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Thao Pham, Agapol Junpen, Penwadee Cheewaphongphan, Atthipthep Boonman, Orachorn Kamnoet, Sitthipong Pengjan, Savitri Garivait
King Mongkut’s University of Technology Thonburi, Bangkok, Thailand
&Suphat Wangwongwattana
Thammasat University, Bangkok, ThailandRegional Resource Centre for Asia and the Pacific, Asian Institute of Technology
Assessment of Health Benefit from Air Quality Improvement in Thailand:
From Concept to Applications
Air Quality Situation in Thailand
2
▪ Two major problem: O3 and PM2.5
▪ Exceedance of national standard occurs in Bangkok Metropolitan region (BMR) and Northern part of Thailand during dry season: Nov – Mar
3
Air Quality Situation in Bangkok
Source: The Pollution Control Department, Thailand
Annual PM 2.5 ambient concentration is on the way to meet National Standard. However, there are still episode during dry season.
4
Air Quality Management Framework
Source: www.cleanairasia.org/ibaq
GAINS Model
Data Input• Energy or Fuel Consumption• Combustion Technology• Engine Technology• Fuel Characteristic• Control Technology• Economic Factors
Result• Thailand’s GHG
emissions & air pollutants (base year 2015)
GIS
Other data Input• Information on
Emissions Spatial and Temporal Distribution
• Gridded 12 x 12 km & 1 x 1 km (BMR)
Result• Gridded of GHG
and Air Pollutants Emissions
CAMxModel
Other Data Input• Meteorological data• Emissions Boundary
Result• Modeled Air
Pollutant ConcentrationStatistical
Analysis / AQM
Validation
Data Input• Monitored or
Observed Air Pollutant Concentration
Result• Uncertainty in
AQ modeling and Emission Inventory
Tool Tool
Tool Tool
1) Emission Inventory
2) AQ Simulation3) AQ Simulation & Emission Validation
Air Benefit Assessment Framework
5
GAINS Model
Data Input• Energy or Fuel Consumption• Combustion Technology• Engine Technology• Fuel Characteristic• Control Technology• Economic Factors
Result• Thailand’s GHG
emissions & air pollutants (base year 2015)
GIS
Other data Input• Information on
Emissions Spatial and Temporal Distribution
• Gridded 12 x 12 km & 1 x 1 km (BMR)
Result• Gridded of GHG
and Air Pollutants Emissions
CAMxModel
Other Data Input• Meteorological data• Emissions Boundary
Result• Modeled Air
Pollutant ConcentrationStatistical
Analysis
Data Input• Monitored or
Observed Air Pollutant Concentration
Result• Uncertainty in AQ
modeling and Emission Inventory
Tool Tool
Tool Tool
1) Emission Inventory
2) AQ Simulation3) AQ modeling & Emission Validation4. Emission Projection Scenarios5. Future Emissions Reduction
Scenarios6. Air Benefit from Emission
Reduction Assessment7. Health Benefit Assessment8. Emission Reduction Cost
Assessment9. Cost-Benefit Analysis and Effective
Emission Reduction Strategy Assessment
6
Air Benefit Assessment Framework
BenMAP
Emissions
Emissions 2015-Bangkok Metropolitan Region
Source: BMR TCAP_2015_Emissions
AQ Simulation Experiment to Assess Air Benefits from Euro 5-6 Implementation
▪ Meteorological Condition using WRF
▪ Air Quality Model using CAMx
▪ On-road transport sector: Year 2035, 2050
▪ Other anthropogenic sources: 2015
8
(+) BAU: Continuously using Euro 4 during 2015-2050
(+) Scenario 1 (SC1): Light Duty Vehicle (LDT)---> new model euro 5 in 2023 all
model euro 5 in 2024, New model euro 6 in 2029 all model euro 6 in 2030
(+) Scenario 2 (SC2): Heavy Duty Vehicle (HDV) ---> Switch from Euro 4 to Euro 5
since year 2026 and euro 6 since year 2032
(+) Scenario 3 (SC3): SC1 + SC2 (LDV+HDV)
Emission Scenarios
AQ Simulations SettingsBMR
Thailand
10
Contribution of On-road Transport Emissions in BMR
mol/hour mol/hour
2015- PM Emissions All anthropogenic sources
2015- PM Emissions On road transport only
11
mol/hour
PM Emissions from On road TransportScenarios BAU vs SC3 Year 2035 & 2050
mol/hour mol/hour
mol/hour mol/hour
2015
2050_BAU 2050_SC3
2035_SC32035_BAU
Environmental Benefits Mapping and Analysis Program—Community Edition
• Open-source PC-based and graphic user interface-driven software program
• Estimates the number and economic value of adverse health outcomes
• Short tutorial available on BenMAP website
• Receive email updates: http://www.epa.gov/airquality/benmap/regis.html
14
BenMAP Software
15
Selecting Data for Benefit Assessment
▪ Air Quality ▪ Temporal (past, future, long term, short term) and horizontal (city, region, country
levels) ▪ Monitored or modelled data▪ Air quality data must be at same time scale as the epidemiological data (e.g. both use
an annual mean, or 8hr max, etc.)
▪ Population▪ Goal is to match the population characteristics (gender, age distribution) of the
epidemiological studies▪ Consider whether to use historical or projected population levels
▪ Incidence Rate▪ Baseline rates of death and disease must match the characteristics of the health
endpoint to be calculated (Location, Demographic characteristics, Year (historical/projected))
▪ BenMAP-CE contains baseline incidence rates matched to each health impact function for U.S., China and GBD tool
▪ Health Impact Epidemiology Function▪ Epidemiological Studies▪ BenMAP-CE contains over a hundred health impact functions
∆ Y = Yo (1-e -ß∆ PM) * Pop
17
Setting of Emissions Input:▪ On-road transport sector: 2 scenarios estimated for year 2035 and 2050 (1) BAU:
Business as Usual (BAU) – Euro 4; and (2) SC3: Euro 5 & Euro 6 implementation as planned,
▪ Other anthropogenic sources: included all sources estimated for year 2015,▪ Biomass burning / biogenic / influence from boundary emissions are included.
Air Benefit Data from Simulation
mg/m3 mg/m3
percentage percentage
Differences of PM2.5 (BAU_2035 vs SC3_2035) Differences of PM2.5 (BAU_2050 vs SC3_2050)
18
Population Data
▪ Data source: For BMA and vicinity (National Statistic Office)▪ Key features: Gender, age, socio-economic, etc. distribution▪ Population Trends: Population Projection for Thailand 2010-2040 (Office of the
National Economic and Social Development Board)
Spatial Distribution of Population in BMR Trends of Population in BMR
0
2,000
4,000
6,000
8,000
10,000
Bangkok Nonthaburi Pathumthani SamutP SamutS NakhonP
Pe
rso
n
Population Trends during 2010-2035
2010 2015 2020 2025 2030 2035
Population Density (person/km2)
Bangkok Nonthaburi Pathum Thani SamutP SamutS NakhonP
5,509 2,390 949 2,008 1,088 480
19
Mortality Incidence Data
▪ Data source: Categorized following ICD WHO Code (Ministry of Public Health)▪ Key features: Gender and age distribution
0
10
20
30
40
50
Ischemic heart disease Stroke Chronic obstructivepulmonary disease
Lung caner
(death
/ 1
00,0
00 p
ers
on
)
Mortality Rate by Province
Bangkok Nonthaburi Pathum Thani Samut Prakan Samut Sakhon Nakhon Pathom
Health Burden in Year 2035 and 2050 in BMR
21
▪ Health burden due to air pollution in year 2035 and 2050 would be approximately be 1,700 and 1,900 premature mortality in total, respectively
703 714
84
204
748
847
93
226
-
200
400
600
800
1,000
Ischemic heart disease Stroke Chronic obstructivepulmonary disease
Lung caner
Mo
rtali
ty (
pe
rso
n)
Long-term Health Burden in year 2035 and 2050
Health Burden CLE_2035 Health Burden CLE_2050
Health Impact of PM2.5 Reduction in Transport Sector in 2035 in BMR
22
▪ There is health benefit (approx. to 120 avoided mortality in year 2035) if strengthen standard is implemented as planned, accounted for 7% of health burden.
▪ Benefit is still limited because it is on early phase of Euro 5/6 implementation.
27
76
5
13
0
20
40
60
80
100
Ischemic heart disease Stroke Chronic obstructivepulmonary disease
Lung caner
Avo
ided
Mo
rtal
ity
(pe
rso
n)
Health Impact of PM2.5 Reduction in Transport Sector in 2050 in BMR
23
▪ There is health benefit (approx. to 300 avoided mortality in year 2050) if strengthen standard is implemented as planned, accounted for 14% of health burden.
▪ Health benefit in year 2050 is more than twice of that in year 2035.
60
178
11
30
0
40
80
120
160
200
Ischemic heart disease Stroke Chronic obstructivepulmonary disease
Lung caner
Avo
ided
Mo
rtal
ity
(pe
rso
n)
Value of Statistical Life
Cost of illness (COI)
▪ These costs can be direct, such as hospital charges, or
▪ Indirect (lost wages for parents who stay home to care for a sick child).
Willingness to Pay (WTP)WTP reflect the values implicit in individual decision-making, including valuation of pain and suffering, and are considered more complete estimates of social value
Value of Statistical Life (VSL)Derived from WTP, reflect value that individual is willing to pay to reduce their risk of dying
Example of VSL study for Bangkok, ThailandVSL (year 2003) =1.3 Million USD
(year 2015) = 1.7 Million USD
Value of Statistical Life
0
10,000
20,000
30,000
40,000
50,000
60,000
70,0002
00
0
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
(cu
rren
t in
tern
atio
nal
$)
Gross National Income per capita (GNI-PPP)
CHN THA USA
2.18
8.75
2.361.73
0
2
4
6
8
10
China (Cui et al.,2017)
United Stated (Cuiet al., 2017)
Thailand (derviedfrom US Study)
Thailand (derviedfrom local WTP)
Mill
ion
USD
Value of Statistical Life (VSL) Year 2015
➢ VSL for Thailand 1.7 – 2.4 Million USD
➢ Valuation of Health Benefit ▪ 0.2 - 0.3 Billion USD
of avoided mortality in year 2035
▪ 0.4 - 0.6 Billion USD of avoided mortality in year 2050
….for just BMR region
➢Implementation of more stringent environmental policy(i.e., Euro 5/6) in transport sector in BMR indicated airbenefit associated to the PM2.5 reduction,
Conclusions
26
➢ There is health benefit up to 120 and 300 avoided mortality in year 2035 and 2050, respectively,
➢ Valuation of Health Benefit
▪ 0.2-0.3 Billion USD of avoided mortality in year 2035
▪ 0.4 - 0.6 Billion USD of avoided mortality in year 2050
➢ Future Work
▪ Extend the domain of study (Thailand and other countries)
▪ Multi-pollutant and multi-sector analysis
▪ BenMAP developer,
▪ Organizations mentioned in the presentation for data
support and discussion,
▪ ABBA-EIP (JGSEE-CEE) for financial support through
TCAP project.
Acknowledgement
Thank you for your attention!
More further information, please contact:
Dr. Thao Pham ([email protected] )