Aerosol Particle and Black Carbon Emission Factors of Vehicular Fleet in Manila, Philippines

Poor air quality has been identified as one of the main risks to human health, especially in developing regions, where the information on physical chemical properties of air pollutants is lacking. To bridge this gap, we conducted an intensive measurement campaign in Manila, Philippines to determine the emission factors (EFs) of particle number (PN) and equivalent black carbon (BC). The focus was on public utility jeepneys (PUJ), equipped with old technology diesel engines, widely used for public transportation. The EFs were determined by aerosol physical measurements, fleet information, and modeled dilution using the Operational Street Pollution Model (OSPM). The results show that average vehicle EFs of PN and BC in Manila is up to two orders of magnitude higher than European emission standards. Furthermore, a PUJ emits up to seven times more than a light-duty vehicles (LDVs) and contribute to more than 60% of BC emission in Manila. Unfortunately, traffic restrictions for heavy-duty vehicles do not apply to PUJs. The results presented in this work provide a framework to help support targeted traffic interventions to improve urban air quality not only in Manila, but also in other countries with a similar fleet composed of old-technology vehicles.

[1]  J. Marshall,et al.  On-highway vehicle emission factors, and spatial patterns, based on mobile monitoring and absolute principal component score. , 2019, The Science of the total environment.

[2]  Alexander B. MacDonald,et al.  Size-resolved composition and morphology of particulate matter during the southwest monsoon in Metro Manila, Philippines , 2019, Atmospheric Chemistry and Physics.

[3]  B. Hoffmann,et al.  Health effects of ultrafine particles: a systematic literature review update of epidemiological evidence , 2019, International Journal of Public Health.

[4]  M. Ketzel,et al.  Determination of black carbon, PM2.5, particle number and NOx emission factors from roadside measurements and their implications for emission inventory development , 2018, Atmospheric Environment.

[5]  T. Tuch,et al.  Mobility particle size spectrometers: Calibration procedures and measurement uncertainties , 2018 .

[6]  T. Müller,et al.  Aerosol particle mixing state, refractory particle number size distributions and emission factors in a polluted urban environment: Case study of Metro Manila, Philippines , 2017 .

[7]  C. Johansson,et al.  Trends in black carbon and size-resolved particle number concentrations and vehicle emission factors under real-world conditions , 2017 .

[8]  M. Andrade,et al.  Relationship between black carbon (BC) and heavy traffic in São Paulo, Brazil , 2015, Transportation Research Part D: Transport and Environment.

[9]  M. Ferm,et al.  Concentrations and emission factors for PM2.5 and PM10 from road traffic in Sweden , 2015 .

[10]  I. Riipinen,et al.  Particulate matter, air quality and climate: Lessons learned and future needs , 2015 .

[11]  Roy M. Harrison,et al.  Review of the efficacy of low emission zones to improve urban air quality in European cities , 2015 .

[12]  D. Cornford,et al.  How good are citizen weather stations? Addressing a biased opinion , 2015 .

[13]  T. Müller,et al.  A fast and easy-to-implement inversion algorithm for mobility particle size spectrometers considering particle number size distribution information outside of the detection range , 2014 .

[14]  A. Wiedensohler,et al.  Measurements of the mass absorption cross section of atmospheric soot particles using Raman spectroscopy , 2013 .

[15]  W. Birmili,et al.  Variability of aerosol particles in the urban atmosphere of Dresden (Germany): Effects of spatial scale and particle size , 2013 .

[16]  J. Olfert,et al.  Coating Mass Dependence of Soot Aggregate Restructuring due to Coatings of Oleic Acid and Dioctyl Sebacate , 2013 .

[17]  U. Pöschl,et al.  Hazardous components and health effects of atmospheric aerosol particles: reactive oxygen species, soot, polycyclic aromatic compounds and allergenic proteins , 2012, Free radical research.

[18]  Rex Britter,et al.  Dynamics and dispersion modelling of nanoparticles from road traffic in the urban atmospheric environment—A review , 2011 .

[19]  Matthias Ketzel,et al.  Operational Street Pollution Model (OSPM) – a review of performed application and validation studies, and future prospects , 2010 .

[20]  Chunsheng Zhao,et al.  Mobility particle size spectrometers: harmonization of technical standards and data structure to facilitate high quality long-term observations of atmospheric particle number size distributions , 2010 .

[21]  Ngo Tho Hung,et al.  Air Pollution Modeling at Road Sides Using the Operational Street Pollution Model—A Case Study in Hanoi, Vietnam , 2010, Journal of the Air & Waste Management Association.

[22]  J. Pichon,et al.  Characterization and intercomparison of aerosol absorption photometers: result of two intercomparison workshops , 2010 .

[23]  J. Chow,et al.  Chemically-speciated on-road PM(2.5) motor vehicle emission factors in Hong Kong. , 2010, The Science of the total environment.

[24]  Luis Ferreira,et al.  Development of a particle number and particle mass vehicle emissions inventory for an urban fleet , 2009, Environ. Model. Softw..

[25]  Gerald Falkenberg,et al.  Real-world emission factors for antimony and other brake wear related trace elements: size-segregated values for light and heavy duty vehicles. , 2009, Environmental science & technology.

[26]  Matthias Ketzel,et al.  Particle number, particle mass and NO x emission factors at a highway and an urban street in Copenhagen , 2009 .

[27]  T. Tuch,et al.  Design and performance of an automatic regenerating adsorption aerosol dryer for continuous operation at monitoring sites , 2009 .

[28]  M. Ketzel,et al.  Particle number emissions of motor traffic derived from street canyon measurements in a Central European city , 2009 .

[29]  Adalgiza Fornaro,et al.  Vehicular particulate matter emissions in road tunnels in Sao Paulo, Brazil , 2009, Environmental monitoring and assessment.

[30]  T. Tuch,et al.  Dispersion of traffic-related exhaust particles near the Berlin urban motorway - Estimation of fleet emission factors , 2008 .

[31]  Martin Hvidberg,et al.  Evaluation and application of OSPM for traffic pollution assessment for a large number of street locations , 2008, Environ. Model. Softw..

[32]  G. Genon,et al.  PM emissions in an urban context , 2007 .

[33]  Roy M. Harrison,et al.  Estimation of the emission factors of particle number and mass fractions from traffic at a site where mean vehicle speeds vary over short distances , 2006 .

[34]  Nghiem Trung Dung,et al.  Particulate air pollution in six Asian cities: Spatial and temporal distributions, and associated sources , 2006 .

[35]  Constantinos Sioutas,et al.  Measurements of particle number and mass concentrations and size distributions in a tunnel environment. , 2005, Environmental science & technology.

[36]  R. Gehrig,et al.  Real-world emission factors of fine and ultrafine aerosol particles for different traffic situations in Switzerland. , 2005, Environmental science & technology.

[37]  M. Ketzel,et al.  Atmospheric number size distributions of soot particles and estimation of emission factors , 2005 .

[38]  Peter Sturm,et al.  Aerosol and NO x emission factors and submicron particle number size distributions in two road tunnels with different traffic regimes , 2005 .

[39]  P. Mcmurry,et al.  Structural Properties of Diesel Exhaust Particles Measured by Transmission Electron Microscopy (TEM): Relationships to Particle Mass and Mobility , 2004 .

[40]  Andreas Petzold,et al.  Multi-angle absorption photometry—a new method for the measurement of aerosol light absorption and atmospheric black carbon , 2004 .

[41]  David Proffitt,et al.  Tailpipe, resuspended road dust, and brake-wear emission factors from on-road vehicles , 2003 .

[42]  Matthias Ketzel,et al.  Particle and trace gas emission factors under urban driving conditions in Copenhagen based on street and roof-level observations , 2003 .

[43]  Xin Wang,et al.  The Relationship between Mass and Mobility for Atmospheric Particles: A New Technique for Measuring Particle Density , 2002 .

[44]  Henning Sten Hansen,et al.  A Danish decision-support GIS tool for management of urban air quality and human exposures , 2001 .

[45]  R. W. Waytulonis,et al.  Chemical analysis of diesel engine nanoparticles using a nano-DMA/thermal desorption particle beam mass spectrometer. , 2001, Environmental science & technology.

[46]  Werner A. Stahel,et al.  Aerosol emission in a road tunnel , 1997 .

[47]  W. MacNee,et al.  Particulate air pollution and acute health effects , 1995, The Lancet.

[48]  T. Müller,et al.  Spatial Characterization of Black Carbon Mass Concentration in the Atmosphere of a Southeast Asian Megacity: An Air Quality Case Study for Metro Manila, Philippines , 2018 .

[49]  Stefan Groer,et al.  Impacts of low emission zones in Germany on air pollution levels , 2017 .

[50]  N. Zíková,et al.  Interactive comment on “ Intercomparison of 15 aerodynamic particle size spectrometers ( APS 3321 ) : uncertainties in particle sizing and number size distribution ” by S . , 2015 .

[51]  Karl N. Vergel,et al.  ESTIMATION OF EMISSIONS AND FUEL CONSUMPTION OF SUSTAINABLE TRANSPORT MEASURES IN METRO MANILA , 2013 .

[52]  D. Westerdahl,et al.  Characterization of on-road vehicle emission factors and microenvironmental air quality in Beijing, China , 2009 .

[53]  D. Ceburnis,et al.  Minimizing light absorption measurement artifacts of the Aethalometer: evaluation of five correction algorithms , 2009 .

[54]  K. Pericleous,et al.  Modelling air quality in street canyons : a review , 2003 .

[55]  R. Berkowicz,et al.  Modelling traffic pollution in streets , 2001 .