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ADB-JICA-WB Joint Study: Climate Change Impact and Adaptation in Asian Coastal Cities ~ Case of Metro Manila ~. Megumi MUTO Research Fellow JICA Research Institute [email protected]. 1. Downscale IPCC climate models for temperature increase @2050 for B1 and A1FI scenarios. 2. - PowerPoint PPT Presentation
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Megumi MUTOResearch Fellow JICA Research [email protected]
ADB-JICA-WB Joint Study: Climate Change Impact and Adaptation in Asian Coastal Cities ~ Case of Metro Manila~
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Downscale IPCC climate models for temperature increase @2050 for B1 and A1FI scenarios
Assess local effects on precipitation and combine with sea level rise/ storm intensification
Simulate different types of hydraulic effects: 1) through river systems, 2) through accumulation of water at lake, and 3) through sea level rise and storm surge at the coast (combination depends on city)
Based on the flood maps produced for 12 cases (3 climate scenarios x 2 infrastructure scenarios x 2 return periods), estimate socio-economic impact (both direct and indirect) with available data, thus deriving the benefit side of adaptation.
Consider investment mix and their costs necessary for adaptation (focusing on flood control infrastructure)
Conduct Net Present Value (economic, not financial) and EIRR calculations
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Flood-prone areas in Manila
In addition:
・ Firm and urban poor household surveys to understand the details of vulnerabilities.
・ Health impact analysis
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Flood Prone Areas in Metro-Manila
West Mangahan Area
Pasig-Marikina BasinKAMANAVA Area
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West Mangahan area
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West Mangahan area
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West Mangahan area
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KAMANAVA area
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Pasig-Marikina area
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1Downscale IPCC climate models for temperature increase @2050 for B1 and A1FI scenarios (University of Tokyo IR3S for all city case studies)
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2Assess local effects on precipitation and combine with sea level rise/ storm intensification
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Simulation Cases (Case of Metro Manila)Simulation Case Temperature
Rise (oC)(downscaled)
Sea Level Rise (cm)(global)
Increase Rate of
Rainfall (%)
Storm Surge Height (m)
1 Status quo climate 0 0 0 0.91
2 B1 with storm level at status quo
1.17 19 9.4 0.91
3 B1 with strengthened storm level
1.17 19 9.4 1.00
4 A1FI with storm level at status quo
1.80 29 14.4 0.91
5 A1FI with strengthened storm level
1.80 29 14.4 1.00
*Note: ground subsidence considered to arrive at local sea level rise
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3Simulate different types of hydraulic effects: 1) through river systems, 2) through accumulation of water at lake, and 3) through sea level rise and storm surge at the coast (combination depends on city)
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B1/30-year Flood/Existing flood control structures
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B1/30-year Flood/Continue 1990 Master Plan
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A1FI/100-year Flood/Existing flood control structures
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A1FI/100-year Flood/Continue 1990 Master Plan
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Based on the flood maps produced for 12 cases (3 climate scenarios x 2 infrastructure scenarios x 2 return periods), estimate socio-economic impact (both direct and indirect) with available data, thus deriving the benefit side of adaptation.
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Summary of Inundation Areain the Pasig-Marikina Basin
Simulation Case
30-year Flood 100-year Flood
Existing Structures
Implementing Current
Master Plan
Existing Structures
Implementing Current
Master Plan 1 Status quo
climate34.6 km2 14.7 km2 53.7 km2 29.1 km2
2 B1 42.5 km2 20.8 km2 63.2 km2 40.1 km2
3 A1FI 47.0 km2 22.8 km2 68.0 km2 44.1 km2
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2020
2Classification of Flood Water Depths 007
CategoryWater Depths (m)
RemarksMinimum Maximum
1 0.0000010 0.080No adverse effect to all buildings,
infrastructures, utilities and transportation
2 0.081 0.200Will affect transportation but no buildings,
infrastructures and utilities3 0.201 0.500 Definitely affects transportation, some
buildings, infrastructures and utilities4 0.501 1.000
5 1.001 3.000Adverse effects on transportation,
infrastructures, utilities and one floor level of buildings
6 3.001 6.000Same as category 5 but will affect two floor
levels of buildings
7 6.001 9.000Same as category 5 but will affect three
floor levels of buildings
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Socio-economic assessment
Source: Adapted with revisions from Southeastern Wisconsin Regional Planning Commission (1976) and Green et. al., (1983)
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Direct Impact Assessment Flowchart
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2020
Data from Direct Impact Secondary (Indirect) Impacts Analysis
Flood Affected Buildings
Flood Affected Area and Roads
Traffic Zones
Firms, residential
Income Loss of Income
Trips Generated/ Attracted (Public Mode)
Trips Generated/ Attracted (Private Mode)
Travel Time Delay Cost
Unit rate from Firm, household surveys
Time Value: Public Users“To work” &
“Business” Trips Time Value:
Private Users
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Added up benefits (savings) Cost of buildingsCost of buildings Vehicle operation cost savingsVehicle operation cost savings Travel time savings through existing/future Travel time savings through existing/future
road investmentsroad investments Avoided income loss (firms, formal/informal Avoided income loss (firms, formal/informal
households)households)- Use future predicted values as much as possible. Use
growth rate to arrive from these future values up to 2050.- Need more work on shadow prices, etc.- Should savings of power/rail operator be included?
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DATA:Future Land Use of Metro Manila, 2020
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DATA:Transport Infrastructurefor Metro Manila, 2015
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Trip dataTrip data
2003 20202007 1999
Sources: JICA-MMUTIS and JICA-PPP/MUEN
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Informal settlers data (present)
20202007
Sources: LGUs of MM and HLURB
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Affected area and population
P100 Affected Area (%)EX SQ 11.87EX B1 12.95EX A1F1 13.64
BAU SQ 5.25BAU B1 6.97BAU A1F1 7.62
P100 Affected Pop (%)EX SQ 20.08EX B1 22.13EX A1F1 23.27
BAU SQ 7.08BAU B1 7.08BAU A1F1 11.74
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Buildings’ Base Cost (present cost)Residential Buildings
Type* Median
Construction Cost
Finishing (25%)
Household Effects (35%)
1A9,200 2,300 4,0251B
1CIIA
6,150 1,538 2,691IIBIICIIIA 2,550 638 1,116
Commercial Buildings
Type1
Median Construction
Cost
Durable Assets2
Stocks2
1A11,100 27,750 333,0001B
1CIIA
7,750 19,375 232,500IIBIICIIIA 5,700 14,250 171,000
Institutional Buildings
Type1
Median Construction
Cost
Durable Assets2
Stocks2
1A11,000 2,970 1,1001B
1CIIA
7,500 2,025 750IIBIICIIIA 4,100 1,107 410
Industrial Buildings
Type1
Median Construction
Cost
Durable Assets2 Stocks2
1A6,050 26,620 22,9901B
1CIIA
3,550 15,620 13,490IIBIICIIIA 1,900 8,360 7,220
Source: LGU Assessor’s Office
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Building Damage Rates2020
Building Use Cost Item - 50 cm 100-200 cm
200-300 cm -
Above 300 cm -
Residential
Finishings 0.0920 0.119 0.580 0.834
Household Effects 0.1450 0.326 0.928 0.991
Business Entities1
(Commercial, Institutional,
and Industrial)
Assets 0.2320 0.453 0.9661 0.966
Stocks 0.1280 0.267 0.8971 0.8971
Source: Adapted from the Manual for Economic Study on Flood Control, May 2000, Ministry of Construction (presently the Ministry of Land, Infrastructure and Transport), Japan1/ maximum rate given is for depth of 200-299 cm. The same rates are likewise applied to Institutional and Industrial.
Flood Damage Rates by Building Use
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2020Cost of Damages to Buildings
Condition of Metro Manila
Land Use
Cost of Damage by Land Use by Water Depth (in 000 Php)
Present
20 - 50 cm Above 50
cm - 3 m Above 3 m - 6 m
Above 6 m - 9 m
Above 9 m Total
Existing Infra
Status Quo 22,523,23 113,559,497 3,919,805 190,832 121,958 140,315,328
B1 18,478,510 155,321,466 5,021,023 288,125 121,958 179,231,083
A1F1 17,871,154 177,466,638 5,504,319 422,788 123,012 201,387,913
Business-as-Usual
Status Quo 14,122,799 34,825,827 3,395,851 7,145,807 87,437 59,577,722
B1 19,535,278 54,809,224 2,717,361 7,173,132 84,651 84,319,648
A1F1 23,360,031 65,140,293 2,822,537 7,184,067 9,473 98,519,007
Building Damage Costs (present cost)
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Flood Scenario (Existing
Infra)
Road Length by Inundation Depth (kms)8-20 cm 21-50 cm Above 50 cm
Total
Major Minor Major Minor Major MinorStatus Quo 4.5 3.9 22.1 23.8 31.9 39.8 125.9 B1 5.4 9.7 13.6 15.1 47.9 55.6 147.3 A1FI 5.3 6.9 14.6 18.2 53.6 60.3 158.9
Flood Scenario
(Business-as-Usual)
Road Length by Inundation Depth (kms)8-20 cm 21-50 cm Above 50 cm
TotalMajor Minor Major Minor Major Minor
Status Quo 3.78 4.33 6.40 10.45 7.45 13.42 45.82B1 7.24 8.15 9.54 15.73 12.07 20.82 73.55A1FI 9.45 9.05 12.62 16.28 14.97 25.63 87.99
Affected Roads
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Affected VehiclesAffected Vehicles
2020
1 23
45
6
7
8 9
10
11
1213
14
15
16
1718
19
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2122
23
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2526
27
28
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Daily Traffic Volumes from Roadside Traffic Count Stations in Metro Manila
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2020
Road ConditionPublic Mode Private Mode
Peso/km Peso/kmGood / Fair 9.614 11.795Inundated (bad) 14.316 16.962
Flood Incremental Cost 4.702 5.167
Vehicle Operating Cost for Vehicles in MM
Traffic Count Stations in
Metro ManilaDirection
Total Public Total Private Total
VehiclesInunda-tion Cost (Php/km)
VehiclesInunda-tion Cost (P
hp/km)Vehicles
Inunda-tion Cost (Php/km)
Total Both Directions
146,313 687,965 796,606 3,745,642 918,271 4,433,607
Source: Department of Public Works and Highways, 2006 Price Levels
Note: Computation for all flood scenarios.
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2020
Mode Type
Time Value of Trip Makers
(Pesos/hour)20021/ 2050
Private 81.30 148.00Public 45.45 83.00
Flood ScenarioNo. of Trips
Cumulative Travel Time Delay Cost (Php/hr)
Public Private Public PrivateEXISTING INFRA: 2002
Status Quo 855,935 217,645 38,517,064 17,629,240B1 1,031,706 280,046 46,426,792 22,683,717
A1F1 1,058,941 295,015 47,652,359 23,896,185EXISTING INFRA: 2050
Status Quo 1,741,191 999,355 144,518,892 147,904,489B1 1,903,258 1,223,565 157,970,385 177,993,032
A1F1 1,924,578 1,212,727 159,739,956 179,483,552BUSINESS-AS-USUAL 2002
Status Quo 335,728 121,971 15,107,760 9,879,688B1 496,336 174,004 22,263,697 14,058,719
A1F1 613,269 229,933 27,597,116 18,624,607BUSINESS-AS-USUAL 2050
Status Quo 396,998 208,314 32,950,807 30,830,421 B1 622,938 341,766 51,703,832 50,581,344
A1F1 824,697 429,490 68,449,818 63,564,534
Travel Time Value
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2020LGU
Flood-affected Generated/Attracted Trips by PurposeSchool Recreation Medical Religious
City of Manila 2,002,254 41,034 164,033 135,976Kalookan City 92,195 284 3,339 5,507Makati City 169,085 2,464 5,445 18,075Malabon City 197,922 1,538 2,764 11,520Mandaluyong City 143,333 1,275 4,052 6,639Marikina City 173,042 2,820 4,878 16,313Navotas 115,391 1,943 1,758 6,840Pasay City 30,505 662 2,199 1,158Pasig City 280,050 4,897 13,777 22,249Quezon City 460,404 4,080 47,833 33,372San Juan City 58,564 499 2,725 3,408Taguig City 96,033 4,665 2,415 5,971Pateros 52,406 600 522 3929
Total MM 3,871,184 66,161 255,218 267,028Source: JICA-MMUTIS
With a trip rate of 2.2, approximately 1.8 M students affected
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Water facilities
2020
No damage of flood assumed since:
• Pipes are positively charged;
• No record of flood–related damage incidences; and
• Facilities are above flood levels.
Source: Maynilad Water Services and Manila Waters, Inc.
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Power sector2020
Flood-affected TRANSCO Substations in Metro Manila
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2020Rise in Flood Water Level
(m)Substations Elevation (m)1 Affected Areas
1CBP 1-A(at Mall of Asia, Pasay City)
0.61 Pasay City Paranaque City
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North Port(at Antipolo St., Tondo, Manila)
4.00 ManilaSouth KalookanNavotas
Capasco(at Napindan Road, Taguig)
4.88 CAPASCOTaguig
Taguig(at Elisco Road, Taguig)
4.88 Taguig CityPaterosMakati CityPasig CityMandaluyong City
Paco(at Quirino Hiway, Sta. Ana, Manila
5.79 Malate, ManilaSta. Ana, ManilaSan Andres, ManilaPaco, ManilaErmita, ManilaMakati City
Pasay(at EDSA near Tramo, Pasay City
6.10 Pasay CityParanaque CityMakati City
Affected Power Distribution Infrastructure
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2020
RSS No. & Location (LRT Line 1) Minimum Flood Depth
3 - Buendia Station 0.45 m
5 - Central Station * 0.42 m
6 - D. Jose Station * 0.55 m
7 - Blumentritt Station 0.26 m
Flood-affected RSS of Urban Rail Transport
* Any impact on these substations would paralyze entire line.Source: Light Rail Transit Authority
= income loss of P 4.7M per day for the line
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5Consider investment mix and their costs necessary for adaptation (focusing on flood control infrastructure)
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Adaptation Measures to Climate Change in Metro Manila
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6 Conduct Net Present Value (economic, not financial) and EIRR calculations
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Framework for EIRR & NPV P100
Benefits
P30 Benefits
Benefit side
•Savings on Buildings•Savings on Travel Time•Avoid Loss of Income •VOC savings, etc.
Investment Options and
Mixes for Climate Change
Adaptation Projects
Assumptions
•Project Life of 50 years•3 – 5 years Construction•2010 start construction•Flood probabilities of 1/100 and 1/30
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Results of EIRR & NPV (tentative numbers only)Results of EIRR & NPV (tentative numbers only)
Description Investment EIRR NPV@15% NPV@3%(%) (Php Million) (Php Million)
NO DAM, combining incremental flood control investments P100 A1FI Level
Php 479 MYen 2,971M
32.83 670 12,700
WITH DAMP100 A1FILevel
Php 3,974 MYen 24,639 M
8.12 1,833 9,912
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In addition
Firm and urban poor household surveys to understand the details of vulnerabilities.
Health impact analysis.
- both using present data
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Geographic distribution of householdsRiver Basin Community/Barangay Number of
HouseholdsTotal
San Agustin, Malabon 15Longos, Malabon 10Bangkulasi, Navotas 15Bagumbayan South, 30West Navotas, Navotas 15Barangay 28, Caloocan 15
Rosario, Pasig City 25Bagong Ilog, Pasig City 25Ugong, Pasig City 25Tumana, Marikina City 25
Ibayo Tipas, Taguig City 25Calzada, Taguig City 25Napindan, Taguig City 25San Joaquin, Pasig City 25
Total 300
West-Mangahan Area
100
KAMANAVA Area
100
Marikina-Pasig River Basin
100
Household Level
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Urban poor households affected by multiple-forms of disasters
Tidal surgeTyphoon
Flood
35 (11.67%)
9(3%) 1
(0.33%)
118(39.33%)
6(2%)
53(17.67%)
20(6.67%) Not affected
58(19.33%)
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Absent days from school of affected households
Days Floods Tidal Surge Typhoons
0 44 21 49(15%) (7%) (16%)
1--5 66 44 65(22%) (15%) (22%)
6--10 20 20 28(7%) (7%) (9%)
11--15 2 2 3(1%) (1%) (1%)
16--20 1 3 2(0%) (1%) (1%)
21--25 2 0 0(1%) (0%) (0%)
26--30 0 1 0(0%) (0%) (0%)
>30 4 3 4(1%) (1%) (1%)
Number of affectedhouseholds
139 94 151
Mean absent days 3.95 5.19 4.09Note:% of sample households is presented in the parenthesis
Type of disaster
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Distribution of sick days caused by the past disasters
Days Flood Tidal Surge Typhoon0 42 35 53 (14%) (12%) (18%)1--7 54 30 36 (18%) (10%) (12%)8--14 4 1 2 (1%) (0%) (1%)>=15 1 0 0 (0%) (0%) (0%)Number of affectedhouseholds
100 66 91
Mean absent days 5.13 2.53 2.33Note:% of sample households is presented in the parenthesis
Type of disaster
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Distribution of sickness caused by the past disaster
Sickness Flood Tidal Surge Typhoon
N/A 207 244 219 (69%) (81%) (73%)Primary Infections 4 0 2 (1%) (0%) (1%)Fever 10 3 7 (3%) (1%) (2%)Flu 55 39 60 (18%) (13%) (20%)Skin Diseases 8 5 3 (3%) (2%) (1%)Digestive Disorders 13 8 9 (4%) (3%) (3%)Dengue 2 0 0 (1%) (0%) (0%)Colds 1 0 0 (0%) (0%) (0%)Kidney Disorder 0 1 0 (0%) (0%) (0%)Total 300 300 300Note:% within column is presented in the parenthesis
Type of disaster
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Distribution of medications fee, caused by the past disasters
Medications Fee(Php) Flood Tidal Surge Typhoon
0 233 257 238 (78%) (86%) (79%)1--1000 60 41 58 (20%) (14%) (19%)1001--2000 0 0 1 (0%) (0%) (0%)2001--3000 1 1 1 (0%) (0%) (0%)3001--4000 0 1 0 (0%) (0%) (0%)4001--5000 2 0 1 (1%) (0%) (0%)>5000 4 0 1 (1%) (0%) (0%)Number ofhousholds getting ill
100 67 91
Mean medications fee 1063 301 318Note:% of sample households is presented in the parenthesis
Type of disaster
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Distribution of absent days from work caused by the past disasters
Days Floods Tidal Surge Typhoons0 244 272 243 (81%) (91%) (81%)1--5 39 21 45 (13%) (7%) (15%)6--10 13 5 10 (4%) (2%) (3%)11--15 3 0 1 (1%) (0%) (0%)>15 1 2 1 (0%) (1%) (0%)Total 300 300 300Note: % within column is presented in the parenthesis
Type of disaster
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Distribution of income loss caused by the past disasters
Value (Php) Floods Tidal Surge Typhoons0 229 267 233 (76%) (89%) (78%)1--500 36 19 38 (12%) (6%) (13%)501--1000 17 7 18 (6%) (2%) (6%)1001--1500 7 3 6 (2%) (1%) (2%)1501--2000 9 2 3 (3%) (1%) (1%)2001--2500 1 0 0 (0%) (0%) (0%)>2500 1 2 2 (0%) (1%) (1%)Number of the householdsabsent from work 92 52 86
Mean income loss 699 649 629
Type of disaster
Note: % of sample households is presented in the parenthesis
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Number of affected firms & the temporarily stopped days
No. % Mean Min Max
Pasig - Marikina Bgys 86 28 32.6 1.0 0.5 2
Kamanava Bgys 66 37 56.1 2.3 0.5 9
West Manggahan Bgys 58 29 50.0 1.8 0.1 14
Other Barangays 76 40 52.6 1.8 0.5 7
All Establishments 286 134 46.9 1.8 0.1 14
Stopped daysArea Obs.
Affected firms(over the past 3 years)
Firm Level
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Affected reasons and cause in typhoon Milenyo
Floodingwithin premise
Floodingwithin 50 km
Meters
Floodingwithin 5 km
RadiusStrong wind Others
Products delivering problem 97 11 13 44 24 1Low sales 109 17 26 31 20 5Raw materials receiving 65 5 16 25 13Employee shortage 154 15 27 53 47 1Machine/Equipments 24 13 1 5 2Inventory damage 38 13 1 4 4 5Order cancelled 25 3 3 9 5 2Electricity /Power outage 172 10 5 8 137 4Damages to 53 1 1 3 32 1Water shortage 9 2 1 3 1Others 11 3 1 3 2
Affected reasons No. of reasonscited by firms
Cause of damage
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Reasons of employees’ absence from work
Transportunavailability
Healthproblem
Foodssecuring
Houserepairing Others
Pasig - Marikina Bgys 148 93 6 6 66 30
Kamanava Bgys 55 46 2 3 30 8
West Manggahan Bgys 43 33 4 4 13 13
Other Barangays 60 46 2 1 13 1Note: One firm may cite more than one reason, so the number of affected firms does not equal the number of thereasons of work absence
Area Obs.Reason
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Income AssetsPasig - Marikina Bgys 86 480,194 254,582
(47) (75)Kamanava Bgys 66 364,359 268,461
(39) (55)West Manggahan Bgys 58 245,317 816,147
(30) (43)Other Barangays 76 229,238 113,247
(40) (60)All Establishments 286 341,719 325,099
(156) (233)Note: Number of affected firms is presented in the parenthesis
Area Obs. Loss in
Income & Assets losses caused by typhoon Milenyo (by Area)
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Income & Assets losses caused by typhoon Milenyo (by Sector)
Income Assets
Manufacturing 168 402,589 509,969
(97) (139)
Construction 12 218,750 31,982
(8) (11)
Wholesale and Retail Trade 43 227,429 57,891
(21) (33)
Hotels and Restaurants 23 102,773 22,310
(11) (21)Transport,Storage andCommunications 16 598,050 141,083
(10) (12)
Financial Intermediation 5 50,000 0
(3) (4)
Health and Social Work 19 78,333 33,744
(6) (13)All Establishments 286 341,719 325,099
(156) (233)Note: Number of affected firms is presented in the parenthesis
Area Obs. Loss in
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Health impact analysis
Estimated daily risk of infection of City of Manila(Data of 2003)
Estimated daily risk of infection via incidental ingestion of flood water in Manila City