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Air Quality & Health Impacts of Coal-Fired Power in the Philippines

Key findings ● The Philippines has 10 GW of installed coal capacity that contributes to air pollution across

the country. This is likely to worsen as another 9 GW of coal are currently in various stages of construction and permitting phases.

● Pollution from the current operating fleet was responsible for an estimated 630 air pollution-related deaths in 2019, as well as 1,300 new cases of child asthma, 149,000 days of work absence (sick leave) and 240 preterm births. The total annual cost borne by the public is estimated at USD 165 million (PHP 8.5 billion). With the additional proposed CFPPs, premature deaths would increase to an estimated 1,000 deaths per year. The associated economic cost would also rise to USD 264 million (PHP 14 billion) annually.

● Without stronger emission standards, the cumulative impact of these plants during the next decade would be over 178,000 exacerbated cases of non-communicable diseases and lower respiratory infections, 7,000 premature deaths, and an economic cost of approximately USD 2 Billion (PHP 103 billion) as a result of lower life expectancy, economic output, and quality of life and increased healthcare cost.

● If the proposed CFPPs are commercialized by 2024, these new plants would result in almost 26,300 premature deaths over 40 years and cumulatively cost the country USD 7.2 billion (PHP 370 billion).

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About CREA The Centre for Research on Energy and Clean Air (CREA) is a new independent research organisation focused on revealing the trends, causes, and health impacts, as well as the solutions to air pollution. CREA uses scientific data, research and evidence to support the efforts of governments, companies and campaigning organizations worldwide in their efforts to move towards clean energy and clean air, believing that effective research and communication are the key to successful policies, investment decisions and advocacy efforts. CREA was founded in Helsinki and has staff in several Asian and European countries. Authors Lauri Myllyvirta Isabella Suarez Contributors Erika Uusivuori Patricia Singson

Acknowledgements We gratefully acknowledge the support, feedback, and insight we received from the following organizations and individuals: Healthcare without Harm; Greenpeace Philippines; Center for Energy, Ecology, and Development (CEED); Philippine Movement for Climate Justice (PMCJ); Sarah Jane Ahmed (Institute for Energy Economics and Financial Analysis); Maria Celina Paula Valencia and Angelika Marie David (Institute for Climate and Sustainable Cities); and the World Wildlife Fund (WWF) - Philippines. The views expressed in this report are those of the authors and should not be attributed to any of the aforementioned.

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Contents

Key findings 1

Introduction 4

Major Air Pollutants and Related Literature 5

Coal, COVID-19 and Economic Recovery 6

Controlling and Monitoring Air Pollution from Coal 7

Methodology 10

Emissions 10

Atmospheric Modeling 13

Health Impact Assessment 14

Economic Valuation 16

Results: Air Quality and Toxic Deposition Impacts 18

Air Quality 18

Toxic Deposition 21

The Hidden Cost of Coal-fired Power 25

Breakdown by Province 26

Cumulative Health and Economic Impact of CFPPs 28

Recommendations 31

Appendix 32

References 38

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Introduction Air pollution is the biggest environmental risk factor to human health in the Philippines (GBD 2019 Risk Factors). The number of deaths attributable to fine particulate matter (PM2.5) in the country has been steadily increasing since the 1990s, even as the average annual population-weighted PM2.5

1 decreased (HEI 2020). This growing threat of air pollution has been accompanied by industrialization and fossil fuel development that come at great cost as cities and communities are exposed to air pollution far above what the World Health Organization deems safe. In 2019, around 21,700 avoidable deaths in the Philippines were attributable to PM2.5 exposure (HEI 2020).

Fossil fuel burning is the largest man made source of this air pollution. In addition to carbon dioxide, it releases toxic airborne pollutants such as sulfur dioxide (SO2), nitrogen oxide (NOx), particulate matter (PM), and mercury (Hg). This has ramifications for public health in the Philippines, where the number of premature deaths associated with fossil fuels such as oil, coal, and gas is estimated to be between 11,000 to 27,000 per year (Myllyvirta 2020; Farrow et al. 2020). While vehicular emissions contribute the most to overall outdoor pollution, particularly in urban centers, the contribution of coal-fired power plants (CFPPs) as a major stationary source is not negligible - it accounts for approximately 87% of SOx emissions, and a third of particulates in the country (EMB 2019).

Currently, coal accounts for 54% of the country’s gross power generation with an installed generating capacity of approximately 10 gigawatts (GW), with another 9 GW in various stages of construction and permitting (DOE 2020a). In October 2020, the Department of Energy (DOE) promised a refocus on renewable energy and announced a moratorium on endorsements for greenfield coal power plants, following department policy reviews that revealed the urgent need to shift away from expensive2, baseload generation — for which excess coal is a feature. The move is a pivot towards a more flexible and resilient power supply mix to better respond to structural changes in demand and the increasing cost competitiveness of renewable energy alternatives, which comparatively emit little to no air pollution when generating.

The moratorium currently only applies to new coal projects and does not cover ones in construction and those with

1 Instead of calculating average air pollution levels where all areas receive equal weight, population-weighted averages give weight to pollution in proportion to population, so that greater weight is given to exposure in areas where many live. 2 The Philippines has the most expensive electricity rates in Southeast Asia.

Figure 1: Location of coal plants in Luzon, Visayas, and Mindanao

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approved permits, which could potentially leave approximately 9 GW of coal projects in the pipeline, according to the Global Energy Monitor (2020). While it reflects a welcomed change in policy and is set to reduce stranded asset risk and investments in unprofitable projects, the health, climate and economic impacts of coal should be an important consideration in reforming the energy supply mix moving forward.

This study is an analysis of the air quality, toxic deposition, and health impacts of coal plants in the Philippines. To date, it is the most detailed bottom-up research to model and predict air pollution impacts from coal power, modeling both emissions from the existing coal fleet and under a scenario where the 9 GW of coal projects excluded from the new DOE moratorium are built. It collects best available emissions data plant-by-plant, using detailed atmospheric modeling and epidemiological data to account for the spread of pollution and toxic metals, the corresponding population exposure to air pollution, and the associated health impacts. Finally, the study highlights the cumulative health impacts and hidden economic costs from air pollution on the Philippine population as a result of continued reliance on coal.

Major Air Pollutants and Related Literature

Coal-burning emits toxic air pollutants and chemicals such as NOx, SO2, particulate matter (PM), and mercury (Hg), which also contribute to the formation of ozone (O3) in the atmosphere. These pollutants spread and cause a range of harmful health effects, even in small doses and especially to vulnerable groups like pregnant women, the elderly and those with pre-existing health conditions.

Long-term exposure to NOx leads to inflammation of the airways, which can exacerbate symptoms of asthma, chronic obstructive pulmonary disorder (COPD), and other respiratory diseases in both adults and children (WHO 2000). Chronic health impacts associated with SO2 include: dementia, fertility problems, reduced cognitive ability, increased risk of heart and lung disease, and premature death (Wu et al. 2015; Carré et al. 2017; Shebab & Pope 2019; Cohen et al. 2017).

PM2.5 — the most dangerous pollutant to human health due to its small size and ability to travel over great distances — is inhaled deep into the lungs and bloodstream, causing damage to the entire human biological system. Formed during initial combustion and as a secondary pollutant when SO2 and NOx react with chemicals in the atmosphere, PM2.5 is linked to chronic respiratory and cardiovascular disease, decreased lung function, and premature mortality (Guaita et al. 2011).

A health impact assessment conducted in 27 Asian cities, including 12 from the Philippines, focused on the relation of long-term exposure to concentration levels of PM10 and PM2.5 and the number of lung cancer cases and cardiopulmonary cases leading to mortality. It found that reducing exposure to high levels of these pollutants would lead to a significantly lower number of deaths from such diseases (Yorifuji et al. 2015). The World Bank Environmental Health report (2007) on the Philippines showed that for 2004, 4.9% of reported diseases, including pneumonia and cardiovascular diseases in adults, were attributed to air pollution. PM10 and PM2.5 levels exceed standards in cities such as

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Quezon City and Valenzuela with the population in these cities being at a higher risk of asthma or bronchitis.

While the literature focusing specifically on air pollution-related health impacts of coal power in the Philippines is scarce, a study dating back to when the 2001 Electric Power Industry Reform Act (EPIRA) was enacted singled out local coal as a particularly polluting energy source. Using a damage-function approach, the study also showed that four power plants accounted for over 40% of PM10 and NO2 emissions from power generation in Luzon and in the country as a whole in 2000. The impact area was limited to a 30-km radius from the location of each plant, but the total population at risk was estimated at 1.75 million spread over 53 municipalities (Orbetta et al. 2003). Notably, the country’s coal power generation has doubled since then (Figure 2).

A more recent study estimated the burden of diseases caused by air pollution of current and projected (2030) coal use, implementing a plant-specific inventory of SO2, NOx and PM2.5 coal emissions in the Philippines and other Southeast Asian countries (Koplitz et al. 2017). It estimated that deaths due to coal emissions were rising, and would increase to 1,500 in the Philippines by 2030. Pollutant levels of SO2 and NOx were projected to more than double in the country in 2030 from 2011 levels. The study used 2011 as the base year and many of the projects included in its future projections have hence been either realized or cancelled.

The elevated health risk of air pollution is linked to increased hospitalizations, disability, loss of ability to work, and early death, which are costs borne by the public and other sectors beyond energy with ramifications for the Philippine economy. Given the close proximity of many of these plants to bodies of water and forest land, deposition of mercury, acid rain, and fly ash are also a threat to the surrounding ecosystem. This, in turn, also increases the risk to community livelihoods. Another study modelled the health benefits that could be reached by reducing air pollution in the country, and found that the implementation of air standards and a reduction in air pollution could lead to decreases in the population mortality, the number of cases of chronic bronchitis, and respiratory symptoms (Elca 2005). Prioritizing better policy in relation to air quality, energy and health is especially urgent as the country deals with the COVID-19 pandemic and new research shows an association between past and current air pollution exposure to increased vulnerability to COVID-19 (CREA 2020).

Coal, COVID-19 and Economic Recovery

The novel COVID-19 pandemic has claimed more than 8,200 lives in the Philippines and infected more than half a million people (as of December 3, 2020), causing public health, social, and economic stress to the country and the world. While the risk factors of the virus are still under investigation, there is emerging research that indicates that environmental factors like air pollution may have contributed to increased susceptibility to the virus.

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A study on Chinese patients found that the risk of severe symptoms requiring intensive care or ventilation, and the risk of death was elevated by 170% for people with chronic respiratory disease, by 60% for people with hypertension or diabetes, by 250% for people with cancer, and by 80% for people with any of the pre-existing conditions listed above (Guan et al. 2020). This impact is highlighted by a recent peer-reviewed study of COVID-19 deaths in the U.S, which indicated greater risk of death from the virus in counties with higher historical average PM2.5 pollution levels (Wu et al. 2020). A published paper in the Netherlands also found a similar relation between small increases in long-term exposure to NO2, SO2 and PM2.5 and worsened COVID impacts (Cole et al. 2020).

Multiple studies suggest that elevated levels of air pollution increase the likelihood of being infected by viruses that cause respiratory illness. A study of more than 100,000 patients in the U.S. found that short-term spikes in PM2.5 air pollution increased acute lower respiratory infections requiring medical care, in both children and adults (Horne et al. 2018). The same effect has been observed during smog episodes in Beijing (Feng et al. 2016; Liang et al. 2014), Rome (Nenna et al. 2017) and Brunei (Yadav et al. 2003).

The suggested mechanisms that link air pollution to virus transmission and likelihood of infection include damage to airways and epithelial barriers (Donaldson & Tran 2002; Li et al. 1996; Lee et al. 2014), and pollution acting as “condensation nuclei” that virus droplets can attach themselves to and be transported in the air (Lee et al. 2014). While these mechanisms are not certain, early experimental evidence suggests that COVID-19 may remain viable as an aerosol for a number of hours (Doremalen 2020).

All efforts to mitigate and control current and future risk factors need to be examined, especially in recovery efforts. The energy sector is one that merits close inspection, especially as the 2020 pandemic and record-breaking climate disasters expose serious weaknesses in the Philippines’ reliance on coal. For example, as electricity demand fell across the country during the first 3-month period of enhanced community quarantine (ECQ), consumers were faced with soaring electricity bills — a consequence of baseload inflexibility in a system where virtually all additional costs incurred by operators can be passed on to consumers (Ahmed 2020). While this drop in electricity demand may have decreased CFPP generation and emissions, the improvements in air pollution will be short-lived. While polluting sectors like transport and energy remain fossil fuel-heavy, air pollution will be an enduring hazard to health and climate. Power market reform and renewable energy deployment shows great potential to lower electricity prices, bring in billions in RE investment, and increase power system resilience for Filipinos (Ahmed 2020) This must be expedited alongside economic recovery that deprioritizes coal.

Controlling and Monitoring Air Pollution from Coal The Philippines’ electricity grid is divided according to its main island groups: Luzon, Visayas, and Mindanao (Figure 1). Of the three, Luzon has approximately 6,900 MW of installed coal capacity, which generated 34% of the country’s gross power generation in 2019. Visayas has almost 1,400 MW

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and Mindanao has just over 2,000 MW (DOE 2020a). The Philippine coal fleet is relatively young. More than half of the current capacity — about 5,500 MW — were built and commercialized in the last decade and the capacity could grow steeply with the additional 32 proposed units (Figure 2).

Plans to build more baseload power are still reflected in the latest draft of the Philippine Energy Plan (PEP) 2018–2040, which is currently under review. Under a reference scenario, renewable energy has a 42% share in total generation capacity in 2040 while coal’s share in installed capacity remains at 34% (PEP, p. 30). Under a clean energy scenario, coal’s share falls to 19% but even then 9 GW of additional projects would have to be built to meet the projected rise in demand. To make the halt in new coal projects more than a temporary respite, the moratorium should be accompanied by an expedited roll-out of renewable energy with the prioritization of existing policies and mechanisms such as the Energy Efficiency Act and the Renewable Portfolio Standard.

Figure 2. Coal power expansion of operating and proposed plants over the years

SOURCE: Global Coal Plant Tracker & DOE, CREA Visualization

With existing plans to continue and expand installed coal power generation, it is a major concern that emission standards for both existing and new coal power sources remain weak. The current Philippine standards fall far behind those of China, the EU and India, and are almost triple that of its close neighbor, Indonesia (Figure 3). While the Department of Environment and Natural Resources (DENR) through the Environmental Management Bureau (EMB) is required to conduct a review of standards for stationary sources every two years and revise for further improvement, the National Emission Standards for Source Specific Air Pollutants (NESSAP) have not been updated since they were set in the Clean Air Act of 1999 (RA 8749, 2000). Similarly, the National Ambient Air Quality Guideline Values (NAAQGV) are meant to control the accumulation of ambient pollution from all sources. These also remain at much higher levels than those recommended by the WHO despite the increasing pollution from all anthropogenic sources (See Appendix, Table A-1).

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The lack of available data on air pollution owing to gaps and inadequacies in data monitoring, collection and reporting — be it ambient or point source — contribute to this problem and make it difficult to track the full extent of the air pollution problem and its impacts on the country.

Figure 3. Emission standards for coal-fired power plants in various countries

Oversight in monitoring and lax compliance extend to operating plants as well. For example, continuous emissions monitoring (CEMs) from the stacks is required by the DENR. However, the data collected in each individual plant is publicly inaccessible, which makes it difficult to monitor and verify whether emissions control technology is functioning at full capacity, or to track emission violations with reasonable response times.

Availability and integrity of data is also a challenge in other areas that are meant to control air pollution from the source. Environmental Impact Assessments (EIA), which are required for the feasibility and evaluation of coal proposals, were used as the main source of information for plant-specific emissions data in this study. However, the researchers found that many of these documents lacked emissions values (most failing to provide mercury emissions altogether) or contained errors in the calculations of pollutant emissions. Some EIAs declared emissions far below the industry standard that they seemed unlikely given the plants’ capacities and emission control technology. Other EIAs simply declared the plant would meet emission standards, which do little to reasonably control emissions as they are set far too high (Figure 3). Some EIAs include baseline air quality modeling of the impact of the plants on surrounding areas, but have no information on emissions values released from the plant stack.

These reports and claims, and the lax standards and estimates of plant emissions, should flag that dangerous levels of emissions may have escaped the notice of regulators. Massive amounts of pollution and toxic deposition from CFPPs and its impacts even in areas kilometers away will only increase with additional coal and unchecked regulations.

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Methodology This study follows CREA’s impact pathway approach (IPA) to quantify the health impacts of coal power generation in the Philippines. It is carried out by (1) developing a plant-by-plant inventory of emissions; (2) estimating pollution dispersion from CFPPs through atmospheric modeling; (3) quantifying air pollution health impacts resulting from changes in ambient concentration; and (4) valuing health impacts in monetary terms using a cost of illness method.

The analysis was carried out in the R data analysis software, in a global spatial grid with 1x1km resolution, with health impacts calculated for each grid cell. All datasets were aggregated or interpolated to this resolution as required.

Emissions A plant-by-plant emissions inventory was used as input data to the CALPUFF model, and accounted for plant-specific technology, location, and capacity for every operating coal plant in the country and 9GW of proposed plants (Tables 1 and 2). It also uses information on stack height and diameter, as well as flue gas release velocity and temperature, to account for plume release height and thermal rise of pollutants.

The list of coal plants was taken from the Global Coal Plant Tracker (GCPT) and cross-verified with the Department of Energy (DOE). For the future scenario, only plants that GCPT classified as in construction, permitting, or pre-permitting were included.3 To estimate emissions rates, data collection followed a hierarchy of sources, based on availability (preferred options listed first):

● Plant-specific, officially reported measured emission data ● Plant-specific emission data based on operator self-reporting ● Plant-specific emission limits or flue gas pollutant concentrations from emission permits or

Environmental Impact Assessment (EIA) documents ● Emission limits based on national emission standards or other regulation ● Average emission factors based on officially reported national total emissions from the

power sector or from coal-fired power plants ● Plant-specific information on installed combustion and emission control technology and

coal type, combined with technology-specific emission factors

When information on a plant’s emissions values were lacking or unavailable, it was generalized using average values for projects with similar capacity and combustion technology. We assumed that such plants were in compliance with the country’s emissions standards and operating emission controls technology at full capacity. Information on installed emission controls were also collected from these primary documents, as well as the S&P (2020) World Electric Power Plants database.

3 Projects without a target commercial operation date, as of August 2020 — equivalent to 2,805 MW in Luzon, 600 MW in Visayas, and 928 MW in Mindanao — were not included in the modelling (DOE 2020b), many of these plants are also considered under the moratorium on greenfield projects

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Stack height as well as flue gas exit velocity and temperature were imputed from available data following the same approach. When missing, the stack diameter was calculated based on estimated total flue gas volume flow and velocity.

Emission mass rates (E) were calculated based on the flue gas concentrations (FGC) as:

𝐸𝑝 = 𝐹𝐺𝐶𝑝 ×𝐶𝐴𝑃𝐸𝐹𝐹 × 𝑆𝐹𝐺𝑉

where CAP is the generating capacity of the plant (MW), EFF is the thermal efficiency, and SFGV is the specific flue gas volume (Nm3/GJ), and p refers to a specific pollutant. If unavailable, thermal efficiencies of 37%, 41% and 43% were assumed for subcritical, supercritical and ultra-supercritical plants, respectively, in line with industry standards.

Data on the type of coal used was also collected per plant, the SFGV for Semirara coal was estimated at 339 Nm3/GJ, based on the “Characterization of Torrefied Biomass from Sugarcane (Saccharum officinarum) Bagasse Blended with Semirara Coal” (Lomeda-De Mesa et al. 2019), and 359 Nm3/GJ for coal exported from Indonesia (Kalimantan) from USGS World Coal Quality Inventory, based on the formula for the ultimate analysis of coal in European standard EN 12952-15 (p. 85, formula A.5N). When the source of coal was unknown, the IFC default value of 350 Nm3/GJ was used.

Separately, mercury emissions were projected using the formula: EHg = CC x MC x (1 - CE),

where CC is the coal consumption mass rate of the plant, MC is the mercury content of the coal, and CE is the capture efficiency. Since over 84% of imported coal is from Indonesia and consumed by the power sector (DOE 2019), we used the UNEP (2017) default value for Indonesian coal, 0.11 ppm Hg, and default capture efficiencies for different coal types and emission control technologies.

When the 2019 coal consumption numbers of the plant were unavailable, coal consumption was estimated as:

CC = CAP / EFF / NCV, where NCV is the net calorific value of the coal, taken as 5,500 kcal/kg for imported bituminous, 5,000 kcal/kg for imported sub-bituminous and 3,900 kcal/kg for Semirara coal.For toxic deposition from main boilers of the power plants, 30% of emitted fly ash was assumed to be PM2.5, and 37.5% PM10, in line with the U.S. EPA (1998) AP-42 default value for electrostatic precipitators (ESP). Mercury deposition was modeled for three different types of mercury: elemental, reactive gaseous and particle-bound mercury, with the speciation between the three types calculated based on Lee et al. (2006).

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Table 1. Estimated air pollution emissions from operating CFPPs used for CALPUFF Modeling (See Appendix for expanded input data and sources)

Facility Name Lat Long Units Capacity (MW) Emission volumes, estimated (t/a)

Hg (kg/a) SO2 NOx PM

LUZON GRID

Anda 15.23627 120.6098 1 84 498.0 350.3 69.3 8.3

SLPGC Calaca 13.93263 120.7897 2 300 2,147.5 1,510.6 681.7 37.1

SCPC Calaca 13.93263 120.7897 2 600 7,759.2 3,879.6 517.3 69.2

Limay Greenfield 14.52041 120.6027 3 450 2,173.2 1,857.4 63.6 59.3

APEC Mabalacat Mill 15.2356 120.6106 1 52 308.3 216.8 42.9 5.1

GNPower Mariveles 14.42517 120.537 2 650 15,693.0 2,625.0 261.0 84.7

Masinloc 15.56406 119.9231 2 674 4245.7 2,773.6 740.6 120.1

Pagbilao 13.8932 121.745 3 1184 21,759.4 11,645.2 695.9 261.3

SLTEC Puting Bato 13.9193 120.8261 2 270 907.5 638.4 126.2 15.1

Quezon Power 14.2296 121.7558 1 511 6,600.0 5,844.0 416.6 107.1

SBPL Quezon 14.2296 121.7558 1 500 324.0 2,892.0 503.1 60.4

Sual 16.125 120.1006 1 1294 5,322.6 9,446.1 421.1 252.2

United Pulp & Paper Co. (UPPC) 14.89535 120.7717 1 30 177.8 125.1 24.7 3.0

Petron RSFFB 14.52885 120.6004 4 140 3,211.6 1,649.3 115.4 29.7

VISAYAS GRID

Palm Concepcion Power Corporation (PCPC) 11.18758 123.1207 1 135 820.0 576.8 114.0 13.4

Panay Energy Development Corporation 10.72444 122.5958 3 317.4 1,615.5 1,136.4 224.7 18.4

Therma Visayas Energy (TVI) 10.34972 123.6036 2 340 2,038.2 1,433.7 283.5 34.0

Cebu Energy Development Corporation (CEDC) 10.38727 123.6398 4 328 1,843.5 1,296.8 256.4 25.7

Toledo Power Corporation - 1A Expansion 10.3874 123.6424 1 83.7 496.2 349.0 69.0 5.6

Toledo Power Corporation-Sangi 10.3874 123.6424 2 66.3 393.0 276.5 54.7 4.5

KSPC (Naga-2) 10.21755 123.7605 2 206 2,031.4 1,457.6 155.1 45.2

MINDANAO GRID

GNPower Kauswagan 8.18691 124.1155 3 450 12,662.8 6,502.8 455.1 117.0

FDC Misamis 8.56096 124.7478 3 405 2,400.9 1,688.8 333.9 40.1

SMC Malita Davao 6.39351 125.6168 2 300 1,348.8 741.6 35.9 29.7

Therma South 6.9644 125.4797 2 300 1,494.3 1,051.2 207.8 24.9

Mindanao Coal STEAG 8.5725 124.7573 2 232 1,409.8 2,502.1 274.5 42.3

SM200 (SEC Kamanga) 5.8686 125.0798 2 237 1,404.9 988.3 195.4 23.4

Minergy Power Corporation (MPC) Balingasag 8.766 124.767 3 165 978.1 688.0 136.0 16.3

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Table 2. Planned CFPPs4 in the Philippines with emissions limits used in CREA calculations (See Appendix for expanded input data and sources)

Plant

Lat

Long

Capacity (MW)

Status

Emission volumes, estimated (t/a)

SO2 NOx PM Hg (kg/a)

GNPower Dinginin Unit 1 14.4246 120.541 668 Construction 7941.1 4159.6 421.7 59.6

Masinloc Unit 3 15.56384 119.9192 335 Construction 444.2 461.0 106.4 29.9

Limay Unit 45 14.52041 120.6027 150 Construction 889.2 625.5 104.9 14.8

GNPower Kauswagan Unit 4 8.18691 124.1155 135 Construction 1778.4 931.5 94.4 28.6

Palm Concepcion Unit 2 11.18758 123.1207 135 Construction 800.3 562.9 94.4 13.4

Atimonan One Energy Unit 1 & 2 14.0569 121.8617 1200 Permitted 1894.3 7124.8 359.3 102.1

La Union Unit 1 & 2 16.83588 120.3425 670 Permitted 2275.7 5120.3 568.9 59.8

GNPower Dinginin Unit 2 14.4246 120.541 668 Permitted 2268.9 4159.6 421.7 59.6

Tagkawayan Unit 1 14.03727 122.3083 1200 Pre-permit 3886.3 7124.8 722.4 102.1

SMC Freeport 14.43671 120.5006 1200 Pre-permit 3010.0 2625.0 261.0 150.5

Sual KEPCO Unit 1 & 26 16.091 120.096 1000 Pre-permit 3238.5 3238.5 485.8 85.1

SRPGC Calaca Unit 5 13.93263 120.7897 350 Pre-permit 2074.8 1459.5 244.9 34.6

SRPGC Calaca Unit 6 13.93263 120.7897 350 Pre-permit 2074.8 1459.5 244.9 34.6

H&WB PCB Unit 1 14.3378 122.6735 350 Pre-permit 1188.8 2179.4 221.0 31.2

H&WB PCB Unit 2 14.3378 122.6735 350 Pre-permit 1188.8 2179.4 221.0 31.2

Masinloc Unit 4 15.56384 119.9192 335 Pre-permit 492.2 510.8 117.9 33.1

SMC Ibabang 13.904 121.758 710 Pre-permit 2411.5 5425.9 602.9 63.4

Zamboanga 6.985512 121.9348 105 Pre-permit 622.4 437.8 73.5 10.4

Atmospheric Modeling The CALPUFF modeling system was used to predict the contribution of CFPPs to ambient air pollutant concentrations at every modeled “receptor” location. These results were processed to extract the annual mean, 24-hour maximum and 1-hour maximum pollutant concentrations for 2019. CALPUFF is the most widely used, industry standard emission dispersion model for long-range air quality impacts of point sources. It is able to model the formation of secondary sulfate and nitrate particles from coal power SO2 and NOx emissions, and able to model long-range transport. These two mechanisms are responsible for more than 90% of the population exposure to PM2.5 and of the health impacts of CFPP emissions; their exclusion would mean omitting the majority of the health impact. By accounting for transport, chemical transformation and deposition of pollutants, it provides short and long-range impacts caused by coal plant emissions.

4 This list excludes plants that GCPT has classified as announced, shelved, or cancelled. Projects without a target commercial operation date, as of August 2020 - equivalent to 2,805 MW in Luzon, 600 MW in Visayas, and 928 MW in Mindanao - were not included in the modelling https://www.doe.gov.ph/list-existing-power-plants?q=private-sector-initiated-power-projects 5 Since the time of modeling, the Limay plant has been constructed and is now operating. 6 Since the time of modeling, KEPCO announced that this plant would be converted to gas-fired technology.

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Meteorological data used for the simulations were generated with the WRF model, with the simulations commissioned from METEOSIM, a leading data provider. The entire country was covered by a 9x9km grid, with all power plant sites in Luzon, Mindanao and Visayas covered by three nested 3x3 km grids (Figure 1). Land-use data were obtained from the European Space Agency (2018) and terrain elevation data were obtained from NASA Shuttle Radar Topography Mission (SRTM) high resolution datasets (Farr et al. 2007).

Because CALPUFF cannot be used to model the effects of acid gas emissions on ground-level ozone formation, the results from the Geos-Chem model for operating coal power plants in the Philippines (Koplitz et al. 2017) were used to assess the impacts on ozone levels. The gridded concentration results were scaled to the updated NOx emissions inventory.

Deposition results were differentiated by land-use type using the European Space Agency global land-use map for the year 2015 at a 300 m resolution (ESA 2018). Land-use codes 10-30 were mapped as cropland; codes 50-100 were mapped as forest and code 170 as mangrove. Monthly average backgrounds for NH3, O3 and H2O2 concentrations were also obtained from the Geos-Chem model results (Koplitz et al. 2017) and were inputted into the CALPUFF chemistry module (ISORROPIA/RIVAD). Sites of protected areas analysed are sourced from the World Database on Protected Areas (2020).

Health Impact Assessment The health impact assessment methodology is adapted from CREA’s “Quantifying the Economic Costs of Air Pollution from Fossil Fuels” (Myllyvirta 2020).

The calculation of health impacts follows a standard epidemiological calculation:

∆𝑐𝑎𝑠𝑒𝑠 = 𝑃𝑂𝑃 × ∑𝑎𝑔𝑒 [𝐹𝑟𝑎𝑐 𝑎𝑔𝑒 × 𝐼𝑛𝑐𝑖𝑑𝑒𝑛𝑐𝑒 𝑎𝑔𝑒 × (1 − 𝑅𝑅(𝑐 𝑏𝑎𝑠𝑒+𝛥𝑐 𝑐𝑜𝑎𝑙,𝑎𝑔𝑒)𝑅𝑅(𝑐 𝑏𝑎𝑠𝑒,𝑎𝑔𝑒)

)],

where POP is the total population in the grid location, age is the analysed age group (in the case of age-dependent concentration-response functions, a 5-year age segment; in other cases, the total age range to which the function is applicable), Fracage is the fraction of the population belonging to the analysed age group, Incidence is the baseline incidence of the analysed health condition, c is pollutant concentration, with cbase referring to the baseline concentration and Δccoal is the concentration attributed to coal-fired power plants, with the contribution from existing plants having a negative sign (subtracted from the baseline concentration) and projected future incremental concentration from new plants a positive sign (added on top of the baseline concentration). RR(c, age) is the function giving the risk ratio of the analysed health outcome at the given concentration, for the given age group, compared with clean air.

In the case of a log-linear, non-age specific concentration-response function, the RR function becomes:

𝑅𝑅(𝑐) = 𝑅𝑅 0

𝑐−𝑐 0𝛥𝑐 0 𝑤ℎ𝑒𝑛 𝑐 > 𝑐 0, 1 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒,

15

where RR0 is the risk ratio found in epidemiological research, Δc0 is the concentration change that RR0 refers to, and c0 is the assumed no-harm concentration (generally, the lowest concentration found in the study data).

Data on total population and population age structure of the Philippines was taken from Global Burden of Disease results for 2019 (IHME 2020), which collects and aggregates data from health departments of national governments. The spatial distribution of population was based on Gridded Population of the World v4 (CIESIN 2018).

Adult deaths and years of life lost from PM2.5 exposure were estimated using the risk functions developed by Burnett et al. (2018), as applied by Lelieveld et al. (2019). Deaths from long-term NO2 exposure were quantified following the recommendations of the WHO HRAPIE project (WHO 2013). Because of substantial population exposure to SO2 in the atmospheric modeling results, a concentration-response function for all-cause mortality from SO2 was included based on Krewski et al. (2009).

Deaths of small children from lower respiratory infections linked to PM2.5 pollution was assessed using the PM2.5 concentration results from Lelieveld et al. (2019) and the GBD risk function for lower respiratory diseases (IHME 2020).

For all mortality results, the baseline death rates and years of life lost for the Philippines were taken from the GBD project 2019 (IHME 2020). The baseline concentrations of PM2.5 and NO2 were taken from van Donkelaar et al. (2016) and Larkin et al. (2017), respectively.

Future health impacts projects account for projected population growth on the national level, and for mortality impacts, using projected changes in age-specific death rates based on the UNDP (2019) medium variant. Use of age-specific death rates captures the impact of expected improvements in population health status and health services, which results in lower mortality for children, while increasing the susceptibility of the adult population to non-communicable diseases associated with air pollution.

Table 3. Input parameters and data used in estimating physical health impacts Age group

Effect Pollutant Concentration response function*

Concentration change

No-risk threshold

Reference Incidence data

1-18 New asthma cases NO2 1.26 (1.10 - 1.37)

10 ppb 2 ppb Achakulwisut et al 2019

Achakulwisut et al 2019

0-17 Asthma emergency room visits

PM2.5 1.03 (1.01–1.04) 10 ug/m3 6 ug/m3 Zheng et al 2015

Anenberg et al 2018

0-17 Asthma emergency room visits

O3 1.02 (1.01–1.02) 10 ppb 2 ppb Zheng et al 2015

Anenberg et al 2018

18-99 Asthma emergency room visits

PM2.5 1.02 (1.02–1.03) 10 ug/m3 6 ug/m3 Zheng et al 2015

Anenberg et al 2018

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18-99 Asthma emergency room visits

O3 1.02 (1.01–1.02) 10 ppb 2 ppb Zheng et al 2015

Anenberg et al 2018

Newborn Preterm birth PM2.5 1.15 (1.07, 1.16) 10 ug/m3 8.8 ug/m3 Trasande et al 2016

Chawanpaiboon et al 2019

0-4 Deaths from lower respiratory infections

PM2.5 GBD 2019 5.8 ug/m3 GBD 2019 GBD 2019

25-99 Premature deaths from non-communicable diseases

PM2.5 Burnett et al 2018

2.4 ug/m3 Burnett et al 2018

GBD 2019

30-99 Premature deaths from COPD

O3 1.12 (1.08, 1.16) 10 ppb 35 ppb Malley et al 2017

GBD 2019

25-99 Disability caused by diabetes, stroke and chronic respiratory disease

PM2.5 GBD 2019 2.4 ug/m3 Burnett et al 2018

GBD 2019

30-99 Premature deaths NO2 1.037 (1.021-1.080)

10 ug/m3 20 ug/m3 WHO HRAPIE 2013

GBD 2019

30-99 Premature deaths SO2 1.020 (1.014-1.026)

5 ppb 0.02ppb Krewski et al 2009

GBD 2019

*Numeric values in the “Concentration-response function” refer to relative risk corresponding to the increase in concentrations given in the “concentration change” column. Literature references indicate the use of a non-linear concentration-response function. No-harm threshold refers to a concentration below which health impact is not quantified, generally due to lack of evidence in the studies from which the function is based on.

Economic Valuation

The economic losses from air pollution-related deaths were assessed based on the resulting reduction in life expectancy, with one year of life lost valued at EUR 56,000 (US$ 69,400 at 2005 exchange rate) in the European Union, following the EEA (2014) cost-benefit methodology. This was adjusted by purchasing power adjusted Gross National Income (GNI PPP) for the Philippines, with an elasticity of 0.9 as recommended by the OECD (2012). The estimates for economic costs per case of each health outcome for the Philippines were calculated using 2018 GDP per capita, GNI per capita, purchasing power and exchange rate data from the World Bank (undated), assuming that the costs are proportional to either GNI or GDP as indicated:

[cost per case in the Philippines] = [cost at reference income level] x [Philippine income level] / [reference income level]

Table 4. Economic cost of different health outcomes

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Effect Valuation Currency Unit Year Source Adjustment Reference income level

Elasticity

New asthma cases 496,000 GBP case 2018 Birchby 2019 GNI PPP UK 1

Asthma emergency room visits

844 USD visit 2010 Brandt et al 2012

GDP PPP California 1

Preterm birth 321,989 USD birth 2010 Trasande et al 2016

GDP PPP U.S. 1

Disability 62,800 GBP year lived with disability

2018 Birchby 2019 GNI PPP UK 1

Premature deaths 56,000 EUR lost life year 2005 EEA 2014 GNI PPP EU 0.9

Work absence 130 EUR work day 2005 EEA 2014 GDP PPP EU 1

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Results: Air Quality and Toxic Deposition Impacts

Air Quality Figures 4 to 6 present the annual mean concentrations of dangerous pollutants attributed to emissions from CFPPs. All the pollutants significantly increase in concentration with the addition of the proposed CFPPS. Current pollutant emissions from coal plants would expose an estimated 300,000 people to 24-hour average SO2 concentrations that exceed WHO guidelines and another 1,000 people to 1-hour average NO2 concentration exceedances. With additional coal capacity, these numbers more than double to over 800,000 people exposed to 24-hour average SO2 exceedances and 3,000 to 1-hour average NO2 exceedances, which in turn also increases air pollution related health impacts from these pollutants.

Figure 4. Annual mean PM2.5 concentration from operating (left) and operating and proposed (right) CFPPs (includes both primary & secondary particles)

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Figure 5. Annual Mean SO2 Concentration from Operating (left) and Operating and Proposed (right) CFPPS

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Figure 6. Annual Mean NO2 Concentration from Operating (left) and Operating and Proposed (right) CFPPS

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Toxic Deposition We estimate that currently operating coal plants in the Philippines emit approximately 1,500 kg of mercury per year, of which approximately 800 kg is deposited onto land and ocean within the modeling domain, according to the results. Annually, 56 kg are deposited in protected areas7 around the country. Of the total projected annual mercury deposition, about 27% occurs on cropland, 13% on forest and scrubland, 53% into ocean and freshwater ecosystems, and 7% into built-up areas. The proposed plants will increase projected mercury deposition within the modeling domain to 1,300 kg annually with a similar split by land use. Annual deposition in protected areas increases by 33%.

Figure 7. Annual total mercury deposition

This is of concern because mercury deposition rates as low as 125 mg/ha per year can lead to the accumulation of unsafe levels of mercury in fish (Swain et al. 1992). Modeling results show that the highest mercury deposition rates for protected areas are fisheries and marine sanctuaries (Appendix Table A-2). This has ramifications to consumers and the supply chain, in addition to dangerous exposure and health impacts that are not included in this study but may have major implications,

7 The boundaries of protected areas were taken from UNEP-WCMC and IUCN (2020).

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especially for fishing and marine communities living in and around these areas. The operating CFPPs in the Philippines expose an estimated 6.7 million people over an area of 13,540 km2 to mercury deposition rates that exceed this 125 mg/ha annual threshold. The proposed plants would increase exposure to a projected 9.2 million people over 21,500 km2.

On cropland, the absorption of errant mercury also affects agriculture. For example, studies show that rice paddies — a major source of food and agriculture in the country — can convert deposited inorganic mercury into methylmercury, which is easily taken up by the rice plant (see e.g. Zhang et al. 2010). The deposition of mercury has a dual impact on water bodies — direct deposition occurs when particles fall into water and additional accumulation happens when mercury deposited on land is washed downstream by rain and runoff into streams, rivers, lakes, wetlands, estuaries and oceans (UNEP 2018). The latter is not accounted for in this research; it is likely that total mercury levels are higher than the rates determined by air deposition alone.

In addition to mercury, an estimated 7,300 tons of fly ash containing toxic and radioactive heavy metals are emitted from coal plants into the air every year, of which approximately 4,700 tons is estimated to be deposited within the modeling domain. Of that 4,700 tons, over 51% of is deposited into the ocean and 32% on cropland. These emissions do not include intentional discharges or possible leakage or accidental discharge from coal ash ponds, coal ash landfills, coal storage and other sources. Such episodes are difficult to project, but could add significantly to the heavy metal load into the environment.

Figure 8. Annual total fly ash deposition

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Furthermore, acid deposition - a secondary compound formed when gases such as SO2 react with other atmospheric chemicals - is estimated at 77,000 tons per year. This could increase to almost 119,000 tons with the proposed coal units. These compounds can be carried over great distances and deposited in wet form as rain or fog, or can simply settle out of the air as dy particles or gases (dry deposition). The 40% of deposition that occurs over cropland and forests could deplete soils of essential nutrients. Acidic particles can also contribute to the corrosion of metals and to the deterioration of buildings, infrastructure, and other structures of cultural significance, resulting in depreciation of the value of these objects to society.

A cluster of coal-fired power plants in the southern part of Luzon is the biggest hotspot of acid deposition in the country, blanketing Batangas and Laguna in acid deposition (Figure 9). The addition of large capacity plants will see this area extend further west, all the way to Paracale, Camarines Norte. A few kilometers away, acid deposition from the Bataan plants are observed over Manila Bay. This hotspot spans over approximately 33 protected areas, many of which are forestlands.

Figure 9. Annual total acid deposition over the Luzon hotspot

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The Hidden Cost of Coal-fired Power Pollution from coal-fired power plants, particularly PM2.5, travels in the atmosphere over long distances and contributes to ambient air pollution, even in areas hundreds of kilometers away (WHO). While many power plants are not built in close proximity to cities, their emissions nevertheless contribute to air pollution in these high-density areas, increasing the risk of death and illness from both acute and chronic diseases. With additional planned capacity, the total number of premature deaths attributed to coal pollution increases by approximately 60% from 632 to 1,009 deaths annually (Table 5). The burden of disease from PM2.5-related ischaemic heart disease and lower respiratory infection, as well as NO2, are the highest of these avoidable deaths.

These numbers are impacts we are able to quantify with the latest science and research, however there are more - like the contribution of toxic metal deposition presented in the previous section - that are excluded from these estimates. Our modeling also assumes that emissions from all coal plants do not exceed the regulated standards and that emissions controls are used all year round. This indicates that the health impacts of air pollution from coal are potentially higher if such considerations are accounted for.

Table 5. Estimated current and future annual health impacts associated with emissions from coal-fired power plants

Pollutant Cause Operating Plants

95% confidence interval

Operating & Proposed Plants

95% confidence interval

PM2.5 COPD 18 (7- 36) 29 (11 - 57)

diabetes 33 (9 - 49) 47 (13 - 71)

ischaemic heart disease 122 (89- 160) 190 (138 - 248)

lower respiratory infections 97 (33 - 177) 158 (54 - 287)

lower respiratory infections in children 9 (5 - 14) 14 (8 - 21)

lung cancer 13 (6 - 23) 21 (10 - 37)

stroke 51 (19 - 93) 82 (31 - 150)

O3 COPD 53 (29 - 89) 83 (45 - 141)

NO2 All Causes 206 (99 - 510) 341 (164 - 847)

SO2 All Causes 59 (35 - 89) 93 (55 - 141)

Total Premature Deaths 632 (373 - 1,131) 1,009 (594 - 1,819)

Because of the health burden, CFPP air pollution has significant economic and social costs – externalities that are not reflected in the balance sheets of owners and operators nor on the market prices of energy production and consumption. Such costs are instead borne by the public and sectors like healthcare. These reflected in the costs of hospitalization and additional need for

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medical assistance and care, the societal cost of premature deaths, and the loss of productivity associated with sickness, disability, and/or time given to caregiving. Currently, air pollution from CFPPs is estimated to cost the country PHP 8.5 billion annually (Table 6). If all new proposed coal makes it onto the grid, this increases to nearly PHP 14 billion.

Table 6. Estimated number of air pollution-related cases and associated cost from current and proposed coal-fired power plants annually

Operating plants Operating & proposed plants

Outcome Number of Cases Cost in PHP Million Number of Cases Cost in PHP Million

Work absence (sick leave days) 148,933

(126,704 - 171,012) 143

(122 - 165) 242,575

(206,374 - 278,528) 234

(199 - 268)

New cases of asthma in children 1,337 (324 - 2,838) - 2,115 (513 - 4,486) -

Children suffering from asthma due to pollution exposure

5,907 (1,631 - 11,700) 78 (22 - 155)

9,341 (2,581 - 18,493) 124 (34 - 245)

Asthma emergency room visits, adults and children

2,074 (1,280 - 2,667)

6 (3.5 - 7) 3,314 (2,045 - 4,263)

10 (6 - 12)

Preterm births 238 (115 - 253) 285 (138 - 303) 411 (199 - 437) 494 (239 - 524)

Total years lived with disability

COPD 188 (70 - 345) 272 (78 - 495)

299 (111 - 548) 409 (120 - 753)

Diabetes 401 (90 - 689) 566 (133 - 990)

Stroke 184 (60 - 372) 289 (97 - 601)

Total Years of Life Lost

COPD 1,061 (572 - 1,763) 7,763 (4,530 - 13,965)

1,683 (908 - 2,793) 12,387 (7,212 - 22,439)

Lower respiratory infections in children 788 (417 - 1,197) 1,226 (672 - 1,839)

Other non-communicable diseases and lower respiratory infections

14,574 (8,593 - 26,584)

23,296 (13,676 - 42,838)

Total Economic Cost 8,549 (4,892 - 15,091) 13,656 (7,810 - 24,242)

Breakdown by Province Luzon bears almost 68% of estimated premature deaths linked to air pollution, as the region has the highest MW capacity of coal installed. This is followed by Mindanao at 19% and Visayas at 13%. With the additional planned capacity, the disparity between the three main island groups widens. Luzon’s burden could increase to 77% of the 1,009 estimated premature deaths, as the greatest

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number of coal plants are proposed here. Since no additional coal capacity is currently under construction or in the permitting phase in Visayas, the region sees the lowest additional health impacts as a result of coal expansion.

With the existing operating fleet, the provinces with the highest health impacts from coal are also among the most populous (Table 7). Under the current scenario, cases of premature death normalized against population density are highest in Batangas, followed by Misamis Oriental and Pangasinan. Health impacts in Metro Manila, and will more than double with the number of coal plants planned within 300 km from the capital city; a similar spike in cases of premature deaths due to coal pollution can be observed in Bataan and La Union, where major MW-capacity projects are proposed to be built. With the additional coal capacity planned, provinces that are at risk of more than a 50% increase in premature deaths linked to air pollution also increase Zambales, Lanao del Norte, Pangasinan, Cavita, Tarlac, and Pampanga.

Table 7. Provinces with number of cases of premature deaths and cost per capita annually as a result of exposure to CFPP emissions (arranged by highest number of premature deaths per million people with current operating capacity)

Current capacity Current & proposed capacity % Increase in cases due to additional MW capacity Province

Cases per 1 million people

Cost per capita in PHP

Cases per 1 million people

Cost per capita in PHP

Batangas 18.70 259.67 25.82 357.54 38%

Misamis Oriental 17.84 247.31 19.33 268.90 8%

Pangasinan 12.54 163.37 22.03 289.30 76%

Laguna 12.12 164.08 16.90 227.63 39%

Quezon 11.14 149.24 16.32 218.89 46%

Zambales 11.08 151.89 17.45 240.28 57%

Bataan 9.35 129.07 19.02 262.30 103%

Lanao del Norte 9.16 127.81 15.98 222.01 74%

Cavite 8.98 122.20 14.66 199.27 63%

Cebu 8.61 116.88 8.65 117.46 --

Tarlac 7.76 103.79 12.11 162.32 56%

Metropolitan Manila 7.65 101.00 16.03 214.41 109%

Bulacan 7.59 100.95 15.35 207.05 102%

La Union 7.13 96.00 22.20 299.60 211%

Pampanga 6.92 92.41 11.08 148.58 60%

Many of these provinces have renewable energy potential that could avoid increased health impacts and costs in the near future, as they coincide with national renewable energy zones (NREZ). These are areas that the DOE, together with USAID and the National Renewable Energy Laboratory (NREL),

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have identified to have high-quality variable RE resources (accounting for technology cost and levelized cost of energy), suitable topography and land-use designations, and proximity to grid transmission.

For example, the Masinloc power complex in Zambales and the Sual power stations in Pangasinan are found in CREZ L1 and L5, where total solar and wind potential are 1,067 MW and 1,040 MW, respectively. Pre-permit plants like the H&WB PCB and Quezon Tagkawayan power stations fall within the L10-12 zones, which cumulatively have over 4GW of RE potential. Currently operating Pagbilao and under-development SMC Ibabang and Atimonan in Quezon are close to these zones. Other major provinces like Misamis Oriental, Bataan, Cebu and Metro Manila are just outside existing NREZ areas.

These zones were selected based on both the quality of available resources and the ease of their development. As the grid evolves and more RE and storage projects come online as the technologies continue to mature, these provinces could benefit from RE generated electricity with better access or local development. With the DOE’s moratorium on greenfield coal projects, RE investments are estimated to attract USD 30 Billion (IEEFA 2020) - all the more reason to avoid sunken and externalized costs of CFPPs, and further transition to cleaner sources of electricity.

Cumulative Health and Economic Impact of CFPPs Without stronger emissions standards to regulate emissions from the stack (Figure 3), existing coal plants will continue to be a public health hazard. Over the next decade, the cumulative impact of air pollution from plants operating today will average nearly 7,000 avoidable deaths and cost the economy and Philippine population nearly PHP 103 billion (Tables 8 and 9). This impact does not yet account for the contribution of pollution if any of the proposed CFPPs currently exempted from the moratorium are built under these existing standards.

Table 8. Cumulative number of cases and economic cost of operating plants from 2021-2030

Cause Cumulative cases, 2021-2030 95% confidence interval

COPD 863 (431 - 1,530)

Diabetes 404 (111 - 604)

Ischaemic heart disease 1,492 (1,087 - 1,951)

Lower respiratory infections 1,191 (408 - 2,167)

Lower respiratory infections in children 78 (42 - 119)

Lung cancer 164 (77 - 286)

Stroke 621 (234 - 1,132)

Total Premature Deaths 6,978 (4,154 - 12,571)

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Table 9. Estimated cumulative economic cost of air pollution of operating CFPPs from 2021-2030 Outcome Cases with operating plants Cost in PHP Million

Work absence (sick leave days) 1,729,851 (1,471,659 - 1,986,294) 1,668 (1,419 - 1,915)

New cases of asthma in children 15,533 (3,765 - 32,968) --

Children suffering from asthma due to pollution exposure, increased prevalence 68,614 (18,949 - 135,896) 909 (251 - 1,800)

Asthma emergency room visits 24,094 (14,868 - 30,976) 69 (43 - 89)

Preterm births 2,418 (1,171 - 2,567) 2,899 (1,404 - 3,079)

Total years lived with disability

COPD 2,305 (854 - 4,224) 812 (301 - 1,487)

Diabetes 4,910 (1,099 - 8,432) 1,729 (387 - 2,970)

Stroke 2,254 (736 - 4,547) 794 (259 - 1,601)

Total Years of Life Lost

COPD 12,978 (7,000 - 21,558) 6,135 (3,309 - 10,191)

Lower respiratory infection, children 6,888 (3,646 - 10,460) 3,256 (1,724 - 4,945)

Other non-communicable diseases and lower respiratory infections

178,239 (105,095 - 325,117) 84,255 (49,679 - 153,685)

Total Cumulative Economic Cost, current operating plants 2021-2030 102,526 (58,776 - 181,762)

The increase in health and economic impacts from additional CFPPs can be avoided completely with the cancellation of pipeline projects. The moratorium on greenfield coal projects puts into question which units will ultimately be commercialized. However, in a scenario where all 9 GW of the proposed CFPPs are commercialized by 2024, in order to account for the required installed generating coal capacity outlined in the current draft of PEP 2018-2040, these new plants would cause approximately 26,300 premature deaths over 40 years. The cumulative economic cost over such time is estimated at PHP 372 billion (Tables 10 and 11).

Table 10. Cumulative premature deaths due to air pollution from proposed CFPPs over 40 years

Cause Cumulative premature deaths 95% confidence interval

COPD 3,183 (1,593 - 5,637)

Diabetes 1,040 (331 - 1,660)

Ischaemic heart disease 5,236 (3,815 - 6,850)

Lower respiratory infections 4,656 (1,594 - 8,483)

Lower respiratory infections in children 121 (70 - 177)

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Lung cancer 612 (286 - 1,069)

Stroke 2,408 (907 - 4,390)

Total Premature Deaths 26,303 (15,478 - 48,413)

Table 11. Cumulative health and economic cost of air pollution from proposed CFPPs over 40 years Outcome Cumulative Cases, proposed plants Cumulative Cost in PHP Million

Work absence (sick leave days) 5,829,506 (4,959,759 - 6,693,237) 5,646 (4,817 - 6,475)

New cases of asthma in children 48,579 (11,796 - 102,996) --

Children suffering from asthma due to pollution exposure, increased prevalence

214,590 (59,365 - 424,563) 2,849 (777 - 5,646)

Asthma emergency room visits 77,485 (47,781 - 99,778) 207 (155 - 311)

Preterm births 6,587 (3,193 - 6,994) 7,925 (3,833 - 8,391)

Total years lived with disability

COPD 8,504 (3,149 - 15,592) 3,004 (1,088 - 5,490)

Diabetes 12,641 (3,287 - 23,180) 4,454 (1,140 - 8,184)

Stroke 8,736 (2,852 - 17,635) 3,056 (984 - 6,216)

Total Years of Life Lost

COPD 47,863 (25,864 - 79,371) 22,635 (12,224 - 37,500)

Lower respiratory infections in children 10,609 (6,176 - 15,562) 5,024 (2,901 - 7,355)

Non-communicable diseases and lower respiratory infections

671,754 (391,472 - 1,251,947) 317,561 (185,067 - 591,821)

Total Cumulative Economic Cost, proposed plants over 40 years 372,311 (213,020 - 677,314)

The cause-specific mortality for PM2.5 in the above tables does not sum up exactly to the estimated total from all causes. This is because the total mortality was estimated using the Burnett et al. (2018) risk function for non-communicable diseases and lower respiratory infections — rather than as a sum of the cause-specific estimates — and can include effects on other causes besides the identified ones. This approach is more robust for estimating total mortality, while the cause-specific estimates give an indication of the breakdown into main causes. Additionally, there are many health impacts as a result of air pollution from coal that we are not able to quantify and more still that we are not able to economically value and include in this study.

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Recommendations Economic development has been linked to an increase in fossil fuel consumption for energy but this is no longer the case as coal is met with mounting climate and resilience risks and financial uncertainty, especially with the rapid development of cost competitive renewable energy. The health, environment and economic costs revealed in this paper can help inform policymakers and regulators to assess existing coal projects and the increasing issue of air pollution. Prioritizing and protecting the right to clean air will require policies to regulate and monitor both ambient air quality and pollution from the major sources, including but not limited to coal. Considerable progress has been made, but will need to be accelerated given the impact on Philippine citizens and ecosystems today. Moving forward, this should include:

● Stringent emission standards should be developed and enforced to control PM, SO2, NO2 and Hg pollution emissions of coal power plants. Philippine emissions standards for stationary sources are some of the weakest in Southeast Asia, and can be raised to match those in the EU and China, and those being implemented in India. Standards should be set at a level that would require Best Available Technology to control emissions from the stack.

● Continuous emissions monitoring (CEMs) from all operating and proposed plants should be required and the data made available to the public to ensure compliance. Such monitoring capabilities should cover the range of dangerous pollutant emissions. Penalties for non-compliance should also be properly enforced to reflect externalities.

● The transition to renewable energy sources should be prioritized, and any addition of coal into the country’s energy mix should internalize environmental and social externalities. Application of the moratorium should be expanded to cover plants in the permit and pre-permit phases, especially in areas with identified NREZ. Plants in the early stages of construction should be halted and converted. Existing policy to increase the uptake of renewables and improve energy efficiency, including mechanisms in the Renewable Portfolio Standard and Green Energy Option Program, and under the Renewable Energy Act and the Energy Efficiency Act, should be prioritized.

● The review and update of current air pollution standards under the Clean Air Act of 1999 must be expedited and implemented. Under this, the government must strengthen emission standards for all sources to reduce air pollution emissions and its impacts, and ensure stronger compliance and implementation.

● Monitoring and publishing of ambient air quality in near-real time should be prioritized to tackle and understand the full scope of the air pollution problem. There is a critical need to expand ground-based air quality monitoring in Philippine cities, and make it available to the public. Collecting and analysing local air quality data can allow deeper understanding and analysis of local pollution and its sources to ensure effective measures to tackle them. This data is also vital for assessing the effectiveness of interventions, both in terms of public health benefits and economic impact.

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Appendix Table A-1. National Ambient Air Quality Guideline Values (NAAQGV) versus World Health Organization Ambient Air Standard Guidelines

Pollutant NAAQGV in μg/m3 WHO in μg/m3

PM10 Annual Mean 60 20

24-hr Mean 150 50

PM2.5 (Since January 2016)

Annual Mean 25 10

24-hr Mean 50 25

SO2

Annual Mean 80 -

24-hr Mean 180 20

NO2 Annual Mean 150 40

24-hr Mean 150 -

1-hr Mean - 200

O3 8-hr Mean 60 100

Source: EMB (Implementing Rules of RA 8749) & WHO Guidelines 2018

Table A-2. Protected Areas with some of the highest mercury and fly ash deposition rates from current operating CFPPs

Area

Mercury deposition total, kg/year

Mercury deposition, mg/km2/year

Fly ash deposition, kg/year

Fly ash deposition, kg/km2/year

Manyukos Island Marine Sanctuary 13.0 178,063.59 65,666.59 899.54

Mansalay (B. Del Mundo) Fish Sanctuary 11.0 2,058.93 126,695.16 23.74

Baganga Protected Terrestrial & Watershed 3.1 4,978.75 40,178.51 63.88

Ayoke Island Marine 2.8 1,327.18 45,751.17 21.78

Burgos Fish Sanctuary 2.5 20,507.21 7,366.89 61.39

Torrijos Watershed Forest Reserve 1.9 1,220.15 6,576.04 4.13

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Uba Marine Protected Areas 1.9 1,124.52 13,690.88 8.00

Marine Sancturary 1.3 4,431.71 12,688.19 44.06

Maliput Rawis Lagbak Fish Sanctuary 0.9 8,411.97 8,026.96 72.31

Bilangbilangan Marine Sanctuary 0.7 1,254.06 2,019.02 3.66

Table A-3. Default values for emissions limits based on installed technology (in mg/Nm3)

Technology SOx NOx PM

Atmospheric circulating-fluidized-bed (ACFB) 315 222 N/A

Compliance fuel, no scrubbers (CF) 211 N/A N/A

Low NOx Burners (LNB) N/A 399 N/A

Low NOx Burners (LNB), FW Controlled Flow design N/A 399 N/A

SEMIDRY flue gas desulfurization (FGD) 417 N/A N/A

Seawater Flue Gas Desulfurization (SWFGD) 225 N/A N/A

Wet lime FGD scrubber (WL) 225 N/A N/A

Wet limestone FGD scrubber, FGD 225 N/A N/A

Overall 211 144 44

New Plant 200 366.7 37.2

Table A-4. Default Values for estimated emissions volumes, according to type of coal used

Coal type

kcal

Mercury Control efficiency

Speciation

RGM Hg0 Hgp

With FGD installed

Sub-bituminous 5000 65% 24.0% 74.2% 1.8%

Lignite 3863 40% 50.0% 49.5% 0.5%

Bituminous 5500 20% 24.0% 74.2% 1.8%

Without FGD installed

Sub-bituminous 5000 25% 54.0% 43.9% 2.1%

Lignite 3863 10% 65.0% 34.6% 0.4%

Bituminous 5500 2% 54.0% 43.9% 2.1%

Table A-5. CALPUFF Input Data for operating plants in the Philippines

Installed Capacity

(MW)

Emissions values, imputed, mg/Nm3

Emissions volumes, estimate, t/a

Stack Propertiesi

Plant Latitude Longitude Combustion Technology

SO2 NOx PM SO2 NOx PM Hg

(kg/a)

Stack height

(m)

Temp (C)

Diameter Emission Control

Technology

Anda / Bundagul 15.23627 120.6098 84 CFB 315 222 44 498 350.3 69.3 8.3 150 120 1.5 ACFB, FGD

Calaca U3-4 / SLPGCii 13.93263 120.7897 300 CFB 315 222 100 2147.5 1510.6 681.7 37.1 150 120 2.9 ACFB, ESP, FGD

Calaca U1-2 / SCPCiii 13.93263 120.7897 600 Subcritical 1500 750 100 7759.2 3879.6 517.3 69.2 150 140 4.1 CF, ESP

Limay Greenfield iv 14.52041 120.6027 600 CFB 187.9 160.6 5.5 2173.2 1857.4 63.6 59.3 150 120 4.2 ACFB, ESP, FGD

Mabalacat Mill / APEC 15.2356 120.6106 52 Subcritical 315 222 44 308.3 216.8 42.9 5.1 150 60 1.2 ACFB, ESP, FGD

GNPower Mariveles v, 14.42517 120.537 650 Subcritical 1219 626 44 15693 2625 261 84.7 100 140 4.2 CF, ESP

Masinloc U1-2vi 15.56406 119.9231 674 Subcritical 292.4 191.0 51.0 4245.7 2773.6 740.6 120.1 150 140 4.4 CF, ESP

Pagbilao U1-3 vii 13.8932 121.745 1184 Subcritical 938.0 502.0 30.0 21759.4 11645.2 695.9 261.3 150 140 5.8 CF (Unit 3: FGD,

MHPS), ESP

Puting Bato / SLTEC U1-2viii 13.91933 120.8261 270 Subcritical 315 222 44 907.5 638.4 126.2 15.1 150 60 2.8 ACFB, FGD

Quezon Power U1ix 14.2296 121.7558 511 Subcritical 416.6 361.0 44 6600 5844 416.6 107.1 150 140 3.8 Semidry, LNB, FW,

CSE

SBPL / Quezon U2x 14.2296 121.7558 500 Supercritical 225 626 44 324 2892 503.1 60.4 150 60 3.6 SWFGD, ESP, FGD

Sual U1-2 xi 16.125 120.1006 1294 Subcritical 225 399.3 17.8 5322.6 9446.1 421.1 252.2 220 60 6.1 WLST, FGD, LNB,

CSE

United Pulp & Paper Co. 14.89535 120.7717 30 Unknown 315 222 44 177.8 125.1 24.7 3 150 60 0.9 ACFB, FGD

Petron 14.52885 120.6004 140 Subcritical 1219 626 44 3211.6 1649.3 115.4 29.7 150 140 2.0 --

Balingasagxii 8.766 124.767 165 CFB 315 222 44 978.1 688 136 16.3 150 120 2.2 ACFB, ESP, FGD

Davao San Miguel xiii 6.39351 125.6168 300 CFB 233.2 128.2 6.2 1348.8 741.6 35.9 29.7 150 120 2.9 ACFB, ESP, FGD

Therma South Davao xiv 6.964444 125.4797 300 CFB 315 222 44 1494.3 1051.2 207.8 24.9 150 120 2.9 ACFB, ESP, FGD

SM200 (SEC Kamanga) 5.86868 125.0798 237 Subcritical 315 222 44 1404.9 988.3 195.4 23.4 150 60 2.6 ACFB, ESP, FGD

Kauswagan xv, xvi 8.18691 124.1155 552 Subcritical 1219 626 44 12662.8 6502.8 455.1 117 150 140 3.9 CF, ESP

Mindanao STEAGxvii 8.5725 124.7573 232 Subcritical 225 399 44 1409.8 2502.1 274.5 42.3 150 60 2.6 WL, LNB, BH, FGD

FDC Misamisxviii 8.560966 124.7478 405 Subcritical 315 222 44 2400.9 1688.8 333.9 40.1 150 60 3.4 ACFB, ESP, FGD

PCPC 11.18758 123.1207 135 CFB 315 222 44 820 576.8 114 13.4 150 120 2.0 ACFB, FGD

PEDC / Panayxix 10.72444 122.5958 317.4 CFB 315 222 44 1615.5 1136.4 224.7 18.4 150 120 3.0 ACFB, FGD, ESP

Therma Visayas Energy xx 10.34972 123.6036 340 CFB 315 222 44 2038.2 1433.7 283.5 34 150 120 3.1 ACFB, FGD, ESP

Table A-5. CALPUFF Input Data for planned coal-fired power plants in the Philippines

Plant Lat Long Capacity

(MW) Combustion Technology

Emissions values, imputed, mg/NM3

Emissions volumes, estimate, t/a Stack Properties

SO2 NOx PM SO2 NOx PM Hg

(kg/a) Stack

height (m) Temp Diameter Emissions

Control

GNPower Dinginin Unit 1 14.4246 120.541 668 Supercritical 700.0 367 37.2 7941.1 4159.6 421.7 59.6 150 60 4.1 New, CF, ESP

Masinloc Unit 3xxv 15.5638 119.919 335 Supercritical 78.1 81.0 18.7 444.2 461.0 106.4 29.9 150 60 2.9 SWFCD, New,

ESP

Limay Unit 4 14.52041 120.6027 150 CFB 315 222 37.2 889.2 625.5 104.9 14.8 150 120 2.1 FGD, ACFB, ESP

GNPower Kauswagan Unit 4 8.18691 124.1155 135 Subcritical 700.0 367 37.2 1778.4 931.5 94.4 28.6 150 140 1.9 CF, New ESP

Palm Concepcion Unit 2 11.18758 123.1207 135 CFB 315 222 37.2 800.3 562.9 94.4 13.4 150 120 1.9 ACFB, ESP

Atimonan One Energy Unit 1 &

2xxvi 14.0569 121.8617 1200 Ultra-super 225 367 37.2 1894.3 7124.8 359.3 102.1 250 60 5.4 SWFCD, New

La Union Unit 1 & 2 16.83588 120.3425 670 Supercritical 200.0 450.0 50.0 2275.7 5120.3 568.9 59.8 180 60 4.1 SWFGD, LNB,

ESP

GNPower Dinginin Unit 2 14.4246 120.541 668 Supercritical 200 367 37.2 2268.9 4159.6 421.7 59.6 150 60 4.1 FGD, New

Tagkawayan Unit 1 14.03727 122.3083 1200 Ultra-super 200 367 37.2 3886.3 7124.8 722.4 102.1 150 60 5.4 FGD, New

SMC Mariveles Freeportxxvii 14.43671 120.5006 1200 CFB 315 222 37.2 3010.0 2625.0 261.0 150.5 100 120 5.8 FGD, ACFB, ESP

Sual KEPCO Unit 1 & 2xxviii 16.091 120.096 1000 Ultra-super 200.0 200.0 30.0 3238.5 3238.5 485.8 85.1 150 60 4.9 SWFCD, SCR,

New

SRPGC Calaca Unit 5 13.93263 120.7897 350 Subcritical 315 222 37.2 2074.8 1459.5 244.9 34.6 150 60 3.1 FGD, ACFB, New

SRPGC Calaca Unit 6 13.93263 120.7897 350 Subcritical 315 222 37.2 2074.8 1459.5 244.9 34.6 150 60 3.1 FGD, ACFB, New

H&WB PCB Unit 1xxix 14.3378 122.6735 350 Supercritical 200 367 37.2 1188.8 2179.4 221.0 31.2 150 60 3.0 FGD, New

H&WB PCB Unit 2xxx 14.3378 122.6735 350 Supercritical 200 367 37.2 1188.8 2179.4 221.0 31.2 150 60 3.0 FGD, New

Masinloc Unit 4xxxi 15.56384 119.9192 335 Subcritical 78.1 81.0 18.7 492.2 510.8 117.9 33.1 150 60 3.1 FGD. New

SMC Ibabang xxxii 13.904 121.758 710 Supercritical 200 450 50 2411.5 5425.9 602.9 63.4 150 60 4.2 FGD. LNB, ESP

Zamboanga 6.985512 121.9348 105 Subcritical 315 222 37.2 622.4 437.8 73.5 10.4 150 60 1.7 ACFB, New

Toledo Power Complex U5-8 /

CEDC xxi 10.38727 123.6398 328 Subcritical 315 222 44 1843.5 1296.8 256.4 25.7 150 60 3.0 ACFB, FGD, ESP

TPC 1Axxii 10.38742 123.64244 83.7 CFB 315 222 44 496.2 349 69 5.6 150 120 1.5 ACFB, FGD, ESP

TPC Sangixxiii 10.38742 123.64244 66.3 Subcritical 315 222 44 393 276.5 54.7 4.5 150 60 1.4 ACFB, FGD, ESP

Naga-2/ KSPCxxiv 10.21755 123.76058 206 Subcritical 524.0 376.0 40.0 2031.4 1457.6 155.1 45.2 150 60 2.4 ACFB, FGD

i Flue gas exit velocity for all plants was assumed to be 15 mph ii Seminara Mining and Power Corporation. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 141 of the Corporation Code of the Philippines.

SEC FORM 17-A. December 31, 2019. http://www.semiraramining.com/uploads/files/SEC%2017%20-%20A/2019_SEC%20Form%2017-A%20COMPLETE.pdf iii Ibid. iv EIA (not available online); SMC Global Power Holdings Corp. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 177 of the Revised Corporation

Code of the Philippines. 2019 Annual Report (SEC Form 17-A). December 31, 2019. https://smcglobalpower.com.ph/files/reports/17-

A/SEC_17A_for_2019_as_of_12April20_Final_Signed_vWebsite1.pdf v Mariveles Power Generation Corporation 2019. Environmental Impact Statement. Proposed Mariveles Coal Power Plant Project. http://eia.emb.gov.ph/wp-

content/uploads/2019/01/01.03.2019.EIS_.MCPP-1.pdf; Aboitiz Power Corporation.

Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 141 of the Corporation Code of the Philippines. SEC FORM 17-A. December 31, 2019.

https://aboitizpower.com/wp-content/uploads/AP-SEC-FORM-17-A-2019-Annual-Report-Full-Report.pdf vi SMC Global Power Holdings Corp. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 177 of the Revised Corporation Code of the Philippines.

2019 Annual Report (SEC Form 17-A). December 31, 2019. https://smcglobalpower.com.ph/files/reports/17-A/SEC_17A_for_2019_as_of_12April20_Final_Signed_vWebsite1.pdf vii EIA; Aboitiz Power Corporation. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 141 of the Corporation Code of the Philippines. SEC FORM

17-A. December 31, 2019. https://aboitizpower.com/wp-content/uploads/AP-SEC-FORM-17-A-2019-Annual-Report-Full-Report.pdf viii EIA (not available online); AC Energy Philippines. 2019 Integrated Report. https://online.pubhtml5.com/aowj/gyhj/#p=18 ix Electricity Generating Public Company Limited. Sustainability Report 2019. https://www.egco.com/uploads/finder/files/EIA/QPL/EIA_QPL.pdf; Electricity Generating Public

Company Limited. Annual Report 2019. https://investor.egco.com/misc/ar/20200312-egco-ar2019-en-02.pdf x Manila Electric Company and Subsidiaries. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 177 of the Revised Corporation Code of the

Philippines. 2019 Annual Report (SEC Form 17-A). December 31, 2019. https://www.pds.com.ph/wp-content/uploads/2020/04/Disclosure-No.-1135-2020-Annual-Report-for-

Fiscal-Year-Ended-December-31-2019-SEC-Form-17-A.pdf; Electricity Generating Public Company Limited. Sustainability Report 2019.

https://investor.egco.com/misc/sd/20200312-egco-sd2019-en-01.pdf xi SMC Global Power Holdings Corp. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 177 of the Revised Corporation Code of the Philippines.

2019 Annual Report (SEC Form 17-A). December 31, 2019. https://smcglobalpower.com.ph/files/reports/17-A/SEC_17A_for_2019_as_of_12April20_Final_Signed_vWebsite1.pdf xii https://minergy.com.ph/business-units/coal-business-unit/ xiii SMC Global Power Holdings Corp. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 177 of the Revised Corporation Code of the Philippines.

2019 Annual Report (SEC Form 17-A). December 31, 2019. https://smcglobalpower.com.ph/files/reports/17-A/SEC_17A_for_2019_as_of_12April20_Final_Signed_vWebsite1.pdf xiv Aboitiz Power Corporation. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 141 of the Corporation Code of the Philippines. SEC FORM 17-

A. December 31, 2019. https://aboitizpower.com/wp-content/uploads/AP-SEC-FORM-17-A-2019-Annual-Report-Full-Report.pdf xv EIA (unavailable online) xvi AC Energy. GNPower Kauswagan. https://www.acenergy.com.ph/gnpower-kauswagan/ xvii Aboitiz Power Corporation. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 141 of the Corporation Code of the Philippines. SEC FORM 17-

A. December 31, 2019. https://aboitizpower.com/wp-content/uploads/AP-SEC-FORM-17-A-2019-Annual-Report-Full-Report.pdf xviii FDC Misamis Power Corporation. Project Description Report (PDR). 2019. http://eia.emb.gov.ph/wp-content/uploads/2019/09/FDCUI-EXPANSION-PDR-090919-rev-1.pdf xix Global Business Power Corp 2019 Annual Report. https://gbp.com.ph/annual-report/ xx Aboitiz Power Corporation. Annual Report Pursuant to Section 17 of the Securities Regulation Code and Section 141 of the Corporation Code of the Philippines. SEC FORM 17-A.

December 31, 2019. https://aboitizpower.com/wp-content/uploads/AP-SEC-FORM-17-A-2019-Annual-Report-Full-Report.pdf xxi DOE. List of Existing Power Plants, as of 31 December 2016. Department of Energy.

https://www.doe.gov.ph/sites/default/files/pdf/electric_power/private_sector_initiated_power_projects/2016_existing_powerplants_visayas_as_of_dec31.pdf xxii DOE. List of Existing Power Plants, as of 31 December 2016. Department of Energy.

https://www.doe.gov.ph/sites/default/files/pdf/electric_power/private_sector_initiated_power_projects/2016_existing_powerplants_visayas_as_of_dec31.pdf

xxiii DOE. List of Existing Power Plants, as of 31 December 2016. Department of Energy.

https://www.doe.gov.ph/sites/default/files/pdf/electric_power/private_sector_initiated_power_projects/2016_existing_powerplants_visayas_as_of_dec31.pdf xxiv http://www.kepcophilippines.com/ xxv SMC Global Power Holdings Corporation. Offering 2020. https://links.sgx.com/FileOpen/SMC%20Global%20Power%20Holdings%20Corp.%20-

%20Offering%20Circular%20(2020.01.14).ashx?App=Prospectus&FileID=41885 xxvi EIA 2020 (unavailable online) xxvii Mariveles Power Generation Corporation (MPGC). Environmental Impact Statement (EIS) Summary for the Public for the Proposed Mariveles Coal Power Plant Project.

October 2018. http://eia.emb.gov.ph/wp-content/uploads/2018/10/2018.10.25.EIS_MPGC_ESP-English.pdf xxviii KEPCO Philippines, INC. (“KEPHILCO”). Proposed 2 x 500MW Pangasinan Coal Power Plant Project. 2019.

http://eia.emb.gov.ph/wp-content/uploads/2019/01/PROPOSED-2-X-500-MW-Pangasinan-Coal-Power-Plant-Project-PCPPP-PDR.pdf xxix 2 x 350 MW Supercritical PCB Power Plant in Jose Panganiban, Camarines Norte Province. http://hwbasiapacific.net/2-x-350-mw-coal-fired-power-plant-in-jose-panganiban-

camarines-norte-province/ xxx Ibid. xxxi SMC Global Power Holdings Corporation. Offering 2020. https://links.sgx.com/FileOpen/SMC%20Global%20Power%20Holdings%20Corp.%20-

%20Offering%20Circular%20(2020.01.14).ashx?App=Prospectus&FileID=41885 xxxii Lumiere Energy Technologies Inc. Project Description for Scoping. February 2020. http://eia.emb.gov.ph/wp-content/uploads/2020/03/PDS_LETI_14FEB2020.pdf

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