Measuring Particulate Mass Emissions with the Electrical Low Pressure Impactor

Maricq, M. Matti; Xu, Nannan; Chase, Richard E.

doi:10.1080/02786820500466591

Cited by 87 publications

(54 citation statements)

References 28 publications

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“…DPM particles are fractal-like agglomerates of approximately spherical 10-to 30-nm diameter primary particles with an effective mass density decreasing with decreasing particle size. 52,54 Pagels et al 36 demonstrated that charge-bearing nanoparticles deposit on the upper ELPI stages, thereby creating biases in these results. Zhu et al 55 implemented an ELPI fitting procedure 52 that accounts for these artifacts by iteratively adjusting the particle size and number concentrations for a bimodal distribution to match the current deposited on each impactor stage.…”

Section: Data Acquisitionmentioning

confidence: 99%

“…51 e C c ͑d m ͒d m 2 ϭ 0 C c ͑d a ͒d a 2 (2) where C c is the Cunningham correction coefficient and 0 the primary particle density, 2 g/m 3 . 52 Approximately 80 -90% of diesel particulate matter (DPM) mass is found in the 30-to 500-nm range. 53 ELPI software converts the current measured on each stage to PM mass assuming that particles are spherical with unit density and that d m ϭ d a .…”

Section: Data Acquisitionmentioning

confidence: 99%

See 1 more Smart Citation

The In-Plume Emission Test Stand: An Instrument Platform for the Real-Time Characterization of Fuel-Based Combustion Emissions

Nussbaum

Zhu

Kuhns

et al. 2009

Journal of the Air & Waste Management Association

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The In-Plume Emission Test Stand (IPETS) characterizes gaseous and particulate matter (PM) emissions from combustion sources in real time. Carbon dioxide (CO 2 ), carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO 2 ), and other gases are quantified with a closed-path Fourier transform infrared spectrometer (FTIR). Particle concentrations, chemical composition, and other particle properties are characterized with an electrical lowpressure impactor (ELPI), a light-scattering particle detector, an optical particle counter, and filter samples amenable to different laboratory analysis. IPETS measurements of fuel-based emission factors for a diesel generator are compared with those from a Mobile Emissions Laboratory (MEL). IPETS emission factors ranged from 0.3 to 11.8, 0.2 to 3.7, and 22.2 to 32.8 g/kg fuel for CO, NO 2 , and NO, respectively. IPETS PM emission factors ranged from 0.4 to 1.4, 0.3 to 1.8, 0.3 to 2.2, and 1 to 3.4 g/kg fuel for filter, photoacoustic, nephelometer, and impactor measurements, respectively. Observed linear regression statistics for IPETS versus MEL concentrations were as follows: CO slope ϭ 1.1, r 2 ϭ 0.99; NO slope ϭ 1.1, r 2 ϭ 0.92; and NO 2 slope ϭ 0.8, r 2 ϭ 0.96. IPETS versus MEL PM regression statistics were: filter slope ϭ 1.3, r 2 ϭ 0.80; ELPI slope ϭ 1.7, r 2 ϭ 0.87; light-scattering slope ϭ 2.7, r 2 ϭ 0.92; and photoacoustic slope ϭ 2.1, r 2 ϭ 0.91. Lower temperatures in the dilution air (ϳ25°C for IPETS vs. ϳ50°C for MEL) may result in greater condensation of semi-volatile compounds on existing particles, thereby explaining the 30% difference for filters. The other PM measurement devices are highly correlated with the filter, but their factorydefault PM calibration factors do not represent the size and optical properties of diesel exhaust. They must be normalized to a simultaneous filter measurement. INTRODUCTIONGas and particle emissions from power generators, gasoline engines, and diesel engines affect attainment of air quality standards, 1 human health, 2 visibility, 3 and climate. 4 Real-world emission estimates from these sources are needed to improve air quality management strategies.Engine certification emission factors (EFs) are determined from chassis or engine dynamometer tests following test protocols that vary vehicle operating conditions over time. 5 Only a few vehicles or engines can be tested on dynamometers because of the time and effort required. Other methods can determine EFs for large vehicle fleets. Tunnel studies yield fleet EFs averaged over many vehicles, but these tests are unable to determine individual vehicle EFs and their distribution across vehicle type and age. 6 Vehicle emission remote sensing systems (VERSS) and in-plume systems can measure fuel-based EFs for many individual vehicles over a wide range of real-world operating conditions. 7,8 Fuel-based EFs are calculated as 9,10

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Section: Data Acquisitionmentioning

confidence: 99%

Section: Data Acquisitionmentioning

confidence: 99%

The In-Plume Emission Test Stand: An Instrument Platform for the Real-Time Characterization of Fuel-Based Combustion Emissions

Nussbaum

Zhu

Kuhns

et al. 2009

Journal of the Air & Waste Management Association

View full text Add to dashboard Cite

show abstract

“…Although aerodynamic distributions require no knowledge of particle density to obtain an accurate mass distribution, particle charging efficiency depends on particle mobility diameter and shape but not aerodynamic diameter, and thus the accuracy of the size distributions reported by the ELPI may vary depending on particle morphology. Considering these fundamental and other experimental uncertainties, Maricq et al (2006) estimated that the integration of aerodynamic size distributions using the ELPI yielded an uncertainty of about 20% in quantifying vehicle exhaust PM mass. Later, Dekati Ltd. developed the Dekati Mass Monitor (DMM) that, among other improvements for measuring engine exhaust, combines aerodynamic and mobility classifications to determine particle effective density in real-time by assuming a unimodal distribution (Lehmann et al 2004).…”

Section: Introductionmentioning

confidence: 99%

“…Maricq et al (2006) reported the estimation of suspended PM mass using an Electrical Low Pressure Impactor (ELPI; Dekati Ltd., Kangasala, Finland). The EPLI measures real-time aerodynamic PSDs using cascade low-pressure impactors and electrometers at each stage.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Vehicle Exhaust Particle Size Distributions Measured by SMPS and EEPS During Steady-State Conditions

Xue

Wang

et al. 2015

Aerosol Science and Technology

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Fast-sizing spectrometers, such as the TSI Engine Exhaust Particle Sizer (EEPS), have been widely used to measure transient particle size distributions of vehicle exhaust. Recently, size distributions measured during different test cycles have begun to be used for calculating suspended particulate mass; however, several recent evaluations have shown some deficiencies in this approach and discrepancies relative to the gravimetric reference method. The EEPS converts electrical charge carried by particles into size distributions based on mobility classification and a specific calibration, and TSI recently released a matrix optimized for vehicle emissions as described by Wang et al. (Submitteda). This study evaluates the performance of the new matrix (soot matrix) relative to the original matrix (default matrix) and reference size distributions measured by a scanning mobility particle sizer (SMPS). Steady-state particle size distributions were generated from the following five sources to evaluate exhaust particulates with various morphologies estimated by mass-mobility scaling exponent: (1) A diesel generator operating on ultralow sulfur diesel, (2) a diesel generator operating on biodiesel, (3) a gasoline direct-injection vehicle operating at two speeds, (4) a conventional port-fuel injection gasoline vehicle, and (4) a light-duty diesel (LDD) vehicle equipped with a diesel particulate filter. Generally, the new soot matrix achieved much better agreement with the SMPS reference for particles smaller than 30 nm and larger than 100 nm, and also broadened the accumulation mode distribution that was previously too narrow using the default matrix. However, EEPS distributions still did not agree with SMPS reference measurements when challenged by a strong nucleation mode during high-load operation of the LDD vehicle. This work quantifies the range of accuracy that can be expected when measuring particle size distribution, number concentration, and integrated particle mass of vehicle emissions when using the new static calibration derived based on the properties of classical diesel soot.

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“…The number concentration in each channel is calculated through the density-dependent charging law. Consequently, if the raw current distribution measured by the ELPI is not used, an assumption must be made on particle density (Maricq et al, 2006). Furthermore, the presence of multiple charged 5 particles at the outlet of the DMA, and consequently integrated into the ELPI signal, should be taken into account to avoid possible bias in estimation of particle effective density.…”

Section: Introductionmentioning

confidence: 99%

Determining the effective density of airborne nanoparticles using multiple charging correction in a tandem DMA/ELPI setup

et al. 2014

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Increasing numbers of workers are exposed to airborne nanoparticles, the health effects of which remain difficult to evaluate. Effective density is considered to be a key characteristic of airborne nanoparticles due to its role in particle deposition in the human respiratory tract and in the conversion of number distributions to mass distributions. Because effective density cannot be measured directly, in this study the electrical mobility and aerodynamic equivalent diameters of airborne nanoparticles were measured simultaneously (tandem DMA/ELPI). Test aerosols consisted of spherical Di-Ethyl-Hexyl-Sebacate nanoparticles produced by nebulization (PALAS AGK 2000). To take into account the presence of multiply-charged particles at the DMA outlet, a theoretical model was developed in which the successive mechanisms undergone by particles are accounted for. Using this model, it is possible to determine the proportion of each population exiting the DMA (p = 1, 2, …5 elementary charges) in each channel of the overall ELPI signal.Thus, particle effective density can be estimated for each population. The results indicate that using the ELPI signal alone could lead to significant misevaluation of particle effective density, with biases up to 150%. However, when the proportion of each population is taken into account, particle effective density is determined within 15% of the theoretical value.3

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Measuring Particulate Mass Emissions with the Electrical Low Pressure Impactor

Cited by 87 publications

References 28 publications

The In-Plume Emission Test Stand: An Instrument Platform for the Real-Time Characterization of Fuel-Based Combustion Emissions

The In-Plume Emission Test Stand: An Instrument Platform for the Real-Time Characterization of Fuel-Based Combustion Emissions

Comparison of Vehicle Exhaust Particle Size Distributions Measured by SMPS and EEPS During Steady-State Conditions

Determining the effective density of airborne nanoparticles using multiple charging correction in a tandem DMA/ELPI setup

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