We compare different approaches to measure surface area of aerosol agglomerates. The objective was to compare field methods, such as mobility and diffusion charging based approaches, with laboratory approach, such as Brunauer, Emmett, Teller (BET) method used for bulk powder samples. To allow intercomparison of various surface area measurements, we defined ‘geometric surface area’ of agglomerates (assuming agglomerates are made up of ideal spheres), and compared various surface area measurements to the geometric surface area. Four different approaches for measuring surface area of agglomerate particles in the size range of 60–350 nm were compared using (i) diffusion charging-based sensors from three different manufacturers, (ii) mobility diameter of an agglomerate, (iii) mobility diameter of an agglomerate assuming a linear chain morphology with uniform primary particle size, and (iv) surface area estimation based on tandem mobility–mass measurement and microscopy. Our results indicate that the tandem mobility–mass measurement, which can be applied directly to airborne particles unlike the BET method, agrees well with the BET method. It was also shown that the three diffusion charging-based surface area measurements of silver agglomerates were similar within a factor of 2 and were lower than those obtained from the tandem mobility–mass and microscopy method by a factor of 3–10 in the size range studied. Surface area estimated using the mobility diameter depended on the structure or morphology of the agglomerate with significant underestimation at high fractal dimensions approaching 3.

The impetus for measuring surface area of aerosols in ambient and work environments comes from recent toxicological studies which have shown that the surface area of ultrafine and nanoparticles correlates better with the biological response than their mass (

The purpose of this study was to assess the difference of mobility and DCS methods, which are simple and most practical methods to use from exposure monitoring point of view, from more rigorous methods such as the BET method for measurement of agglomerate surface area. To allow intercomparison of various surface area measurements, we defined ‘geometric surface area’ of agglomerates (assuming agglomerates are made up of ideal spheres), and compared various surface area measurements to the geometric surface area. Four approaches for measuring the surface area of agglomerate aerosols in the submicrometer size range were compared:

An approach involving the tandem measurement of agglomerate mobility and mass using differential mobility analyzer and aerosol particle mass analyzer (APM), followed by primary particle size measurement using the transmission electron microscopy (TEM) to estimate the surface area.

The diffusion charging approach, using three different commercially available diffusion charging-based sensors.

Measurement of the surface area based directly on mobility diameter assuming spherical particles.

Surface area measurement based on mobility diameter with correction to account for primary particle size.

These approaches were evaluated using agglomerated aerosols of known properties. An intercomparison of these methods is presented, and the results are discussed.

The first approach (referred to as APM–TEM) for measurement of surface area of agglomerates involved measurement of particle mass of mobility classified particles using aerosol particle mass analyzer (APM) and primary particle size using transmission electron microscopy (TEM). If an agglomerate consists of many primary particles with an approximately uniform primary particle diameter, and if mass of the agglomerate (M) and the primary particle size are known (_{p}_{t}_{p}_{p}_{t}

The second approach (referred to as DCS) consisted of estimation of surface area using the diffusion charging-based sensors. The measurement scheme in diffusion charging-based sensors involves the use of attachment of unipolar ions to particles by diffusion followed by detection of particle current. Ions undergoing Brownian motion attach to particle surface, imparting an electrical charge to the particles (_{ion} is the ion mass,

Three commercially available diffusion charging sensors were used in this study to compare their responses: DC2000CE (Ecochem, USA), LQ1-DC (Matter Engineering, Switzerland; this is discontinued as a commercial product), and the Nanoparticle Surface Area Monitor (NSAM; Model 3550, TSI Inc.). These are semi-empirical instruments that give a size-integrated response proportional to input surface area. The first two sensors measure the so-called “active surface area” of the aerosol directly (

For conversion of the NSAM data to surface area provided to the inlet of NSAM, once the data from the NSAM were obtained for each single mobility diameter, a fraction of lung-deposition (alveolar deposition) for each particle size was first found based on the ICRP curve and then, the NSAM data were divided by the deposition fraction for each diameter to give surface area comparable to the other DCs data. The related equation can be expressed:
_{LD}_{m}_{m}_{m}_{m}

The third approach (referred to as MD) was based on the estimation of surface area directly from the particle’s mobility diameter (_{m}

The fourth approach (referred to as mobility diameter and linear chain approximation [MD-LCA]) was based on estimation of surface area using mobility diameter of the agglomerate, but assuming linear chain morphology instead of a spherical shape, as was done in the MD approach above. This simplifying assumption was introduced by _{m}

_{p}^{*} is the dimensionless drag force for agglomerates (^{*}=9.17 for orientation-averaged motion, and ^{*}=6.62 for motion parallel to viscous flow of gas (_{LCA}

Because of the linear chain approximation, the above approach is suitable for agglomerates with fractal dimension close to 1. We used the standard MD-LCA correction module available in the TSI AIMS software.

_{2} agglomerates were obtained by aerosolizing the TiO_{2} powder (P25, Evonik-Degussa) using a vortex shaker (

_{2} agglomerates, with primary particle sizes of 18, 20, and 22.5 nm, respectively. A mass scaling factor (_{f}_{m}^{Df}_{f}_{f}_{2} agglomerates it was 2.63. This suggests a more open structure of silver agglomerates compared to TiO_{2} and PSL agglomerates.

_{2} agglomerates were measured using the TEM analysis. The distribution of primary particle diameters of silver agglomerates is shown in _{2} agglomerates ranged from 10 to 46 nm with a peak diameter of 22.5 nm (_{2} agglomerates was more challenging due to significant necking and sintering of primary particle pairs. The primary particle diameter was estimated by taking the mean of the largest and smallest diameter encompassing a primary particle. Our estimate of peak diameter of 22.5 nm is slightly smaller than that reported by the manufacturer (25 nm based on Brunauer, Emmett, Teller [BET] analysis), and earlier studies (26–27 nm) (

The accuracy and precision of surface area measurement by the APM–TEM method depends on many factors, such as (i) uncertainty in estimating primary particle size by TEM, (ii) measurement precision or width of transfer function of the APM, (iii) fluctuation in aerosol concentration, and (iv) fraction of multiply charged particles passing through the APM. The last factor, the multiply charged fraction, can introduce large uncertainties in the measurement depending on the particle size distribution of the aerosol entering the APM. To probe the extent of combined effect of these sources of uncertainties, we compared the surface area measured by the APM–TEM method with that obtained from an independent method for TiO_{2} and PSL aerosols. Surface area of TiO_{2} was obtained using BET analysis, whereas for the PSL aerosol (consisting of only singlet monomers, not agglomerates), the surface area was estimated based on the precisely known diameter of the NIST-traceable PSL standard spheres. _{2} and PSL aerosol with the surface area measured using APM–TEM analysis. Input surface area for TiO_{2} agglomerates was calculated by multiplying the BET-measured “specific surface area” (SSA) of the bulk TiO_{2} sample (100 mg) by the peak particle mass obtained from the APM assuming unit charge on the particles. _{2} agglomerates. It is worth noting that the BET surface area is derived from measurement on large mass of bulk sample on the order of few hundred milligrams, whereas the APM mass measured in our experiments is on the order of femtograms. The fact that the BET surface area agrees well with that from the APM–TEM method based on a much smaller mass suggests that the TiO_{2} aerosol is quite homogeneous. For TiO_{2} agglomerates, there is an excellent agreement at lower mobility diameters (<250 nm); however, at large mobility diameter (>350 nm) the APM–TEM approach tends to overestimate the surface area. This is possibly due to the peak location of the APM transfer function and multiply charged fraction of particles. The effect of the multiply charged particles classified by the DMA may be not as much on the peak location of the APM transfer function because APM measures mass/charge—multiply charged particles from the DMA have higher mass and with higher charge contribute approximately to a similar peak location, but with a broad mass distribution (assuming the multiply charged fraction is small). Barone et al. recently reported the combined DMA-APM transfer function and its possible effect on particle mass from the location of the peak in the APM (

In this section DCS data are used to explain the differences between active and geometric surface area, and to clearly convey that these surface areas are different metrics and any comparison only serves to bring out the difference in methods themselves rather than quantifying their accuracy or error.

_{2}. For comparison, the surface area on the

The data in

Also shown in

_{2} agglomerates. This difference is attributed to the difference in the structure of agglomerates as will be discussed later. As noted earlier for diffusion charging-based sensors, in case of both MD and MD-LCA approaches, the deviation from the APM–TEM method also increases with increasing mobility size of the agglomerate. TiO_{2} agglomerates showed highest deviation compared to silver and PSL particles, though the error is much lower compared to that from the DCS measurements. Based on the analysis for two options of the TSI SMPS module for silver agglomerates (one is that agglomerate orientation in DMA is parallel to relative motion and the other is randomly oriented), the difference between APM–TEM and MD-LCA for the case of parallel alignment in the DMA are higher for agglomerates with sizes below 200 nm than those for random orientation while the opposite happens for agglomerates larger than 200 nm. It is hypothesized that the agglomerates larger than 200 nm may be aligned to the electric field in the DMA.

To probe the measurement error introduced by different instruments for different aerosols, calculations were performed to compare surface area of true fractal agglomerates (of spherical primary particles) obtained from measured sensitivity _{tot}_{gm}_{g}_{p}_{p}_{p}_{mob}_{est}_{est}

_{2} agglomerates, respectively. The sensitivity

_{f}_{2} agglomerates having very compact structure (_{f}

_{f}

Four different approaches for measuring surface area of submicrometer particles were compared in this study: (i) diffusion charging-based sensors (three sensors from three manufacturers were evaluated: TSI Inc., model 3550 nanoparticle surface area monitor; Ecochem, model DC2000CE diffusion charger; Matter Engineering, model LQ1-DC diffusion charger), (ii) mobility diameter-based surface area estimation, (iii) surface area based on mobility diameter assuming a linear chain morphology of an agglomerate with uniform primary particle size (MD-LCA), and finally, (iv) the surface area estimation based on the mass measurement from APM and primary particle size measurement using TEM (APM–TEM). It was shown that the APM–TEM method, which can be applied directly to airborne particles unlike the BET method, agrees well with the BET method. It was also found that the response of the three diffusion charging-based sensors to silver agglomerates substantially underestimated the surface area measured by the APM–TEM approach by a factor of 3–10 in the size range studied. These differences in surface area measured by diffusion charging-based sensors could be more drastic for large complex aerosols with high dynamic shape factors and large internal area. Mobility diameter-based methods (MD and MD-LCA) generally gave good agreement at low mobility sizes; however, they significantly underestimated surface area at large mobility diameters. MD and MD-LCA approaches was sensitive to the structure or morphology of the particles. Measurements for particles with open structure with _{f}

The authors would like to thank Drs. Art Miller and Emanuele Cauda at NIOSH for helpful suggestions, and Ellen Galloway for editorial assistance. This work was funded by the National Institute for Occupational Safety and Health through the Nanotechnology Research Center program (Project CAN 927ZBCL).

The mention of any company or product does not constitute an endorsement by the Centers for Disease Control and Prevention. The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.

_{2}nanotoxicity

_{2}: Role of the specific surface area and of surface methylation of the particles

Experimental setup. Evaporation/condensation generator was used to produce silver agglomerates, and electrospray generator used to generate polystyrene latex particles. DC2000CE (Ecochem), LQ1-DC (Matter Engineering), and NSAM (TSI Inc.) are diffusion charging-based instruments.

Log–log plot of mass versus mobility diameter for three different agglomerates: silver agglomerate (_{p}_{p}_{2} agglomerate (_{p}_{f}

(a) Number distributions measured downstream of the APM as a function of the APM classifying voltage for mobility-selected aerosol particles of silver and PSL. The peak voltage was used to determine the “average” particle mass of DMA-classified agglomerate particles. Top _{2} agglomerates. (c) Comparison of surface area from mass measured by APM–TEM with input surface area calculated on the basis of nominal mobility diameter classified by DMA for spherical PSL particles. Nominal surface area for PSL spheres is calculated from PSL spherical diameter, and for TiO_{2} is calculated from multiplying BET-measured specific surface area of bulk TiO_{2} material by particle mass measured by APM.

Comparison of diffusion charging-based surface area (DCS) with the APM–TEM method for three different particle agglomerates. Normalized surface area on

Comparison of mobility-based surface area (MD and MD-LCA) with the APM–TEM method for three different particle agglomerates.

(a) Sensitivity for each instrument as a function of mobility diameter for silver agglomerates with primary particle diameter of 18 nm. The sensitivity _{2} agglomerates with primary particle diameter of 22.5 nm. The sensitivity

Sensitivity (_{f}

Definition of different surface area from each instrument.

Instrument | Definition |
---|---|

LQ1-DC, DC2000CE | Active surface area is defined as the surface of a particle that is involved in interactions with the surrounding gas |

NSAM | Lung-deposited surface area is defined as the surface of a particle deposited in the alveolar or tracheobronchial region with its deposition efficiency based on the ICRP curve |

SMPS | Mobility diameter-based surface area assuming spherical particles |

APM–TEM | Surface area assuming all primary particles have the same size, and no necking between primary particles |

BET | Surface area based on nitrogen adsorption and analysis of the data using the Brunauer–Emmet–Teller isotherm |

Surface area calculation of TiO_{2} particles from BET measurements.

_{m} | _{p} | SSA from BET (m^{2}/g) | SA (_{p}^{2}) |
---|---|---|---|

170 | 4.052 | 59.3 | 240283.6 |

250 | 11.25 | 59.3 | 667125 |

350 | 29.23 | 59.3 | 1733339 |

Surface area difference of each approach relative to surface area (_{APM–TEM}) measured by APM–TEM method for silver agglomerates (_{p}_{p}_{2} agglomerates (_{p}_{APM–TEM} − _{APM–TEM} × 100.

Mobility diameter (nm) | DC2000CE | LQ1-DC | NSAM | MD | MD-LCA |
---|---|---|---|---|---|

100 | 85.03 | 62.03 | 83.30 | −47.07 | −86.02 |

120 | – | – | 86.55 | – | – |

150 | 86.20 | 69.28 | 73.17 | −15.54 | −28.37 |

180 | – | – | 81.84 | – | – |

200 | 91.37 | 81.86 | – | −0.06 | −0.85 |

250 | – | 90.12 | – | 7.76 | 16.64 |

300 | 96.12 | 91.89 | – | 22.14 | 33.06 |

60 | 81.55 | – | – | 41.80 | 22.81 |

100 | 85.84 | – | – | 55.20 | 41.68 |

150 | 70.30 | – | – | 58.40 | 59.33 |

_{2} | |||||

170 | 86.23 | – | – | 66.94 | – |

250 | 90.38 | – | – | 73.31 | – |

350 | 97.04 | – | – | 78.99 | – |

MD=mobility diameter

MD-LCA=mobility diameter and linear chain approximation

Comparison of total surface area of a polydisperse aerosol (with each particle being an agglomerate) obtained from fractal theory to that predicted for mobility diameter and diffusion charging sensor approaches using measured sensitivity

_{g} | _{est}^{2}/cm^{3}) | S_MD | S_DCS (DC2000CE) | S_DCS (LQ1-DC) | S_DCS (NSAM) |
---|---|---|---|---|---|

50 | 2.59E+02 | 2.67E+02 | 3.63E+01 | 8.81E+01 | 4.15E+01 |

100 | 1.25E+03 | 1.29E+03 | 1.76E+02 | 4.26E+02 | 2.01E+02 |

200 | 4.65E+03 | 4.79E+03 | 6.50E+02 | 1.58E+03 | 7.43E+02 |

300 | 1.16E+04 | 1.19E+04 | 1.62E+03 | 3.93E+03 | 1.85E+03 |

400 | 2.70E+04 | 2.78E+04 | 3.78E+03 | 9.17E+03 | 4.32E+03 |

600 | 7.15E+04 | 7.36E+04 | 1.00E+04 | 2.43E+04 | – |

800 | 1.46E+05 | 1.50E+05 | 2.04E+04 | 4.95E+04 | – |

1000 | 2.54E+05 | 2.62E+05 | 3.56E+04 | 8.65E+04 | – |

2000 | 1.60E+06 | 1.65E+06 | 2.24E+05 | 5.45E+05 | – |

_{g} | _{est} (μm^{2}/cm^{3}) | S_MD | S_DCS (DC2000CE) | S_DCS (LQ1-DC) | S_DCS (NSAM) |

| |||||

_{2}, 22.5 nm | |||||

100 | 1.96E+03 | 4.90E+02 | 2.16E+02 | – | – |

400 | 4.21E+04 | 1.05E+04 | 4.64E+03 | – | – |

600 | 1.12E+05 | 2.79E+04 | 1.23E+04 | – | – |

800 | 2.27E+05 | 5.69E+04 | 2.50E+04 | – | – |

1000 | 3.97E+05 | 9.94E+04 | 4.37E+04 | – | – |

2000 | 2.50E+06 | 6.26E+05 | 2.75E+05 | – | – |

Calculated using a relation between mobility diameter and number of primary particles in an agglomerate based on the fractal theory work of _{tot}) is 10,000 cm^{−3} and geometric standard deviation (_{g}