Environmental Health: Economic Costs of Environmental Damage And Suggested Priority Interventions A Contribution to the Philippines Country Environmental Analysis Submitted to The World Bank Final Report March 31, 2009 The results indicate that the economic costs of pollution and sanitation-related health effects are high and cannot be ignored. The combined costs for all three sectors in 2003 totaled PhP 42.4 billion (USD 783.2 million) in lost productivity due to premature deaths or PhP 168.4 billion (USD 3.1 billion) in terms of value of statistical life (Table1). In addition, the cost of morbidity was PhP 18.3 billion (USD 337.6 million), comprising of loss in productivity totaling PhP 10.4 billion (USD 191.3 million), direct costs to Filipino households to treat these illnesses totaling PhP 6.4 billion (USD 118.7 million), and the cost to the government health care insurance system—representing the subsidy for PhilHealth members’ hospitalization costs—and for general government subsidy for publicly-owned health facilities was close to PhP 1.5 billion (USD 27.6 million).

1. Environmental Health:
Economic Costs of Environmental Damage
And Suggested Priority Interventions
A Contribution to the Philippines
Country Environmental Analysis
Submitted to
The World Bank
Final Report
March 31, 2009
1
Agustin L. Arcenas
1
World Bank Consultant. The findings, interpretations, and conclusions expressed herein are those of
the author’s, and do not necessarily reflect the views of the World Bank and its affiliated organizations,
or those of the Executive Directors of the World Bank or the governments they represent. Please email
comments about the report to the author at alarcenas@econ.upd.edu.ph.
The author would like to acknowledge and thank the following individuals and groups of individuals for all
the help, assistance and comments and suggestions they generously shared in the conduct of the research
and writing of this report: Dr. Jan Bojo and Ms. Maya Villaluz; the author’s research assistants, Ralph
Bulatao and Iva Sebastian; Dr. Bjorn Larsen and Dr. Maureen Cropper; Prof. Elma Torres; Mr. Karl
Galing; Dr. Dennis Batangan; The Manila Observatory; Dr. Bernardino Aldaba, Dr. Carlo Panelo, Mr.
Carlos Tan, Mr. Paul Mariano and the HPDP group based at U.P. School of Economics; the staff at
PhilHealth and the Department of Health; Dr. Stella Quimbo; and finally, Dr. Aleli Kraft.
1

2. LIST OF ABBREVIATIONS
4-STC Four Stroke Tricycles
ADB Asian Development Bank
AF Attributable Fractions
ALRI Acute Lower Respiratory Infection
BCA Benefit-Cost Analysis
CH4 Methane
COPD Chronic Obstructive Pulmonary Diseases
CO Carbon Monoxide
CO2 Carbon Dioxide
COC Certificate of Compliance
COI Cost of Illness
DALY Disability-Adjusted Life-Year
DENR Department of Environment and Natural Resources
DHS Demographic and Health Survey
ECC Environmental Compliance Certificate
EMB Environmental Management Board
EO Executive Order
ESI Economic Impacts of Sanitation in the Philippines
FHSIS Field Health Surveillance Information System
GNI Gross National Income
GS Good Shepherd
HCA Human Capital Approach
HCV Human Capital Value
HECS Household Energy Consumption Survey
IAP Indoor Air Pollution
I/M Inspection and Maintenance
LC Local Currency
LPG Liquefied Petroleum Gas
LRT Light Rail Transit
LTO Land Transportation Agency
MMAQISDP Metro Manila Air Quality Improvement Sector Development
Program
MMDA Metro Manila Development Authority
MO Manila Observatory
MRT Metro Rail Transit
MT/T motorcycles and tricycles
MVIS Motor Vehicle Inspection System
NDHS National Demographic and Health Survey
NGO Non-governmental Organization
NO Nitrogen Oxide
NO2 Nitrogen Dioxide
NOx Nitrogen Oxides
NPO National Press Office
OAP Outdoor Air Pollution
2

3. PEM Philippine Environmental Monitor
PETC Private Emission Testing Center
PGH Philippine General Hospital
PhP Philippine Peso
PHS Philippine Health Statistics
PM Particulate Matter
PNRI Philippine Nuclear Research Institute
RR Relative Risk
SOx Sulfur Oxide
SPM Suspended Particulate Matter
TOGs Total Organic Gases
USAID United States Agency for International Development
USD United States Dollar
UV Ultraviolet
VOC Volatile Organic Compound
VSL Value of Statistical Life
WHO World Health Organization
WPR Western Pacific Region
WSH Water Pollution, Sanitation and Hygiene
WSP Water Pollution, Sanitation and Hygiene Project
3

4. List of Figures
Figure 1 - Comparative Summary of the Economic Costs of WSH, IAP and OAP-
Related Illnesses, 2003
Figure 2 - Annual Average PM10 Levels in cities in Metro Manila and in Antipolo City
Figure 3 - Annual Average PM2.5 Levels in Metro Manila
Figure 4 - OAP Cost to Households of Treatment (Net of Public Health Care Subsidy),
2003
Figure 5 - Government Health Care Subsidy per OAP-Illness, 2003
Figure 6 - Lost Income Due to OAP-related Illnesses, 2003
Figure 7 - Total Economic Cost of OAP-related Morbidity, 2003
Figure 8 - Mortality Cases Due to OAP, Grouped According to Working and Non-
working Age Groups, 2003
Figure 9 - Cost of Premature Deaths due to OAP, 2003
Figure 10 - New Vehicle Registration (All Types) Trend, 2007
Figure 11 - Percentage of Households Use of the Type of Cooking Fuel, 2004
Figure 12 - Household Fuel Use by Urbanity, 1995
Figure 13 - Household Use of Solid Fuel by Income Class, 2004
Figure 14- Primary Cooking Fuel for Households, 2004
Figure 15 - Households Exposed to Indoor Air Pollution (in percentage)
Figure 16 - Morbidity Cases Attributable to IAP, By Gender, 2003
Figure 17 - IAP Cost to Households of Treatment (Net of Public Health Care Subsidy),
2003
Figure 18 - Government Health Care Subsidy per IAP-Illness, 2003
Figure 19 - Lost Income Due to IAP-related Illnesses, 2003
Figure 20 - Total Economic Cost of IAP-related Morbidity, 2003
Figure 21 - Cost of Premature Deaths due to IAP, 2003 (HCV)
Figure 22 - Mortality Cases Due to IAP Grouped According to Working and Non-
working Age Groups, 2003
Figure 23 - Household Access to Improved Water Supply and Sanitation, 2003 (National)
Figure 24 - Household Access to Improved Water Supply and Sanitation, 2003 (Metro
Manila)
Figure 25 - WSH Cost to Households of Treatment (Net of Public Health Care Subsidy),
2003
Figure 26 - WSH Cost to Households of Treatment (Net of Public Health Care Subsidy),
2003 per Illness
Figure 27 - Government Health Care Subsidy per WSH-Illness, 2003
Figure 28 - Lost Income due to WSH-related Illnesses, 2003
Figure 29 - Total Economic Cost of Morbidity from WSH, 2003
Figure 30 - Mortality Cases Due to WSH Grouped According to Working and Non-
working Age Groups, 2003
Figure 31 - Cost of Premature Deaths due to WSH, 2003 (HCV)
Figure 32 - Median Construction Cost of Water Supply Facilities for Select Regions (in
USD)
Figure 33 - Percent Reduction in Diarrhea Morbidity of Different Water and Sanitation
Interventions
4

5. Figure 34 - Cost-effectiveness of Water Supply, Sanitation, and Hygiene Promotion
(USD/DALY)
Figure 35 - Median Construction Cost of Sanitation Technologies in Select Regions (in
USD)
List of Tables
Table 1 - Summary Table of Economic Costs Breakdown per Sector (USD’000)
Table 2 - Summary of Mortality Cases Per Sector and Age Group, 2003
Table 3 - Summary of Morbidity Cases Per Sector and Age Group, 2003
Table 4 - Attributable Fractions (AF) for OAP-related Morbidity, 2003
Table 5 - Cases of OAP-related Illnesses by Age Group, 2003
Table 6 - Relative Risk Ratios and Corresponding Attributable Fractions for Specific
Illnesses
Table 7 - Mortality Cases due to OAP, by Specific Age Group, 2003
Table 8 - BCA-ratios for Cases of Retro-fitting of In-use Diesel Vehicles in the
Philippines
Table 9 - Light Rail Transits Lines in the Philippines
Table 10 - Proposed Railway Projects with project costs (in USD millions)
Table 11 - Financial Summary of MRT Line 3 Operations (in million pesos)
Table 12 - Cost Estimates for the Metro Manila Air Quality Improvement Sector
Development Program (MMAQISDP) (in USD millions)
Table 13 - Particulate Emissions from Household Cooking, 2004
Table 14 - Attributable Fractions Used for Morbidity Cases per Illness
Table 15 - Cases of IAP-related Illnesses by Age Group, 2003
Table 16 - Attributable Fractions Used for Mortality Cases per Illness
Table 17 - Mortality Cases Due to IAP by Specific Age Group, 2003
Table 18 - Overview of Costs and Impacts, Time Horizon of Modeled Impacts
Table 19 - Benefit-Cost Ratios of Converting to a New Stove Technology to Control IAP
in the Philippines.
Table 20 - Levels of Households According to Access to Water and Sanitation Facilities
Table 21 - Responses to the Demographic and Health Survey, 2003
Table 22 - Attributable Fractions (AF) for WSH-related Illnesses, 2003
Table 23 - Total Cases of WSH-related Illnesses, 2003
Table 24 - Number of Cases of Diarrhea by Age Group, 2003
Table 25 - Number of Cases of WSH-related Illnesses (excluding Diarrhea) by Age
Group, 2003
Table 26.A -Mortality Cases due to WSH by Specific Age Group, 2003
Table 26.B -Mortality Cases due to WSH by Specific Age Group, 2003
Table 26.C - Mortality Cases for Malnutrition caused by Diarrhea for Children under 5
years old, 2003
Table 27 - Malnutrition-related Mortality Resulting from Diarrheal Infection, 2003
5

6. Summary
Perhaps one of the most important and urgent issues that the Philippines faces
today is that of environmental health. Defined to be the area of health concerns due to
pollution and unsanitary conditions, it has caught the attention of government, prompting
the national leadership to create an inter-agency committee focusing on these health
issues; to bring forward an agenda of technical collaboration, information collection and
dissemination, and policy review.
This study on environmental health issues in the Philippines was conducted to
provide guidance—in terms of information and suggestions on policy interventions—to
policy managers and researchers, and donor agencies. There are three areas of focus:
urban outdoor air pollution (OAP), household indoor air pollution (IAP), and water
pollution, sanitation and hygiene (WSH)(including WSH-related child malnutrition). It
gathered the available data from different published data sources in the Philippines on
morbidity and mortality, to calculate the number of cases, and the corresponding
economic costs to the country in terms of lost productivity, direct costs to households,
and public funds used to subsidize treatment costs. A comparative summary of the
economic valuation of the environmental health costs of these three is presented below in
Figure 1:
Figure 1 – Comparative Summary of the Economic Costs of WSH, IAP, and OAP
Health Effects, 2003
Water, Sanitation and PhP 102.5 B
Hygiene (including u5 PhP 51.0 B ($1.9 B)
Malnutrition) ($ 0.9 B)
PhP 60.6 B
Outdoor Air Pollution PhP 5.1 B ($1.1 B)
($0.1 B)
PhP 23.6 B
Indoor Air Pollution PhP 4.7 B ($0.4 B)
($0.1 B)
0 20 40 60 80 100 120
Morbidity + Mortality (HCA) Morbidity + Mortality (VSL)
Source: Author’s calculations
As reflected in Figure 1, two methods were used to calculate the economic costs
of premature deaths: the human capital value (HCV) and the value of statistical life
(VSL)—the results were used as the lower and upper bounds of the economic cost of
6

7. mortality. The HCV is the economic cost to society of premature death in terms of lost
contribution to production of an individual. The VSL , on the other hand, is based on
individuals’ willingness-to-pay for a reduction in the risk of death. The cost-of-illness
(COI) approach is used to estimate the cost of morbidity and is based on the costs of
treatment and the lost income from being ill. It must be noted that this report made
additional calculations to estimate the economic costs of malnutrition-related deaths
resulting from diarrhea in children under 5 years old. The analysis was limited to this age
group as there were no data on the other age groups that could be used to estimate
premature deaths from diarrhea-induced malnutrition mortality for these groups of
individuals.
The results indicate that the economic costs of pollution and sanitation-related
health effects are high and cannot be ignored. The combined costs for all three sectors in
2003 totaled PhP 42.4 billion (USD 783.2 million) in lost productivity due to premature
deaths or PhP 168.4 billion (USD 3.1 billion) in terms of value of statistical life (Table
1). In addition, the cost of morbidity was PhP 18.3 billion (USD 337.6 million),
comprising of loss in productivity totaling PhP 10.4 billion (USD 191.3 million), direct
costs to Filipino households to treat these illnesses totaling PhP 6.4 billion (USD 118.7
million), and the cost to the government health care insurance system—representing the
subsidy for PhilHealth members’ hospitalization costs—and for general government
subsidy for publicly-owned health facilities was close to PhP 1.5 billion (USD 27.6
million).
Table 1 – Summary Table of Economic Costs Breakdown per Sector (USD’000)
Water,
Sanitation and
Indoor Air Outdoor Air All Sectors
Hygiene
Pollution Pollution
(including u5
Malnutrition)
Economic Cost (in USD‘000)
Morbidity 18,727 11,327 307,583 337,638
Mortality (HCV) 68,017 82,702 632,474 783,192
Mortality (VSL) 415,975 1,107,532 1,584,394 3,107,900
Morbidity and
86,744 94,029 940,057 1,120,830
Mortality (HCV)
Morbidity and
434,702 1,118,859 1,891,977 3,445,538
Mortality (VSL)
Economic Cost as Percentage of GNI
Morbidity 0.02 0.01 0.31 0.34
Morbidity and
0.09 0.09 0.94 1.12
Mortality (HCV)
Morbidity and
0.43 1.12 1.89 3.45
Mortality (VSL)
Source: Author’s calculations based on published data sets and empirical studies. The
information on malnutrition was based on the calculations of B. Larsen.
7

8. A comparison of the economic costs for all three sectors (including malnutrition-
related health effects in children under 5 years old from WSH) indicates that the most
pressing issue in environmental health is water, sanitation and hygiene, costing the
Philippine society almost USD 1-2 billion per year (HCV and VSL estimates for cost of
deaths) representing more than 33 million cases of illness and 22 thousand deaths in
2003. Outdoor air pollution comes in second with USD 94 million to USD 1 billion in
economic costs, registering close to one million cases of respiratory illness and over 15
thousand premature deaths. Indoor air pollution comes next, costing the Philippine
society USD 87 to 434 million in 2003, resulting from nearly half a million cases of IAP-
related illnesses and almost 6 thousand deaths due to exposure to indoor air pollution
from household use of solid fuels for cooking. (Details of these figures are in Tables 2
and 3). Tables 2 and 3 show us that OAP and IAP-related deaths are heavily skewed
toward adult and working age groups, while deaths resulting from WSH are in the
youngest members of society. This has implications in terms of vulnerability assessment,
policy prioritization, and target-setting.
Table 2 – Summary of Mortality Cases per Sector and Age Group, 2003
Water, Under-5
Indoor Air Outdoor Air All
Age Group Sanitation and Malnutrition
Pollution Pollution Sectors
Hygiene from WSH
Younger than 1 653 199 2,048 3,719 6,620
1 to 4 632 194 8,502 3,897 13,225
5 to 14 0 0 1,637 0 1,637
15 to 19 19 0 135 0 154
20 to 29 82 0 189 0 271
30 to 64 1,890 5,588 1,043 0 8,520
65 and older 2,492 9,369 851 0 12,711
Age not reported 4 17 2 0 23
All Age Groups 5,772 15,367 14,406 7,616 43,161
Sources: The author calculated the mortality cases for OAP, IAP and WSH. For the
malnutrition-related numbers, this report used B. Larsen’s calculations.
Note: Those entries with zeroes do not mean that there were no cases, but simply that
there were no available data which could be used to calculate the number of cases for
these age groups.
8

9. Table 3 – Summary of Morbidity Cases per Sector and Age Group, 2003
Water,
Indoor Air Outdoor Air
Age Group Sanitation and All Sectors
Pollution Pollution
Hygiene
Younger than 1 147,517 259,966 4,766,078 5,173,561
1 to 4 244,185 441,859 14,704,145 15,390,189
5 to 14 0 256,578 6,170,901 6,427,479
15 to 19 716 8,474 277,625 286,815
20 to 29 1,173 13,891 455,031 470,095
30 to 64 47,746 40,415 6,610,177 6,698,338
65 and older 16,435 16,856 478,527 511,818
All Age Groups 457,772 1,038,039 33,462,483 34,958,294
Source: Author’s calculations
Suggested interventions were culled from the existing literature. For outdoor air
pollution, the interventions in discussion are those that address emissions from mobile
sources such as improved traffic management to lessen travel time, improved inspection
and maintenance systems, additional investments in affordable mass transport systems,
and affordable pollution control devices for tricycles and motorcycles. For indoor air
pollution and water, sanitation and hygiene, it is apparent that interventions must target
behavior—cooking practices and ventilation for indoor air2; and hygiene of household
members to prevent water and sanitation illnesses. Interventions to involve the
communities to create and promote low-cost alternative stoves to the current solid fuel-
using stoves are suggested. Additional initiatives to increase the access of households
especially in the rural areas and the urban poor to a sewage system and clean water are
needed in order to decrease the exposure of the population to pathogens that cause
diseases.
2
It must be noted that cases of indoor air pollution-related illnesses due to cigarette smoking is not part of
the study. Hence, cigarette-smoking as a risk factor is not mentioned.
9

10. Introduction
One of the clearest indicators of the state of the environment in the Philippines is
perhaps the magnitude of the cases of pollution-related illnesses. The Philippines, being a
country with increasing productive activities fueled by a growing population, is squarely
confronted with the impacts of pollution on human welfare—a pollution-welfare nexus—
which take on several forms: availability of income opportunities, access to
environmental services, and in recent times, on human health. Among the areas of
concern within the pollution-welfare nexus, it is the human health angle that has captured
the attention and alarm of policy managers because of its growing incidence, and the
burden that it forces the poorest members of society to shoulder as a result of it.
Environmental health—the area of health concerns arising from poor
environmental quality, causing disease, injuries and deaths—is a serious and pressing
issue in countries such as the Philippines, which is still finding that point of sustainable
economic growth. It is an important enough issue that the Philippine government enacted
and adopted Executive Order (E.O.) 489 which created an inter-agency committee on
environmental health to establish and bring forward an agenda of technical collaboration,
information collection and dissemination, and policy review.
As part of the support for the country to plan and develop programs that are
consistent with addressing the problems in environmental health in the Philippines, the
information and analyses contained in this study have been carefully collected. The
objective is to aid policy makers understand how the country is faring in environmental
health issues; and determine what these health problems are costing the country in terms
of loss in productivity and direct costs to households. This study on environmental health
quantifies and analyzes the bio-physical dimensions of environmental degradation and
likewise determines the social costs of environmental degradation; and the potential
economic benefit of environmental improvement as they relate to environment-related
health effects. In addition, potential priority interventions—as suggested by the existing
literature— is examined to determine the feasibility of each in addressing the
environmental health issues in the Philippines.
These health effects of poor environmental quality negatively impact human
welfare (and ultimately, the welfare of society) by lowering the quality of life for
individuals afflicted with these health effects—which is represented by the lost income
opportunities as a result of being ill, and the opportunity cost of income that has to be
spent on treatment and care—and the loss of valuable and productive members of
society—as measured either by a permanent loss in productivity as a result of death (the
human capital value), or by the willingness-to-pay of individuals to reduce the risk of
deaths resulting from these illnesses (the value of statistical life approach).
There are three areas of specific interests that will be discussed: 1) urban outdoor
air pollution; 2) household indoor air pollution; and finally, 3) water pollution, sanitation
and hygiene. The primary research objectives are to determine and quantify the economic
costs of environmental degradation—focusing on these three areas—in terms of their
impacts on the health of the citizens of the country, and to evaluate the economic
10

11. feasibility and efficiency of potential interventions. There is a particular interest in
evaluating environmental health in the context of poverty and other high risk groups such
as women and children. The poor are the most susceptible members of society to the
health risks posed by a degraded environmental quality, because they lack the necessary
resources for disease prevention and treatment. Women and children are in a similar risky
position because they do not have the same health-care opportunities and access to
education and information that adult men possess.
To calculate the economic impacts of morbidity arising from environment-related
illnesses, the fundamental approach used was the cost-of-illness (COI) valuation method.
This necessitated a determination of the different treatment-seeking behaviors of
Filipinos, and an estimation of the corresponding medical costs attributable to each. In
addition, productivity losses were calculated by estimating a reduction in gross national
income as a result of missed days from work resulting from illness. To these numbers,
the public expenditures on subsidies for health treatment were added to determine the
total economic costs of environment-related morbidity.
The computation of the economic costs of premature deaths caused by pollution
and unsanitary practices proved to be more challenging than the calculations for
morbidity costs. This is due to the differing perspectives among scholars on how best to
estimate the value of a lost human life. To capture these differences, this study calculated
lower and upper bounds values based on the human capital value approach (HCV) and
the value of statistical life (VSL). The HCV estimates the value of loss of life based on an
individual’s foregone contribution to aggregate income as a result of premature death—
measured in terms of per capita gross national income. The VSL, on the other hand, is a
measure of one life lost in terms of how much money people are willing to pay to reduce
the risk of death. Which of these two approaches better approximates the cost of loss of
human life as a consequence of environment-related illnesses is not for this report to
decide on. But whichever that may be, the fact remains that many people could have
lived a longer, healthier and more productive life if the risks to life were not increased as
a result of a degraded environment. The estimated values of the lives lost presented in
this report—both the HCV and VSL—merely provide a benchmark by which the gravity
of these environment-related health causes are represented.
The organization of this report is based according to the issues within the areas of
environmental health mentioned earlier. The basic idea is to present estimates of the
environmental health effects of the degradation of the natural environment to aid policy
managers. This information is crucial in evaluating the feasibility of potential policy
interventions and determining which among these interventions promise to deliver the
highest net benefit at the least cost. To the maximum extent possible, the methodologies
and assumptions used to calculate the number of cases of illness and deaths and the
corresponding economic costs were harmonized with the existing World Bank studies
such as the Philippine Environmental Monitor (PEM) and the Economics of Sanitation
Initiative in the Philippines (ESI). There were many instances, however, when new
information were uncovered that could refine the computations in these studies. In these
cases, this study expanded the set of assumptions and modified the methodologies to
build on the results of these existing research reports. A great deal of effort was exerted
to list all the numerous assumptions to guide the reader in understanding the process by
11

12. which the calculations in this study were made. It is strongly suggested that the readers
refer to Annex 1 for clarifications on the computations.
It must be emphasized that great effort was undertaken to review the existing
empirical studies on environmental health issues in the Philippines. Whenever
appropriate, comments on the drafts of this report were solicited from some of the authors
of these studies to determine any points of contention and contradiction between the
information contained in this study and the existing literature on environmental health in
the country. The conclusion is that there are some differences in the numbers of cases
and valuation, but these differences are due to the differing scopes of work, assumptions,
methodologies used in this report and the other empirical works. This report made
detailed assumptions and modified the standard dose-response methodologies to capture
the different treatment-seeking behavior of Filipinos to estimate morbidity figures. The
result is a general methodological framework of valuation and analysis that is unique to
the situation in the Philippines.
As a final note, the issue of how different is this report from the PEM and ESI—
the two most recent initiatives of the World Bank dealing with environmental health—
must be squarely addressed. The data used in this study are the same basic data used by
the PEM and the ESI, but its approach in filling data gaps is different because of recent
information that were not available to the authors of those studies during the time they
were conducting the research. In addition, this report also has a different scope of
analysis than the PEM and ESI—the PEM focusing solely on the determination of the
number of cases of illness and deaths while this report took the next step of economic
valuation; the ESI’s economic analysis, on the other hand, was more encompassing than
this report in relation to sanitation and hygiene, as it included the impacts on non-
production activities such as tourism. It is important that the readers and users of this
report keep these differences in mind, so as not to pit the findings and conclusions of this
report against those of PEM’s and the ESI’s.
Outdoor Air Pollution
The deterioration of urban outdoor air quality in the Philippines is at a level
where one can visually observe air pollution in major cities such as those in Metro
Manila. An individual only needs to take public transportation any time of the day and
see black fumes spew out of decade-old buses to get a sense of the tight spot that the
country faces when it comes to air quality. The threat of poor air quality has already
reached the attention of law makers and the average Filipino, prompting Congress to pass
the Clean Air Act in 1999 in order to properly address the impacts of mounting air
pollution in the country. It is expected that the implementation of the law will translate
into concrete steps both by the public and private sectors to reverse the deterioration of
the nation’s air quality.
There are generally two types of air pollution: outdoor (mobile, stationary and
area sources) and indoor (stoves and cigarette-smoking). Outdoor air pollution is an
external (to the household) pollutant and often large-scale in its presence, affecting
12

13. multiple sectors and crossing geographical boundaries. Indoor air pollution is a household
issue attributable to proximity to indoor air pollutants such as smoke from cooking, and
cigarette smoke. Between the two types, it is outdoor air pollution that attracts greater
public attention. Not surprisingly, this has resulted in a greater awareness among the
citizens and a heightened sentiment of urgency to address. In most instances, however,
the discussion on outdoor air pollution has been confined to the experience and issues of
mega-cities, specifically, the high-profile cities in Metro Manila. This due to the fact that
based on the existing data, the highest concentration of outdoor air pollutant sources—
e.g., production plants and factories, private vehicles, buses, public jeepneys and other
modes of public transportation—is in Metro Manila.
The main driver of outdoor air pollution is the rapid urbanization, transport and
increasing expansion of manufacturing activities and industrial production in the country.
The ADB (2006) reports that the industrial sector in the Philippines grew by an average
of 3.2 percent between 1988 and 2002; and the National Statistics Office (2006) reports
that close to half (47 percent) of the manufacturing activities in the country occur in
Metro Manila, and more than a third (32 percent) are located in the urban centers around
or close to Metro Manila. This trend, along with the increasing migration from the rural
areas to the urban centers, has caused a heightened demand for services and transport
that—in the absence of effective air pollution management—resulted in degradation of
outdoor air quality in the cities and other urban areas.
It is difficult to pin down in exact terms what the state of air quality is in the
Philippines because of the very limited data collected. The law requires the
Environmental Management Board (EMB) to monitor air quality in the country, and to
establish an inventory of air emissions every three years. The monitoring, however, has
been limited to a review of studies conducted by non-government and international
development agencies, limited field surveys, and collation of information from self-
monitoring reports submitted by industry members.3 The latest emissions inventory (the
2001 Philippine Emissions Inventory) included particulate matter (PM), sulfur oxide
(SOx), nitrogen oxide (NO), carbon monoxide (CO), volatile organic compounds, and
total organic gases (TOGs) from mobile sources (ADB, 2006). The report estimates that
CO contributes the heaviest to total pollution load at 39 percent, followed by NO at 35
percent, SOx and PM at 8 percent, TOG at 7 percent and finally, VOC at 2 percent.
Regular source apportionment4 analyses, however, are not done by EMB. Apportionment
studies, instead, are being conducted by two institutions: the Philippine Nuclear Research
Institute (PNRI, a government facility) and the Manila Observatory (a non-government
institution). Both of these institutions’ regular apportionment analyses, however, are only
on the small particulate matter: PM10 and PM2.5 or particulate matters that measure less
than 10 and 2.5 micrometers in diameter respectively; and the samples are gathered from
stations which are (at present) only in Metro Manila or in close proximity to the area. The
3
The law requires that industry members submit periodic self-monitoring reports as part of the conditions
contained in their Environmental Compliance Certificate (ECC).
4
Source apportionment analysis determines what the contribution of each source of pollutant to a specific
location.
13

14. air quality of a few cities5outside of Metro Manila has been monitored by EMB but has
since stopped in 2006.
Given the data availability, this study can only focus on the health impacts that
are associated with particulate matter of sizes 10 and 2.5 micrometers. While it is
recognized that the other pollutants cited earlier have potentially significant impacts on
the health of Filipinos, the data gaps that characterize these other outdoor air pollutants
are too wide to be overcome. Nevertheless, a meaningful assessment—albeit limited—on
the economic impacts of health problems arising from is possible, because there is
sufficient information on PM10 and PM2.5 levels available; and there is sufficient supply
of technical data—raw PM levels and epidemiological studies that establish the “dose-
response” connections between long-term exposure to particulate matter and specific
identified illnesses such as respiratory and cardiovascular ailments.
If the reported levels of particulate matter were to be indicators of the state of
health effects in Filipinos exposed to particulate matter, then there is indeed a cause for
concern. This report’s estimates on PM10 and PM2.56 in Metro Manila indicate a
population-weighted average of 72 μg/m3 and 48 μg/m3, respectively for 2003. For urban
areas outside of Metro Manila, the estimates also show values of 38 μg/m3 for PM10 and
18 μg/m3 for PM2.5 for the same year. There are no PM values for the rural areas because
of insufficient data. These numbers are significantly above the guidelines set by the
World Health Organization (WHO) of 20 μg/m3 for PM10, and 10 μg/m3 for PM2.5.
Figures 2 and 3 below illustrate the PM levels data gathered from the different
stations in Metro Manila and one baranggay right outside of Metro Manila (baranggay
Inarawan in Antipolo; the Good Shepherd (GS) is another station located also in
Antipolo). The sites that the Manila Observatory (MO) uses to test and collect data on
PM concentrations in Metro Manila show a consistently high level—even if the level has
somewhat declined through the years—of PM concentrations. It must be pointed out that
the different sites vary in characteristics; the MO categorizes the sites as high, medium,
and low mobile source presence. As to be expected, the site at the National Press Office
(NPO), which has the heaviest vehicle-density, has the highest PM concentrations; the
Good Shepherd site in the city of Antipolo—categorized as the low mobile source
presence—registered the lowest PM concentrations. While this is not conclusive
evidence, it does provide some basis to the assertion that vehicles are very likely to be a
major contributor to the high PM levels in the Metro Manila, as well as to the other urban
areas in the country.
5
These cities are Indang (Cavite), Batangas City (Batangas), Angeles City (Pampanga), and Los Baños,
Laguna. Cebu city is also monitored but only for NO2, SO2, O3, benzene, toluene, and xylene only. (Source:
EMB’s National Air Quality Status Report, 2003, as cited in the discussion draft of the Country Synthesis
Report on Urban Air Quality Management in the Philippines by ADB).
6
The PM10 and PM2.5 average estimates for Metro Manila were calculated using actual data collected by
the Manila Observatory, and weighted according to population around the stations. These stations were
Manila Observatory (MO), National Printing Office (NPO), Philippine General Hospital (PGH), Good
Shepherd (GS in Antipolo), Pasig, Las Pinas, Valenzuela, Pateros, Taguig, and Inarawan (in Antipolo). The
MO’s data collection was part of the ADB/WHO/DOH project in 2003-04.
14

15. Figure 2 - Annual Average PM10 Concentrations in cities in Metro Manila and in
Antipolo City
100
PM10 Level
75
(ug/m )
3
50
25
0 PO
S
s
O
H
ig
an
la
na
G
PG
M
gu
ue
w
N
Pi
a
Ta
nz
ar
s
e
La
Site
In
al
V
2001 2002 2003
Source: Manila Observatory, 2004
Figure 3 - Annual Average PM2.5 Concentrations in Metro Manila
Annual Average PM2.5 Levels, Metro Manila
Source: Manila Observatory
75
2000
PM2.5 Level
(ug/m )
50 2001
3
2002
25 2003
2004
0
MO NPO PGH GS Pasig Las Pinas Valenzuela
Site
Source: Manila Observatory 2004
Economic Costs of OAP-related Morbidity
To estimate the health effects and economic burden caused by exposure to
particulate matter (PM), it is necessary to identify the illnesses that can be feasibly
included, and to determine the attributable fractions7 (AFs) of these illnesses from PM.
The decision as to which illness to include in this analysis is fundamentally about data
availability. Two considerations are at hand: the availability of information regarding
risks of becoming ill (for each disease) from exposure to PM, and the availability of
reliable information on the frequency or incidence for each disease. Unfortunately, the
information is wanting, and this study is thus limited to analyzing the economic burden of
disease of two health endpoints: acute lower respiratory infection (ALRI, including
7
Attributable fractions are defined simply as the fraction or ratio of incidence of illness that can be
accounted or attributed to a certain health risk such as exposure to particulate matter.
15

16. pneumonia), and acute bronchitis.8 Other diseases that could not be included due to data
gaps are chronic obstructive pulmonary diseases (COPD), cardiovascular disease,
exacerbation of asthma, lung cancer and possibly tuberculosis. The data on risk ratios
were sufficient to compute the AFs for specific ALRI illnesses, as summarized below in
Table 4:
Table 4 – Attributable Fractions (AF) for OAP-related Morbidity, 2003
Attributable
Health Outcome
Fractions
Pneumonia*
- Hospital cases 0.02555
- Non-hospital cases 0.11297
Acute Bronchitis, under 5 0.42343
Source: Author’s calculations based on Galassi et al (2000)
Note: The AFs for pneumonia are adopted from the AFs for respiratory diseases.
It must be noted also that the AFs were calculated only for Metro Manila and
other urban areas. AFs for the rural areas could not be compute due to
insufficient data.
The data presented above frame the discussion on the elevated levels of PM
concentration in the country. Comparing the data with the guidelines set by the WHO, it
is apparent that the concentrations of particulate matter has consistently been above the
guidelines of 10 μg/m3 for PM2.5 and 20 μg/m3 for PM10 during the period the data were
collected. In the absence of mitigating measures that could shield the population from
long-term exposure, continuously high levels of PM10 and PM2.5 have taken their toll on
the health and consequently, the productivity and welfare of Filipinos. The calculations
show that the total number of people who have been ill due to outdoor air pollution—
specifically from PM emissions—reached more than 1 million Filipinos in 2003. This
cost the national economy in lost productivity a total of PhP 254.7 million (equivalent to
USD 4.7 million9, as shown in Figure 6) from lost days due to illnesses related to outdoor
air pollution (including the lost income of parents who have missed work days to care for
their sick children). The burden on the households resulting from these illnesses reached
PhP 289.1 million (USD 5.3 million), and an additional PhP 70.0 million (USD 1.3
million) in health care subsidy10 from the national government. Table 5 below
summarizes the morbidity cases of OAP-related illnesses by each group.
8
Technically, acute bronchitis is included in ALRI. The data from the Department of Health (DOH),
however, list ALRI and acute bronchitis separately. This report is consistent with the distinction between
the two.
9
The foreign exchange rate used was PhP 54.2 = USD 1.0 which was based on the average exchange rate
for the year 2003.
10
The health care subsidy represents PhilHealth payments to its members and subsidy to patients who are
admitted in public-owned hospitals for treatment.
16

17. Table 5 – Cases of OAP-related Illnesses by Age Group, 2003
ALRI (including
Acute Bronchitis
Pneumonia)
Younger than 1 104,494 155.471
Age 1 to 4 169,618 272,240
Age 5 to 14 60,766 195,812
Age 15 to 19 8,464 10
Age 20 to 29 13,875 16
Age 30 to 64 40,374 41
65 and older 16,844 12
TOTAL 414,437 623,602
Source: Author’s calculations
Figure 4 – OAP Cost to Households of Treatment (Net of Public Health Care
Subsidy), 2003
Acute
Bronchitis
PhP 100 M
34%
ALRI and
Pneumonia
PhP 190 M
66%
Source: Author’s calculations
17

18. Figure 5 – Government Health Care Subsidy per OAP-Illness, 2003
ALRI and
Acute Pneumonia
Bronchitis PhP 61 M
PhP 9 M 87%
13%
Source: Author’s calculations
Figure 6 – Lost Income Due to OAP-related Illnesses, 2003
Acute
Bronchitis
PhP 85 M
33%
ALRI and
Pneumonia
PhP 170 M
67%
Source: Author’s calculations
18

19. Figure 7 - Total Economic Cost of OAP-related Morbidity, 2003
Acute
Bronchitis
PhP 194 M
32%
ALRI and
Pneumonia
PhP 420 M
68%
Source: Author’s calculations
The data in Table 5 indicate that it is the youngest members of society (those that
are 14 years old and younger) that carry the heaviest burden of lower respiratory
infections due to outdoor air pollution. This is alarming because it hits the potential
productive members of society during their formative stage, and may impact the
productivity of the future labor force in the Philippines. It should however be noted that
these estimates are limited to ALRI and acute bronchitis due to data limitations, and do
not include cardiovascular disease, chronic bronchitis and other diseases that
predominantly affect the adult population.
Economic Costs of Premature Deaths due to OAP
The calculations of the value premature deaths for all the mortality cases
attributable to OAP (as well as for IAP and WSH-related illnesses) were done under two
sets of definitions of value of premature deaths: 1) value in terms of the lost contribution
of the individual to economic activity (HCV or human capital value); 2) value of
statistical life as measured by how much individuals are willing to pay to reduce the risk
of dying. These two approaches yield two different valuations, but it is difficult to assert
if one is superior to the other. As a way to establish a range of values of economic or
welfare loss to society as a result of premature death, both of the values computed using
the HCV and the VSL approaches are presented. The lower bound of the range is
represented by HCV figures, while the VSL numbers are used as the upper bound. As a
starting point to determine this range of values, the mortality cases attributable to OAP
are computed, the results of which are presented in Figure 8. Mortality cases per age
group is also summarized and presented in Table 7. The number of cases is calculated
19

20. using AFs derived from relative risk ratios (RRs) which are computed using the data from
MO. The RRs and the AFs used for this section are summarized in Table 6 below:
Table 6 – Relative Risk Ratios and Corresponding Attributable Fractions for
Specific Illnesses
Relative Risks Attributable
Health Outcome Metro Fractions
Urban Rural (National)
Manila
Respiratory Mortality, under 5 1.10006 1.03980 1.00000 0.03058
Cardiopulmonary Mortality, older than 30 1.31085 1.13199 1.00000 0.08431
Lung Cancer, older than 30 1.49940 1.20386 1.00000 0.12683
Source: Author’s calculations based on collected information on PM concentrations from
the Manila Observatory, published data from the government, and methodology for
estimating mortality adopted from Ostro, 2004. There are no estimates for the age group
5-29 because of insufficient data.
Figure 8 – Mortality Cases Due to OAP, Grouped According to Working and Non-
working Age Groups, 2003
Source: Author’s calculations
20

21. Table 7 – Mortality Cases due to OAP, by Specific Age Group, 2003
Cardiopulmonary Diseases
Lung Cancer
(including respiratory diseases )11
Younger than 1 0 199
Age 1 to 4 0 194
Age 5 to 14 0 0
Age 15 to 19 0 0
Age 20 to 29 0 0
Age 30 to 64 498 5,090
65 and older 413 8,956
Not Reported 0 17
Total 911 14,456
Source: Author’s calculations
The computations show that in 2003, the total loss in productivity (Figure 9) due
to premature deaths resulting from illnesses caused by outdoor air pollution reached close
to PhP 4.5 billion (USD 82.7 million) or PhP 60.0 billion (USD 1.1 billion) in terms of
VSL. These figures were calculated based on pre-computed attributable fractions and
applied to the total prevalence of each cause of death. The breakdown of the cost of
premature deaths (using HCVand VSL (in parentheses)) is indicated in the bar-graph
below (Figure 9):
11
This is listed as: cancer of trachea, bronchus and lung; Hypertension with and without heart
involvement; Angina pectoris, Other forms of ischaemic heart disease; Acute myocardial infarction;
Disease of pulmonary circulation and other forms of heart disease; Complications and ill-defined
description of heart disease; Cerebrovascular disease; aterosclerosis; Acute upper respiratory infections;
Influenza; Pneumonia; Acute bronchitis and bronchiolitis; Chronic obstructive pulmonary disease and
allied conditions; Pneumoconioses and chemical effects; Pneumonitis due to solids and liquids; Other
diseases of respiratory system
21

22. Figure 9 - Cost of Premature Deaths due to OAP, 2003
Source: Author’s calculations. The Value of Statistical Life (VSL) estimates are in
parentheses.
Suggested Interventions
Mohanty et al (2004) concluded that particulate matter levels are influenced by
several factors namely: “vehicle and fuel characteristics, fleet characteristics and
operating characteristics”. Similarly, the PEM (2007) reported that the bulk of the total
quantity of particulate matter in Metro Manila (84 percent) is from mobile sources. The
data shows that the volume of vehicles that are added yearly into the highways and roads
in country is rising as can be concluded from Figure 10 below. The growth of the number
of vehicles every year has been steady at an average of 12 percent per year, or roughly
50,000 new vehicles each year.
22

23. Figure 10 – New Vehicle Registration (New and Used vehicles) Trend, 2007
Source: Land Transportation Office (www.lto.gov.ph/stats.html)
It becomes apparent therefore, that one of the necessary interventions in order to
limit PM emissions (and lessen the number of cases of OAP-related illnesses and
premature deaths) must include vehicle management. This is not to diminish the
importance of stationary sources management to lessen PM emissions, but merely to
highlight a choice in policy interventions based on greater urgency.
Inspection and maintenance (I/M) programs
A well functioning inspection and maintenance (I/M) program is one of the most
cost effective interventions in abating outdoor air pollution. Vehicle inspection in
particular strengthens the enforcement of emission standards as well as increases in the
demand for vehicle repair and maintenance (Kojima and Lovei, 2001). Subida, et al
(2005) report that for Metro Manila, maintenance of vehicles and inspection system
(MVIS) is one of the more effective interventions they have examined.
The implementation of an effective I/M program is not without cost as it entails
specific activities to make it work. Gwilliam, et al (2005) conclude that an I/M program
must be able to target gross polluters, which requires an examination of the
characteristics of the vehicle fleet. The program therefore requires superior management
and technical backstopping. All of these necessitate that a successful I/M program an
investment on training and regular data collection. In addition, the I/M program must be
complemented by laws and checks and balance to ensure that it is not tainted by
corruption and politicking. Like any program, corruption and politicking would weaken
the enforcement of any of the I/M program’s policies, and will surely result in an
eventual breakdown.
A review of the existing initiatives in the Philippines that address outdoor air
pollution indicates that positive steps have been taken. Indeed, there have been marked
23

24. declines in the PM levels in Metro Manila despite the increasing number of vehicles in
the region. This is attributed mainly to the government’s phase out of leaded gasoline
which has been successfully implemented. In addition, the emission standards were
tightened to comply with Euro 2 standards. The government also continues to review and
revise the allowable emission limits for vehicles equipped with compression ignition and
spark ignition. This should significantly limit increases in particulate matter levels from
the mobile sources.
Currently, the country also has an existing Motor Vehicle Inspection System
(MVIS) which requires motor vehicles to pass emission testing prior to registration.
Emission testing is performed either by private emission testing centers (PETCs) or by
the LTO. For private vehicles, there are over 300 PETCs all over the country that conduct
the emission testing while for public utility vehicles, the LTO MVIS is offering emission
testing services at lower costs (EMB-DENR, 2005).
The Philippines also has an existing smoke belching program that was established
to enforce motor vehicle emission standards through roadside inspection and
apprehension of violators. Teams which were trained by a multi-agency group led by
MMDA and LTO implements the initiative (EMB-DENR, 2003). On the ground, this
program could be improved with solid support from the local government units. Local
ordinances, capacity building, and roadside apprehension are best handled by the
municipal and city governments.
The benefit-transfer BCA of an inspection and maintenance program for diesel
vehicles done for the Philippines by Larsen (2008) reflects a B-C ratio of 3.9. This
indicates that in terms of health benefits (averted loss in human lives), sound maintenance
and inspection program delivers almost four times the cost of implementing such a
program. This supports conventional wisdom regarding the need for sufficient and
effective vehicle emission monitoring and regulation to address air pollution from mobile
sources.
From two-stroke tricycles to four-stroke tricycles
The popularity of the two-stroke tricycles in the country is a major concern, air
pollution-wise. Many motorcycle-drivers prefer the two-stroke over its four-stroke
counterpart because they are more powerful, and often times less expensive. Tricycles—
which oftentimes are two-stroke, and a very popular mode of public transportation—are
ubiquitous and will most likely remain popular in generations to come. The social cost of
using two-stroke tricycles, however, remains unaddressed satisfactorily. Aside from the
noise pollution they create, a significant volume of particulate matter is from these two-
stroke tricycles. The challenge is how to approach this emission problem and create an
incentive system to entice two-stroke drivers and owners to switch to less polluting
modes of transportation, or at the very least, to properly maintain their motorcycles and
reduce emissions. With barely minimum wage, the tricycle drivers do not have enough
money for tricycle maintenance. There is also very little incentive to conduct
maintenance operations since most tricycle drivers do not own the units they drive. More
often than not, an operator owns the tricycle units and a single unit is being shared by
three to four drivers (Camagay, et al, 2005).
24

25. The social benefit of the switch is potentially large. In the strategy scenarios
evaluated by Subida et al (2005), switching from the two-stroke to the four stroke
tricycles (4-STC) under several assumptions will result in an 80 percent reduction in PM
emissions from these vehicles. Realistically, however, switching from 2-stroke to 4-
stroke tricycles for the Philippines is very difficult, although not impossible. The biggest
issue is cost, not just in terms of providing the funds to help finance the switch, but also
to promote the acceptability of the program among the citizens by providing information
and awareness. In the short-run, the government can do a bit more drastic action by, for
example, banning the introduction of new two-stroke tricycles into the system while
providing inspection and maintenance services to the existing two-stroke tricycles.
Owners of “retiring” two-stroke vehicles should also be encouraged to make the switch;
but this entails financing. As an example, the city government of San Fernando in La
Union offered a loan package to encourage the shift from two-stroke tricycles to 4-STCs.
Tricycle operators were offered an interest-free loan amounting to P9,000 payable within
one year for the down payment on the purchase of 4-STCs. Old two-stroke tricycles with
age ranging from 20 years old and above were phased out (San Fernando City
Government, undated). As of July 2005, a total of 643 two-stroke units were converted
into 4-strokes, of which 97 units received financial assistance (Ortega, undated).
Installation of pollution control devices
Larsen (2008) used benefit-transfer to determine if retro-fitting of in-use diesel
vehicles with diesel oxidation catalysts (DOC) or diesel particulate filters (DPF) makes
economic sense for the Philippines12 (Refer to Annex 2 for the complete paper). Using
the experience of Mexico, Peru, and Senegal as the basis for the analysis, the benefit-cost
analysis indicates that the benefits (in terms of the economic values of averted premature
deaths calculated using VSL) of a retro-fitting program more than outweigh the average
costs of adopting the technologies for diesel vehicles. A summary of the BCA results for
retro-fitting of in-use diesel vehicles in the Philippines is shown below13:
12
Effective functioning of DOCs and DPFs requires diesel with a maximum sulfur content of 500 and 50
ppm, respectively.
13
Larsen applies a VSL of US$109,000 to the Philippines (reflecting GNI per capita in 2007) for valuation
of mortality.
25

26. Table 8 - BCA-ratios for Cases of Retro-fitting of In-use Diesel Vehicles in
the Philippines
Diesel Oxidation Catalysts (DOC) BCA Ratio
Old buses 6.54
Large buses 6.74
Buses 4.12
Newer buses 2.97
Old delivery trucks 2.23
Newer delivery trucks 1.81
Diesel Particulate Filters (DPF)
High usage taxis 5.30
Old buses 2.80
Large buses 2.89
Newer buses and delivery trucks 1.47
Source: Larsen, 2008.
Vehicle emission technologies are useful short term interventions while the
country is building capacity, awareness and adoption of cleaner fuels. As such, a national
program that requires vehicles (new and in-use), especially public utility vehicles such as
the jeeps, buses and tricycles—to install pollution control devices must be implemented.
There are several pollution control devices being offered in the market today.
Kojima and Lovei (2001) note that for gasoline powered vehicles, catalytic converters are
the most effective in reducing exhaust emissions. As much as 95% reduction in CO and
hydrocarbon emissions and around 75% NOx reduction can be achieved if the three-way
catalytic converters are efficiently used. However, according to Kojima and Lovei
(2001), there are several pre-requisites for this option to work successfully: wide use of
unleaded gasoline; low sulfur level in gasoline; emission standards and adjustment period
to meet these standards; and effective I/M programs. Along with improvement in fuel
specifications, particulate traps or filters can also be used for diesel powered engines.
Buses and jeepneys can be fitted with particulate traps to reduce emissions.
Cost is one of the main concerns regarding the implementation of this
intervention. Vehicle emission technologies entail additional costs to vehicle owners.
Moreover, given certain technologies, lower emissions come at the price of fuel
efficiency making installation of emission technologies even more costly. While newer
vehicle imports come with installed catalytic converters, the problem lies with older
vehicles (Gwilliam, et al., 2005). One way to encourage owners of vehicles (especially
the old units) to install pollution control devices is to strictly implement compliance with
emission standards. If emission standards are being strictly enforced through a well
functioning I/M system, vehicles owners are left with no choice but to install pollution
control devices to avoid apprehension or the risk of the vehicle units not being registered.
26

27. In addition, the government can remove the barriers that prevent the entry of anti-
pollution technologies or impose lower tariffs (if not zero) on the importation of emission
technologies to help ease the price in the domestic market (Kojima and Lovei, 2001).
Rehabilitation of Current Traffic Management System
Traffic congestion is a ubiquitous phenomenon in the major cities in the
Philippines. The length of time a vehicle is on the road is the most significant factor in
the contribution of the vehicle to particulate matter emission. As such, the minimization
of traffic in the country will improve the level of particulate matter released by vehicle
combustion in the air. The current traffic management system in the Philippines has
improved the traffic situation in the country—especially in Metro Manila—but additional
efforts are needed to completely eliminate regular traffic congestion in the major cities.
To illustrate the potential of traffic management, a study conducted in Bangkok and
Kuala Lumpur in 2004 revealed that the reduction in emissions from the installation of 3-
way catalytic converters in 50% of the cars in these cities can be achieved by increasing
vehicle speed from 12-15 km per hour to 30 km per hour (Kojima and Lovei, 2001).
Strategies that can greatly improve flow of traffic include the following:
coordinated signals/traffic lights, channelization, reversible lanes, one-way street pairs,
and other traffic control device, area licensing schemes, parking controls, exclusive
pedestrian zones, vehicle bans (Faiz, et. al, 1990); and segregated busways (Gwilliam, et.
al, 2005).
Potential of traffic management in reducing pollution is no doubt very effective in
the short run but caution should be exercised in the long run. Reduced travel time
encourages more trips and thus translates into higher emissions. For example, after
increasing capacity of road networks in United Kingdom and United States additional
traffic was generated. About half of the 2.7 percent growth in traffic in the US can be
attributed to the additional roads that were constructed. Traffic management is only
effective to the extent that it does not create additional traffic. When it does, policies to
redirect traffic flow, especially away from environmentally sensitive locations should be
enforced (Kojima and Lovei, 2001).
Investments in Additional Mass Transport System
Investments in additional mass transport systems such as additional electric trains
will significantly reduce the public’s reliance on jeepneys and tricycles which are
notorious for outdoor air pollution emissions. Currently, there are three light rail transit
lines in operation/available in Metro Manila, which service the population of the
metropolis daily as described below in Table 9:
27

28. Table 9 - Light Rail Transits Lines in the Philippines
Length/Ridership
LRT Line 1 15-km line / 300,000 passengers per day
LRT Line 2 13-km / 200,000 passengers per day
EDSA-MRT 17-km / 400,000 passengers per day
Source: ADB, 2006.
A number of authors have suggested the use of trains and railways as an effective
strategy combating air pollution (Gwilliam, et al., 2005; Ostro, 2004; Kojima and Lovei,
2001; Subida, et al., 2005). By expanding the railway network, it is expected that the
number of commuters using the LRT/MRT will increase. With a larger number of the
population using non-motorized transport, volume of traffic will be reduced and thus help
in lessening outdoor air pollution. The projections made by Subida, et al (2005) show
that in 2015 (under several assumptions), the use of metro railways will generate 18.2
percent and 13 percent reduction in SPM and CO2 emissions respectively. The costs of
this intervention, on the other hand, are summarized below in Table 10:
Table 10 - Proposed Railway Projects with project costs (in USD millions)
Railway Route Distance Fixed Cost Variable Cost TOTAL
Line (km) (Operating
and
Maintenance)
LRT line 6 South extension of 30 km 600 750 1,350
line 1
MRT line 3 North Ave- 12 km 306 261 567
extension Navotas; Taft-
Reclamation
MRT line 2 Recto-North 15.7 km 351 182 533
(east west harbor; Santolan-
extension) Masinag
MRT line 2 Masinag-Antipolo 22.8 km 288 150 438
MRT line 4 Recto-Novaliches 26 km 724 646 1370
North Rail PNR line 45.5 km 589 649 1238
MCX PNR Line 554 996 1550
Total Cost 3,412 3,634 7,046
Source: JICA in Subida, et al, 2005.
However, there are several issues that need to be addressed when implementing
this intervention. First, MRT and LRT operations are financed heavily by government
subsidies. The Inquirer reported that MRT for example receives approximately P6.8
28

29. billion subsidies per year. This put a lot of pressure on the fiscal position of the
government. Therefore, to prevent perverse use of subsidies, great caution should be
exercised during project conceptualization and contract design. For the proposed railway
projects, the government should avoid taking on risks beyond its control to prevent
incurring huge amount of contingent liabilities.
Second issue is the setting of fare rates. In theory, the fare rate should reflect the
true costs of service being provided. However, this is not a viable option in practice for
several reasons: political and demand elasticity considerations.
Focusing on the MRT, the fare rate has been set very low, revenues from which
are not enough to cover the operating expenses. Table 11 shows the financial summary of
MRT Line 3 Operations.
Table 11 - Financial Summary of MRT Line 3 Operations (in million pesos)
CY 2003 CY 2004 CY 2005
Total Expenses 6,500.00 6,700.00 8,000.00
Revenues 1,600.00 1,800.00 1,900.00
Development Rights revenues 12percent 17percent 17percent
Farebox revenues 88percent 83percent 83percent
Amount being subsidized by the P44.23 P39.94 P49.57
Government per passenger $0.88 $0.8 $0.99
Total Ridership 112,653,067 122,483,642 121,753,952
Source: Morales-Mariano (http://www.cleanairnet.org/baq2006/1757/docs/SW7_2.ppt)
In order to make the operation of an additional MRT feasible, it would be
necessary to increase the current fare and reduce the subsidy that the government pays to
keep it afloat. Morales-Mariano (http://www.cleanairnet.org/baq2006/1757/docs/SW7_2.ppt)
suggested that the optimal fare rate is around PhP 14.40-19.90. The average optimal fare
of P17.15 generates the lowest subsidy required (PhP 6.449 billion). Increasing the fare to
an average of P17.15 will not result to increase traffic volume and road congestion.
However, beyond this amount, revenues will begin to decrease as 52 percent of the
passengers will shift to buses and around 2 percent will shift to cars.
Martinez and Tolentino (2007) estimated the optimal fare using a sensitivity
analysis. Their study revealed that the optimal fare is around PhP18.15 in 2007. This fare
rate maximizes farebox revenues and minimizes the subsidy. Beyond this amount,
subsidies begin to increase as revenues fall. It is expected that there will be opposition
against building another MRT that will be subsidized heavily by government, especially
if the subsidy is substantial. Without the subsidy, however, the MRT fare would be more
expensive than the jeepneys and buses that ply the same route, dampening the impact of
the expansion of the electric train on the particulate matter emission. Additional studies
must therefore be done to find a solution to the fare increase problem.
Finally, a summary of activities related to reducing outdoor air pollution was done
by the Metro Manila Air Quality Improvement Sector Development Program
29

30. (MMAQISDP) in 2003. These figures were inflated to reflect the current costs of creating
the same projects, as shown below in Table 12:
Table 12 - Cost Estimates for the Metro Manila Air Quality Improvement Sector
Development Program (MMAQISDP) in million USD
2003 Prices 2007 Prices
Item FE LC Total FE LC Total
Road Rehabilitation 19.52 19.52 39.04 28.13506 28.13506 56.2701
Traffic Engineering
Management 9.01 11.64 20.65 12.98652 16.77726 29.7638
Ambient Air Quality
Management 10.59 1.96 12.55 15.26385 2.825037 18.0889
Public Health Monitoring 0.15 0.01 0.16 0.216202 0.014413 0.23062
Anti-smoke Belching 0.5 0.05 0.55 0.720673 0.072067 0.79274
Capacity Building 7.46 5.36 12.82 10.75244 7.72561 18.478
Consulting 6.06 5.06 11.12 8.734552 7.293207 16.0278
Program Administration 4.61 4.61 0 6.644601 6.6446
Contingencies 6.43 6.52 12.95 9.26785 9.397571 18.6654
Interest and Other Charges 7.86 7.86 11.32897 0 11.329
TOTAL 67.58 54.73 122.31 97.40611 78.88482 176.291
Note: FE- foreign exchange;
LC- local currency
Source: 2002 National Air Quality Status Report. The 2007 prices are the author’s own
computation given annual inflation rate and exchange rate data from BSP and the 2003
data from the 2002 National Air Quality Status Report.
Indoor Air Pollution
The WHO estimates indoor air pollution as the 8th most significant risk factor in
the global burden of diseases. It contributes around 3.7 percent of the disease burden in
developing countries and ranks fourth behind malnutrition, unprotected sex, and water,
sanitation and hygiene, as the main causes of premature deaths (WHO websites:
http://www.who.int/ indoorair/health_impacts/burden_global/en/index.html;
http://www.who.int/mediacentre/factsheets/fs292/en/).
Indoor air pollution-related illnesses result from both short and long-term
exposure to smoke inside the home—smoke that originates from cooking with solid fuels,
cigarette smoking and other sources. In this study, however, the focus in is only on
households’ solid fuel use as the source of indoor air pollution. The choice of solid fuel
use as the basis of the analysis is borne of the practical consideration—the data are
available on solid fuel use, but no sufficient data on cigarette smoking inside the home—
30

31. and the appropriateness and rationale for intervention. The WHO reports that the impact
of indoor air pollution (from solid fuel use for cooking) on individuals’ health is
significant, causing an estimated 1.6 million deaths globally due to respiratory diseases
and lung cancer.
Public health specialists who were interviewed for this report believe that
cigarette smoke is the largest contributor to indoor air pollution; even as they
acknowledge that smoke from cooking fuel is a significant source of IAP as well. There
is no sufficient data on cigarette smoking—i.e., epidemiological studies that estimated the
relative risk ratios for cigarette smoking in the Philippines—in the household to conduct
an economic analysis. As such, this study is limited to analyzing the impacts of exposure
to smoke from fuel used for cooking even as the author acknowledges the importance of
cigarette smoke on the deterioration of human health in the Philippines14. But despite the
idea that solid fuel is only secondary to cigarette smoke as the sources of indoor air
pollution, its impact on health and life is huge. It is expected, however, that as more data
become available (particularly, technical and household data on the impacts of exposure
to cigarette smoking in the homes) that these valuations will be revised to include these
information.
We begin the formal discussion by characterizing solid fuels—at least based on
how it is defined in this report. Desai, et al. (2004) defines solid fuel use as “the
household consumption of biomass (dung, charcoal, wood, or crop residues), or coal.”
Results of the 2004 Household Energy Consumption Survey (HECS) show that the
percentage of households using electricity and LPG increased from 1995 to 2004 while
the percentage of household using fuelwood, charcoal, kerosene and other biomass fuels
declined as illustrated in Figure 11 below:
Figure 11 – Percentage of Households Use of the Type of Cooking Fuel, 2004
100
75
50
25
0
Electricity LPG Gasoline Diesel Kerosene Fuelwood C harcoal Other
Biomass
Residue
1995 2004
Source: Household Energy Consumption Survey, 2004
14
Another limitation of the study is that it does not include the incidence of IAP-related illnesses in the
workplace. The focus of this section is solely on the household members’ exposure to smoke from cooking,
which in turn is based on the use of cooking fuel, cooking practices and ventilation of the home.
31

32. The literature on indoor air pollution suggests that the bulk of the environmental
burden of disease due to solid fuel is borne by low-income households in rural and peri-
urban areas—sectors that typically have inadequate access to clean and affordable fuels.
The results of the 1995 HECS presented in Figure 12 show that solid fuel use is indeed
high in rural areas. The 2004 HECS data however, do not include a classification of
households according to urbanity, but nevertheless supports the claim that a big portion
of poor households use solid fuel such as wood, charcoal and other biomass residue
(Figure 13). Additional information is needed to verify if it is the rural poor or the urban
poor that is exposed to air pollutants from solid fuel use. Anecdotal evidence, however,
point to the incidence of solid fuel use to be higher in the rural areas this is the traditional
use of fuel in the rural sector, and this is also the cheapest and most accessible cooking
fuel available.
Figure 12 – Household Fuel Use by Urbanity, 1995
Household Fuel Use, By Urbanity, 1995
100%
Percentage of households
75%
Philippines
50%
Urban
Rural
25%
0%
Electricity LPG Gasoline Diesel Kerosene Fuelwood Charcoal Biomass
Residues
Source: Household Energy Consumption Survey, 1995.
32

33. Figure 13 – Household Use of Solid Fuel by Income Class, 2004
PhP25,000 and over
PhP15,000-24,999
PhP10,000-14,999
PhP5,000-9,999
Less than PhP5,000
0% 25% 50% 75% 100%
Fuelwood C harcoal Other Biomass Residue
Source: Household Energy Consumption Survey (HECS), 2004.
The data on PM emissions from solid fuel use is wanting in the Philippines. One
major source is the ADB (2004) which looked at the indoor PM10 levels in rural and
urban households. It did not have, however, a definitive conclusion on the sources of PM
levels within the household. It is also difficult to assess without additional analysis if the
PM levels found inside homes are from the “trans-boundary” movements of fumes from
outdoor air pollution sources.
Based on the available information reviewed for this report, it is hard to make a
definitive conclusion on indoor air PM levels especially since the sites included in the
studies are few—the data collection on the PM10 levels from the indoor sources are done
regularly but not at the ideal level of frequency. Some deductive results, however, can be
made and used to paint a general picture of the link between solid fuel use and exposure
to particulate matter. Using data from HECS and combined with emission factors
collected from the different technical literature available, an estimate of PM emissions
from solid fuel use of households is calculated. Table 13 summarizes these calculations.
Table 13 – Particulate Emissions from Household Cooking, 2004
PM Emission Total PM
Fuel Type 2004 Consumption
Factor Emissions
Fuelwood 10.694 M tons 15.30 g/kg 163,618 tons
Charcoal 0.888 M tons 36 mg/kg 32 tons
Biomass Residues 1.351 M tons 7.40 g/kg 9,997 tons
Source: Author’s estimates based on HECS data.
33

34. Most health outcomes that have been associated with exposure to indoor air
pollution have been limited to children younger than 5, women older than 30, and to
some extent, men older than 30. This trend is borne of the fact that the individuals who
belong to these age groups are the most likely to spend the most time inside the home.
With this information at the forefront, particular attention to young children and adult
women is given, since they are the people most likely to suffer from illnesses caused by
indoor air pollution. The estimates done on the number of cases of IAP-related illnesses
support this conclusion, as the discussion in this section will illustrate later.
To start off the discussion, this study looks at the existing data on household fuel
use, and found that 42 percent of households in the Philippines use fuel wood as their
primary cooking fuel (Figure 14). To calculate the population that has been exposed to
indoor air pollution, we first exclude from the households that used any of the three solid
fuels of interest in 2004, but used other energy sources as their primary cooking fuel a
year prior to the actual survey. Figure 15 shows that a little more than 48 percent of the
households in the country are exposed to indoor air pollution, based on solid fuels used as
the primary cooking fuel. As expected, the proportion is much higher in the rural areas
where cooking using biomass and fuel wood, is the traditional and practical method—
solid fuel is easily accessible and cheaper in the rural areas than LPG and other cooking
fuel.
Figure 14– Primary Cooking Fuel for Households, 2004
Others Electricity
Charcoal 2.1% 1.3%
7.2%
LPG
42.7%
Fuelwood
42.0% Kerosene
4.8%
Source: Household Energy Consumption Survey (HECS), 2004.
34

35. Figure 15 – Households Exposed to Indoor Air Pollution (in percentage)
Source: Author’s estimates based on HECS data.
The numbers in Figure 15 illustrate the prevalence of the use of solid fuel in rural
areas, and that a relatively small proportion of households in Metro Manila can be
considered exposed to indoor air pollution. However, there is a need to adjust these
figures by the associated ventilation factors because cooking practices and the structural
characteristics of houses in the Philippines may mitigate the exposure of Filipino
households to indoor air pollution and the subsequent health outcomes. Desai, et al.
(2004) suggest using a ventilation factor of 0.25 for households that use improved stoves
or cook outside, and a ventilation factor of 1.00 for those that use traditional stoves. A
ventilation factor of 0.25 means that the health effects of indoor air pollution emanating
from cooking fuel are expected to be reduced by three quarters as result of the ventilation
conditions. Saksena et al. (2005) summarized these mitigating ventilation conditions to
be based on a variety of factors including the distance of rooms and walls, height of
ceiling, size of windows, materials used to build the house, and whether the household
uses improved stoves or not. Taking into account the “airiness” of the areas where
cooking is done even if the stoves were traditional, a ventilation factor of 0.25 is used for
urban and rural areas outside Metro Manila as households in these areas typically do their
cooking outside their houses. Metro Manila households that use solid fuel, however, are
assigned a ventilation factor of 0.5 since they would normally be found in informal
settlements where houses are crammed together.
With the above assumptions, the proportion of the cases of the health outcomes
outlined above that can be attributed to exposure to indoor air pollution is computed. To
accomplish this, attributable factors were estimated based on the relative risk ratios—
calculated based on gender, age, and specific illness—obtained from several
35

36. epidemiological studies are used. The pollutant in discussion is PM resulting from the
smoke from solid fuel use in the households. Adjustments on the potency of exposure to
smoke are made by integrating the (significant) impact of household ventilation on the
degree of exposure. The computed weighted-AFs for each health endpoint used in this
study are summarized in Table 14.
Table 14 – Attributable Fractions Used for Morbidity Cases per Illness
Risk Ventilation Attributable
Health Endpoint Ratios Factor Fractions
Acute lower respiratory infections, children 1.8 0.25 0.1009
younger than 5 and women older than 30.
Chronic obstructive pulmonary diseases, women 3.2 0.25 0.2359
>= 30
Chronic obstructive pulmonary diseases, men >= 1.8 0.25 0.1009
30
Tuberculosis, all >= 15 1.5 0.25 0.0656
Sources: AFs calculated by author, based on risk ratios from Desai, et al (2004) and
Dherani et al (2008).
The results of the calculations for morbidity cases are shown in Figure 16. Table
15 shows in more detail the number of cases of acute bronchitis, ALRI and pneumonia,
COPD and respiratory tuberculosis, given the different age groups. It must be
emphasized that the estimates of cases (as well as the inclusion of the specific diseases)
were based on the available data on relative risk ratios (and the consequent computation
for attributable fractions) and on the total number of cases of each of the diseases.
Figure 16 – Morbidity Cases Attributable to IAP, By Gender, 2003
Source: Author’s calculations. COPD refers to chronic obstructive pulmonary disease.
36

37. Table 15 - Cases of IAP-related Illnesses by Age Group, 2003
Acute ALRI and
COPD Tuberculosis
Bronchitis Pneumonia
Age 0 to 4 101,949 289,753 0 0
Age 5 to 14 0 0 0 0
Age 15 to 19 0 0 0 716
Age 20 to 29 0 0 0 1,173
Age 30 to 64 18,630 22,842 2,670 3,604
65 and older 4,900 8,839 1,558 1,139
TOTAL 125,479 321,434 4,228 6,631
Source: Author’s calculations
The Economic Costs of IAP-related Morbidity
As with the calculations for the economic costs of OAP, the estimates for the
costs to society and the economy of indoor air pollution related illnesses include direct
costs to households (based on treatment-seeking behavior) and the indirect costs (lost
income due to days off from work due to illness). The estimates of economic burden
include the cost to the government health care system in terms of subsidy to PhilHealth
members’ medical costs15 and the per-patient hospitalization subsidy for government-
owned hospitals. Figure 17 illustrates the direct treatment costs to households for the
indoor air pollution-related illnesses in 2003, while Figure 18 describes the costs that are
shouldered by the government.
15
It must be noted that only 70 percent of cases in Metro Manila and in urban areas, and 20 percent of
cases in rural areas, are subsidized by the government through PhilHealth. The PhilHealth also indicated
that only (an average of) 35 percent of costs incurred by its members are paid by the agency.
37

38. Figure 17 – IAP Cost to Households of Treatment (Net of Public Health Care
Subsidy), 2003
ALRI and
Pneumonia
PhP 415 M
89%
Respiratory
Tuberculosis
PhP 19 M
4%
Acute Bronchitis COPD
PhP 20 M PhP 13 M
4% 3%
Source: Author’s calculations.
Figure 18 - Government Health Care Subsidy per IAP-Illness, 2003
ALRI and
Pneumonia
PhP 177 M
93%
Respiratory Acute
Tuberculosis COPD Bronchitis
PhP 6 M PhP 5 M PhP 2 M
3% 3% 1%
Source: Author’s calculations.
It is also estimated that the Philippine economy loses the productive contribution
of working-age patients when they take time off to get treatment, or to take care of a sick
child. Lost productivity resulting from IAP-related illnesses is calculated based on the
2003 per capita GNI of the Philippines, with the figures adjusted for stay-at-home
38

39. mothers. Figure 19 illustrates the computed indirect costs from the diseases mentioned
above.
Figure 19 – Lost Income Due to IAP-related Illnesses, 2003
ALRI and
Pneumonia
PhP 199 M
55%
Respiratory
Acute Tuberculosis
Bronchitis PhP 33 M
PhP 49 M 9%
14%
COPD
PhP 79 M
22%
Source: Author’s calculations.
Total foregone income due to indoor air pollution amounted to PhP 360 million
(USD 6.6 million) in 2003, a significant amount for a country like the Philippines,
especially if we consider the fact that majority of these cases occurred in the rural areas
where most of the poor reside. In total (treatment cost and foregone income and time
losses), the calculations show that IAP-related illnesses cost the Philippine economy in
2003 a total of PhP 1.0 billion (USD 19.0 million) in morbidity costs (Figure 20).
Figure 20 – Total Economic Cost of IAP-related Morbidity, 2003
ALRI and
Pneumonia
PhP 791 M
77%
Respiratory
COPD Tuberculosis
Acute
PhP 114 M PhP 56 M
Bronchitis
11% 5%
PhP 71 M
7%
Source: Author’s calculations
39