Prediction of VOC adsorption performance for estimation of service life of activated carbon based filter media for indoor air purification

Accepted Manuscript Prediction of VOC adsorption performance for estimation of service life of activated carbon based filter media for indoor air purification Roman Ligotski, Uta Sager, Ute Schneiderwind, Christof Asbach, Frank Schmidt PII:

S0360-1323(18)30736-4

DOI:

https://doi.org/10.1016/j.buildenv.2018.12.001

Reference:

BAE 5834

To appear in:

Building and Environment

Received Date: 6 September 2018 Revised Date:

6 November 2018

Accepted Date: 1 December 2018

Please cite this article as: Ligotski R, Sager U, Schneiderwind U, Asbach C, Schmidt F, Prediction of VOC adsorption performance for estimation of service life of activated carbon based filter media for indoor air purification, Building and Environment (2019), doi: https://doi.org/10.1016/ j.buildenv.2018.12.001. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT

Prediction of VOC Adsorption Performance for Estimation of Service Life of Activated Carbon Based Filter Media for Indoor Air Purification Roman Ligotskia *, Uta Sagerb, Ute Schneiderwindb, Christof Asbachb, Frank Schmidta

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a

University of Duisburg-Essen, Nanoparticle Process Technology (NPPT), Duisburg, Germany b Institut für Energie- und Umwelttechnik e. V. (IUTA), Duisburg, Germany

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*Corresponding author: [email protected], phone: +49 203 379 3923, fax: +49 203 379 3547, address: office MC 142, Lotharstraße 1, D-47057 Duisburg Keywords: Adsorption; VOC; Filter Media; Indoor Air Quality; HVAC; Model

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Abstract

The importance of adsorptive purification of the gas phase in HVAC-systems has constantly increased over the last few years, because people spend a large part of the day indoors. During this time they can be exposed to a variety of harmful

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gaseous contaminants, e.g. volatile organic compounds (VOC), which negatively influence health. Adsorptive HVAC-filters can help to reduce the concentration levels of noxious gases. For the comparison of HVAC-filter media the standard ISO 10121-

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1 determines test procedures. In ISO 10121 toluene is suggested as representative test substance for VOC at concentrations of 9 or 90 ppm in conditioned air (23 °C, 50

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% RH). The test concentrations in the standard tests are clearly higher than VOC concentrations in real buildings in order to limit testing times and to avoid being dependent on highly sensitive measurement technology. In this study, a methodology was investigated that forecasts breakthrough curves of toluene at concentrations down to 0.09 ppm predicted from measurement data at normatively proposed higher concentrations. The results can be used to estimate the service life of adsorptive filter media. The prediction is based on the isotherm equations of

1

ACCEPTED MANUSCRIPT Langmuir, Freundlich or Dubinin-Radushkevich and the Wheeler-Jonas equation. The methodology was validated using three commercially available activated carbon based filter media. Good agreement between prediction and experimental data was achieved for s-shaped and moderate agreement for convex breakthrough curves.

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For the prediction of the equilibrium, the Freundlich and Dubinin-Radushkevich

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equation have proven to be accurate.

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ACCEPTED MANUSCRIPT 1 Introduction The duration of people´s stay in indoor environments is continuously increasing. It is estimated that Europeans and Americans spend an average of 85-90% of their time indoors [1] and are exposed to various gaseous pollutants with the corresponding

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negative effects on health and well-being [2]. Re-circulating ventilation systems, used to minimize heating and air-conditioning costs, can further enrich health-relevant substances in interiors [3]. VOC (volatile organic compounds) are a particularly

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relevant group of indoor air pollutants. Benzene, toluene, ethylbenzene, o-xylene, styrene, as well as terpenes α-pinene and limonene were found as VOCs in the

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indoor air of e.g. residential and office buildings, schools and shopping centres [411]. The real indoor concentrations of these substances vary depending on geographical location, climate, season, type of building, building materials used, furniture and the use of indoor spaces [6, 12]. The latter includes, for example, the

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ventilation behavior, type and frequency of use of cleaning and cosmetic products, etc. The respective sources of VOC are diverse and often difficult to identify. The highest concentrations are measured in renovated rooms, in new buildings or in

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rooms with new furniture [8, 13].

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One option for reducing VOC concentrations indoors is to integrate adsorptive filters into ventilation systems. Adsorptive HVAC-filters have various designs such as cartridges with granulated activated carbon (AC) or bag filters and filter cassettes made of flat sheet filter media. The latter have a lower pressure drop compared to cartridges, which can be an important design and selection criterion in view of the energy efficiency of the ventilation systems. In order to enable testing of filter media according to standard procedures the international standard ISO 10121-1 [14] came into force in 2014. In North America, 3

ACCEPTED MANUSCRIPT ASHRAE 145.1 [15] is an alternative standard for testing the filter media against VOCs. According to ISO 10121, the volatile aromatic hydrocarbon toluene is proposed as a representative substance. For general comparative tests of adsorption performance and capacity, a volumetric concentration of 9 or 90 ppm in conditioned

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air (23 °C, 50 % RH) is given as a guide value in ISO 10121. In accordance to ASHRAE 145.1 a concentration of 100 ppm of a VOC (e.g toluene) is used for accelerated tests. However, a VOC concentration of 9 ppm is already a high value

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from the point of view of the IAQ (indoor air quality) [16, 17]. Such indoor VOC concentrations are measured in individual cases [18], but are usually orders of

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magnitude lower [4, 10]. The high concentrations are used in the standard in order to limit the test time. The experiments at low concentrations would require a very long experimental time (equal to the life expectancy of the filter), as e.g. van Osdell et al. [19] showed in first investigations on the adsorption of toluene on activated carbons

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under indoor air conditions. These results are in accordance with the experiments with other substances as shown by further researchers [20-22]. Furthermore, a correspondingly sensitive measuring technique with low detection limits is required.

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With decreasing test gas concentration, not only the time but also the measurement effort is increased. Since the respective standard is intended to form a compromise

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between the measurement effort and the meaningfulness of the test results, such a high concentration as 9 or 90 ppm therefore makes sense. However, knowledge of the more realistic adsorption behavior and thus the estimation of service life of filter media and filters is desirable from both the designer´s and the user's point of view. To counter this discrepancy, a combination of measurements at normatively specified concentrations with subsequent calculation of the breakthrough curves at low concentrations can be an alternative.

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ACCEPTED MANUSCRIPT Since the topic of the description of breakthrough curves at low concentrations has gained importance in recent years, other researchers have also dealt with analysis and prediction methods of breakthrough curves of organic and inorganic substances in the low concentration range [19, 22-27]. Analytical and semi-empirical approaches

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were investigated. Semi-empirical approaches such as the Wheeler-Jonas equation have been highlighted as particularly useful. With this equation the breakthrough time in a fixed bed can be calculated as a function of the inlet concentration considering

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the properties of the fixed bed (mass, bulk density and equilibrium capacity of adsorbent) and operation parameters (volumetric flow rate, inlet and outlet

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concentration). A major advantage of the Wheeler-Jonas equation is that the required parameters are easily measurable and accessible [27]. In order to use the WheelerJonas equation for predictions, equilibrium capacities must be determined. This is done with a suitable isotherm equation. The equations of Langmuir, Freundlich and

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Dubinin-Radushkevich are appropriate for the description of equilibrium capacity at low concentrations of organic molecules such as toluene on activated carbon [19, 2831].

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The lowest concentrations at which a Wheeler-Jonas prediction of VOC breakthrough

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curves based on measurement data at higher concentrations could be successfully applied are between 200 and 15 ppm MEK as well as between 300 and 15 ppm nhexane [22]. In this study the authors showed a very good agreement of the calculated and the experimental breakthrough curves using the Langmuir equation for the prediction of equilibrium capacity. They also compared the prediction with the Wheeler-Jonas equation and with a dynamic simulation (differential mass balance and LDF approach). Using the Wheeler-Jonas equation, they have achieved a better estimation of breakthrough curves at low concentrations than with dynamic 5

ACCEPTED MANUSCRIPT simulation. However, the authors note that the Wheeler-Jonas based prediction method still needs to be validated at lower concentrations relevant to indoor air. This paper focuses on this topic. Breakthrough curves of toluene through three commercially available activated carbon based filter media are predicted at 0.9 or

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0.09 ppm using the Wheeler-Jonas equation with experimental input data of breakthrough curves at 90 and 9 ppm. The isotherm equations of Langmuir, Freundlich and Dubinin-Radushkevich are validated for a necessary accurate

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description of the equilibrium capacity.

2 Theory

For predicting breakthrough curves, the equilibrium capacity

, which is described

via adsorption isotherms, as well as the mass transfer (adsorption dynamics,

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adsorption kinetics), which is taken into account via transfer coefficients, are important parameters [32]. In the following, the relevant isotherm models and then the semi-empirical Wheeler-Jonas approach for the description of breakthrough

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curves are presented.

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2.1 Adsorption isotherms:

Adsorption isotherms describe the mass-specific quantity of the adsorbed substance at equilibrium gas phase

[mg/mg] as a function of the concentration of this substance in the

[ppm] under isothermal and isobaric conditions. Various isotherm

models exist, which are based on different physical assumptions or are of semiempirical or purely empirical character [33]. The adsorption isotherms used in this study are shortly explained.

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ACCEPTED MANUSCRIPT The Langmuir isotherm [34a, 34b] is based on the assumption of a (energetically) homogeneous adsorbent surface as well as the neglect of the interactions between the adsorbed molecules [33]. In the form according to Axley [35]: 1+

∙

∙

∙

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=

1

with the maximum adsorption capacity at a monomolecular loading of the adsorbent as a constant and the input concentration

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, the Langmuir coefficient

.

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At very low concentrations, the Langmuir equation reduces to the linear or Henry isotherm. The latter is therefore a special case of the Langmuir isotherm [35, 36]. The linear isotherm can be expressed in the following form [35]: ∙

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=

Where the proportionality constant is the Henry coefficient

2

. With the linear

isotherm equation, the equilibrium capacities of toluene on activated carbon below

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1.5 ppm could be described by Pei and Zhang [29]. The concentration range of the

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investigation was between 0.1 and 100 ppm. Seo et al. [37] report for the adsorption of toluene on activated carbon that the adsorption equilibrium shows the Henry behavior only below 1 mg/m³ (0.27 ppm). However, the adsorbed amount up to a breakthrough of 5 % was considered in this study. The probably best known empirical isotherm equation postulated by Ostwald, Boedecker and Freundlich [38] is the Freundlich isotherm [22]: =

∙ 7

/

3

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and the Freundlich exponent 1/ , where usually

n > 1 applies [33]. This initially empirical approach was theoretically derived by Zeldovich [33, 36], assuming an energetically heterogeneous surface, whose energy distribution can be described by an exponentially decreasing function. The Freundlich

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equation is therefore suitable for describing adsorption equilibria of substances on heterogeneous surfaces, such as organic molecules on activated carbons [33, 35, 36, 39]. The disadvantage of the Freundlich equation is that it is not applicable in the

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whole concentration range. It has neither the Henry behavior at low concentrations

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nor a finite value at high concentrations [33].

A well-known semi-empirical approach is of Dubinin and Radushkevich [40]. It is based on the potential theory of Polanyi [41] and the filling of micropores is assumed as adsorption mechanism. In the Dubinin-Radushkevich (D-R) equation [33]: ∙ exp −

the specific adsorbate volume partial pressure % .

1

∙ !" ∙ # $

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=

%&, () * %

4

at equilibrium is described as a function of the

can be converted into the specific adsorbed mass

via the

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density of the adsorbate assumed as liquid at a given absolute temperature ". The

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same applies for the specific maximum adsorbed volume the D-R equation are the characteristic energy

. The other parameters of

, the ideal gas constant ! and the

saturation vapor pressure %&, at a given temperature. The pressures can be converted into concentrations (saturation concentration: concentration:

&,

and gas phase

) and vice versa using the ideal gas equation. The D-R isotherm

equation has been widely used for years to describe the adsorption equilibria of vapors on activated carbons and zeolites in the subcritical range [31, 33, 42]. A

8

ACCEPTED MANUSCRIPT disadvantage of the D-R equation is that it does not show correct Henry behavior when the partial pressure or concentration is approaching zero [33]. 2.2 Semi-empirical breakthrough model: In addition to analytical methods for modeling breakthrough curves, such as the

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differential mass balance, for example, using the Linear Driving Force (LDF) approach [43] to describe kinetics [23, 44], semi-empirical models are a suitable tool. One of the probably best-known approaches is the Wheeler-Jonas equation [45, 46],

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which was validated using various systems and identified to be useful for modeling

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and predicting breakthrough curves [27]. This equation was originally derived from a mass balance over a fixed bed reactor for a first order chemical reaction and modified for use in adsorption [47]. The modified Wheeler-Jonas equation is: -∙ +, = ./ ∙ c

1, ∙ − 23 ∙

∙ ln 6

1−

78

78

from the fixed bed

78

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where +, is the time at a defined relative breakthrough

9

78 /

5

(outlet concentration

[mg/m³] related to the inlet concentration

[mg/m³]), - the

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mass of adsorbent, ./ the volumetric flow rate, 1, the bulk density of the adsorbent

and 23 the overall mass transfer coefficient. The first term on the right-hand side is

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the ratio of the fixed bed capacity to the mass flow of a substance into the fixed bed. This term is thermodynamically consistent and is also called stoichiometric time +& . If

the second term on the right hand side were zero, the breakthrough curve would take the form of a Heaviside function based on an ideal, infinitely fast mass transfer (Figure 1, dashed line). This would mean that a complete separation first takes place in the fixed bed until the capacity at time +& reaches its maximum to exhibit a

complete breakthrough. This breakthrough curve is called the stoichiometric breakthrough curve [47, 48]. The second, empirical term on the right-hand side takes 9

ACCEPTED MANUSCRIPT into account the influence of the mass transfer kinetics and the fixed bed dynamics via the mass transfer coefficient 23 . So with the modified Wheeler-Jonas equation point symmetric (s-shaped) breakthrough curves with an inflection point at the time +& 78 /

and the relative breakthrough of

= 50 % are modeled. The stoichiometric 78 /

= 50 %)

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time +& is therefore the time until 50 % breakthrough. With +& = +, (

the modified Wheeler-Jonas equation can be presented in the following form [44]: ∙ ln 6

1−

78

78

9 :;+ℎ +& = + $

78

= 50 %( =

-∙ ./ ∙ c

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1, ∙ +, = +& − 23 ∙



6

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A comparison of the stoichiometric breakthrough curve and the result of the

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Wheeler-Jonas equation is shown in Figure 1.

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Figure 1: Schematic comparison of the stoichiometric (dashed) and a breakthrough curve from the modified Wheeler-Jonas equation (solid)

The determination of the equilibrium capacity is done by measurements or with the help of one of the isotherm equations shown above (section 2.1). To predict the

overall mass transfer coefficient 23 of the Wheeler-Jonas equation, several empirical correlations have already been published. An overview and validation of seven of the best known equations for predicting 23 are given by Zhou et al. [49]. Six of these correlations do not consider the influence of challenge gas concentration on the overall mass transfer coefficient. Wood and Lodewyckx [50] countered this situation. 10

ACCEPTED MANUSCRIPT For this purpose, a correlation was established which takes into account the influence

of the concentration on the overall mass transfer coefficient 23 [1/min] via the equilibrium capacity

[50]: 23 = @ ∙ A

.CC

∙

.DE

∙ FGH

.E

∙$

I

(

7

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with the overall correlation coefficient @, the affinity coefficient A, linear flow velocity , particle diameter FG , the molecular weight of the vapor I and

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exponent.

an adjustable

The affinity coefficient A can be calculated using the molar polarizability J [51]: .DE

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A = 0.08622 ∙ J

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The molar polarizability can be determined using the Lorenz-Lorenz equation [51]: P

−1

P+2

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J =

I N O∙ 1

The substance parameters of this equation (1 : liquid density of the vapor,

9 P:

refractive index) can be taken from a handbook [52].

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Another way to determine the mass transfer coefficient is to measure and consider 23

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as a function of the concentration [22]. The advantage is that neither the knowledge of the adsorbent geometry nor the substance data are required.

3 Materials and methods 3.1 Materials: The experimental and theoretical investigations were carried out using three different commercially available filter media (media A, B and C). Experiments were conducted at 90 - 40 - 9 - 0.9 - 0.09 ppm toluene in conditioned air (23 °C and 50 % RH). The 11

ACCEPTED MANUSCRIPT media A and B were tested with a face velocity of 5.6 cm/s and the medium C with 18 cm/s. The respective mean face velocity corresponds to the medium face velocity within the assembled filter at the intended operating volume flow rate. It is determined from the nominal volume flow through the filter in relation to the installed media

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surface area.

The media examined differ both in their macroscopic properties, which also affects the pressure drop of the media, and in the properties of the activated carbons used.

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Figure 2 first shows the media in photographic form and the medium B additionally

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using the SEM images to illustrate and compare the macroscopic properties (Figure 2, B-3 and B-4). The media A and C are classic combination filter media with a thin layer of activated carbon granulate which is fixed between two nonwovens. Medium B consists of a polymer fiber matrix with clusters of activated carbon and binder within this fiber structure. The bulk density of the activated carbon in the filter medium

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B is significantly lower than in the media A and C. Table 1 compares the relevant parameters of the filter media. The BET surfaces of the activated carbons were determined from measurements of the nitrogen adsorption isotherms at 77 K with the

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Quantachrome Autosorb device.

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Figure 2: Photographic representation of the adsorptive media blanks (X-1), the media structure (X-2) and SEM images of medium B from the upstream side (B-3) and the crosssection (B-4)

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ACCEPTED MANUSCRIPT Table 1: Properties of the adsorptive filter media investigated

Medium

Thickness

Adsorbent

Pressure drop

mass

BET-surface area in m²/g adsorbent

in g/100 cm²

∆p(v) in Pa

Medium A

1.65

1.6

7 Pa (5.6 cm/s)

864

Medium B

6

2.2

< 5 Pa (5.6 cm/s)

584

Medium C

1.3

5.6

20 Pa (18 cm/s)

842

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in mm

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6 Pa (5.6 cm/s)

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Figure 3 shows the differential pore width distributions of the ACs of investigated media calculated from nitrogen isotherms at 77 K using NLDFT (Non-Local Density

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Functional Theory) assuming slit pores as pore geometry [53].

Figure 3: Differential pore width distributions of the activated carbons of the investigated adsorptive filter media

As can be seen in Figure 3, the activated carbons used in media A, B and C differed particularly with regard to the micropore volume (w < 20 Å) and slightly with regard to the mesopore volume (2 Å < w < 50 Å). The activated carbons of media A and C have a higher volume fraction of micropores below 15 Å (1.5 nm) than the activated carbon of medium B. However, a higher mesopore fraction was measured on the 14

ACCEPTED MANUSCRIPT activated carbon of the latter medium than on the activated carbons of media A and C. The BET surfaces of the activated carbons of media A and C are also larger than those of medium B (Table 1).

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3.2 Experimental set-up and testing procedure:

The set-up for the adsorption breakthrough tests with filter media is shown schematically in Figure 4. A defined air flow rate is drawn in from a central duct by

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means of a radial fan and conditioned to the desired conditions according to the

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ISO 10121 (23 °C, 50 % RH) using two heat exchangers (cooling and heating coil) and a steam generator. Temperature and humidity are controlled by a temperature and humidity sensor. Two PID controllers ensure constant temperature and relative humidity conditions over a long period of time. The conditioned air is flowing into the test chamber in which an adsorber with an inner diameter of 113 mm and a height of

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750 mm is installed. Filter media in the form of round blanks with an area of 100 cm² are inserted and fixed in the adsorber. Using an external pump, conditioned air is

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drawn in and mixed with the toluene/air mixture provided in a static mixer. The toluene vapor is supplied by a temperature-controlled bubbler, operated with clean

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air from a compressed air supply. The air mass flow rate is controlled by a mass flow controller. The test gas mixture with a defined toluene concentration flows through the filter medium with a constant volumetric flow rate and returns to the test channel after cleaning in a separate activated carbon cartridge. For the experiments with concentrations ≥ 0.9 ppm two flame ionization detectors (FID, Bernath Atomic, Wennigsen,

Germany)

and

for

0.09 ppm

two

proton-reaction-transfer-mass

spectrometers (PTR-MS, Ionicon, Innsbruck, Austria) are used. The analyzers

15

ACCEPTED MANUSCRIPT continuously sample from upstream and downstream of the filter medium. In addition, the pressure and temperature are measured both before and after the filter medium. In order to ensure a homogeneous flow through the adsorber, honeycomb structures are installed as flow straighteners at the inlet and outlet of the adsorber. In

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preliminary tests, a uniform spatial distribution of toluene was investigated during the flow through the adsorber. Sampling in the raw gas was carried out at three different points of the cross-section (in the middle and at the respective wall). The measured

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concentrations were almost identical (in accordance to ISO 10121 below 5 %

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deviation).

Figure 4: Scheme of the test set-up for experiments on adsorptive filter media

At the beginning of each test, the measuring instruments were calibrated. Subsequently, a test dosage was carried out in the empty adsorber to adjust the 16

ACCEPTED MANUSCRIPT concentration setpoint and to compare the measured values of the FIDs or PTR-MS on the raw (

and clean gas (

78 )

side. The ratio of

78 /

should be 1 ± 0.02

according to ISO 10121. After the test dosage, the test chamber was purged and a medium blank was inserted into the adsorber. Next, the medium was conditioned with

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challenge gas-free air for 15 minutes according to the standard. Subsequently, toluene dosing was started.

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3.3 Prediction of breakthrough curves at lower concentrations:

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The modified Wheeler-Jonas equation is to be used to predict breakthrough curves at concentrations relevant for indoor air (0.9 or 0.09 ppm) based on measurements at normatively recommended concentrations (9 and 90 ppm). In addition to the tests at 9 and 90 ppm, it makes sense to carry out a test at a third concentration (e.g. 40 ppm) in order to be able to make a further measurement point for the prediction of

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(step 1 below) and 23 (step 2 below) for equation 6.

Step 1). The prediction of the equilibrium capacity at lower concentration

,GQ R

is

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based on an isotherm fit to the equilibrium toluene capacities at 9, 40 and 90 ppm. The equilibrium capacities are then approximated at 0.9 or 0.09 ppm using the

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appropriate isotherm equation. The equilibrium capacity at higher concentrations are determined from the recorded breakthrough curves using a mass balance with the measured values at points in time i: =

./ I %, S ∙U -! " 8T

,

−

78,

V Δ+

10

in which I is the molar mass of toluene (92.14 g/mol), - the activated carbon mass within the medium, ! the ideal gas constant, " the absolute temperature, % the measured absolute pressure of the system and Δ+ the time interval between the 17

ACCEPTED MANUSCRIPT measuring points. The latter is 10 s. During the entire experiment, both the inlet and outlet concentrations were measured continuously. For the calculation of the equilibrium capacity, the experiments were carried out up to a breakthrough of 100 %

shows the procedure for determining the isotherm values.

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and all measured values were taken into account. Figure 5 (step 1) schematically

Step 2). To estimate the overall mass transfer coefficients of equation 6 at lower concentrations 23,GQ

R

the overall mass transfer coefficients 23 are plotted as a

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function of the concentration. In the concentration range considered, using a linear regression, the mass transfer coefficient at the desired low concentration can be

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predicted, as will be shown later. The calculation of 23 at higher concentrations is based on a non-linear fit of equation 6 to the measured breakthrough curves with the Levenberg-Marquardt algorithm according to the principle of least squares with 23 as

the only fit variable. For the stoichiometric time +& at the respective concentration, the

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measured value of the time up to a breakthrough of 50 % is used as a constant. The equilibrium capacity

is known from step 1 and all other parameters of the

modified Wheeler-Jonas equation (equation 6) are operating parameters (./ ,

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material parameters (-, 1, ) or measurement data +,

78 /

),

.

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Step 3). To estimate the breakthrough curve at low concentrations, first +&,GQ ∙XYZ,[\Y] ^/∙_`a

must be calculated from the first term of equation 5 or 6 with

step 1. Using the 23,GQ

R

,GQ R

R

=

from

from step 2 and the operating and material parameters, the

breakthrough time +, can then be calculated as a function of the relative breakthrough

78 /

.

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ACCEPTED MANUSCRIPT

Figure 5: Step diagram for the prediction method using the example of Medium A

4 Results and discussion

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4.1 Isotherms and validation of isotherm models: The isotherms of toluene at 23 °C and 50 % RH determined on the media examined are shown in Figure 6. All three isotherms are of type I according to IUPAC

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classification, which is often given for the adsorption of hydrocarbons on microporous

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activated carbons [53]. A comparison of the equilibrium capacities of the three media under consideration shows that in the investigated concentration range the medium A has the highest and the medium B the lowest toluene capacity. The medium A, whose AC has the highest micropore volume of pores below 1.5 Å (see Figure 3), shows the highest toluene capacity and the medium B (lowest micropore volume of the AC) the lowest toluene capacity. To obtain an accurate prediction of the equilibrium capacity at low concentrations, an isotherm model must be selected that describes the measured data with sufficient 19

ACCEPTED MANUSCRIPT accuracy. To validate the known isotherm models described above (section 2.1), these were fitted to the experimental equilibrium data of toluene at 23 °C and 50 % RH for the three media investigated (Figure 6) with the Levenberg-Marquardt algorithm. The parameters of the respective isotherm models determined from the fits

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to the measured capacity data and the corresponding coefficients of determination are listed in Table 2.

First, it can be seen that the Langmuir equation only describes well the equilibrium

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capacities of the medium B, with a lower micro- and higher mesopore content in

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relation to the other two media. The representation of the equilibrium capacities of the more microporous media A and C with the Langmuir equation is not satisfactory. However, a description of the equilibrium capacities as a function of the inlet concentration of all three media can be achieved with very good accuracy using both the Freundlich and Dubinin-Radushkevich (D-R) equations. This result is also in

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agreement with other studies [19, 28, 30, 31]. For this reason, the Freundlich and D-

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R equations were used to predict the breakthrough curves at lower concentrations.

20

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Figure 6: Toluene isotherms of media A, B and C at 23 °C and 50 % RH Table 2: Determined Langmuir, Freundlich and D-R isotherm model parameters of media A, B and C by non-linear fit

Medium B

Medium C

0.477

0.09

0.773

/ mg/mg

0.297

0.217

0.225

R²

0.8538

0.944

0.8267

0.124

0.045

0.112

4.697

2.974

5.681

0.998

0.996

0.999

/ cm³/g

0.582

0.474

0.408

/ kJ/mol

7.211

6.449

7.615

0.997

0.995

0.995

Langmuir

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/ 1/ppm

Medium A

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Model parameters

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Freundlich

R²

D-R

R²

4.2 Shapes of breakthrough curves of investigated media:

21

ACCEPTED MANUSCRIPT Figure 7 shows the breakthrough curves of the media at the respective face velocity (A and B: 5.6 cm/s, C: 18 cm/s), 9 ppm, 23 °C and at 50 % RH. The measurement data were recorded every second and the data set was reduced due to the large amount of information so that every tenth value was used for analysis. For better

the illustration of the breakthrough curves.

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visibility, a time interval of 5 minutes was selected between the measuring points for

The breakthrough curves depicted in Figure 7 show the good reproducibility of the

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test results. The small deviations are partly due to minor fluctuations in the

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experimental conditions, but mainly due to heterogeneity of the activated carbon distribution within the medium of a batch.

Figure 7 shows an initial breakthrough of slightly more than 20 % and about 10 % when using media A and B, respectively. This adsorption behavior is mainly caused

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by the properties of the media A and B. Due to the high degree of void volume in the media and the low thickness, the probability of contact with the adsorbent is reduced for some of the toluene molecules.

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In addition to the initial breakthroughs, the shape of the breakthrough curves of the media A and B shown in Figure 7 are also different. While the breakthrough curves of

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medium A are approximately s-shaped, the breakthrough curves of toluene at media B are convex (from the time axis). The latter is disadvantageous in view of the indoor air purification performance. An explanation for the poorer adsorption performance of the medium B can be a slower external mass transfer in relation to the supplied toluene mass flow. The slower mass transfer can be attributed to the nature of the media B, with individual comparatively large clusters within a fiber matrix (see Figure 2). Media B has a low bulk density and thus higher porosity compared to the medium A. The high porosity results in a lower Sherwood number 22

ACCEPTED MANUSCRIPT and consequently a slower external mass transfer through the laminar boundary layer of the activated carbon particles [54, 55]. The slow mass transfer of the adsorptive from the bulk phase to the adsorbent coupled with internal pore diffusion resistances can have a significant negative effect on the shape of the breakthrough curve [48,

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56].

The breakthrough curves of toluene at medium C (Figure 7) show only a low initial breakthrough and an s-shaped form. This behavior results from a dense activated

SC

carbon layer with a comparatively high activated carbon mass throughout the

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medium C (see Table 1). However, compared to media A and B, the complete breakthrough at medium C is achieved faster due to a higher face velocity (media A

AC C

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and B: 5.6 cm/s, medium C: 18 cm/s).

23

ACCEPTED MANUSCRIPT Figure 7: Breakthrough curves of toluene on filter media A and B at 5.6 cm/s (top) and medium C (bottom) at 18 cm/s, 23 °C, 50 % RH

4.3 Validation of prediction of breakthrough curves at low concentrations: Figure 8 compares on the one hand the breakthrough curves at low concentrations

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(indoor air relevance) and at higher concentrations (according to standard). On the other hand, the breakthrough curves at low concentrations, calculated using the prediction methodology described, are compared with the experimental ones.

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Looking at the breakthrough curves, it can first be seen that, as the concentration

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decreases they become flatter, as expected [19, 20, 22]. This means that the time to achieve a certain relative breakthrough increases with decreasing toluene

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concentration.

24

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ACCEPTED MANUSCRIPT

Figure 8: Experimental and predicted breakthrough curves of toluene (modified Wheeler-Jonas and Freundlich equation, linear regression for estimation of bc ) on medium A (top: A-1 and A2), medium B (middle) both at 5.6 cm/s and medium C (bottom) at 18 cm/s and 23 °C, 50 % RH

25

ACCEPTED MANUSCRIPT The modeled breakthrough curves shown in Figure 8 were each calculated from the measurement data at 90, 40 and 9 ppm using the methodology described above. First, the equilibrium capacity

,GQ R

was predicted at 0.9 or 0.09 ppm using the

Freundlich fit to the equilibrium capacities at higher concentrations (9, 40 and 90 ,GQ R

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ppm) according to step 1 in section 3.3. With this predicted equilibrium capacity the stoichiometric time was calculated with the first term of the modified

Wheeler−Jonas equation (equation 6) +& =

∙XYZ,[\Y] . ^/ ∙_`a

The parity diagrams in Figure 9

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compare the measured and calculated +& values for the three investigated media.

Figure 9: Comparison of the measured and calculated stoichiometric times de of the modified Wheeler-Jonas equation for the media A, B and C

26

ACCEPTED MANUSCRIPT

The comparison of the measured and calculated stoichiometric times +& at the investigated concentrations shows good (maximum difference between calculation and measurement of +124 min) or very good (maximum difference of –12.4 min) agreement for media A and C, respectively. In contrast, the stoichiometric times

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calculated for the media B are higher than those measured, especially at 9 and 0.9 ppm (difference of 121 min and 254 min, respectively). The different degree of agreement between calculated and measured +& can be traced back to the shapes of

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the breakthrough curves. As explained in Figure 7, the breakthrough curves of medium B do not show an s-shaped form with an inflection point at a relative

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breakthrough of 50 %, but have a convex shape without an inflection point. Thus, the stoichiometric time cannot be approximated as the time at a 50 % breakthrough, as determined by Equation 6. Due to this fact, the breakthrough curves of medium B are not completely represented by the modified Wheeler-Jonas equation, which has a

later.

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corresponding effect on the quality of the prediction. This will be discussed again

R

at

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The second step (section 3.3) of the prediction consists of estimating the 23,GQ

low concentrations using a linear regression to the overall mass transfer coefficients

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at higher concentrations. The mass transfer coefficients fitted with the LevenbergMarquardt algorithm to experimental breakthrough curves as a function of concentration are shown in Figure 10. It can be seen that the overall mass transfer coefficients assume values with appreciably different sizes depending on the medium. The smallest determined mass transfer coefficient was determined at 0.9 ppm at medium B (23 =187 1/min) with the lowest bulk density, the largest at medium

C with the highest bulk density at 90 ppm (23 =18851 1/min). Furthermore, when

looking at the 23 values as a function of the inlet concentration, it can be observed 27

ACCEPTED MANUSCRIPT

that 23 tend to decrease with decreasing concentration. The decreasing trend of 23 with decreasing inlet concentration was also observed by Khazraei Vizhemehr et al. [22] on the system n-hexane and activated carbon and is in accordance with the

Wood-Lodewyckx equation for calculation of 23 [50]. This relationship can be

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described for the three investigated media in the present study and within the investigated concentration range by a linear function. Therefore one can estimate from the 23 values at higher concentrations 23,GQ

at lower concentrations with a

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linear regression.

R

Figure 10: Overall mass transfer coefficients bc of the modified Wheeler-Jonas equation for the media A, B and C as a function of inlet concentration, determined by non-linear fit of

28

ACCEPTED MANUSCRIPT

measurement data (solid), linear regression to these points (dashed line) and bc determined with the Wood-Lodewyckx correlation (dotted circles)

Figure 10 also shows for comparison the overall mass transfer coefficients according to the Wood-Lodewyckx correlation. In order to estimate the respective 23 at 0.9 ppm using the correlation, equation 7 was fitted to the 23 values at 9, 40 and 90 ppm with

of equation 7 were determined. The

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a nonlinear fit. Thus the parameters @ and

mass transfer coefficient 23 at 0.9 ppm was then calculated with the correlation using

these values. The affinity coefficient was determined according to equations 8 and 9.

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A particle diameter of 0.05 cm was chosen for the media A and B, which corresponds

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to the mean particle size of the activated carbon of these media. In the case of medium C, the clusters of activated carbon and binder show strongly varying cluster sizes with indefinable geometry. Here, an estimation from SEM images was used to assume a diameter of 0.5 cm.

By means of the Wood-Lodewyckx correlation, a satisfactory prediction of 23 at

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0.9 ppm was achieved for media B and C. The mass transfer coefficients 23 were

slightly underestimated. The deviations between the 23 values from the non-linear fit

EP

to the measured data at 0.9 ppm and the calculation with the Wood-Lodewyckx equation are 6 % (medium B) and 2 % (medium C). In the case of medium A, with Wood-Lodewyckx correlation, the mass transfer coefficient at 0.9 ppm was

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underestimated by 48 %. In comparison, the deviation between the 23 values from the non-linear fit to the measured data and the prediction using a linear regression was 3 % (medium A), 4 % (medium B) and 8 % (medium C). Due to the significant underestimation of the 23 using the Wood-Lodewyckx correlation at medium A, the linear regression was preferred for the prediction of the breakthrough curves

(Figure 8) to estimate 23 . However, only three investigated systems cannot be used to make a general statement as to whether a linear regression or the Wood29

ACCEPTED MANUSCRIPT

Lodewyckx correlation is the better method for predicting 23 for the application described here. Rather, further research in the low concentration range using other media and adsortives is required. The comparison of the experimentally determined and predicted breakthrough curves

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at media A at 0.9 ppm and 0.09 ppm and 23 °C and 50 % RH in Figure 8 (A-1) shows that a satisfactory prediction of the breakthrough curves at 0.9 ppm and 0.09 ppm toluene on filter medium A was obtained with the calculation scheme described in

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section 3.3. Figure 8 (A-2) also shows the complete modeled breakthrough curve at

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0.09 ppm toluene. Based on the assumption that a satisfactory prediction is possible by the modeling scheme (an acceptable agreement between calculated and experimentally determined breakthrough curves is given in the first 45 h), the equilibrium state would be reached after about 900 h. The test duration or the estimated service life of the medium A up to a breakthrough of 50 % would already

TE D

be approximately 250 hours at 0.09 ppm toluene according to the calculation. A good prediction of the breakthrough curve at 0.9 ppm was also achieved for filter medium C using the prediction method (Figure 8, C). In particular, the initial breakthrough and

EP

the inflection point at 50 % breakthrough are very well predicted. In comparison, the

AC C

accuracy of the prediction of the breakthrough curve at 0.9 ppm at medium B is only moderate (Figure 8, B). As mentioned above, this can be explained by the convex shape of the breakthrough curves of toluene on medium B, which are not reproduced by the presented modified Wheeler-Jonas approach. Here, especially in the range between 35 % and about 80 % breakthrough, a significant difference between the experimental and the predicted breakthrough curves at 0.9 ppm is given. This difference has a maximum of 10 % for the relative breakthrough (at about 12 h) and 4 h for the breakthrough time at a breakthrough of about 50 %. More research is 30

ACCEPTED MANUSCRIPT needed to investigate the prediction method especially for convex breakthrough curves. There are few possibilities mentioned in the literature using the WheelerJonas equation in a further modified form (2 additional fit parameters) [47] or a dynamic simulation using a differential mass balance [22, 35, 44].

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The presented results of the prediction were obtained from only three breakthrough curves (at 90, 40 and 9 ppm) shown in Figure 8. However, the reproducibility of the breakthrough curves was satisfactory (see Figure 7), which justifies a prediction

SC

based on individual measurements. However, in case of doubt, the minimum set of

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measurements required at higher concentrations must be determined individually by the user, depending on the reproducibility of test results and desired accuracy of the prediction. Another study will investigate a method based on a partial measurement of breakthrough curves at higher concentrations. This should save experimental time

TE D

even in case of repeated measurements.

Furthermore, the presented prediction was investigated at 50 % relative humidity. In the humidity range ≤ 50 % RH a comparatively small amount of water is adsorbed

EP

onto activated carbon. The water vapor isotherms of the investigated activated carbon are of type V according to IUPAC classification [53]. At relative humidities of >

AC C

60 %, a significantly larger amount of water is adsorbed, which leads to a decrease in the capacity of toluene and other VOC and a rapid breakthrough. For example Nelson and Harder [57] have shown by means of the adsorption of benzene, acetone, methyl acetate and methyl chloroform at relative humidities up to 80 % that the influence of humidity has a greater influence at low concentrations than at higher ones. This effect was particularly pronounced at a relative humidity of 80 % and less at 50 % or lower. This fact should be taken into account in predictions of the breakthrough curves for estimating the service life at relative humidities > 50 %. 31

ACCEPTED MANUSCRIPT

5 Conclusions The objective of this study is to develop and validate a methodology to predict breakthrough curves of HVAC filter media for toluene at typical low indoor air

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concentrations based on the measurement data at normatively recommended higher concentrations. In this way, a procedure was checked in order to estimate the service life under more realistic conditions on the basis of normative measurement data. The

SC

method presented in this study is based on the modified Wheeler-Jonas equation. In

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order to validate the prediction method, breakthrough curves at 0.9 and 0.09 ppm (at 23 °C and 50 % RH) were measured on three different commercially available activated carbon filter media and compared with the predicted ones. The result is that a good prediction was achieved for s-shaped breakthrough curves. For these, a measurement time of only a few hours is needed, whereas several days would be

TE D

required for the measurements at typical indoor concentrations. Furthermore, the use of highly sensitive devices with low detection limits in the ppb range can be avoided.

EP

For convex breakthrough curves, the prediction was only moderate, which is accounted to the restrictions of the Wheeler-Jonas approach. The isotherm models of

AC C

Langmuir, Freundlich and Dubinin-Radushkevich were investigated for the prediction of equilibrium capacity. The latter two were suitable for the conditions considered. However, Freundlich and D-R isotherm models used in the study do not show correct Henry behavior at very low concentrations. Thus, there will be a lower concentration limit when using these two isotherm models. In addition it should be noted that the method presented here is an estimation of the service life of filter media based on predicted breakthrough curves. Usually, the operating situation in real applications is characterized by much more complex conditions. Therefore more research is needed 32

ACCEPTED MANUSCRIPT regarding the prediction of adsorptive performance of filters and media at different relative humidities, fluctuating conditions, even lower concentrations and other substances and mixtures relevant to indoor air. Acknowledgements

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The project (no. 18516 N) was funded via the German Federation of Industrial Research Associations (AiF) within the program to support industrial collective research (IGF) by the German Federal Ministry for Economic Affairs and Energy

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Declaration of interests

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(BMWi) based on a decision of the German Bundestag.

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The authors declare no conflict of interests.

33

ACCEPTED MANUSCRIPT References [1]

Adan, O.C.G.; Samson, R.A. (2011): Fundamentals of mold growth in indoor environments and strategies for healthy living, Wageningen Academic Publishers, Utrecht, p. 283 Burge, P.S. (2004): Sick building syndrome. In: Occupational and Environmental

Medicine

61

(2),

10.1136/oem.2003.008813 [3]

185–190.

DOI:

Weschler, C.J. (2009): Changes in indoor pollutants since the 1950s. In: Atmospheric

Environment

43

(1),

p.

153–169.

DOI:

SC

10.1016/j.atmosenv.2008.09.044 [4]

p.

RI PT

[2]

Hippelein, M. (2004): Background concentrations of individual and total

M AN U

volatile organic compounds in residential indoor air of Schleswig-Holstein, Germany. In: Journal of environmental monitoring: JEM 6 (9), p. 745–752. DOI: 10.1039/b401139m [5]

Mandin, C.; Trantallidi, M.; Cattaneo, A.; Canha, N.; Mihucz, V.G.; Szigeti, T. et al. (2017): Assessment of indoor air quality in office buildings across Europe - The OFFICAIR study. In: The Science of the total environment

[6]

TE D

579, p. 169–178. DOI: 10.1016/j.scitotenv.2016.10.238 Paciência, I.; Madureira, J.; Rufo, J.; Moreira, A.; Fernandes, E. (2016): A systematic review of evidence and implications of spatial and seasonal variations of volatile organic compounds (VOC) in indoor human

EP

environments. In: Journal of toxicology and environmental health. Part B, Critical reviews 19 (2), p. 47–64. DOI: 10.1080/10937404.2015.1134371 Sagunski, H.; Heinzow, B. (2003): Richtwerte für die Innenraumluft).

AC C

[7]

Bicyclische Terpene (Leitsubstanz α-Pinen). In: Bundesgesundheitsblatt Gesundheitsforschung - Gesundheitsschutz 46 (4), p. 346–352. DOI: 10.1007/s00103-003-0584-7

[8]

Sarigiannis, D.A.; Karakitsios, S.P.; Gotti, A.; Liakos, I.L.; Katsoyiannis, A.

(2011): Exposure to major volatile organic compounds and carbonyls in European indoor environments and associated health risk. In: Environment international 37 (4), p. 743–765. DOI: 10.1016/j.envint.2011.01.005 [9]

Su, F.C.; Mukherjee, B.; Batterman, S. (2013): Determinants of personal, indoor and outdoor VOC concentrations: an analysis of the RIOPA data. 34

ACCEPTED MANUSCRIPT In:

Environmental

research

126,

p.

192–203.

DOI:

10.1016/j.envres.2013.08.005 [10]

Wang, C.M.; Barratt, B.; Carslaw, N.; Doutsi, A.; Dunmore, R.E.; Ward, M.W.;

Lewis,

A.C.

(2017):

Unexpectedly

high

concentrations

of

monoterpenes in a study of UK homes. In: Environmental science.

[11]

RI PT

Processes & impacts 19 (4), p. 528–537. DOI: 10.1039/c6em00569a Wissenbach, D.K.; Winkler, B.; Otto, W.; Kohajda, T.; Roeder, S.; Müller, A. et al. (2016): Long-term indoor VOC concentrations assessment a trend analysis of distribution, disposition, and personal exposure in cohort study

SC

samples. In: Air Quality, Atmosphere & Health 9 (8), p. 941–950. DOI: 10.1007/s11869-016-0396-1 [12]

Salthammer, T.; Uhde. E. (2009): Organic Indoor Air Pollutants, Wiley-

[13]

M AN U

VCH, Weinheim

Missia, D.A.; Demetriou, E.; Michael, N.; Tolis, E.I.; Bartzis, J.G. (2010): Indoor exposure from building materials. A field study. In: Atmospheric Environment 44 (35), p. 4388–4395. DOI: 10.1016/j.atmosenv.2010.07.049

[14]

ISO 10121-1:2014: Test method for assessing the performance of gasphase air cleaning media and devices for general ventilation - Part 1: Gas-

[15]

TE D

phase air cleaning media

ANSI/ASHRAE 145.1-2015: Laboratory Test Method for Assessing the Performance of Gas-Phase Air-Cleaning Systems: Loose Granular Media Seifert, B. (1999): Richtwerte für die Innenraumluft. Die Beurteilung der

EP

[16]

Innenraumluftqualität mit Hilfe der Summe der flüchtigen organischen Verbindungen

(TVOC-Werte).

In:

Bundesgesundheitsblatt –

[17] [18]

AC C

Gesundheitsforschung – Gesundheitsschutz 3:270-278 Umweltbundesamt (2007): Leitwerte für TVOC in der Innenraumluft Zhou, C.; Zhan, Y.; Chen, S.; Xia, M.; Ronda, C.; Sun, M. et al. (2017):

Combined effects of temperature and humidity on indoor VOCs pollution. Intercity comparison. In: Building and Environment 121, p. 26–34. DOI: 10.1016/j.buildenv.2017.04.013

[19]

van Osdell, D.W.; Owen, M.K.; Jaffe, L.B.; Sparks, L.E. (1996): VOC Removal at Low Contaminant Concentrations Using Granular Activated Carbon. In: Journal of the Air & Waste Management Association 46 (9), p. 883–890. DOI: 10.1080/10473289.1996.10467524 35

ACCEPTED MANUSCRIPT [20]

Yao, M.; Zhang, Q.; Hand, D.W.; Perram, D.; Taylor, R. (2012): Adsorption and Regeneration on Activated Carbon Fiber Cloth for Volatile Organic Compounds at Indoor Concentration Levels. In: Journal of the Air & Waste Management

Association

59

(1),

p.

31–36.

DOI:

10.3155/1047-

3289.59.1.31 Das, D.; Gaur, V.; Verma, N. (2004): Removal of volatile organic

RI PT

[21]

compound by activated carbon fiber. In: Carbon 42 (14), p. 2949–2962. DOI: 10.1016/j.carbon.2004.07.008 [22]

Khazraei Vizhemehr, A.; Haghighat, F.; Lee, C.S. (2013): Predicting gas-

SC

phase air-cleaning system efficiency at low concentration using high concentration results. Development of a framework. In: Building and Environment 68, p. 12–21. DOI: 10.1016/j.buildenv.2013.05.023 He, C.; Chen, W.; Han, K.; Guo, B.; Pei, J.; Zhang, J.S. (2014): Evaluation

M AN U

[23]

of filter media performance. Correlation between high and low challenge concentration tests for toluene and formaldehyde (ASHRAE RP-1557). In: HVAC&R Research 20 (5), p. 508–521. DOI: 10.1080/10789669.2014.907096 [24]

Qi, N.; Appel, W.S.; LeVan, M.D.; Finn, J.E. (2006): Adsorption Dynamics

TE D

of Organic Compounds and Water Vapor in Activated Carbon Beds. In: Industrial & Engineering Chemical Research 45 (7), p. 2303–2314. DOI: 10.1021/ie050758x

Guo, J.; Lua, A.C. (2002): Microporous activated carbons prepared from

EP

[25]

palm shell by thermal activation and their application to sulfur dioxide adsorption. In: Journal of colloid and interface science 251 (2), p. 242–247.

[26]

AC C

DOI: 10.1006/jcis.2002.8412 Khazraei Vizhemehr, A.; Haghighat, F.; Lee, C.S. (2014): Gas-phase filters breakthrough models at low concentration – Effect of relative humidity. In: Building

and

Environment

75,

p.

1–10.

DOI:

10.1016/j.buildenv.2014.01.010 [27]

Lodewyckx, P.; Wood, G.O.; Ryu, S.K. (2004): The Wheeler–Jonas equation: A versatile tool for the prediction of carbon bed breakthrough times.

In:

Carbon

42

(7),

p.

1351–1355.

DOI:

10.1016/j.carbon.2004.01.016 [28]

Benkhedda, J.; Jaubert, J.; Barth, D. (2000): Adsorption isotherms of m36

ACCEPTED MANUSCRIPT xylene on activated carbon: measurements and correlation with different models. In: Journal of Chemical Thermodynamics 32, p. 401-411. DOI: 10.1006/jcht.1999.0613 [29]

Pei, J. and Zhang, J. (2012): Determination of adsorption isotherm and diffusion coefficient of toluene on activated carbon at low concentrations. Building

and

Environment

10.1016/j.buildenv.2011.08.005 [30]

46,

p.

66-76.

DOI:

RI PT

In:

Shiue, A.; Kang, Y.H.; Hu, S.C.; Gt, Jou; Lin, C.H.; Hu, M.C. et al. (2010): Vapor adsorption characteristics of toluene in an activated carbon

SC

adsorbent-loaded nonwoven fabric media for chemical filters applied to cleanrooms. In: Building and Environment 45, p. 2123-2131. DOI: 10.1016/j.buildenv.2010.03.008

Sager, U. and Schmidt, F. (2010): Binary Adsorption of n-Butane or

M AN U

[31]

Toluene and Water Vapor. In: Chemical Engineering Technology 33 (7), p. 1203-1207. DOI: 10.1002/ceat.201000086 [32]

Ruthven D.M. (1985): Principles of Adsorption and Adsorption Processes, John Wiley & Sons, New York

[33]

Do, D.D. (1998): Adsorption Analysis: Equilibria and Kinetics. Empirial

[34a]

TE D

College Press, London

Langmuir, I. (1916): Evaporation, Condensation and Reflection of Molecules and the Mechanism of Adsorption. In: Physical Reviews 8, p.

[34b]

EP

149-176

Langmuir, I. (1918): The Adsorption of Gases on Plane Surfaces of Glass, Mica and Platinum. In: Journal of Americal Chemical Society 40, p. 1361-

[35]

AC C

1403

Axley, J.W. (1991): Adsorption Modelling for Building Contaminant

Dispersal Analysis. In: Indoor air 1 (2), p. 147–171. DOI: 10.1111/j.1600-

0668.1991.04-12.x

[36]

Ng, J.C.Y.; Cheung, W.H.; McKay, G. (2003): Equilibrium studies for the sorption of lead from effluents using chitosan. In: Chemosphere 52 (6), p. 1021–1030. DOI: 10.1016/S0045-6535(03)00223-6

[37]

Seo, J.; Kato, S.; Atakab, Y.; Chino, S. (2009): Performance test for evaluating the reduction of VOCs in rooms and evaluating the lifetime of sorptive building materials. In: Building and Environment 44 (1), p. 20737

ACCEPTED MANUSCRIPT 215. DOI: 10.1016/j.buildenv.2008.02.013 [38]

Freundlich, H. (1907): Über die Adsorption in Lösungen. In: Zeitschrift für Physikalische Chemie 57U (1), p. 385-470. DOI: 10.1515/zpch-1907-5723

[39]

Yu, J.W.; Neretnieks, I. (1990): Single-component and multicomponent adsorption equilibria on activated carbon of methylcyclohexane, toluene,

RI PT

and isobutyl methyl ketone. In: Industrial & Engineering Chemical Research 29 (2), p. 220–231. DOI: 10.1021/ie00098a012 [40]

Dubinin, M.M.; Radushkevich, L.V. (1947): The Equation of Characteristic Curve of Activated Charcoal. In: Doklady Akademii Nauk SSSR 55, p.327-

[41]

SC

329

Polanyi, M. (1914): Adsorption from the Point of View of the Third Law of Thermodynamics. In: Verhandlungen der Deutschen Physikalischen

[42]

Gregg, S.J.; Sing, K.S.W. (1967): Adsorption, Surface Area, and Porosity, Academic Press, London

[43]

M AN U

Gesellschaft 16, p. 1012-1016

Glueckauf, E.; Coates, J.I. (1947): Theory of chromatography; the influence

of

incomplete

equilibrium

on

the

front

boundary

of

chromatograms and on the effectiveness of separation. In: Journal of the

[44]

TE D

Chemical Society, p. 1315–1321

Grévillot, G.; Marsteau, S.; Vallières, C. (2011): A comparison of the Wheeler-Jonas model and the linear driving force at constant-pattern

EP

model for the prediction of the service time of activated carbon cartridges. In: Journal of occupational and environmental hygiene 8 (5), p. 279–288. DOI: 10.1080/15459624.2011.567131 Wheeler, A.; Robell, A.J. (1969): Performance of fixed-bed catalytic

AC C

[45]

reactors with poison in the feed. In: Journal of Catalysis 13 (3), p. 299-305. DOI: 10.1016/0021-9517(69)90404-7

[46]

Jonas, L.A.; Rehrmann, J.A. (1972): The kinetics of adsorption of organo-

phosphorus vapors from air mixtures by activated carbons. In: Carbon 10 (6), p. 657–663. DOI: 10.1016/0008-6223(72)90073-5 [47]

Wood, G.O. (2002): Quantification and application of skew of breakthrough curves for gases and vapors eluting from activated carbon beds. In: Carbon 40 (11), p. 1883–1890. DOI: 10.1016/S0008-6223(02)00031-3

[48]

Sontheimer, H.; Frick, B.R.; Fettig, J.; Hörner, G.; Hubele, C.; Zimmer, G. 38

ACCEPTED MANUSCRIPT (1985):

Adsorptionsverfahren

zur

Wasserreinigung,

DVGW-

Forschungsstelle am Engler-Bunte-Institut der Universität Karlsruhe, Karlsruhe [49]

Zhou, C.; Feng, S.; Zhou, G.; Jin, Y.; Liang, J.; Xu, J. (2011): A Simple Method for Calculating the Overall Adsorption Rate Constant in the

RI PT

Wheeler–Jonas Equation. In: Adsorption Science & Technology 29 (1), p. 71–82. DOI: 10.1260/0263-6174.29.1.71 [50]

Lodewyckx, P.; Wood, G.O. (2003): An Extended Equation for Rate Coefficients for Adsorption of Organic Vapors and Gases on Activated

SC

Carbons in Air-Purifying Respirator Cartridges. In: AIHA Journal 64 (5), p. 646-650. DOI: 10.1202/443.1 [51]

Wood, G.O. (2001): Affinity coefficients of the Polanyi/Dubinin adsorption

M AN U

isotherm equations: A review with compilations and correlations. In: Carbon 39 (3), p. 343-356. DOI: 10.1016/S0008-6223(00)00128-7 [52]

Lide, D.R. (1998): CRC Handbook of Chemistry and Physics, 79th Edition, CRC Press, Boca Raton, Florida

[53]

Thommes, M.; Kaneko, K.; Neimark, A.V.; Olivier, J.P.; RodriguezReinoso, F.; Rouquerol, J.; Sing, K.S.W. (2015): Physisorption of gases,

TE D

with special reference to the evaluation of surface area and pore size distribution (IUPAC Technical Report). In: Pure and Applied Chemistry 87 (9-10), p. 1051-1069. DOI: 10.1515/pac-2014-1117 Wakao, N.; Funazkri, T. (1978): Effect of fluid dispersion coefficients on

EP

[54]

particle-to-fluid mass transfer coefficients in packed beds: Correlation of sherwood numbers. In: Chemical Engineering Science 33 (10), p. 1375-

[55]

AC C

1384. DOI: https://doi.org/10.1016/0009-2509(78)85120-3

Dwiwedy, P.N. and Upadhyay, S.N. (1977): Particle-Fluid Mass Transfer in Fixed and Fluidized Beds. In: Industrial & Engineering Chemistry Process Design and Development 16 (2), p. 157-165. DOI: 10.1021/i260062a001

[56]

Kast, W. (1988): Adsorption aus der Gasphase. VCH Verlagsgesellschaft, Weinheim

[57]

Nelson, G.O. and Harder, C.A. (1976): Respirator Cartridge Efficiency Studies: VI. Effect of Concentration. In: AIHA Journal 37 (4), p. 205-216. DOI: 10.1080/0002889768507444

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Service time of HVAC filters against VOC can be estimated at low concentrations The estimation is based on data at higher concentrations and a prediction method Combination of isotherm models and Wheeler-Jonas equation was used for the method Accurate or moderate prediction have been achieved for toluene breakthrough curves Freundlich and Dubinin-Radushkevich isotherm models gave the best fit

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