Fuel-based fine particulate and black carbon emission factors from a railyard area in Atlanta

Abstract. We have used two methods for measuring emission factors (EFs) in real driving conditions on five cars in a controlled environment: the stationary method, where the investigated vehicle drives by the stationary measurement platform and the composition of the plume is measured, and the chasing method, where a mobile measurement platform drives behind the investigated vehicle. We measured EFs of black carbon and particle number concentration. The stationary method was tested for repeatability at different speeds and on a slope. The chasing method was tested on a test track and compared to the portable emission measurement system. We further developed the data processing algorithm for both methods, trying to improve consistency, determine the plume duration, limit the background influence and facilitate automatic processing of measurements. The comparison of emission factors determined by the two methods showed good agreement. EFs of a single car measured with either method have a specific distribution with a characteristic value and a long tail of super emissions. Measuring EFs at different speeds or slopes did not significantly influence the EFs of different cars; hence, we propose a new description of vehicle emissions that is not related to kinematic or engine parameters, and we rather describe the vehicle EF with a characteristic value and a super emission tail.

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Plume-based analysis of vehicle fleet air pollutant emissions and the contribution from high emitters

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-8-2881-2015 ◽

2015 ◽

Vol 8 (3) ◽

pp. 2881-2912 ◽

Cited By ~ 3

Author(s):

J. M. Wang ◽

C.-H. Jeong ◽

N. Zimmerman ◽

R. M. Healy ◽

D. K. Wang ◽

...

Keyword(s):

Carbon Monoxide ◽

Black Carbon ◽

Time Resolution ◽

Real World ◽

Vehicle Emissions ◽

Particle Number ◽

Emission Factors ◽

Air Pollutant ◽

Automated Identification ◽

Vehicle Fleet

Abstract. An automated identification and integration method has been developed to investigate in-use vehicle emissions under real-world conditions. This technique was applied to high time resolution air pollutant measurements of in-use vehicle emissions performed under real-world conditions at a near-road monitoring station in Toronto, Canada during four seasons, through month-long campaigns in 2013–2014. Based on carbon dioxide measurements, over 100 000 vehicle-related plumes were automatically identified and fuel-based emission factors for nitrogen oxides; carbon monoxide; particle number, black carbon; benzene, toluene, ethylbenzene, and xylenes (BTEX); and methanol were determined for each plume. Thus the automated identification enabled the measurement of an unprecedented number of plumes and pollutants over an extended duration. Emission factors for volatile organic compounds were also measured roadside for the first time using a proton transfer reaction time-of-flight mass spectrometer; this instrument provided the time resolution required for the plume capture technique. Mean emission factors were characteristic of the light-duty gasoline dominated vehicle fleet present at the measurement site, with mean black carbon and particle number emission factors of 35 mg kg−1 and 7.7 × 1014 kg−1, respectively. The use of the plume-by-plume analysis enabled isolation of vehicle emissions, and the elucidation of co-emitted pollutants from similar vehicle types, variability of emissions across the fleet, and the relative contribution from heavy emitters. It was found that a small proportion of the fleet (< 25%) contributed significantly to total fleet emissions; 95, 93, 76, and 75% for black carbon, carbon monoxide, BTEX, and particle number, respectively. Emission factors of a single pollutant may help classify a vehicle as a high emitter. However, regulatory strategies to more efficiently target multi-pollutants mixtures may be better developed by considering the co-emitted pollutants as well.

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Determination of black carbon, PM2.5, particle number and NOx emission factors from roadside measurements and their implications for emission inventory development

Atmospheric Environment ◽

10.1016/j.atmosenv.2018.05.042 ◽

2018 ◽

Vol 186 ◽

pp. 229-240 ◽

Cited By ~ 22

Author(s):

Patricia Krecl ◽

Admir Créso Targino ◽

Thiago Pereira Landi ◽

Matthias Ketzel

Keyword(s):

Black Carbon ◽

Emission Inventory ◽

Particle Number ◽

Emission Factors ◽

Nox Emission ◽

Inventory Development

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Short-Term Association between Black Carbon Exposure and Cardiovascular Diseases in Pakistan’s Largest Megacity

Atmosphere ◽

10.3390/atmos9110420 ◽

2018 ◽

Vol 9 (11) ◽

pp. 420 ◽

Cited By ~ 1

Author(s):

Daniel Malashock ◽

Haider Khwaja ◽

Zafar Fatmi ◽

Azhar Siddique ◽

Yi Lu ◽

...

Keyword(s):

Cardiovascular Diseases ◽

Black Carbon ◽

Hospital Admissions ◽

Statistical Significance ◽

Fine Particulate Matter ◽

Tertiary Care ◽

Short Term ◽

Residential Site ◽

Fine Particulate ◽

Tertiary Care Hospitals

This study investigated the association between black carbon (BC) exposure and hospital admissions (HAs) and outpatient department/emergency room (OPD/ER) visits for cardiovascular diseases (CVD) among residents of Karachi, the largest city in Pakistan. We measured daily concentrations of BC in fine particulate matter (PM2.5) and collected records of HAs and OPD/ER visits for CVD from 2 major tertiary care hospitals serving Karachi for 6 weeks continuously during each quarter over 1 year (August 2008–August 2009). We subsequently analyzed daily counts of hospital and BC data over 0–3 lag days. Daily mean BC concentrations varied from 1 to 32 µg/m3. Results suggest that BC concentrations are associated with CVD HAs and OPD/ER visits. However, associations were generally only observed when modeled with BC from Tibet Center, the commercial-residential site, as compared to Korangi, the industrial-residential site. Overall, low statistical significance suggests that while BC may be a valuable indicator for CVD health risks from combustion-derived particles, further evaluation of the constituents of PM2.5 and their relative contributions to CVD health impacts is necessary.

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Development of an Empirical Model to Estimate Real-World Fine Particulate Matter Emission Factors: The Traffic Air Quality Model

Journal of the Air & Waste Management Association ◽

10.1080/10473289.2006.10464566 ◽

2006 ◽

Vol 56 (11) ◽

pp. 1540-1549 ◽

Cited By ~ 6

Author(s):

Ahmed S.M. Soliman ◽

Robert B. Jacko ◽

George M. Palmer

Keyword(s):

Particulate Matter ◽

Air Quality ◽

Empirical Model ◽

Real World ◽

Fine Particulate Matter ◽

Emission Factors ◽

Air Quality Model ◽

Quality Model ◽

Particulate Matter Emission ◽

Fine Particulate

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Emission Factors of Black Carbon and Co-pollutants from Diesel Vehicles in Mexico City

10.5194/acp-2017-695 ◽

2017 ◽

Author(s):

Miguel Zavala ◽

Luisa T. Molina ◽

Tara I. Yacovitch ◽

Edward C. Fortner ◽

Joseph R. Roscioli ◽

...

Keyword(s):

Remote Sensing ◽

Developing Countries ◽

Black Carbon ◽

Mexico City ◽

Urban Areas ◽

Fine Particulate Matter ◽

Emission Factors ◽

Remote Sensing Technique ◽

Driving Conditions ◽

Comparison Of The Results

Abstract. Diesel-powered vehicles are intensively used in urban areas for transporting goods and people but can substantially contribute to high emissions of black carbon (BC), organic carbon (OC), and other gaseous pollutants. Strategies aimed at controlling mobile emissions sources thus have the potential to improve air quality as well as help mitigate impacts of air pollutants on climate, ecosystems, and human health. However, in developing countries there are limited data on the BC and OC emission characteristics of diesel-powered vehicles and thus there are large uncertainties in the estimation of the emission contributions from these sources. We measured BC, OC and other inorganic components of fine particulate matter (PM), as well as carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), ethane, acetylene, benzene, toluene, and C2-benzenes under real-world driving conditions of 20 diesel-powered vehicles encompassing multiple emission level technologies in Mexico City with the chasing technique using the Aerodyne mobile laboratory. Average BC emission factors ranged from 0.41–2.48 g/kg-fuel depending on vehicle type. The vehicles were also simultaneously measured using the cross-road remote sensing technique to obtain the emission factors of nitrogen oxide (NO), CO, total hydrocarbons, and fine PM, thus allowing the inter-comparison of the results from the two techniques. There is overall good agreement between the two techniques and both can identify high and low emitters but substantial differences were found in some of the vehicles, probably due to the ability of the chasing technique to capture a larger diversity of driving conditions in comparison to the remote sensing technique. A comparison of the results with the US-EPA MOVES-2014b model showed that the model underestimates CO, OC, and selected VOC species whereas there is better agreement for NOx and BC. Larger OC / BC ratios were found in comparison to ratios measured in California using the same technique, further demonstrating the need for using locally-obtained diesel-powered vehicle emission factors database in developing countries in order to reduce the uncertainty in the emissions estimates and to improve the evaluation of the effectiveness of emissions reduction measures.

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