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APPENDIX 2.3 Field Survey Result
(Presentation Summary)
1. Amman, Jordan
2. Buenos Aires, Argentina
3. Conakry, Guinea
4. Kathmandu, Nepal
5. Lahore, Pakistan
6. Sarajevo, Bosnia And Herzegovina
7. Shanghai, China
8. Kawasaki, Japan
9. Atlanta, Georgia, USA
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1
1
City 1: Amman (Jordan)
2
Schedule, Meetings and Site Visit
Schedule:Nov. 14 Nov. 26
Visited Organizations for Meeting:GAM (Greater Amman Municipality), Jordan Biogas Co, ArabPaper Converting & Trading Co, Jordan Paper and CardboardFactories Co, Friends of Environment Society, Ministry ofEnvironment, Ministry of Municipal Affairs, Ministry of Health,Ministry of Planning and International Cooperation, UNHABITAT
Visited SWM Facilities:Al Ghabawy Landfill, Al Rusaifah Landfill and Biogas facility, AlShaer TS, Al Yarmook TS, Ain Gazal TS, Slaughterhouse,
3
City & SWM Profile
Capital City, 688 km2
Temperature: 26, Precipitation: 230 mm GNI per capita: US$2,500 (2005, WDI)
Population: 2,125,000 Total Generation: 2,174 tonnes/day Generation rate: 1.02 kg /person/day
4
Waste Composition
2%
42%
11%9%
16%
2%
2% 14%
2%
Yard Trim m ings, Leaves Food W aste
C orrugated C ardboard M ixed Paper
Plastic G lass
M etal Textile and R ubber
O thers
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2
5
Waste Flow in Amman
Collection
Incineration*Ash
LandfillMSW
Landfill
Remanufacturing
Facility
Recycling
* Incineration can be with or without energy recovery.
Composting
Compost Product
End Use
6
Summary of SWM System
Discharge: 1100 litre metal containers, some220 litre plastic containers, street sweepers
Collection: High Rate, Municipality Collects, HighFrequency, Mixed Collection
Transfer: Three Transfer Stations
Disposal: Landfill with small scale MRF
Others: Gas recovery and Biogas digesters atold landfill with Electricity Generation
7
Collection
8
Transfer
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3
9
Disposal
10
Alternatives
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1
1
City 2: Buenos Aires (Argentina)
2
Schedule, Meetings and Site Visit
Schedule:Sep. 24 Oct. 6
Visited Organizations for Meeting:CBA, WB, ARS (Solid Waste Association), CEAMSE(Metropolitan Area Ecologic Coordination Society), AIDIS (Inter-americanAssociation of Sanitary Engineers), UBA, Cliba, IATASA, El
Ceibo Visited SWM Facilities:
Pompeya T/S, Relleno Sanitario Norte III,Relleno Sanitario Villa Dominico
3
City & SWM Profile
Capital City, 203 km2 (CBA), 4,758 km2 (GBA) Temperature: 17, Precipitation: 1,200 mm GNI per capita: US$4,470 (2005, WDI)
Population: 2,776,138 (2001), nearly 3 million inCBA in 2006, 12.4 million (2001) in GBA Total Generation: 4,300 tonnes/day (CBA),
13,617 tonnes/day Generation rate: 0.979 kg /person/day
4
Waste Composition
5% 1%
24%
14%1%35%
4%
3% 2% 4%1%6%
Yard Trim m ings, Leaves W oods
Paper Plastic
Rubber, Leather Food W aste
Diapers M etal
G lass Dem olition
Hazardous M isc.
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2
5
Waste Flow in Buenos Aires
Collection
Incineration*Ash
LandfillMSW
Landfill
Remanufacturing
Facility
Recycling
* Incineration can be with or without energy recovery.
Composting
Compost Product
End Use
6
Summary of SWM System
Discharge: Container, on-the-Ground, PlasticBags
Collection: High Rate, Private Contractor, HighFrequency, few Segregated Collection
Transfer: Three Transfer Stations Disposal: Landfill with small scale MRF &
Composting Others: Gas Recovery at Landfill, Beatification
Inspection, Cartonaros (Recycling)
7
Discharge
8
Collection
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3
9
Transfer Haul
10
Disposal
11
Landfill Gas Collection
12
Alternatives (compost)
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4
13
Alternatives (MRF)
14
Alternatives (Community Based Recycling)
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1
1
City 3: Conakry (Guinea)
2
Schedule, Meetings and Site Visit
Schedule:Dec. 6 Dec. 18
Visited Organizations for Meeting:SPTD (Service Public de Transfert des Dechets),PDU3 (3rd Urban development Project), Guinenned'Assainissement (SME), Electricit de Guine,Ministry of Public Health
Visited SWM Facilities:La Minire Landfill, Transfer points, Pilot compost,Slaughterhouse
3
City & SWM Profile
Capital City, Temperature: 27, Precipitation: 4,293 mm GNI per capita: US$ 370 (2005, WDI)
Population: 2,000,000 Total Generation: 800 tonnes/day Generation rate: 0.4 kg /person/day
4
Waste Composition
8%
40%
19%5%
3%
1%
12%5% 7%
Y ard W aste Food W astePaper PlasticsM etal G lass
Textile & Rubber Leather & Anim al M anureO thers
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2
5
Waste Flow in Conakry
Collection
Incineration*Ash
LandfillMSW
Landfill
Remanufacturing
Facility
Recycling(informal)
* Incineration can be with or without energy recovery.
Composting(pilot)
Compost Product
End Use
6
Summary of SWM System
Discharge: on-the-ground, in non standardcontainers within properties
Pre-Collection: Low Rate, SMEs (Small &Medium-sized Enterprises), High Frequency,Mixed Collection
Collection/Transfer: Low Rate, MunicipalityCollects, High Frequency, Mixed Collection
Transfer: 62 transfer points (Arm-roll containers) Disposal: Landfill with informal recycling & pilot
composting
7
Pre-collection
8
Collection
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3
9
Disposal
10
Alternatives
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1
1
City 4: Kathmandu (Nepal)
2
Schedule, Meetings and Site Visit
Schedule:
Dec. 11 Dec. 23
Visited Organizations for Meeting:
SWMRMC, KMC, LSMC, BKM, MTM, KRM,SchEMS, Watsan
Visited SWM Facilities:Teku T/S, Sisdol Landfill, BKMs SegregatedCollection and Compost
3
City & SWM Profile
Capital City, 580Km2 (Valley) Temperature: 13, Precipitation: 2,000 mm GNI per capita: US$ 270 (2005, WDI)
Population: 1,099,158 (5 municipalities total,estimated for 2004) Total Generation: 434.9 tonnes/day (5
municipality, 2004 estimate) Generation rate: 0.4 kg /person/day (5
municipality average, 2004)
4
Waste Composition
3% 12%8%
3%
0%
71%
0%
1%0%
2%
Yard Trim m ings, Leaves Paper
P lastic Textile
Rubber, Leather Food W aste
M etal G lass
C eram ics M isc.
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2
5
Waste Flow in Kathmandu
Collection
Incineration*Ash
LandfillMSW
Landfill
Remanufacturing
Facility
Recycling
* Incineration can be with or without energy recovery.
Composting
Compost Product
End Use
6
Summary of SWM System
Discharge: Container, on-the-Ground, PlasticBags
Collection: Mid Rate, Door to Door (PrivateCompany, NGO by Tri-cycle), Bell Collection,few Segregated Collection
Transfer: One Transfer Station
Disposal: Landfill, Open Dumping, Composting(very small scale; windrow, vermi, home-composting)
Others: Long transportation haul
7
Discharge
8
Collection
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3
9
Transfer Haul
10
Disposal (Sisdol Landfill)
11
Disposal (Open Dump)
12
Alternatives (compost)
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4
13
Alternatives (Vermi Composting)
14
Alternatives (Recycling)
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1
1
City 5: Lahore (Pakistan)
2
Schedule, Meetings and Site Visit
Schedule:
Nov. 25 Dec. 10
Visited Organizations for Meeting:
The Urban Unit, CDGL, University ofEngineering and Technology
Visited SWM Facilities:Mahamood Booti LF, Saggian D/S, NashitarD/S, CDGLs workshops, Lahore Composting,Waste Busters, Children Hospital
3
City & SWM Profile
Capital City of Punjab, 1,772 Km2
Temperature: 20, Precipitation: 500 mm GNI per capita: US$ 690 (2005, WDI)
Population: 8,000,000 (2006, estimate) Total Generation: 5,200 tonnes/day Generation rate: 0.65 kg /person/day (2006,
estimate)
4
Waste Composition
28%
19%4%9%
1%
2%
1%
0%
25%0%
11%
F ood / K itchen L eaves & G rass, S traw & W ood
P aper P lastic & R ubber & P olyethylene B ags
C lothes/ Rags Bones
Anim al W aste G lass
M etal Dust, Dirt, Ashes, Stones, Bricks, etc
O ther
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2
5
Waste Flow in Lahore
Collection
Incineration*Ash
LandfillMSW
Landfill
Remanufacturing
Facility
Recycling
* Incineration can be with or without energy recovery.
Composting
Compost Product
End Use
6
Summary of SWM System
Discharge: Container, on-the-Ground, PlasticBags
Collection: Mid Rate, Door to Door (PrivateCompany, NGO by Tri-cycle),
Transfer: No Transfer Station
Disposal: Landfill, Open Dumping, Composting Others: Hospital waste incinerator
7
Discharge
8
Collection
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3
9
Intermediate Treatment (Composting Plant)
10
Disposal
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1
1
City 6: Sarajevo (Bosnia & Herzegovina)
2
Schedule, Meetings and Site Visit
Schedule:Sep. 26 Oct. 9
Visited Organizations for Meeting:Cantonal Public Utility Rad, Cantonal PublicUtility Park, Papir Servis, Ministry ofEnvironment and urban development
Visited SWM Facilities:Smiljevii Landfill (& MRF), Papir Servis,Hospital, Slaughterhouse
3
City & SWM Profile
Capital City, 1,227 km2
Temperature: 17, Precipitation: 1,200 mm GNI per capita: US$2,440 (2005, WDI) Population: 410,000 Total Generation: 492 tonnes/day Generation rate: 1.2 kg /person/day
4
Waste Composition
1%
37%
17%13%
6%
8%
18%
Yard Trimmings, Leaves Food Waste
Paper Plastics
Metal Glass
Misc.
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2
5
Waste Flow in Sarajevo
Collection
Incineration*Ash
LandfillMSW
Landfill
Remanufacturing
Facility
Recycling
* Incineration can be with or without energy recovery.
Composting
Compost Product
End Use
6
Summary of SWM System Discharge: 1100 litre metal containers,
occasional collection of large items (furniture,white goods) some dedicated yard waste pick-up, street sweepers
Collection: High Rate, Municipality Collects,Medium Frequency, Pilot Segregated Collection
Transfer: Direct to Landfill Disposal: Landfill & MRF Others: Gas Recovery and Electricity Generation
at Landfill
7
Collection
8
Disposal
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3
9
Alternatives
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1
1
City 7: Shanghai (China)
2
Schedule, Meetings and Site Visit
Schedule:
Oct. 26 Nov. 13, Dec. 18 22
Visited Organizations for Meeting:
SCEID, SIDREE, SCAESAB, Shanghai ElectricPower Design Institute, Tongji University
Visited SWM Facilities:Huangpu Transfer Station, Jiangqiao incinerator,Yangpu Transfer Station, Huling Dock, Gacu dumping
site, Minghan dumping site, Laogang Landfill Site
3
City & SWM Profile
Most urbanized city in China, 6,340 Km2
Temperature: 15, Precipitation: 1,440 mm GNI per capita: US$ 1,740 (2005, WDI), Local
GDP per capita: >US$ 7,000 (2006, investment
Shanghai) Population: 17,800,000 Total Generation: 17,000 tonnes/day Generation rate: 0.96 kg /person/day
4
Waste Composition
63%
19%
2%
8%
3%0%
3%2% 0%
Kitchen and Fruits Plastic
Papers Cloth
Bam boo & wood M etal
Glass Slag & stones
Hazardous and others
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2
5
Waste Flow in Shanghai
Collection
Incineration*Ash
LandfillMSW
Landfill
Remanufacturing
Facility
Recycling
* Incineration can be with or without energy recovery.
Composting
Compost Product
End Use
6
Summary of SWM System
Discharge: Container, on-the-Ground, PlasticBags
Collection: High Rate, Compactor Truck
Transfer: 5 Transfer Stations, 8 Canal Docks
Disposal: 1 Landfill, Many Open Dumping sites,
1 Composting Plant, 2 Incinerators Others: Gas recovery at landfill
7
Discharge and Pre-collection
8
Collection
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3
9
Transfer Station and Dock
10
Intermediate Treatment
11
Disposal
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1
1
City 8: Kawasaki (Japan)
2
Schedule, Meetings and Site Visit
Schedule:
October 2006 February 2007
Visited Organizations for Meeting:
Environmental Dept. of Kawasaki City
Visited SWM Facilities:
Kase Transfer Station, Sikine Incinerator,Ukisima Final Disposal Site (sea reclamation),Ukisima Incinerator, Nanbu MRF, ShikineMRF
3
City & SWM Profile
Metropolitan City between Tokyo and Yokohama,144 Km2
Temperature: 17, Precipitation: 1,932 mm GNI per capita: US$ 38,980 (2005, WDI) Population: 1,327,000 Total Generation: 1,399 tonnes/day Generation rate: 1.01 kg /person/day
4
Waste Composition
3%
33%
14%4%5%
36%
1% 4%
W ood and leaves Paper Plastic
M etals G lass Food W aste
Fabric M isc.
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2
5
Waste Flow in KawasakiCollection
Incineration*Ash
LandfillMSW
Landfill
Remanufacturing
Facility
Recycling
* Incineration can be with or without energy recovery.
Composting
Compost Product
End Use
6
Summary of SWM System Discharge: Plastic bags, Community collection
points Collection: High Rate, Segregated collection,
Small compactor truck, Group recyclablecollection
Transfer: 1 Transfer Station, Railwaytransportation
Disposal: 4 Incinerators, 5 MRF, 1 Ash Landfill(Sea Reclamation)
Others: Power generation at 3 Incinerators
7
Collection and Transport
8
Transfer Station
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3
9
Material Recovery Facility
10
Incinerator
11
Disposal
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1
City 9: Atlanta (United States)
City Profile
Atlanta was selected as a representative US city
Area: 343 km
Atlanta has a population of roughly 442,000
GNI per capita is US$37,750
Annual precipitation is about 1,270 mm
The average temperature is 16.
City Waste Data
Total Generation: 2,899 tonnes/day
Population: 442,000
Generation rate: 1.72 kg /person/day
Collection: 2,174 tonnes/day
Collection efficiency: 75%
Waste landfilled: 2,038 tonnes/day
7%
41%
15%6%
4%
12%
15%
Yard Trim m ings Paper Plastic M etals
Glass Food W aste M iscellaneous
Waste Composition
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APPENDIX 2.4.1 Composition Rate for Compostablematerials vs. Economic Indicator (GDP or GNI)
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0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Tan
za
nia/Da
rE
sS al a
am(
39
wa
rds)(
19
96
)
Ni g
er/Ni a
mey
(20
01
)
Lao
s/V
ien
tia
n(1
99
1)
Ke
nya
/Nai r
ob
i(19
97
)
Nep
al/K
athm
an
du
(***)
Egy
pt/
Ale
xa
nd
ria(1
98
4)
G uine
a/C
onak
ry(*
** )
Vietn
am/H
anoi
(20
00
)
Nicar a
gua
/Mana
gu
a(1
995)
Pak
ista
n/Raw
alpi n
di(19
95
)
Paki s
tan/Q
uetta
(199
6)
I nd
on
es
ia/Ja
ka
rta
(1986
)
Ind
on
esi a
/S ur a
ba
ya
(199
2)
Eg
yp
t/A
lexa
nd
ria
(1994
)
Phil
ipp
ine
s/M
etr
op
olita
nM
an
ila(1
99
7)
Paki s
tan/L
ah
ore
(***)
S ryL
an
ka
/Mo
ratu
wa
(19
97
)
Indo
nes
ia/U
jung
pa
nd
an
g(19
94
)
S r y
Lan
ka/B
adu
lla(2
00
2)
S ry
Lan
ka/C
hi l
aw
(2002
)
S ry
La
nk
a/G
am
pa
ha(2
002
)
S ryL
anka
/Ka
nd
y(2
002)
S r y
Lan
ka
/Ma
tal e
(200
2)
S ry
La
nk
a/N
eg
om
bo(2
002
)
S ryL
ank
a/Nu
wara
Eliya
(20
02
)
G u
ate
ma
la/M
etro
pol i
tan(1
99
2)
Bul g
aria
/S of i
a(1
993
)
S yri
a/L a
tak
iaan
do
ther
thr e
eci ti e
s(2
001
)
S yr i
a/A
lepp
o(1
997
)
Per u
/Lima
(7
distr
icts
in
no
rtha
na
reas
)(1
98
4)
S y
ria/D
ama
sc
us(1
99
5)
Mo
rocc
o/S
afi(
Thre
eu
r ban
co
mmu
nes
)(1
99
6)
Kaza
khs
tan/A
lmaty
(19
99
)
Po
lan
d/P
oz
na
n(1
99
2)
Do
mi n
ica/S
an
toD
om
ingo
(200
6)
Ro
mania
/Buc
har e
st(1
99
4)
Pe
ru/K
aja
yo(
19
95)
Par ag
uay/A
sun
cin
Metr
opolita
n(19
94
)
Ma
laysia
/Pen
an
(198
8)
Bosn
ia/S
ara
jevo
(** *
)
Jo
rdan/A
mm
an(*
**)
Pa
na
ma/P
an
am
a(2
00
2)
Tu
rke
y/A
da
na
metr
opo
lita
n(1
99
8)
Tu
rkey/M
ersi n
Metr
op
oli
tan(1
998
)
Hu
nga
ry/B
uda
pes
t(1
99
2)
Me
xic
o/M
exico
city(
1998
)
Ar g
en
tine
/Buen
os
Aire
s(**
*)
C h
ina/S
han
gh
ai(**
*)0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
Kitchen waste(%) Wood, Grass(%) GDP or GNI(dollors/person/year)% dollors/person/year
GDP, GNI or RGDPLow High
A2.4-2
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APPENDIX 2.4.2 Compostable: kitchen waste and yard waste(wood and grass), by regional areas
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0
10
20
30
40
50
60
70
80
90
100
Tanzania/DarEsSalaam
(39wards)(1996)
Niger/Niamey(2001)
Kenya/Nairobi(1997)
Guinea/Conakry(***)
LaoPDR/Vientian(1991)
Indonesia/Jakarta(1986)
Indonesia/Surabaya(1992)
Philippines/Metropolitan
Manila(1997)
Indo
nesia/Ujungpandang(1994)
Malaysia/Penan(1988)
China/Shanghai(***)
Bulgaria/Sofia(1993)
Kazakhstan/Almaty(1999)
Poland/Poznan(1992)
Romania/Bucharest(1994)
Bosnia/Sarajevo(***)
Turkey/Adana
metropolitan(1998)
Turkey/Mersin
Metropolitan(1998)
Hungary/Budapest(1992)
Nicaragua/Managua(1995)
Guatemala/Metropolitan(1992)
Peru/Lima(7districtsin
northanareas)(1984)
Dominica/Santo
Domingo(2006)
Peru/Kajayo(1995)
Paraguay/Asuncin
Metropolitan(1994)
Panama/Panama(2002)
Mexico/Mexicocity(1998)
Argentine/BuenosAires(***)
Egypt/Alexandria(1984)
Egypt/Alexandria(1994)
S
yria/Latakiaandotherthree
cities(2001)
Syria/Aleppo(1997)
Syria/Damascus(1995)
Morocco/Safi(Threeurban
communes)(1996)
Jordan/Amman(***)
Nepal/Kathmandu(***)
Pakistan/Rawalpindi(1995)
Pakistan/Quetta(1996)
Pakistan/Lahore(***)
SriLanka/Moratuwa(1997)
SriLanka/Badulla(2002)
SriLanka/Chilaw(2002)
SriLanka/Gampaha(2002)
SriLanka/Kandy(2002)
SriLanka/Matale(2002)
SriLanka/Negombo(2002)
SriLanka/NuwaraEliya(2002)
Africa East Asia & Pacific Europe and Central Asia Latin America and Caribbean Middle East and North
Africa
South Asia
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
Kitchen waste Wood, Grass GDP or GNI(dollors/person/year)% dollors/person/year
A2.4-4
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APPENDIX 2.4.3 Composition Rate for Combustiblematerials vs. Economic Indicator (GDP or GNI)
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0
10
20
30
40
50
60
70
80
90
100
Tan
zan i
a/Dar
EsS
ala
am
(3
9w
ard
s)(
199
6)
Nig
er /
Ni a
me
y(2
001)
Lao
s/V
ien
tia
n(19
91
)
Ke
ny
a/N
air
ob
i(1
997
)
Ne
pal /
Ka
thma
ndu
(** *
)
Egy
pt/
Alex
an
dr i
a(1
98
4)
G uin
ea/C
ona
kry(*
**)
Vie
tna
m/Ha
no
i(2
000
)
Nica
rag
ua
/Mana
gu
a(1
99
5)
Pa
ki s
tan/R
aw
alp
ind
i(19
95
)
Pa
kista
n/Q
uetta
(199
6)
Indo
ne
sia
/Ja
ka
rta
(198
6)
Indon
es
ia/S
ur a
ba
ya
(19
92
)
Eg
yp
t/Ale
xa
nd
ria(1
99
4)
P h
i lipp
ine
s/M
etrop
olita
nMa
nila
(1997
)
Pa
kista
n/La
hor e
(***
)
Sry
La
nk
a/M
ora
tuwa
(199
7)
Indo
nes
ia/U
jung
pan
da
ng
(19
94
)
Sry
Lank
a/B
ad
ulla
(20
02
)
Sry
La
nka
/C hila
w(2
002)
SryL
ank
a/G
am
pah
a(2
00
2)
Sr y
La
nk
a/K
an
dy
(20
02)
Sry
La
nka
/Mata
le(2
00
2)
Sr y
Lan
ka/N
ego
mbo
(20
02
)
Sry
Lank
a/N
uw
ara
Eliya
(20
02
)
G ua
tem
ala
/Metr
opo
lita
n(1
99
2)
Bu
lga
ria
/So
fia(1
993)
Syr i
a/La
takia
and
oth
er
thr e
ec
itie
s(2
00
1)
Sy
ria
/Ale
pp
o(1
99
7)
Pe
ru/L
ima(7
distr
ictsin
no
rth
ana
reas
)(1
98
4)
Syr i
a/D
am
as
cus
(19
95
)
Moroc
co
/Sa
fi(
Th
ree
urb
an
comm
un
es
)(19
96
)
Kaz
akh
sta
n/A
lmaty
(19
99
)
Po
lan
d/P
oz
nan
(199
2)
Do
min
ica
/Santo
Dom
ing
o(2
00
6)
Rom
an
ia/B
uch
ar e
st(19
94
)
Pe
ru/K
aja
yo
(1995
)
Pa
ra
guay
/Asu
nci
nM
etrop
olita
n(199
4)
Malay
si a
/Pena
n(1
98
8)
Bos
ni a
/Sara
jev
o(*
**)
Jord
an
/Am
ma
n(*
**)
Pa
na
ma/Pa
na
ma(20
02
)
Tu
rke
y/A
da
na
metr
opo
litan
(19
98
)
Turk
ey
/Me
rsi n
Metr
op
olita
n(1
99
8)
Hu
ng
ary
/Bu
da
pe
st(1
99
2)
Me
xico
/Mex
icoc
ity
(1
998
)
Ar g
entin
e/B
ue
nos
Aire
s(**
*)
C hi n
a/Sh
ang
ha
i(*
**)
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
Combustible(%) GDP or GNI(dollors/person/year)% dollors/person/yearGDP, GNI or RGDPLow High
A2.4-6
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APPENDIX 2.4.4 Composition Rate for Combustiblematerials vs. Economic Indicator (GDP or GNI), by regionalareas
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0
10
20
30
40
50
60
70
80
90
100
Tanzania/DarEsSalaam
(39wards)(1996)
Niger/Niamey(2001)
Kenya/Nairobi(1997)
Guinea/Conakry(***)
Laos/Vientian(1991)
Vietnam/Hanoi(2000)
Indonesia/Jakarta(1986)
Indonesia/Surabaya(1992)
Philippines/Metropolitan
Manila(1997)
Indo
nesia/Ujungpandang(1994)
Malaysia/Penan(1988)
China/Shanghai(***)
Bulgaria/Sofia(1993)
Kazakhstan/Almaty(1999)
Poland/Poznan(1992)
Romania/Bucharest(1994)
Bosnia/Sarajevo(***)
Turkey/Adana
metropolitan(1998)
Turkey/Mersin
Metropolitan(1998)
Hungary/Budapest(1992)
Nicaragua/Managua(1995)
Gu
atemala/Metropolitan(1992)
Peru/Lima(7districtsin
northanareas)(1984)
Dominica/Santo
Domingo(2006)
Peru/Kajayo(1995)
Paraguay/Asuncin
Metropolitan(1994)
Panama/Panama(2002)
Mexico/Mexicocity(1998)
Argentine/BuenosAires(***)
Egypt/Alexandria(1984)
Egypt/Alexandria(1994)
S
yria/Latakiaandotherthree
cities(2001)
Syria/Aleppo(1997)
Syria/Damascus(1995)
Morocco/Safi(Threeurban
communes)(1996)
Jordan/Amman(***)
Nepal/Kathmandu(***)
Pakistan/Rawalpindi(1995)
Pakistan/Quetta(1996)
Pakistan/Lahore(***)
S
ryLanka/Moratuwa(1997)
SryLanka/Badulla(2002)
SryLanka/Chilaw(2002)
SryLanka/Gampaha(2002)
SryLanka/Kandy(2002)
SryLanka/Matale(2002)
SryLanka/Negombo(2002)
SryLanka/NuwaraEliya(2002)
Africa East Asia & Pacific Europe and Central Asia Latin America and Caribbean Middle East and North
Africa
South Asia
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
Combustible(%) GDP or GNI(dollors/person/year)% dollors/person/year
A2.4-8
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APPENDIX 2.4.5 Composition Rate for Recyclable materialsvs. Economic Indicator (GDP or GNI)
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0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Tan
zan
ia/Da
rE
sS
al a
am
(3
9w
ards)(
19
96
)
Nige
r/Ni a
mey
(20
01)
Lao
s/V
ienti
an(1
99
1)
Ken
ya
/Na
irob
i(1
997
)
Nepa
l/K
ath
ma
nd
u(*
**)
Eg
ypt/
Alexa
nd
ria
(198
4)
G ui n
ea
/C o
na
kry
(** *
)
Vi e
tnam
/Ha
no
i(2
00
0)
Ni c
ar a
gu
a/M
anag
ua
(19
95)
Pak
ista
n/R
awal p
indi(
199
5)
Pa
ki s
tan/Q
ue
tta
(199
6)
Indon
esi a
/Jaka
rta
(1986)
Indo
ne
sia
/Su
rabay
a(1
99
2)
Egyp
t/A
lex
an
dria
(19
94
)
Ph
ili p
pin
es
/Metro
po
lita
nM
an
ila
(199
7)
Paki s
tan/L
aho
re(** *
)
Sr y
Lan
ka/M
oratu
wa
(1
997)
Ind
on
es
ia/U
jun
gp
and
an
g(1
99
4)
SryL
anka
/Ba
du
lla(2
00
2)
SryLa
nk
a/C
hi l
aw
(2002
)
Sry
La
nk
a/G
am
pa
ha(2
002
)
Sry
Lan
ka
/Ka
nd
y(2
00
2)
Sr y
Lan
ka/M
atale
(2002
)
Sry
Lank
a/N
eg
om
bo
(20
02)
SryL
an
ka
/Nu
wa
raEliy
a(2
002)
G u
ate
ma
la/M
etro
po
lita
n(1
992
)
Bul g
ar i
a/S
of i
a(1
99
3)
Syri
a/L
ata
kia
an
do
the
rth
ree
ci t
ies(2
001
)
Sy
ria/A
leppo
(199
7)
Per u
/Lim
a(7
di s
tricts
inn
orth
ana
reas)
(19
84
)
Sy
ria
/Da
ma
sc
us(1
99
5)
Mo
rocco
/Sa
fi(
Th
reeu
rban
co
mm
unes)(
199
6)
Kaz
akh
sta
n/A
lmaty
(19
99
)
Po
lan
d/P
ozn
an
(1992
)
Dom
inica
/Sa
nto
Dom
ing
o(2
006
)
Rom
an
ia/B
uch
ar e
st(19
94
)
Pe
ru/K
aja
yo
(1
99
5)
Para
gu
ay
/Asunc
inM
etrop
olita
n(199
4)
Mala
ysia
/Pen
an(1
98
8)
Bos
ni a
/Sar a
jev
o(*
**)
Jord
an
/Am
man
(***)
Pan
ama
/Pan
ama
(200
2)
Tu
rke
y/A
da
nam
etro
pol i
tan
(1998
)
Tur k
ey/Me
rsinM
etr
op
ol i
tan(1
998
)
Hu
ng
ary
/Bu
da
pes
t(1
99
2)
Me
xic
o/M
ex
ico
cit
y(
199
8)
Arge
nti
ne/B
uen
osA
ire
s(*
**)
C hin
a/S
ha
ngh
ai(*
**)
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
Paper Plastic Metal Glass GDP or GNI(dollors/person/year)% dollors/person/year
GDP, GNI or RGDPLow High
A2.4-10
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APPENDIX 2.4.6 Composition Rate for Recyclable materialsvs. Economic Indicator (GDP or GNI), by regional areas
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0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
90.0
100.0
Tanzania/DarEsSalaam
Niger/Niamey(2001)
Kenya/Nairobi(1997)
Guinea/Conakry(***)
Laos/Vientian(1991)
Vietnam/Hanoi(2000)
Indonesia/Jakarta(1986)
Indonesia/Surabaya(1992)
Philippines/Metropolitan
Indo
nesia/Ujungpandang(1994)
Malaysia/Penan(1988)
China/Shanghai(***)
Bulgaria/Sofia(1993)
Kazakhstan/Almaty(1999)
Poland/Poznan(1992)
Romania/Bucharest(1994)
Bosnia/Sarajevo(***)
Turkey/Adana
Turkey/Mersin
Hungary/Budapest(1992)
Nicaragua/Managua(1995)
Guatemala/Metropolitan(1992)
Peru/Lima(7districtsin
Dominica/Santo
Peru/Kajayo(1995)
Paraguay/Asuncin
Panama/Panama(2002)
Mexico/Mexicocity(1998)
A
rgentine/BuenosAires(***)
Egypt/Alexandria(1984)
Egypt/Alexandria(1994)
Syria/Latakiaandotherthree
Syria/Aleppo(1997)
Syria/Damascus(1995)
Morocco/Safi(Threeurban
Jordan/Amman(***)
Nepal/Kathmandu(***)
Pakistan/Rawalpindi(1995)
Pakistan/Quetta(1996)
Pakistan/Lahore(***)
S
ryLanka/Moratuwa(1997)
SryLanka/Badulla(2002)
SryLanka/Chilaw(2002)
SryLanka/Gampaha(2002)
SryLanka/Kandy(2002)
SryLanka/Matale(2002)
SryLanka/Negombo(2002)
Sry
Lanka/NuwaraEliya(2002)
Africa East Asia & Pacific Europe and Central Asia Latin America and Caribbean Middle East and North
Africa
South Asia
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000
10,000
Paper Plastic Metal Glass GDP or GNI(dollors/person/year)% dollors/person/year
A2.4-12
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APPENDIX 2.5 ANALYSIS ASSUMPTIONS
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Waste:
For scenario analysis, each city has a large enough waste flow to get economiesof scale in each treatment option considered.
Lf not providedassume percent office paper in waste is 5 percent of paper
waste; remaining paper waste is then assumed split equally between cardboard
and newsprint.
Collection Assumptions;
For the purpose of focusing analysis on comparison of treatment technologies,
Collection is being made similar across the cities. There are TWO sets of
relevant assumptions one for the Cost of Collection the other related to
emissions and energy consumption for collection. In this manner we can
capture the relevant differences between collection of Non-segregated waste
and collection of Segregated wastes that will be appropriate for some of the
technologies considered. The following are those assumptions identified to
date:
A. Cost of Collection:
Low income $35
Middle income $45
Shanghai, Buenos Aires $55
US $90
Japan $120
*for extra 20 km to landfill, add $10 per metric ton
B. Emissions and Energy Consumption of Collection
1) Assume 100 percent collection
2) Daily collection is 6 days per week"
3) Collection vehicle travel speeds:
I it 30 k / h
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4) Travel distances
Collection vehicle to city boundary 20 km
City boundary to treatment 10 km
Treatment to landfill 20 km
Composting to end user 20 km
MRF to remanufacturing 10 km
5) Waste segregation at the households
We may find it useful to include this in the list of sensitivity analyses rather than
building into the Collection assumptions for the scenario runs. However it is
provided here for clarity
High cooperatjon 60 percent
Low cooperation 20 percent
6) For the purposes of collection assumptions, we defined low, middle and
higherincome cities. They are assumed as follows:
Low: Kathmandu, ConakryMiddle: Lahore, Amman, Sarajevo
Higher: Shanghai, Buenos Aires
7) Split of city waste:
% of waste Families per stop
Laid out areas" 10 percent 2
Mixed Commercial and Multi-family 90 percentLow income cities 30
Middle income cities 30
Shanghai & Buenos Aires 60
8) Household size:
Low income 6 persons per family
Middle income 6 persons per familyShanghai & Buenos Aires 4 persons per family
AII Laid out areas 6 persons per family
9) Collection vehicle mix:
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10) Equipment Prices
Compactor $85,000
Open Tipper $60,000 assumes construction type vehicles rather than
lighter duty waste truck design a common practice in
developing countries.
11) Annual O&M on vehicles:
20 percent of capital cost
12) Economic life of collection vehicles: 7 years throughout
13) Waste density in collection vehicles in developing country cities:
Compacted 500 kg per cubic meter
Un-compacted 300 kg per cubic meter
14) Labor requirements assumptions:
Always driver and 3 collectors on compactors
Always driver and 4 collectors on open trucks
1 supervisor per 5 trucks
1 mechanic per5trucks
1 inspector per5trucks
Collectors paid 10 percent less than driver. others above paid drivers rate.
15) Labor rates VERY city specific; use data collected in field visits
16) Benefits above salary [since govt employees] are typically 30%
Economic Scale for Treatment Technologies in metric tons perday
Landfill 300
Incineration 300 with energy recovery and meeting EU standards
Composting 150
MRF 150*below 100 metric tons per day, we assume the volume is too small to conduct
incineration
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Landfill
1. Open Dump Scenario has 30% open burning; bums in pockets; remaining isas open dump landfill. The burning results in issues with lead, volatilized
organics, etc. Need to deal with resulting pollutants.Ozge is checking
whether the open barrel burning work included lead. on the remaining open
dump, Thornloe-provided emission factors will be used.
2. Assuming ALL remaining landfills described in the scenarios [i.e. beyond
number l above on open dump"] will be FLARED LANDFILLS. This issomewhat different from what some team members remember Sandra
suggesting so we will check this before proceeding. Some recall this being
energy recovery landfills". Flared seems like a better assumptions since
this is little increase on carbon avoided between these two and energy
recovery are more difficult.
3. Landfills are 15 meters deep. 3:l slope except will add note in report thatindicates that 5:1 may be required in areas of seismic activity. Seventy (70)
percent of acreage is landfill cells. Remainder is buffer, lagoons for
treatment, etc
4. Gas capture 70 percent
Will use 50 and 80 percent on sensitivity analysis
5. The World Bank acknowledges that municipal landfills in developing
countries are okay to accept 10 percent of waste volume as sanitary
sludges and animal wastes. Sanitation sludges are expected to be
dewatered to 70 percent moisture. Animal wastes are typically 60 percent
moisture.
6. The following ranges were assumed for composition of these wastes inlandfill as mentioned above:
Percent of Total Waste
Lo Base Hi
S it ti l d 3% 6% 10%
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MRF and IncinerationRequire skilled labor
EU standards apply
Vehicle and Other Equipment FuelsAll vehicles use diesel fuel which contains NOLEAD
Vermicomposting
l. Vermicomposting is always performed on waste that has already been
treated [at least partially] in a Composting treatment step. (1)
2. Assume 10 percent of Composting always goes to vermicomposting.
3. Assume price multiplier from India study for differential of vermicompost
market price over regular compost.
Incineration
NK/RTI will check for anomalies using the following that are typical values of
wastes are as follows:
Low income 800900 kcal/kg
Middle 900 1000 kcal / kgHigher income 1000 1 300 kcal / kg
The above were provided by Sandra considering her former field work that
included the following: Singapore 1500; Seoul 1300; India 800
Assume oil is bought to bring the heating value up high enough to sustain burning
in scenarios requiring the use of incineration.
Per Capita Income for Cities Studied
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Carbon Finance
1. World Bank assumes l metric ton methane = 21 metric ton CO22. Carbon credit is currently $10/ metric ton Carbon. Since this has been as low
as $3.50 as recently as 3 years ago, Bank Carbon Finance staff should be
asked to provide a forecast so team can do sensitivity analysis.
3. Carbon Finance is based on metric tons of methane reduced or avoided.
4. Always include Carbon Finance as Revenue in relevant scenarios. Need to
discuss whether there is a minimum economic floor for level of carbon
credit.5. Use UN requirements for determining most likely payment. This requires the
use of the landfill decay model. UN does not presently allow recycling
offsets.
6. Consider also analyzing for what the World Bank would LIKE to see as the level
of payment.
7. Check new lPPC report.
8. Charles Peterson, World Bank, is a resource on this.
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APPENDIX 2.5.1 FIELD DATA FOR GENERAL INPUT BY CITY
Appendix 2.5.1 Field Data for General Input by City
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Katmandu Conakry Lahore Sarajevo Amman Buenos Aires Shanghai Kawasaki Atlanta
270 370 690 2,440 2,500 4,470 1,740 (7,000) 38,980 43,740
0.08 0.09 0.49 1.78 0.70 6.90 2.10 18.49 11.00
16 27 23 10 26 17 15 17 16
Mixed waste MRF-Manual sorting
yes yes yes yes
Mixed waste MRF-Automated sorting
yes yes yes
Commingled MRF-Manual sorting
Commingled MRF-Automated sorting
yes
Windrow composting yes yes yes yesAerated Pile composting yes yes
stemanagementunits
GNI/capita ($US)
Collector Wage ($US/person-hour)
Temperature (Deg C)
WTE yes yesIncineration yes
Anaerobic bioreactor yesAsh Landfill yes yes
Landfill vented yes yes yes
Landfill flared yes yes yesLandfill energy recovery yes yes yes
Notes :The value in the colum of GNI is based on World Development Indicators on database (Atlas methodology), World Bank, 1 July in 2005.The data in parenthesis is GDP data from "http://www.investment.gov.cn/2007-02-09/1169371958133.html".Katmandu & BsAs Temperature: http://www.bbc.co.uk/weather/world/city_guides/Lahore Temperature: http://worldweather.wmo.int/047/c00891.htmKawasaki Collector Wage: JP\440,000/25(d/m)/8(hr/d)/119(\/$)
Existingwa
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APPENDIX 2.5.2 FIELD DATA FOR GENERATION INPUTSBY CITY -METRIC
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Appendix 2.5.2 Field Data for Generation Inputs by City - Metric
Input to the
model
Katmandu
(collected)
Katmandu
(modeled)
Conakry
(collected)
Conakry
(modeled)
Lahore
(collected)
Lahore
(modeled)
Sarajevo
(collected)
Sarajevo
(modeled)
Amman
(collected)
Amman
(modeled)
Buenos Aires
(collected)
Buenos Aires
(modeled)
Shanghai
(collected)
Shanghai
(modeled)
Kawasaki
(collected)
Kawasaki (for
adjustment)
Kawasaki
(modeled)
Atlanta
(collected)
Atlanta
(modeled)
Plastic - Non-Recyclable yes 12.8%bles
DST
ories
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Misc. Combustibles yes 2.2% 11.6% 10.2% 10.2% 7.0% 6.2% 13.6% 12.0% 13.6% 12.6% 2.6% 0 .1% 4.6% 4.6% 5.2%
C&D Wood 1.7%
Other C&D 0.8%Inerts 0.2%
Drywall 0.5%
Carpet 1.7%
rubber/leather 0.5% 0.7% 0.3%Tires 0.3%
Ferrous - Non-recyclable yes 6.0% 5.3%
Al - Non-recyclable yes
Glass - Non-recyclable yes 8.0% 7.0% 0.0% 0.0% 0.4%
Misc. Non-combustibles yes 0.8% 7.4% 1 0.5% 22.7% 18.0% 15.8% 1.3% 4.1% 1.6% 1.5% 3.0% 0 .1% 4.2% 4.2% 2.3%
Ceramics 0.2%Ceramic, soil, rock 0.2%
Dust, Dirt, Ashes,
Stones, Brickes, slag, etc24.8% 0.3%
Other Inorganics 0.6%Supplement moisture and other wastes 3.9%
Computers 0.1%
Other Electronics 1.6%
6.0% 6.0% 6.0% 6.0% 6.0% 6.0% 6.0%
Bones 0.8%
Animal Waste 1.8%
1.3% 0.1% 0.5%
0.7% 0.9% 3.2%
4.5% 1.1%
100.0% 100.0% 100.0% 100.0% 100.5% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0%
MSWDST
categories
WasteComposition
M
iscellaneousCombustib
MSWD
catego
Others
Others
Animal
waste
Sanitary Sludge
Hazardous
Others
MiscellaneousNon-Combustibles
Others
Unclassified
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APPENDIX 2.5.3 FIELD DATA FOR COLLECTION INPUTS BY
CITY -METRIC
Appendix 2.5.3 Field Data for Collection Inputs by City - Metric
Collection costFamilies per stop
Household size in
the multifamilyNumber of Fraction of
Fraction of openUsable capacity of
Waste density in
compactor
Waste density in
compactor
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Collection cost
($US/metric ton)*in the multifamily
sector**
the multifamily
sector
(people/house)**
multifamily
collection locations
compactor
vehicles***
Fraction of open
trucks***compactor vehicles
(m3)
compactor
vehicles-
compacted (kg/m3)
vehicles-
uncompacted
(kg/m3)***
Katmandu 35 30 6 5,490 0.1 0.9 12 NF NFConakry 35 30 6 3,215 0.1 0.9 12 NF NF
Lahore 35 30 6 28,000 0.1 0.9 12 NF NF
Sarajevo 45 30 6 1,976 0.7 0.3 12 NF NF
Amman 45 30 6 10,520 0.7 0.3 12 NF NF
Buenos Aires 55 60 4 39,270 0.9 0.1 12 NF NF
Shanghai 55 60 4 64,413 0.9 0.1 12 NF NF
Kawasaki 120 50 2 12,784 1 1 6 500 300
Atlanta 90 50 2 11,352 1 1 12 500 300
Notes :
*Used to adjust the final results.**Used to estimate the number of multifamily collection locations
***MSW DST tool does not have a corresponding input.
NF: Not found. Set to be Kawasaki and Atlanta's value.
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APPENDIX 2.5.4 FIELD DATA FOR MRF INPUTS BY CITY
-METRIC
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APPENDIX 2.5.5 FIELD DATA FOR COMPOST INPUTS BY
CITY -METRIC
Appendix 2.5.5 Field Data for Compost Inputs by City - Metric
Number of
operating hours
(hours/day)
Number of
days per week
Operating days
per year
Wage for operator
($US/hour)
Wage for manager
($US/hour)
Compost
residence time
(days)
Curing stage
residence time
(days)
Compost pile
turning frequency
(times/week)
Value of compost
product ($US/metric
ton)
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(hours/day) (days) (days) (times/week) ton)Katmandu 7 7 365 0.08 0.18 57 0 0.75 15.00
Conakry 9 6 312 0.07 0.00 90 0 0.75 15.00
Lahore 0 0 0 0.39 0.00 90 0 0.00 30.00
Sarajevo 0 0 0 0.00 0.00 0 0 0.00 40.00
Amman 0 0 0 0.00 0.00 0 0 0.00 40.00
Buenos Aires 0 0 0 3.47 5.20 60 45 NA 50.00
Shanghai 0 0 0 0.00 0.00 0 0 0.00 50.00
Kawasaki 0 0 0 0.00 0.00 0 0 0.00 60.00
Atlanta 8 5 262 8.00 15.00 168 90 1.00 25.00
Notes :
NF means Not Found
Zero values mean that the default values are used (see Atlanta values)
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APPENDIX 2.5.6 FIELD DATA FOR INCINERATION INPUTS
BY CITY -METRIC
Appendix 2.5.6 Field Data for Incineration Inputs by City - Metric
Waste heating values-
typical ranges (kcal/kg)*
Waste heating values
(kcal/kg)**
Unit WTE capital cost
($US/metric ton/year)
Unit WTE O & M cost
($US/metric ton/year)
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Katmandu 800- 900 2,212
Conakry 800- 900 2,147
Lahore 800- 900 2,161
Sarajevo 900- 1000 1,911
Amman 900- 1000 3,199
Buenos Aires 1000- 1300 3,134
Shanghai 1000- 1300 3,133 220.27 65.33
Kawasaki 3,185 1381.50 127.82
Atlanta 3,841 311.62 65.33
Notes :*Values provided as typical values.
**Values presented for comparison with typical values
Blank cells mean default values are used (see Atlanta values)
e au t va ue s use or t e un t & cost n ang a see t anta va ue
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APPENDIX 2.5.7 FIELD DATA FOR LANDFILL INPUTS BY
CITY - METRIC
Appendix 2.5.7 Field Data for Landfill Inputs by City - Metric
Active life of facility
(years)Number of cells
Post closure period
(years)Liner?
Depth of soil in
primary liner (cm)
Liner is single or
double?
Depth of soil in
secondary liner (cm)
Gas collection
efficiency (collected)
Gas collection
efficiency (modeled)
Katmandu 2 0 2 yes 24.99 single 0.00 0.00 0.70
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Conakry 30 2 10 no NA NA NA 0.00 0.70
Lahore 0 0 0 no NA NA NA 0.00 0.70
Sarajevo 25 7 10 yes 29.87 double 60.05 0.90 0.70
Amman 23 9 30 yes 20.12 double 0.61 0.75 0.70Buenos Aires 15 0 30 yes 91.44 single NA 0.70 0.70
Shanghai 20 12 0 yes 0.00 double 0.00 0.65 0.70
Kawasaki* 21 0 0 yes 0.00 0.00 0.00 0.00 0.00
Atlanta 20 5 30 yes 60.96 single 60.96 0.75 0.70
CO2 quality CH4 qualitySludge CH4 yield
(m3/metric tons)Precipitation (mm/yr)
Engineering rate
(capital)
Engineering rate
(operations)
Minimum labor cost
($US/year)
Maximum daily
waste handled by
minimum labor costs
(metric ton/day)
Utility rate as (as
fraction of labor
costs)
Katmandu 0.00 0.00 82.59 1995 0.00 0.00 5,991 384 0.00
Conakry 0.74 0.26 82.59 4293 0.05 0.05 1,827 298 0.00
Lahore 0.00 0.00 50.83 800 0.00 0.00 0 0 0.00Sarajevo 0.45 0.55 27.53 940 0.10 0.10 0 0 0.06
Amman 0.52 0.48 32.39 228 0.10 0.10 0 0 0.00
Buenos Aires 0.475 0.50 33.74 1194 0.00 0.00 0 0 0.00
Shanghai 0.3223 0.5487 34.41 1437 0.00 0.00 0 0 0.04
Kawasaki* 0 00 0 00 NA 1659 0 00 0 00 0 0 0 00. . . . .
Atlanta 0.45 0.55 NA 889 0.10 0.10 327,000 363 0.01
Overhead costs
(overhead cost $US/
wage $US)
Equipment and
maintenance
($US/year)
Capital cost of
turbine ($US)
Capital cost of
internal combustion
engine ($US)
Land prices
($US/m2)
Revenue from
electric buyback
rates ($US/Kwh)
Katmandu 0.18 0 0 0 2.0 0.00
Conakry 0.00 0 0 0 6.7 0.00
Lahore 0.00 0 0 0 29.3 0.00
Sarajevo 0.37 421 389,188 259,459 8.4 0.13
Amman 0.00 0 0 600,000 108.6 0.09
Buenos Aires 0.00 0 0 0 0.6 0.02
Shanghai 0.00 580 0 0 62.1 0.06
Kawasaki* 0.00 0 0 0 855.3 0.00
Atlanta 0.46 2,000 4,725,245 1,417,573 4.3 0.04
Notes :
NF: Not Found
NA: Not Applicable
*Kawasaki only has an ash landfill*Cost for equipment and maintenance in Conakry is set zero instead of the data collected in the field.
Zero values mean default values are used (see Atlanta values)
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APPENDIX 2.5.8 FIELD DATA FOR ENERGY INPUTS BY CITY
Appendix 2.5.8 Field Data for Energy Inputs by City
Katmandu Conakry Lahore Sarajevo Amman Buenos Aires Shanghai Kawasaki Atlanta
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Coal 0.076 0.47 0.011 0.2470 0.5645
Natural Gas 0.503 0.947 0.458 0.3327 0.2570 0.0975Residual Oil 0.745 0.02 0.046 0.3327 0.0262
Distillate Oil 0.046 0.005 0.3327 0.0820 0.0023
Nuclear 0.012 0.090 0.2910 0.2213
Hydro 0.9 0.225 0.110 0.51 0.006 0.390 0.1000 0.0859
Wood 0.0024
Other* 0.1 0.030 0.005 0.001 0.0018 0.0002
Coal yes yes yes yes yesNatural Gas yes yes yes yes
Residual Oil yes yes yes yes yes
Distillate Oil yes yes yes yes yes
Nuclear yes yes yes
Hydro yes yes yes
Wood yes yes yes
Other (diesel oil) yes yes yes
NF 0.07 NF 0.13 0.09 0.021 0.08 0.16 0.04
NF 0.0114 NF 0.05 0.05 0.018 0.06 0.09 0.04
3.26 3.46 2.39 4.62 1.67 1.76 2.24 3.60 2.40
Notes :
* In Lahore the others category correspond to diesel oil.
0.294
EnergyBreakdown
Electricity Cost- purchase
($US/kWh)
Electricity Price- sale
($US/kWh)
Diesel Fuel ($US/gal)
LFGTEFuelDisplacement
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APPENDIX 2.5.9 FIELD DATA FOR CONSTANS DATA
-METRIC
Appendix 2.5.9 Constants Data - Metric
Parameter Value Units Comments
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Parameter Value Units Comments
Fract ion o f res ident ial waste 0 .1 unit less Used to est imate the tota l generated was te for the res ident ia l sector .
Fract ion o f mult ifamily was te 0 .9 unit less Used to est imate the tota l generated was te for the mult ifami ly sec tor.
Fraction of residential waste- Kawasaki and Atlanta 0.5 unitlessUsed to estimate the total generated waste for the residential sector. Obtained from the Comprehensive Solid WasteManagement Plan- Introduction, City of Atlanta, December 2005.
Fraction of multifamily waste- Kawasaki and Atlanta 0.5 unitlessUsed to estimate the total generated waste for the residential sector. Obtained from the Comprehensive Solid Waste
Management Plan- Introduction, City of Atlanta, December 2005.
Fraction of sanitary sludges 0.06 unitless Used to estimate the modeled waste composition.
Fraction of animal waste 0.06 unitless Used to estimate the modeled waste composition.
Sanitary sludges moisture content 0.7 unitless
Animal waste moisture content 0.6 unitless This value was not used since animal waste was modeled as foodwaste per Keith Weitz et al.'s e-mail, May 23, 2007
Addit ional cos t per ext ra 20 km 10 $US/metri c ton MSW DST tool does not have a corresponding input .
Capture rate 1 unitless
Collection frequency 6 days/week
Families per stop in the residential sector 2 unitless
Household size in the residential sector 6 people/house
Usable capacity in open trucks 5 m3 MSW DST tool does not have a corresponding input.
Travel speeds:
*To city boundary 30 km/hr
*City boundary to treatment 45 km/hr
Travel distances:
*To city boundary 20 km
Generation
Collection
*City boundary to treatment 10 km
Fraction of waste to open burning 0.3 unitless Used to define the modeled scenarios.
Fraction of waste to open dumping 0.7 unitless Used to define the modeled scenarios.
MRF economic scale 150 metric tons/day Used to make decisions.
Travel speeds:
*MRF to remanufacturing 55 km/hr MSW DST tool does not have a corresponding input.
Travel distances:
*MRF to remanufacturing 10 km
Composting economic scale 150 metric tons/day Used to make decisions.
Fraction of composted waste to vermicompost 0.1 uni tless Used to adjust f inal resul ts.
Travel speeds:
*Composting to end user 55 km/hr MSW DST tool does not have a corresponding input.
Travel distances:
*C i d k MSW DST l d h di i
Open dump
Composting
MRF
Appendix 2.5.9 Constants Data - Metric
Parameter Value Units Comments
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Parameter Value Units Comments
Animal waste heating value 1797 Kcal/wet KgSet to be the foodwaste heating value as suggested by Keith Weitz and documented in Keith et al.'s e-mail, May 23,
2007.
Sanitary s ludge ult imate analysis data- Carbon 0.546 uni tless
Sanitary sludge ultimate analysis data- Hydrogen 0.079 unitless
Sanitary s ludge ult imate analysis data- Oxygen 0.32 uni tless
Sanitary sludge ultimate analysis data- Nitrogen 0.045 unitless
Sanitary s ludge ul timate analys is data- Chlorine 0 unit less
Sanitary s ludge ult imate analysis data- Sul fur 0.01 uni tless
Animal waste ult imate analysis data- Carbon 0.1790 uni tless
Animal waste ultimate analysis data- Hydrogen 0.0260 unitless
Animal waste ult imate analysis data- Oxygen 0.1290 uni tless
Animal waste ult imate analysis data- Nitrogen 0.0110 uni tless
Animal waste ult imate analysis data- Chlorine 0.0040 uni tless
Animal waste ult imate analysis data- Sul fur 0.0010 uni tless
Animal waste ult imate analysis data- Water 0.6000 uni tless
Animal waste ult imate analysis data- Ash 0.0510 un it less
Sanitary sludge ash content 0.05weight fraction (dry
basis)Set to be the foodwaste's value as suggested by Keith Weitz and documented in Keith et al.'s e-mail, May 23, 2007.
Animal waste ash content 0.05 weight fraction (drybasis)
Set to be the foodwaste's value as suggested by Keith Weitz and documented in Keith et al.'s e-mail, May 23, 2007.
Sanitary sludge combustion efficiency 0.95weight fraction
(volatile solidsSet to be the foodwaste's value as suggested by Keith Weitz and documented in Keith et al.'s e-mail, May 23, 2007.
Animal waste combustion efficiency 0.95weight fraction(volatile solids
Set to be the foodwaste's value as suggested by Keith Weitz and documented in Keith et al.'s e-mail, May 23, 2007.
Set to be the foodwaste's values as suggested by Keith Weitz and documented in Keith et al.'s e-mail, May 23, 2007.
Landfill
From Partial Oxidation of Sewage Sludge document, as suggested in Keith's e-mail, 5/29/07
Landfill Economic scale 300 metric tons/day Used to make decisions.
Travel speeds:
*Treatment to landfill 55 km/hr MSW DST tool does not have a corresponding input.
Travel distances:
*Treatment to landfill 20 km
Landfill depth 15 m
Landfill slope 33 percent
Landfill usable capacity 0.7 unitless MSW DST tool does not have a corresponding input.
Fraction of LF gas capture 0.7 unitless
Animal waste Lo (methane yield) 300.7 L/kg Set to be the foodwaste Lo value as suggested by Keith Weitz and documented in Keith et al.'s e-mail, May 23, 2007.
Sanitary sludge K (degradation rate) 0.11 yr-1 Set to be the foodwaste K value as suggested by Dr. Barlaz and documented in Ozge et al.'s e-mail, April 18, 2007.
Animal waste K (degradation rate) 0.11 yr-1 Set to be the foodwaste K value as suggested by Keith Weitz and documented in Keith et al.'s e-mail, May 23, 2007.
Methane Carbon dioxide equiv alent 21 unitless Used to adjust final results.
Carbon credit 12 $US/metric ton Used to adjust final results.
Others
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APPENDIX 3.3 OPTIMIZATION SCENARIOS MASS FLOWS BYCITY AND MANAGEMENT PROCESS
Table A3.3.1 Group 3- Maximizing Materials Recovery (Via Recycling and Composting) Mass Flow
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Mass Flow (Ton/year)
CollectionCity Scenario
R-Commingled
R-Residuals MF- YardWaste
MF- Commingled
Commingled
Recycling
Mixed Waste
Composting
Landfill
Disposal
Group 3 DHC 1,982 15,652 17,841 140,864 19,824 156,515 33,149
Group 3 BHC 1,982 15,652 17,841 140,864 19,824 156,515 33,149
Group 3 DLC 881 16,636 7,929 150,775 8,811 167,412 37,333Katmandu
Group 3 BLC 881 16,753 7,929 150,775 8,811 167,528 37,358
Group 3 DHC 1,437 8,890 12,931 80,008 14,368 65,112 36,143
Group 3 BHC 1,437 8,890 12,931 80,008 14,368 65,112 36,143
Group 3 DLC 639 9,688 5,747 87,192 6,386 87,192 27,796Conakry
Group 3 BLC 639 9,688 5,747 87,192 6,386 87,192 27,796
Group 3 DHC 11,518 134,628 103,663 1,211,651 115,181 734,284 730,730
Group 3 BHC 11,518 134,628 103,663 1,211,651 115,181 734,284 730,730
Group 3 DLC 5,119 141,027 46,072 1,269,242 51,192 820,727 730,730Lahore
Group 3 BLC 5,119 141,027 46,072 1,269,242 51,192 820,727 730,730
Group 3 DHC 2,176 16,939 19,587 152,454 21,763 169,393 27,578
Group 3 BHC 2,176 16,939 19,587 152,454 21,763 169,393 27,578
Group 3 DLC 967 18,149 8,705 163,336 9,673 181,484 32,656Sarajevo
Group 3 BLC 967 18,149 8,705 163,336 9,673 181,484 32,656
Group 3 DHC 14,941 71,451 134,473 643,058 149,414 714,508 147,520
Group 3 BHC 14,941 71,451 134,473 643,058 149,414 714,508 147,520
Group 3 DLC 7,159 79,233 64,431 713,099 71,590 687,998 259,177Amman
Group 3 BLC 7,159 79,233 64,431 713,099 71,590 687,998 259,177
Group 3 DHC 92,070 320,742 828,628 2,886,673 920,698 2,488,742 1,238,434
Group 3 BHC 92,070 320,742 828,628 2,886,673 920,698 2,488,742 1,238,434
Group 3 DLC 40,920 371,891 368,279 3,347,022 409,199 3,228,039 1,238,434
B
uenosAires
Group 3 BLC 40,920 371,891 368,279 3,347,022 409,199 3,228,039 1,238,434
Group 3 DHC 90,568 574,002 811,267 5,141,653 901,835 5,715,655 1,259,013
Group 3 BHC 90,568 574,002 811,267 5,141,653 901,835 5,715,655 1,259,013
Group 3 DLC 42,562 622,009 366,358 5,586,562 408,919 6,208,571 1,455,848Shanghai
Group 3 BLC 42,562 622,009 381,250 5,571,670 423,812 6,185,513 1,455,848
Group 3 DHC 67,688 220,056 84,278 203,466 151,967 423,521 108,399
Group 3 BHC 67,688 220,056 84,278 203,466 151,967 423,521 108,399
Group 3 DLC 30,084 257,660 37,457 250,287 67,541 507,947 140,768Kawasaki
Group 3 BLC 30,084 257,660 37,457 250,287 67,541 507,947 140,768
Group 3 DHC 103,499 333,853 102,137 329,460 205,636 663,312 182,673
Group 3 BHC 103,499 333,853 102,137 329,460 205,636 663,312 182,673
Group 3 DLC 46,000 391,352 45,394 386,203 91,394 777,555 227,180Atlanta
Group 3 BLC 46,000 391,352 45,394 386,203 91,394 777,555 227,180
Table A3.3.2 Group 4- Maximizing Energy Recovery Mass Flow
Mass Flow (Ton/year)
Collection Separation
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Collection Separation
City
ScenarioR-Mixed
Waste
R-
Commingled
R-
Residuals
MF-
Commingle
d
MF-
Residuals
Mixed
WasteCommingled
Combustion Disposal
Group 4 DHC 17,634 0 0 15,940 142,765 160,399 15,940 150,131 16,628
Group 4 BHC 17,634 0 0 15,940 142,765 160,399 15,940 150,131 16,628
Group 4 DLC 17,634 0 0 7,084 151,621 169,255 7,084 157,435 11,998Katmandu
Group 4 BLC 17,634 0 0 7,084 151,621 169,255 7,084 157,435 11,998
Group 4 DHC 10,327 0 0 8,602 84,337 94,663 8,602 88,910 12,845
Group 4 BHC 10,327 0 0 8,602 84,337 94,663 8,602 88,910 12,845
Group 4 DLC 10,327 0 0 3,823 89,116 99,443 3,823 92,820 13,552Conakry
Group 4 BLC 10,327 0 0 3,823 89,116 99,443 3,823 92,820 13,552
Group 4 DHC 146,146 0 0 82,473 1,232,841 1,378,987 82,473 1,306,119 241,879
Group 4 BHC 0 9,164 136,982 82,473 1,232,841 1,369,824 91,636 1,303,322 241,317
Group 4 DLC 0 4,639 141,507 41,751 1,273,563 1,415,070 46,390 1,343,481 249,850Lahore
Group 4 BLC 0 4,639 141,507 41,751 1,273,563 1,415,070 46,390 1,343,481 249,850
Group 4 DHC 19,116 0 0 11,584 160,457 179,573 11,584 168,601 52,518
Group 4 BHC 0 1,287 17,829 11,584 160,457 178,286 12,871 167,917 52,448
Group 4 DLC 19,116 0 0 5,148 166,893 186,008 5,148 175,750 53,159Sarajevo
Group 4 BLC 19,116 0 0 5,148 166,893 186,008 5,148 175,750 53,159
Group 4 DHC 86,392 0 0 15,466 762,064 0 15,466 848,457 85,309
Group 4 BHC 86,392 0 0 15,466 762,064 0 15,466 848,457 85,309
Group 4 DLC 86,392 0 0 6,874 770,657 0 6,874 857,049 90,179Amman
Group 4 BLC 86,392 0 0 6,874 770,657 0 6,874 857,049 90,179
Group 4 DHC 0 46,047 366,765 414,419 3,300,882 3,667,647 460,465 3,281,803 267,131
Group 4 BHC 0 46,047 366,765 414,419 3,300,882 3,667,647 460,465 3,281,803 267,131
Group 4 DLC 412,811 0 0 184,186 3,531,115 3,943,926 184,186 3,515,909 342,197
B
uenosAires
Group 4 BLC 0 20,465 392,346 184,186 3,531,115 3,923,461 204,651 3,506,190 338,732
Group 4 DHC 664,570 0 0 151,605 5,801,315 6,465,886 151,605 6,189,352 449,778
Group 4 BHC 0 16,925 647,646 151,605 5,801,315 6,448,961 168,530 6,181,379 447,630
Group 4 DLC 664,570 0 0 108,753 5,844,167 6,508,737 108,753 6,280,649 479,837Shanghai
Group 4 BLC 664,570 0 0 108,753 5,844,167 6,508,737 108,753 6,280,649 479,837
Group 4 DHC 0 46,404 241,340 46,404 241,340 482,680 92,808 447,299 54,688
Group 4 BHC 0 46,404 241,340 46,404 241,340 482,680 92,808 447,299 54,688
Group 4 DLC 0 20,624 267,120 20,624 267,120 534,240 41,248 473,587 61,754Kawasaki
Group 4 BLC 0 20,624 267,120 20,624 267,120 534,240 41,248 473,587 61,754
Group 4 DHC 0 83,134 354,217 82,040 349,557 703,774 165,175 602,327 86,779
Group 4 BHC 0 83,134 354,217 82,040 349,557 703,774 165,175 602,327 86,779
Group 4 DLC 0 36,949 400,403 37,897 393,700 794,103 74,846 675,852 104,377Atlanta
Group 4 BLC 0 36 949 400 403 37 897 393 700 794 103 74 846 675 852 104 377
Table A3.3.3 Group 5- Minimize Carbon (Global Warming) Emissions Mass Flow
Mass Flow (Ton/year)
Collection Separation
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Collection Separation
City
ScenarioR-Yard
waste
R-
MixedWaste
R-CommingledR-
Residuals
MF-
Commingled
MF-
Residuals
Mixed
Waste Commingled
CombustionAsh
Landfill
Group 5 DHC 0 0 1,349 15,285 12,137 145,558 152,853 13,485 155,220 17,203
Group 5 BHC 0 0 1,349 15,285 12,137 145,558 152,853 13,485 155,220 17,203
Group 5 DLC 0 0 505 17,128 4,549 154,155 171,284 5,055 152,944 12,531Katmandu
Group 5 BLC 0 0 505 17,128 4,549 154,155 171,284 5,055 152,944 12,531
Group 5 DHC 0 10,327 0 0 4,420 88,519 98,845 4,420 93,978 13,525
Group 5 BHC 0 0 491 9,835 4,420 88,519 98,355 4,911 93,855 13,497
Group 5 DLC 0 10,327 0 0 1,955 90,975 101,301 1,955 95,381 14,035Conakry
Group 5 BLC 0 0 218 10,108 1,955 90,975 101,083 2,183 95,283 14,011
Group 5 DHC 0 0 14,974 131,172 134,755 1,180,548 1,311,720 149,740 1,224,371 237,472
Group 5 BHC 14,131 0 14,974 117,041 134,755 1,180,548 1,297,588 149,740 1,224,371 237,472
Group 5 DLC 0 0 5,555 139,491 59,895 1,255,418 1,394,909 55,551 1,285,099 247,010Lahore
Group 5 BLC 0 0 5,555 139,491 59,895 1,255,418 1,394,909 55,551 1,285,099 247,010
Group 5 DHC 0 0 558 18,548 5,110 155,931 185,479 5,577 177,881 53,500
Group 5 BHC 0 0 558 18,548 5,110 155,931 185,479 5,577 177,881 53,500
Group 5 DLC 0 0 252 18,853 2,271 159,770 188,533 2,523 181,325 53,820Sarajevo
Group 5 BLC 0 0 252 18,853 2,271 159,770 188,533 2,523 181,325 53,820
Group 5 DHC 0 0 7,701 78,592 59,305 708,225 785,917 77,005 731,530 72,220
Group 5 BHC 0 0 7,701 78,592 59,305 708,225 785,917 77,005 731,530 72,220
Group 5 DLC 0 0 3,422 82,970 30,802 745,728 829,598 34,225 755,525 77,825Amman
Group 5 BLC 0 0 3,422 82,970 30,802 745,728 829,598 34,225 755,525 77,825
Group 5 DHC 0 0 53,580 349,231 572,224 3,143,077 3,492,308 535,804 3,121,422 253,575
Group 5 BHC 0 0 53,580 349,231 572,224 3,143,077 3,492,308 535,804 3,121,422 253,575
Group 5 DLC 0 0 28,258 384,553 254,322 3,450,979 3,845,533 282,580 3,379,275 335,395
Bu
enosAires
Group 5 BLC 0 0 28,258 384,553 254,322 3,450,979 3,845,533 282,580 3,379,275 335,395
Group 5 DHC 0 0 59,783 594,787 525,084 5,327,835 5,922,523 594,857 5,517,283 415,474
Group 5 BHC 0 0 59,783 594,787 525,084 5,327,835 5,922,523 594,857 5,517,283 415,474
Group 5 DLC 0 0 31,015 533,555 277,815 5,575,105 5,308,550 308,830 5,799,091 455,385Shanghai
Group 5 BLC 0 0 31,015 533,555 277,815 5,575,105 5,308,550 308,830 5,799,091 455,385
Group 5 DHC 0 0 45,595 241,049 45,595 241,049 482,097 93,391 442,147 55,272
Group 5 BHC 0 0 45,595 241,049 45,595 241,049 482,097 93,391 442,147 55,272
Group 5 DLC 0 0 20,754 255,990 20,754 255,990 533,981 41,507 455,494 52,541Kawasaki
Group 5 BLC 0 0 20,754 255,990 20,754 255,990 533,981 41,507 455,494 52,541
Group 5 DHC 0 0 42,257 395,085 41,711 389,885 784,971 83,978 735,984 100,575
Group 5 BHC 0 0 42,257 395,085 41,711 389,885 784,971 83,978 735,984 100,575
Group 5 DLC 0 0 18,785 418,555 18,538 413,059 831,525 37,324 770,041 114,045Atlanta
Table A3.3.4 Group5- Minimize PM (Global Dimming) Emissions Mass Flow
Mass Flow (Ton/year)
C ll i S i Di l
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Collection Separation DisposalCity Scenario
R-Commingled R-Residuals MF-Commingled MF-Residuals MixedWaste Commingled
Combustion
Landfill Ash-landfill
Group 5 DHC 89,255 348,097 88,081 343,515 591,513 177,335 599,287 0 85,592
Group 5 BHC 89,255 348,097 88,081 343,515 591,513 177,335 599,287 0 85,592
Group 5 DLC 39,559 397,583 39,147 392,450 790,133 78,815 574,055 0 104,258Atlanta
Group 5 BLC 39,559 397,583 39,147 392,450 790,133 78,815 574,055 0 104,258
Group 5 DHC 95,754 558,805 857,810 5,095,110 5,553,915 953,574 5,158,031 0 381,953
Group 5 BHC 95,754 558,805 857,810 5,095,110 5,553,915 953,574 5,158,031 0 381,953
Group 5 DLC 42,552 522,009 381,249 5,571,571 5,193,579 423,811 5,570,281 0 433,833Shanghai
Group 5 BLC 42,552 522,009 381,249 5,571,571 5,193,579 423,811 5,570,281 0 433,833
Group 5 DHC 92,070 320,742 828,528 2,885,573 3,207,414 920,598 2,785,581 0 228,221
Group 5 BHC 92,070 320,742 828,528 2,885,573 3,207,414 920,598 2,785,581 0 228,221
Group 5 DLC 40,920 371,891 358,279 3,347,022 3,718,913 409,199 3,189,992 0 315,539
BuenosAires
Group 5 BLC 40,920 371,891 358,279 3,347,022 3,718,913 409,199 3,189,992 0 315,539
Group 5 DHC 1,982 15,552 17,841 140,854 155,515 19,824 0 147,415 0
Group 5 BHC 1,982 15,390 17,841 140,854 155,253 19,824 0 147,155 0
Group 5 DLC 787 15,847 7,084 151,520 158,457 7,872 0 157,029 0Katmandu
Group 5 BLC 787 15,847 7,084 151,520 158,457 7,872 0 157,029 0
Group 5 DHC 54,208 223,535 54,208 223,535 447,071 128,417 395,458 0 51,559
Group 5 BHC 54,208 223,535 54,208 223,535 447,071 128,417 395,458 0 51,559
Group 5 DLC 28,537 259,207 28,537 259,207 518,414 57,074 431,548 0 59,181Kawasaki
Group 5 BLC 28,537 259,207 28,537 259,207 518,414 57,074 431,548 0 59,181
Group 5 DHC 1,287 17,829 11,584 150,457 178,285 12,871 173,594 0 52,795
Group 5 BHC 1,287 17,829 11,584 150,457 178,285 12,871 173,594 0 52,795
Group 5 DLC 572 18,544 5,148 155,893 185,435 5,720 179,538 0 53,377Sarajevo
Group 5 BLC 572 18,544 5,148 155,893 185,435 5,720 179,538 0 53,377
Group 5 DHC 17,500 128,545 158,398 1,155,915 1,285,452 175,998 1,190,581 0 233,955
Group 5 BHC 17,500 128,545 158,398 1,155,915 1,285,452 175,998 1,190,581 0 233,955
Group 5 DLC 7,822 138,324 70,399 1,244,915 1,383,239 78,221 1,254,085 0 244,835Lahore
Group 5 BLC 7,822 138,324 70,399 1,244,915 1,383,239 78,221 1,254,085 0 244,835
Group 5 DHC 15,108 70,285 144,959 532,551 702,845 151,077 0 520,224 0
Group 5 BHC 15,108 59,341 144,959 532,551 701,903 151,077 0 519,281 0
Group 5 DLC 7,159 79,233 54,431 713,100 792,333 71,590 0 588,455 0Amman
Group 5 BLC 7,159 79,233 54,431 713,100 792,333 71,590 0 588,455 0
Group 5 DHC 1,437 8,890 12,931 80,008 88,898 14,358 82,187 0 12,303
Group 5 BHC 1,437 8,890 12,931 80,008 88,898 14,358 82,187 0 12,303
Group 5 DLC 539 9,588 5,747 87,192 95,880 5,385 88,444 0 13,215Conakry
G 5 BLC 539 9 588 5 747 87 192 95 880 5 385 88 444 0 13 215
APPENDIX 3.4 Simulation and Optimization Scenario
Results by City
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Results by City
1. Amman, Jordan
2. Atlanta, Georgia, USA
3. Buenos Aires, Argentina
4. Conakry, Guinea
5. Kathmandu, Nepal
6. Kawasaki, Japan
7. Lahore, Pakistan
8. Sarajevo, Bosnia And Herzegovina
9. Shanghai, China
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APPENDIX 3.4.1 Amman, Jordan
ParameterUnits (per
year)Recycling- manual sort Recycling- Mechanical sort
Group 2- All MSW to One Option
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Col lect ion Transfer Separation Treatment Disposal Transportat ion Remanufacturing Col lect ion Transfer Separation Treatment Disposal Transportat ion Remanufacturing
Cost with land price US$ 24,210,508 0 16,965,986 0 33,658,185 1,439,922 -17,578,557 24,210,508 0 14,691,851 0 33,658,185 1,439,922 -17,578,557
Cost without land price 17,449,346 17,449,346
Energy Consumption MJ 123,688 0 138,644 0 295,602 14,043 -2,385,737 123,688 0 247,385 0 295,602 14,043 -2,385,737
Air Emissions
Mercury (Air) kg n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a
Total Particulate Matter kg 1,390 0 3,301 0 23,890 1,200 -729,841 1,390 0 4,338 0 23,890 1,200 -729,841
Nitrogen Oxides kg 116,164 0 97,904 0 75,686 8,334 -870,462 116,164 0 190,881 0 75,686 8,334 -870,462
Sulfur Oxides kg 8,826 0 296,607 0 23,765 2,365 -891,091 8,826 0 654,358 0 23,765 2,365 -891,091
Carbon Monoxide kg 18,904 0 52,682 0 815,908 8,215 -1,025,072 18,904 0 99,831 0 815,908 8,215 -1,025,072
Carbon Dioxide Biomass kg 2,048 0 5,116 0 185,553,987 233 75,316,646 2,048 0 10,378 0 185,553,987 233 75,316,646
Carbon Dioxide Fossil kg 2,701,454 0 24,858,205 0 2,553,137 971,367 -93,910,984 2,701,454 0 50,510,514 0 2,553,137 971,367 -93,910,984
Carbon Equivalents MTCE 821 0 7,821 0 53,352 293 -28,305 821 0 15,956 0 53,352 293 -28,305
Hydrocarbons (non CH4) kg 4,601 0 88,524 0 8,937 3,353 -1,316,886 4,601 0 184,722 0 8,937 3,353 -1,316,886
ea r g 0 0 0 0 0 0 -49 0 0 1 0 0 0 -49
Ammonia (Air) kg 0 0 438 0 14 2 -3,593 0 0 969 0 14 2 -3,593
Methane (CH4) kg 1,391 0 55,110 0 8,329,242 154 -11,502 1,391 0 122,084 0 8,329,242 154 -11,502
Hydrochloric Acid kg 8 0 19 0 10,720 1 -3,194 8 0 37 0 10,720 1 -3,194
Ancillary Solid Waste kg 45,099 0 855,443 0 342,158 5,073 4,546,340 45,099 0 1,883,322 0 342,158 5,073 4,546,340
Water Emissions
Dissolved Solids kg 11,934 0 447,941 0 13,926 1,327 -44,979 11,934 0 991,991 0 13,926 1,327 -44,979
Suspended Solids kg 270 0 8,152 0 414 30 24,481 270 0 18,027 0 414 30 24,481
BOD kg 44 0 450 0 73,173 5 55,798 44 0 981 0 73,173 5 55,798
COD kg 295 0 6,310 0 203,835 33 -275,591 295 0 13,910 0 203,835 33 -275,591
Oil kg 276 0 7,872 0 65,729 31 7,228 276 0 17,401 0 65,729 31 7,228
Sulfuric Acid kg 2 0 18 0 1 0 58 2 0 39 0 1 0 58
Iron kg 6 0 14 0 2 1 9,485 6 0 28 0 2 1 9,485
Ammonia (Water) kg 5 0 11 0 2,337 1 -1,517 5 0 22 0 2,337 1 -1,517
Copper kg 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Cadmium kg 0 0 20 0 1 0 -1 0 0 45 0 1 0 -1
Arsenic kg 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Mercury (Water) kg 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Phosphate kg 1 0 9 0 16 0 -1,555,421 1 0 20 0 16 0 -1,555,421
Selenium kg 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Chromium kg 0 0 20 0 1 0 -2 0 0 45 0 1 0 -2
Lead (Water) kg 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Zinc kg 0 0 7 0 0 0 -51,720 0 0 15 0 0 0 -51,720
PPENDIX3.4_AmmanSimulationResults Group 2 Page 1
ParameterUnits (per
year)
C ll t i T f S ti T t t Di l T t t i R f t i C l l t i T f S ti T t t Di l T t t i R f t i
Composting- manual turning
Group 2- All MSW to One Option
Composting- windrow turner
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Cost with land price US$
Cost without land price
Energy Consumption MJ
Air Emissions
Mercury (Air) kg
Total Part iculate Matter kg
Nitrogen Oxides kg
Sulfur Oxides kg
Carbon Monoxide kg
Carbon Dioxide Biomass kg
Carbon Dioxide Fossil kg
Carbon Equivalents MTCE
Hydrocarbons (non CH4) kg
Col lect ion Transfer Separation Treatment Disposal Transportat ion Remanufacturing Col lect ion Transfer Separation Treatment Disposal Transportat ion Remanufacturing
24,210,508 0 0 15,743,952 15,215,292 439,372 0 24,210,508 0 0 40,244,386 15,215,366 439,368 0
7,888,033 7,888,072
123,688 0 0 255,009 152,918 8,065 0 123,688 0 0 301,541 152,918 8,065 0
n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a
1,390 0 0 550 3,055 689 0 1,390 0 0 7,675 3,055 689 0
116,164 0 0 47,386 20,437 4,786 0 116,164 0 0 140,052 20,437 4,786 0
8,826 0 0 182,237 3,891 1,358 0 8,826 0 0 202,250 3,892 1,358 0
18,904 0 0 24,057 81,691 4,718 0 18,904 0 0 56,047 81,694 4,718 0
2,048 0 0 309,765,661 14,833,766 134 0 2,048 0 0 309,765,413 14,834,486 134 0
2,701,454 0 0 13,077,715 1,094,935 557,851 0 2,701,454 0 0 16,694,338 1,094,941 557,847 0
821 0 0 4,147 5,305 168 0 821 0 0 5,250 5,305 168 0
4,601 0 0 49,586 3,762 1,926 0 4,601 0 0 64,755 3,762 1,926 0
ea r g
Ammonia (Air) kg
Methane (CH4) kg
Hydrochloric