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Urban air pollution in developing countries:

Case study of Metro Manila, Philippines

Simonas Kecorius*, Honey Dawn Alas, Leizel Madueño, Thomas Müller, Wolfram Birmili, Edgar Vallar, James Bernard B. Simpas, Everlyn Gayle T. Tamayo, Mylene G. Cayetano, and Alfred Wiedensohler

Honey Dawn C. AlasPresenting author

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Motivation

Source: http://www.ecoclimax.com

Source: WHO (2016, September 27)

air‐pollution‐related deaths occur in low‐and middle‐income countries92%

deaths occurSoutheast Asia and  Western Pacific regions

2 out of 3

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Motivation

PHILIPPINES1990 2013

Annual PM2.5 (µg/m³) 9.1 8.6

DEATHS 38 676 57 403

IMPROVED45

62

25 21 4

8WORSEN

25 out of 140 countries reported a decrease in PM2.5 from 1990‐2013 but an increase in total deaths due to air 

pollution

21 of those are DEVELOPING COUNTRIES

PM 2.5 and air pollution‐related deaths

Source: The Cost of Air Pollution, The World Bank and Institute for Health Metrics and Evaluation, 2016

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Motivation

Source: Hopke et al., 2008

Mean Annual PM2.5 Mean Annual BC

Annual limit24 hr limit

2nd highest BC concentration

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Motivation and Objectives

• To determine soot properties and its sources in a megacity 

• To determine the spatial and temporal variability of soot in a megacity

• To estimate excess lifetime cancer risk of the populace in megacities

Source: WHO (2016, September 27)Source: The Cost of Air Pollution, The World Bank and Institute for Health Metrics and Evaluation, 2016

• Health effect associated with short‐term exposure to BC is more robust than PM

BC is a better indicator of harmful particulate substances from combustion sources than undifferentiated PM mass

(WHO, 2012)

Cardio‐vascular diseases

toxic materials and heavy metals

carcinogenic components

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Study Domain: Metro Manila, Philippines

12.8 Million

20,785 persons/km2 

2.3 Million

METRO MANILA(17 Cities)

LAGUNABAY

MANILABAY

CHINA

INDONESIAMALAYSIA

JAPAN

PHILIPPINE SEA

90% of emissions Mobile sources

Source: DENR ‐ EMBSource: PSA

Source: LTOTraffic Reduction Policies: Number Coding Scheme ‐ ex. ABC 001 – Mondays Truck Ban Policy – No trucks: 6 – 9AM and 5 – 9PM

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The Campaign 

Manila Aerosol Characterization Experiment – MACE 2015FIXED: 

Urban background station“UBS”

SEMI‐FIXED: Subsequent Roadside Sites

“RS”

MOBILE: Fixed Route 

TROPOS Aerosol Container

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MACE 2015 Experiment Design – Measurement Sites

LAGUNABAY

MANILABAY

TAFT RS

KAT RSMO UBS

MO ‐ Urban background station (MO UBS)

PERIOD: April 1 – June 5, 2015

MO UBS

MAIN ROADSCAMPUS

KAT RS

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Roadside Sites

LAGUNABAY

MANILABAY

TAFT RS

KAT RSMO UBS

KAT RS TAFT RS

PERIOD: April 1 – May 5• 8‐lane road• West: buildings• East: university campuses 

• MO UBS

PERIOD: May 17 – June 10• 4 to 6 – lane road• STREET CANYON + railway

MACE 2015 Experiment Design – Measurement Sites

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MACE 2015 Experiment Design ‐ Instrumentation

PARAMETER INSTRUMENT UBS AEROSOLCONTAINER

Black carbon (eBC)

MAAPMulti‐angle absorptionphotometer 

Mixing state of refractory particles

TROPOS ‐ VTDMAVolatility Tandem Differential Mobility Analyzer

Particle number concentration

TROPOS ‐MPSSMobility Particle Size Spectrometer

PAHs 5‐Stage Cascade BernerImpactor

eBC ‐ equivalent black carbon 

Soot  ‐ carbonaceous particles formed from incomplete combustion

PAH  ‐ polycyclic aromatic hydrocarbons‐ carcinogenic component of soot

BaP ‐ benzo(a)pyrene‐ carcinogenic to  humans  

BaPeq ‐ benzo(a)pyrene equivalent‐ relative carcinogenic potency of PAH compounds in reference to BaP

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MACE 2015 Experiment Design – Instrumentation

PARAMETER INSTRUMENT

Black carbon (eBC)

AE51microAeth

Particle Number Concentration

MCPCCondensationParticle Counter

Particle Number Size Distribution

TSI OPSS 3330Optical Particle Size Spectrometer

Position GPS

TROPOS AEROSOL BACKPACK v.1

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RESULTS

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Results: eBC in Metro Manila

NUMBER CODING

NUMBER CODING

TRUCK BANWINDOW

UBS: boundary layer 

height

RS: ??

Roadside:Vehicle emissions Traffic 

scheme/policy Vehicle fleetStreet configuration

TRUCK BANWINDOW

TRUCK BANWINDOW

Time (hour)

TRAFFIC REDUCING SCHEMES IMPROVEMENT IN AIR QUALITY

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Results: eBC in Metro Manila vs Other Cities 

Hung et al., 2014Cao et al., 2009

Song et al., 2013

Lee et al., 2007

Part et al., 2002

Part et al., 2002

TROPOS

This Study

Asia

Europe

Daily mean BC

BC in µg/m³

eBC mass concentration is up to 30 times higher than in 

Western countries

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Results: Soot Size distribution – number and volume

~15 000 #/cm3

Soot:~70% of PM1

Soot particle NUMBER concentration Soot particle VOLUME concentration

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Results: Size Segregated Emission factors

Vehicle Type PMsoot g/km PNsoot, #/km

LDV + PC 0.027 9.79•1013

Jeepneys 1.618 1.15•1015

Average fleet 0.313 3.29•1014

• Jeepney emit 12 times more soot in terms of number and 60 times more in terms ofmass when compared to LDV 94% of total roadside soot mass

JeepneyLight duty vehicles (LDV + passenger cars)

80% 20%

• Jeepney showed 2000 times higher emission when compared to EURO 6standard for diesel in Europe.

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Results: PAHs and Excess Lifetime Cancer Risk 

Total PAH in PM10  = 119 ± 26 ng/m3 

ULTRAFINE

34%

28%21%

12%

5%

FINE

COARSE

WHO Guideline for BaPeq  = 1 ng/m3 

Carcinogenic PAH38%

Total Benzo(a)pyrene equivalent Metro Manila12.7 ng/m3 

Additional 1,100 cases of lung cancer for every 1 million people exposed!

(Accepted: 1 in 1 million)

Benzo(a)pyrene (BaP)

Source: WHO Regional Office for Europe 2010. WHO Guidelines for Indoor Air Quality: Selected Pollutants. Tamayo et al., In Progress

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Results: Spatial Distribution of eBC

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Results: Spatial Distribution of eBC

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Results: Who are at risk?

pedestriansdrivers and conductors

(and their families)

vendors traffic enforcersstreet sweepers

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Summary and Conclusions

• Soot dominates PM1 by ~70% and the main sources are the old jeepneys despite beingonly 20% of the total vehicle number.

• eBC has high temporal and spatial variabilities with hotspots found Jeepney terminals,traffic light areas or major intersections, and street canyons affecting people stayingthere for HOURS (traffic enforcers, street vendors, drivers, and conductors)

• The estimated excess lifetime lung cancer risk is 1000 times higher than the acceptednorms.

In developing regions, where primary pollutant emission dominates, PM10 and PM2.5 must be supplemented by additional parameters such as eBC mass concentration or soot particle number size distribution, in order to better 

evaluate possible adverse health effects and create effective mitigation policies.

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Honey Dawn C. Alasalas@tropos.de

Simonas Kecorius  kecorius@tropos.deLeizel Madueño leizel.imperial@yahoo.comEverlyn Tamayo gayle.tamayo@gmail.com

THANK YOUSALAMAT

DANKEAČIŪ

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Size‐segregated emission factors

OSPMOperational Street Pollution Model 

surface topography

roof top wind speed and direction

particulate pollutant concentration

Emission factors

Inverse Modelling Approach

Background concentration

Traffic countsVehicle fleet

(Berkowicz et al., 2000)

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Excess lifetime cancer risk calculation

PAH  FactorAce 0.001Phe 0.001An 0.01Ft 0.001Py 0.001B[a]an 0.1Chy 0.01B[b]ft 0.1B[k]ft 0.1B[a]py 1D[a,h]an 1B[g,h,i]pe 0.01

Table 5. TEFs for PAHs (Nisbet and Lagoy, 1992)

Toxic equivalence factors (TEFs) approach• relative carcinogenic potency

Concentration of each PAH compound

BaP equivalent of each 

compound

Excess lifetime cancer risk

Unit risk (UR) for lung cancer = 8.7 x 10‐5 per ng/m3

→ 8.7 cases per 100,000 people with chronic inhalational exposure to 1 ng/m3 BaP over a lifetime of 70 yrs (ave. adult weight) (WHO, 2000)

BaPeq = (PAH conc) x (TEF values)

Lifetime cancer risk = BaPeq X UR

• Curie‐Point Pyrolysis – GC/MS• Solvent Extraction