Measurements of Polycyclic Aromatic Hydrocarbon Adsorption on

Ind. Eng. Chem. Res. 2003, 42, 155-161

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Measurements of Polycyclic Aromatic Hydrocarbon Adsorption on Activated Carbons at Very Low Concentrations Ana M. Mastral,* Toma´ s Garcıá, Ramo´ n Murillo, Marıá S. Calle´ n, Jose´ M. Lo´ pez, and Marıá V. Navarro Instituto de Carboquı´mica, CSIC, M Luesma Castan 4, 50015 Zaragoza, Spain

The aim of this paper is to describe the existent equilibrium between polycyclic aromatic hydrocarbons (PAHs) and granular carbonaceous materials in adsorption processes occurring in carbon beds used for air pollution control. The adsorption of the most volatile PAHs listed by the USEPAsnaphthalene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, and pyreneswas measured under the conditions at which they are emitted in energy generation processes, that is, with concentrations ranging from 0.020 to 25 ppm and at a temperature of 150 °C. Experimental results show that their adsorption capacity is dependent on PAH concentrations. From the measured adsorption capacities, original isotherms have been plotted and adsorption parameters based on the two-parameter models of Langmuir, BrunauerEmmett-Teller, Freundlich, and Dubinin-Radushkevich have been calculated. Neither of the two-parameter models was able to fit the experimental data in all PAH concentration ranges studied. Furthermore, no relationship was found between the PAH physical propertiessmolecular volume, boiling point, and vapor pressure at 150 °Csand the parameters obtained in the four models. Introduction Polycyclic aromatic hydrocarbons (PAHs) are a group of structurally related compounds that are generated during combustion processes.1 They constitute an important class of environmental pollutants, which as are metabolized into derivatives, capable of reacting with DNA to promote mutagenic and carcinogenic responses.2,3 Their origin is related to both anthropogenic sourcess such as engine exhaust,4 industrial processes,5 natural gas combustion,6 domestic heating systems,7 incinerators,8 and smoke8sand natural sourcesssuch as volcanic eruptions and forest fires. PAH emissions from anthropogenic sources could be reduced by controlling the combustion process variables: oxygen excess percentage,9 residence time,10 and temperature.11 However, it is not always possible to achieve a total PAH abatement during the combustion process. PAH emissions, because of their high volatility and reactivity,12 can be released, not only supported onto particulate matter (PM) but also in the gas phase.13,14 While the most volatile compounds, with two and four aromatic rings are mainly released in the gas phase, the heaviest compounds, that is, those containing three or more aromatic rings, can be emitted in association with the PM. The main advantage of the PAHs supported onto the PM is that they can be trapped using the proper systems to collect the PM such as cyclones, electrostatic precipitators, scrubbers, etc. On the other hand, the most volatile compounds and those on the smallest PM can be released to the atmosphere, and their control becomes more difficult. Two different technologies that are the most promising alternatives to reduce gaseous PAH emissions are catalytic PAH elimination15,16 and PAH adsorption on carbonaceous materials.17,19 * To whom correspondence should be addressed. Phone: 34 976 733977. Fax: 34 976 733318. E-mail: amastral@carbon. icb.csic.es.

Packed beds of carbonaceous materials have been used to remove organic emissions from about 100 to 10 000 ppmv concentrations in industrial waste gas streams.20 Recently, it has been shown that dioxins, furans, and PAHs, at ppbv or lower concentrations, can be effectively removed from waste incinerator combustion gases by using carbon injection or carbon bed technology.17 The theoretical and quantitative study of the PAH adsorption capacity of the granular carbonaceous materials has a great significance in order to predict the behavior of these materials for air pollution control. In previous works,18,19 the authors demonstrated that the phenanthrene (Phe) adsorption capacity on different carbon materials depends on the material textural parameters. The next step is to describe the equilibrium between PAHs and carbonaceous materials during the adsorption process. In previous works, the authors described the influence of temperature18 and the presence of steam in the gas stream on the adsorption equilibrium,21 demonstrating that low temperatures and low steam percentage favored the adsorption process and that the Dubinin-Radushkevich (DR) model was the most appropriate to describe the system. Cal et al.22,23 studied the adsorption of acetone and benzene on activated carbon fibers, concluding that there was a clear relationship between the pore size distribution and the adsorbate molecular size. They found that adsorption was favored when molecular size pores where accomplished in adsorbate molecules retention. In addition, they applied the Freundlich and DR adsorption models to their experimental results successfully. Lin et al.24 studied the adsorption of different volatile organic carbons (VOCs) on granulated activated carbons and activated carbon fibers. They concluded that not only were the adsorbent properties relevant during the adsorption process but some adsorbate properties, like

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Ind. Eng. Chem. Res., Vol. 42, No. 1, 2003

molecular weight and polarity, should also be considered. Foley et al.25 investigated the adsorption of C5C12 hydrocarbons in the ppbv and ppmv range. They found that the Langmuir model parameters obtained at ppmv concentrations could not be used to predict breakthrough volumes at ppbv concentrations. In addition, they concluded that the Freundlich and Dubinin-Polanyi models are shown to be more successful in describing the adsorption behavior of the VOCs at ppbv levels where breakthrough volumes are independent of the concentration. Bibliographic references on the modeling of PAH adsorption on activated carbons are scarce. In this paper, the adsorption of the most volatile PAHs listed by the USEPA was measured at low concentrations to determine the most suitable method to describe the adsorption process. Using adsorption equilibrium data and previously established adsorption equilibrium equations [Langmuir,26,27 Brunauer-Emmett-Teller (BET),26-28 Freundlich,26,27 and DR26,27,29], adsorption models have been calculated. Theory PAH abatement from waste gas stream generated in power generation systems by carbonaceous materials of high specific surface is a process that is beginning to acquire more and more importance. This is mainly due to the high adsorption ability of these materials to retain volatile compounds at low concentrations, in the ppb range or lower. Inside a carbonaceous material, the adsorbent pore walls can be so close that one surface adsorption potential will overlap the other surface attractive potential, magnifying greatly the ability of the adsorbent to adsorb and/or condense the gas inside the pore. To explain the adsorption process, any mathematical model should take into account the complex chemical and physical characteristics of the system: first, the adsorbate energy attraction for the adsorbent surface should be considered; second, the number distribution and the pore size distribution of the adsorbentswhich will determine the presence of molecular diffusional problems to get into the poressand the quantity of pores that are present at each energy level; third, the adsorbate ability to condense within a pore of a certain size (this pore size is independent of the adsorbent chemical surface, and it will depend on the adsorbent partial pressure); finally, the adsorbate affinity for itself. Adsorbate-adsorbate interactions will affect the thickness of the adsorption layer. Because the energy distribution is influenced by the pore size, this multilayer adsorption will also be affected by the pore size distribution. An appropriate mathematical model should be able to describe the way the above phenomena affect the adsorption equilibrium when the adsorbent partial pressure is changed. Previously established adsorption equilibrium models discussed in this paper include the Langmuir, BET, Freundlich, and DR models. To simplify comparisons between the different models, a unifying nomenclature, proposed by Paulsen and Cannon,30 that is different from the one traditionally found in the literature is used in this work. Table 1 shows the equations used to describe the adsorption process. According to Paulsen and Cannon, the q0 term corresponds to a maximum adsorption capacity and the k term is a coefficient that characterizes equilibrium between the adsorbed and gas

Table 1. Adsorption Isotherm Equilibrium Equations q) Langmuir

p/psat p/psat 1 ) + q q0L kLq0L q)

BET

q0LkL(p/psat) 1 + kL(p/psat)

q0BkBET(p/psat) [1 - (p/psat)][1 - (1 - kBET)(p/psat)] p/psat

q[1 - (p/psat)] Freundlich DR

)

kBET - 1 1 + (p/psat) kBETq0B kBETq0B

(1A)

(1B)

(2A)

(2B)

q ) q0F(p/psat)kF

(3A)

LN(q) ) LN(q0F) + kFLN(p/psat)

(3B)

LN(q) ) LN(qDR) + kDR[LN(psat/p)]2

(4)

phases. In these equations, the PAH gas pressure (p) is normalized by its saturation pressure (pSAT) at 150 °C, listed in Table 2. This normalized variable is called the relative pressure (p/pSAT), and it is the independent variable in all of the equations. The dependent variable (q) is obtained from the adsorption experiments carried out in the experimental rig shown in Figure 1, and it is used to obtain the adsorption isotherms. The PAH adsorption isotherms are shown in parts A-G of Figure 2. The model ability to describe the PAH adsorption process will be determined by the lineal correlation coefficient, r2, the correlation diagram analysis, and the residual values. Each proposed mathematical model assumes a set of hypotheses to predict the adsorption process. Therefore, the Langmuir model assumes that the adsorption energy for every site is equal, that each adsorption site is distinct and well-defined, and that each surface site has the ability to adsorb only one atom or molecule (monolayer adsorption). The Langmuir isotherm further assumes that the adsorption at one surface site is independent of the presence of adsorbed species at the other surface sites. The BET theory is an extension of the Langmuir model that takes into account the multilayer adsorption. The BET isotherm assumes that there are no interactions between adsorbed molecules, that the adsorption energy for the first layer is different from those of the subsequent layers, and that the adsorption energy for these subsequent layers is equal to the condensation energy. In both the Langmuir and BET models, the adsorption energy of the surface is supposed to be uniform throughout the adsorbent surface. This assumption is a simplification of the structure of real carbonaceous materials because they usually have a wide range of pore sizes with a different adsorption energy associated with each pore size. The Freundlich equation allows for the average of different multilayer adsorption energies and different surface adsorption energies, which are both affected by the size and distribution of the pores in an adsorbent. The theory of volume filling of micropores, expressed via the DR equation, is based on the concept of Polanyi. This theory assumes that there is a variable adsorption potential where the free energy of adsorption is related to the degree of pore filling. The application of these different mathematical models to the experimental isotherm data obtained showed how the nature of the adsorbate affects the adsorption process.

Ind. Eng. Chem. Res., Vol. 42, No. 1, 2003 157 Table 2. PAH Physical and Chemical Properties and the Range of Concentration Studied

a Vermeulen, T.; LeVan, M. D.; Hiester, N. K.; Klein, G. In Perry’s Chemical Engineers Handbook; Perry, R. H., Green, D. W., Maloney, J. A., Eds.; McGraw-Hill: New York, 1984. b http://chrom.tutms.tut.ac.jp/JINNO/DATABASE/00alphabet.html. c By the gas saturation method (Regnault, H. V. Ann. Chim. 1845, 1 (15), 129).

Figure 1. Experimental system used for Phe adsorption measurement.

Experimental Section Adsorbents. A carbon material, RWE-1, was used to study the adsorbate influence on the PAH equilibrium adsorption capacities. RWE-1 is a coke from German Rhenish lignite supplied by RWE Rheinbraun. The BET specific surface area was analyzed in an automatic volumetric sorption analyzer (model ASAP 2000, Micromeritics Instrument Co., Norcross, GA) using N2 adsorption at 77 K. Five different experiments were carried out to determine the experimental error, finding a value of around 4%. The calculated value was 300 m2/ g. Adsorbates. Naphthalene (Np), acenaphthene (Ac), fluorene (Fu), phenanthrene (Phe), anthracene (An), fluoranthene (Fl), and pyrene (Py), within the most volatile PAHs designated as priority pollutants by the

USEPA, were selected to carry out this study. The PAH physical and chemical properties are compiled in Table 2. All PAHs were provided by Supelco Inc. and were analysis grade. Adsorption Isotherms. Isotherm experiments were conducted using the experimental rig shown in Figure 1, which was described in detail in previous publications.19,21 The experimental system was used to generate gas streams containing PAHs at the required concentration. The PAH gas generation was obtained by subliming reagent-grade solid PAHs contained in a quartz cylindrical saturator (6.8 mm i.d.) into a stream of pure helium (10 mL/min). The saturator was kept at a fixed temperature by a cylindrical ceramic furnace driven by a proportional-integral-derivative temperature controller ((1 °C accuracy), which allows control of the inlet PAH concentrations in each run. Before starting each experiment, it was necessary to reach a constant and known concentration of PAHs in the adsorbent tubes inlet stream, by passing the saturator outlet gas stream to the flame ionization detector (FID) until these concentrations were obtained. When these were reached, the gas stream was drawn through the adsorbent tubes, starting the reaction time, which lasted until saturation was reached (C ) C0). The adsorbent tubes used were 1/4 in. Teflon tubes that contained a bed composed of 25 mg of adsorbent (100-200 µm average particle size diameter) and 1.0 g of sand. The mixture was held in place by two plugs of silanized glass wool, to provide enough bed length (11 cm), assessing in this way a uniform flow throughout the reactor. Blank tests were carried out to check the inert material adsorption capacity. The temperature of the adsorption reactor was fixed with an accuracy of (1 °C inside a chromatographic furnace.

158


Figure 2. PAH adsorption isotherms on the RWE-1 sample at 150 °C: (A) Np; (B) Ac; (C) Fu; (D) Phe; (E) An; (F) Fl; (G) Py.

Adsorption isotherms were constructed from the adsorption capacity data. Adsorption capacities, w* (mg of PAHs/mg of CA), were calculated as tbC0Q/W, where tb was the breakthrough time for 2% of the penetration time (min), C0 was the PAHs inlet stream concentration (ppm), Q was the flow (mL/min), and W was the adsorbent weight (mg). The PAH concentration (C) in the outlet gas stream was directly measured with a previously calibrated FID. The reproducibility analysis of PAH adsorption capacity was carried out at a Phe inlet concentration of 2.0 ( 0.1 ppm (mean ( standard deviation). A value of 0.11 ( 0.01 mg of Phe/mg of CA-3

was obtained for five experimental runs. The adsorption capacity of each PAH was studied at least at seven different inlet concentrations in the range of 0.025-25 ppm. The exact concentration range for every compound is shown in Table 2. Results and Discussion Adsorption Isotherms. The adsorption isotherms of seven of the most volatile PAHs, prioritized by USEPA as pollutant agents, are shown in Figure 2. These adsorption isotherms at 150 °C were obtained from the

Ind. Eng. Chem. Res., Vol. 42, No. 1, 2003 159 Table 3. Langmuir Adsorption Parameters, Linear Range, and Linear Correlation Coefficient Calculated from the Experimentally Measured w* at 150 °C

Table 4. BET Adsorption Parameters, Linear Range, and Linear Correlation Coefficient Calculated from the Experimentally Measured w* at 150 °C

Langmuir parameters

BET parameters

compound

q0L

kL

[PAH] range

r2

compound

q0B

kB

[PAH] range

r2

naphthalene acenaphthene fluorene phenanthrene anthracene fluoranthene pyrene

0.058 0.045 0.073 0.13 0.14 0.13 0.13

1700 990 2000 300 74 44 75

0.17-25 0.060-4.0 0.027-3.7 0.025-2.1 0.050-3.0 0.064-1.6 0.069-1.0

1.00 1.00 1.00 0.99 1.00 1.00 1.00


0.055 0.056 0.077 0.12 0.10 0.10 0.087

2300 260 480 350 350 81 120

0.17-25 0.060-13 0.027-9.8 0.025-11 0.050-3.0 0.064-1.6 0.069-1.7

1.00 0.99 1.00 1.00 1.00 0.99 1.00

adsorption equilibrium results on the RWE-1 sample for different PAH concentrations. The adsorption isotherms are close to type I of the BDDT (Brunauer, Deming, Deming, and Teller) classification.26 Thus, the initial part of the adsorption of the isotherm represents micropore filling, and the slope of the plateau at higher concentrations is due to multilayer adsorption on the nonmicroporous surface (mesopores, macropores, and the external surface). It is observed that the plateau of the adsorption isotherm has a higher slope at decreasing PAH volatility. Np, the most volatile PAH, has an isotherm plateau almost parallel to the x axis showing no multilayer adsorption. However, Py, the least volatile PAH studied, has an isotherm plateau with the highest slope, probably because this is the PAH in which adsorbate-adsorbate interactions are more favored. Finally, a comparison between adsorption capacities of each PAH shows that the higher the PAH boiling point, the higher the PAH adsorption capacity at the same PAH inlet concentration. These results are consistent with those obtained for VOC31 and PAH19,21 adsorption. Langmuir Model. Table 3 shows the Langmuir model parameters obtained from the PAH adsorption isotherm data. The linear range and the correlation coefficients calculated for each PAH are also shown. The model linear range will be determined by the correlation coefficient (higher than 0.97), the correlation diagram analysis, and the residual values. According to the above-mentioned Langmuir hypothesis, only this model was able to fit the Np isotherm data, where a monolayer adsorption is observed. Because of the high volatility of the Np molecule, the adsorption occurs preferentially in those pores showing molecular size where the adsorption potential is maximum. Concerning the other PAHs, it is observed in Table 3 how the linear range is limited to the lowest concentrations studied where the monolayer adsorption is produced. No significant relationships were found between the Langmuir equation parameters and the PAH physical properties shown in Table 2. BET Model. The BET model parameters, linear range, and correlation coefficients for PAH adsorption isotherm data are compiled in Table 4. The BET equation was able to fit the experimental data in a higher concentration range than the Langmuir model because the BET model takes into account the adsorbate-adsorbate interactions during the adsorption process, as mentioned above. The BET model fit the whole studied concentration range for the most volatile PAHs (Np, Ac, Fu, and Phe) but did not predict the adsorption data for the less volatile studied PAHs (An, Fl, and Py) at high inlet concentrations when the PAHs adsorption process was dependent on the presence of other adsorbed molecules on the adsorbent surface. In the same way as with the Langmuir model, no significant rela-

Table 5. Freundlich Adsorption Parameters, Linear Range, and Linear Correlation Coefficient Calculated from the Experimentally Measured w* at 150 °C Freundlich parameters compound

q0F

kF

[PAH] range

r2


0.11 0.081 0.10 0.20 0.18 0.16 0.15

0.16 0.16 0.10 0.17 0.19 0.22 0.15

0.17-2.8 0.060-13 0.027-9.8 0.025-11 0.050-11 0.064-3.9 0.069-1.0

0.98 0.97 0.97 0.97 0.98 0.98 0.97

tionship was found between the BET parameters, q0B and kB, and the PAH physical properties shown in the Table 2. Freundlich Model. Table 5 shows the Freundlich parameters obtained from PAH adsorption isotherm data on the RWE-1 sample. As happened with the formerly described models, no significant relationship was found between these parameters and the PAH physical properties compiled in Table 2. In Table 5, the linear range and the correlation coefficients for the Freundlich model are also shown. It is observed that this equation was able to fit the adsorption data in all of the studied concentration ranges for Ac, Fu, Phe, An, and Fl but not for Np and Py because the adsorption process was not consistent with the hypothesis model. As mentioned above, because of the high volatility of the Np molecule, the adsorption mainly occurs in those molecular size pores where the adsorption potential is maximum and not in an interval of adsorption energies as is assumed by the Freundlich model. The Py adsorption process is not described by the Freundlich model. As shown in Figure 2G, within the studied concentration range, the micropore filling is completed and the adsorption only occurs on the nonmicroporous adsorbent surface by multilayer adsorption. The Py adsorption capacity on the RWE-1 sample within the experimental condition is linearly related to the inlet concentration, r2 ) 0.994. The behavior of Py is described by the following equation:

q ) q0Py + k0Py(p/psat)

(5)

In eq 5, q0Py (0.086 mg of Py/mg of RWE-1) is the term which corresponds to the Py adsorbed on the micropores and k0Py (0.13 mg of Py/mg of RWE-1) is a constant related to the surface layering.32 The linear model errors were lower than 4% in the entire studied concentration range. As shown in Table 2, Fl presents physical properties close to those of Py, so a similar behavior could have been expected during the adsorption, but it did not occur. This fact could be due to the different physical states of Py and Fl molecules (solid and liquid states, respectively) at 150 °C.

160


Figure 3. Values of the Np adsorption capacities calculated from each model. Experimentally measured values are also shown.

Figure 5. Values of the Phe adsorption capacities calculated from each model. Experimentally measured values are also shown.

Figure 4. Values of the Fu adsorption capacities calculated from each model. Experimentally measured values are also shown.

Figure 6. Values of the Py adsorption capacities calculated from each model. Experimentally measured values are also shown.

Table 6. DR Adsorption Parameters, Linear Range, and Linear Correlation Coefficient Calculated from the Experimentally Measured w* at 150 °C

Phe, and Py adsorption isotherm values. The logarithmic x-axis scale was used to improve the data understanding. Within the studied experimental conditions, any model could not fit the adsorption equilibrium values obtained for each PAH in the whole concentration range. It is observed that not only does the Langmuir model not fit the whole concentration range for most of the studied PAHs but the model calculated values are around 20% lower than the experimental ones when concentration is in the ppbv range. At low adsorbate concentrations, the Langmuir model is simplified to Henry’s law, predicting a linear relationship between adsorbate concentration and adsorption capacity. This relationship was not observed in the experimental results probably because of adsorbate-adsorbate interactions even at low concentrations. This effect was also observed when the BET model was applied to the experimental results at the ppbv range, although this model could fit the experimental results in a wider range than the Langmuir model as mentioned above. Figures 3-6 show that the Freundlich model has proven to be the most successful method to explain the experimental results except in the cases of Np, where a monolayer adsorption occurs, and Py, where a surface layering is observed. As for the other PAHs, calculated values are within the experimental error in the entire concentration range. The DR model was the appropriate method to explain the adsorption process at very low concentrations usually emitted in energy generation processes, ppb range or lower, except in the case of Py. In this concentration range, the PAH adsorption is produced by micropore

DR parameters compound

q0DR

kDR × 103

[PAH] range

r2

naphthalene acenaphthene fluorene phenanthrene anthracene fluoranthene

0.068 0.050 0.081 0.12 0.14 0.13

-12 -12 -9.2 -14 -25 -41

0.17-25 0.060-4.0 0.027-5.0 0.025-2.1 0.050-3.0 0.064-1.6

0.98 0.99 0.98 0.97 0.99 0.97

DR Model. The DR parameters for PAH data are shown in Table 6. In this table, the linear range and the correlation coefficient are also included. This model describes the adsorption process as a pore-filling effect rather than a layer-by-layer adsorption effect so the accuracy of using the DR equation varies for different adsorbate-adsorbent systems and concentration ranges. Therefore, this model only fits the total experimental data for the Np adsorption because of its high volatility at 150 °C, which will avoid the multilayer adsorption. In the other PAHs, the DR equation only fits the experimental data at low concentrations where micropore filling occurs, except for Py adsorption. As mentioned above, in the studied concentration range, the micropore filling for Py is completed and the adsorption is given by surface layering. Therefore, eq 5 describes the adsorption process better than any other mathematical model studied. Comparative Evaluation of the Adsorption Models. Figures 3-6 show the Langmuir, Freundlich, BET, and DR adsorption isotherms obtained from Np, Fu,

Ind. Eng. Chem. Res., Vol. 42, No. 1, 2003 161

filling and the predicted adsorption capacities are within the experimental error of the system. Therefore, results show that the adsorption process is different and dependent on the adsorbate nature. There is not a unique model able to explain the isotherm in the entire concentration range studied for each PAH. Acknowledgment This work has been partially supported by the European Union, Energy and Transport Commission (Contract 7220/Pr 067) and by the General Council of Aragoń (DGA, Spain) through the Pre-Doc Grants of T.G. and J.M.L. R.M. and M.S.C. thank the Spanish Science and Technology Ministry for the Ramoń y Cajal Program contract. Literature Cited (1) Mastral, A. M.; Calleń, M. S.; Murillo, R.; Garcıá, T. Polycyclic Aromatic Hydrocarbons and Organic Matter Associated to Particulate Matter Emitted from Atmospheric Fluidized Bed Coal Combustion. Environ. Sci. Technol. 1999, 33, 3177. (2) Williams, P. T. Sampling and Analysis of Polycyclic Aromatic Compounds from Combustion SystemssA Review. J. Inst. Energy 1990, 63, 22. (3) Lee, M. L.; Novotny, M.; Bartle, K. D. Analytical Chemistry of Polycyclic Aromatic Hydrocarbons; Academic Press: New York, 1981. (4) Marr, L. C.; Kirchstetter, T. W.; Harley, R. A.; Miguel, A. H.; Hering, S. V.; Hammond, S. K. Characterization of polycyclic aromatic hydrocarbons in motor vehicle fuels and exhaust emissions. Environ. Sci. Technol. 1999, 33 (18), 3091. (5) Kirton, P. J.; Crisp, P. T. The Sampling of Coke Oven Emissions for Polycyclic Aromatic HydrocarbonssA Critical Review. Fuel 1990, 69 (5), 633. (6) Rogge, W. F.; Hildemann, L. M.; Mazukek, M. A.; Cass, G. R.; Simoneit, B. R. T. Sources of Fine Organic Aerosol. 5. Natural Gas Home Appliances. Environ. Sci. Technol. 1993, 27 (13), 2736. (7) Oanh, N. T. K.; Reutergardh, L. B.; Dung, N. T. Emission of Polycyclic Aromatic Hydrocarbons and Particulate Matter from Domestic Combustion of Selected Fuels. Environ. Sci. Technol. 1999, 33 (16), 2703. (8) Zimmermann, R.; Heger, H. J.; Kettrup, A. On-line monitoring of traces of aromatic-, phenolic- and chlorinated components in flue gases of industrial scale incinerators and cigarette smoke by direct-inlet laser ionization mass spectrometry (REMPITOFMS). Fresenius’ J. Anal. Chem. 1999, 363 (8), 720. (9) Mastral, A. M.; Calleń, M. S.; Murillo, R.; Garcıá, T. Assessment of PAH emissions as a function of coal combustion variables in fluidised bed. 2. Air excess percentage. Fuel 1998, 77 (13), 1513. (10) Mastral, A. M.; Calleń, M. S.; Murillo, R.; Garcıá, T. Influence on PAH emissions of the air flow in AFB coal combustion. Fuel 1999, 78 (13), 1553. (11) Mastral, A. M.; Calleń, M. S.; Murillo, R. Assessment of PAH emissions as a function of coal combustion variables. Fuel 1996, 75 (13), 1533. (12) Sloss, L. L.; Gardner, C. A. Sampling and analysis of trace emissions from coal-fired power stations; IEA Coal Research IEACR/77; IEA: London, 1995; p 48. (13) Mastral, A. M.; Calleń, M. S. A review on polycyclic aromatic hydrocarbon (PAH) emissions from energy generation. Environ. Sci. Technol. 2000, 34 (15), 3051.

(14) Grace Lee, W.-M.; Tong, H.-C.; Yeh, S.-Y. Partitioning Model of PAHs between Gaseous and Particulate Phases with Consideration of Reactivity of PAHs in an Urban Atmosphere. J. Environ. Sci. Health 1993, A28 (3), 563. (15) Liljelind, P.; Unsworth, J.; Maaskant, O.; Marklund, S. Removal of dioxins and related aromatic hydrocarbons from flue gas streams by adsorption and catalytic destruction. Chemosphere 2001, 42, 615. (16) Weber, R.; Plinnke, M.; Xu, Z.; Wilken, M. Destruction efficiency of catalytic filters for polychlorinated dibenzo-p-dioxin and dibenzofurans in laboratory test and field operationsinsight into destruction and adsorption behavior of semivolatile compound. Appl. Catal. B 2001, 31, 195. (17) Cudahy, J. J.; Helsel, R. W. Removal of products of incomplete combustion with carbon. Waste Manage. 2000, 20, 339. (18) Mastral, A. M.; Garcıá, T.; Calleń, M. S.; Navarro, M. V.; Galbań, J. Assessment of phenanthrene removal from hot gas by porous carbons. Energy Fuels 2001, 15 (1), 1. (19) Mastral, A. M.; Garcıá, T.; Calleń, M. S.; Navarro, M. V.; Galbań, J. Removal of naphthalene, phenanthrene, and pyrene by sorbents from hot gas. Environ. Sci. Technol. 2001, 35 (11), 2395. (20) USEPA, EPA-456/R-95-003, Office of Air Quality Planning and Standards, Research Triangle Park, NC, May 1995. (21) Mastral, A. M.; Garcıá, T.; Murillo, R.; Calleń, M. S.; Lopez, J. M.; Navarro, M. V. Moisture Effects on the Phenanthrene Adsorption Capacity by Carbonaceous Materials. Energy Fuels 2002, 16, 205. (22) Cal, M. P.; Rood, M. J.; Larson, S. M. Removal of VOCs from humidified gas streams using activated carbon cloth. Gas Sep. Purif. 1996, 10 (2), 117. (23) Cal, M. P.; Larson, S. M.; Rood, M. J. Experimental and Modeled Results Describing the Adsorption of Acetone and Benzene onto Activated Carbon Fibers. Environ. Prog. 1994, 13 (1), 26. (24) Lin, S. H.; Hsu, F. M.; Ho, H. J. Gas-Phase Adsorption of VOC by GAC and Activated Carbon Fiber. Environ. Technol. 1995, 16 (3), 253. (25) Foley, P.; Gonzalez-Flesca, N.; Zdanevitch, I.; Corish, J. An investigation of the adsorption of C-5-C-12 hydrocarbons in the ppmv and ppbv ranges on Carbotrap B. Environ. Sci. Technol. 2001, 35 (8), 1671. (26) Gregg, S. J.; Sing, K. S. W. Adsorption Surface Area and Porosity, 2nd ed.; Academic Press: London, 1982. (27) Lowell, S.; Shields, J. K Powder Surface Area and Porosity, 3rd ed.; Chapman and Hall: London, 1991. (28) Brunauer, S.; Emmett, P. H.; Teller, E. Adsorption of gases in multimolecular layers. J. Am. Chem. Soc. 1938, 60, 309. (29) Stoekli, H. F. Porosity in Carbons, 1st ed.; J. W. Patrick: London, 1995. (30) Paulsen, P. D.; Cannon, F. S. Polytherm model for methylisobutyl ketone adsorption onto coconut-based granular activated carbon. Carbon 1999, 37 (2), 249. (31) Karpowicz, F.; Hearn, J.; Wilkinson, M. C. Dynamic adsorption of vapours by activated carbons and by polymer-derived adsorbents: 1. Adsorption at 0% RH. Adsorption 2000, 6 (4), 337. (32) Nguyen, C.; Do, D. D. Adsorption of benzene and ethanol on activated carbon, MCM-41 and zeolite Y. Adsorpt. Sci. Technol. 1998, 16 (6), 439.

Received for review March 11, 2002 Revised manuscript received September 11, 2002 Accepted September 13, 2002 IE020189I

Measurements of Polycyclic Aromatic Hydrocarbon Adsorption on

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