
Conclusions
Conclusions
Semi-hypothetical case cities provide valuable possibilities as all data
needed for evaluation are present
Source control and mitigation options can be highly beneficial
Not all priority pollutants can be substituted
Some substances are not removed with conventional treatment units
Combined approaches merging source control and treatment is needed
Substance flow analysis can be a valuable tool for evaluation emission
control strategies and identification of the most important emissions
Acknowledgement
Tonie, Maria and Arne from Miljöforvaltningen (SV)
Mike, Erica, Lian and Christoph from Middelsex University (UK)
Webbey, Veerle, Lorenzo and Frederik from University of Ghent (BE)
André from ENVICAT (BE)
Kemi, Luis and Emmanuel from Anjou Recherche (FR)
Matej, Natasa, Primoz and Boris from University of Ljubljana (SL)
Peter from Université Laval (CAN)
Colette and José from Estudis (SP)
Luca, Anna and Peter (project coordinator) from DTU Environment (DK)
The presented results have been obtained within the framework of the project
ScorePP - “Source Control Options for Reducing Emissions of Priority Pollutants”,
contract no. 037036, a project coordinated by Department of Environmental
Engineering, Technical University of Denmark within the Energy, Environment and
Sustainable Development section of the European Community’s Sixth
Framework Programme for Research, Technological Development and
Demonstration.