Sustain. Environ. Res., 21(1), 37-43 (2011) 37 (Formerly, J. Environ. Eng. Manage.)

AGING-INDUCED CHANGES IN PROPERTIES OF MOTORCYCLE CATALYTIC CONVERTERS

Yi-Chi Chen, Kun-Hsien Lee and Fu-Tien Jeng* Graduate Institute of Environmental Engineering

National Taiwan University Taipei 106, Taiwan

Key Words: Motorcycle catalytic converter, thermal deactivation, poisoning, phosphate overlayer

ABSTRACT

Motorcycle engine exhaust is the major source of air pollutants in Taiwan and some countries with high population densities and low income in Southeast Asia. As a result, catalytic converters are used to reduce motorcycle pollutant emissions, Nevertheless, catalysts’ properties would be affected attributed to deactivation mechanisms during the used periods. According to the results of this study, the presence of thermal deactivation and poisoning was identified. Loss in specific surface area and total pore volume, the growth in pore diameter and the phase transition were observed as the aging-induced changes in catalytic properties. The deactivation phenomena were highly correlated to the age and mileage. A decreasing trend of specific surface area of catalyst with the accumulation of the used time was observed. To determine the effects of age and mileage of converters on specific surface areas, the empirical models were constructed on the basis of physisorption measurements. The constructed exponential model can reflect the actual deactivation conditions according to the high statistical significance of the applicability evaluation.

*Corresponding author Email: ftjeng@ntu.edu.tw

INTRODUCTION

The number of motorcycles in Taiwan increases

by 1-5% annually. At the end of 2009, motorcycles accounted for about 68% of the total number of regis-tered motor vehicles, which is equal to 14.6 million [1,2]. Motorcycles contribute about 3, 11 and 13% to NOx, HC and CO emissions, respectively. Their emis-sions were reported to be one of the major sources of air pollutants in urban areas and causes negative im-pact on air quality and public health [3]. In some de-veloping countries in Southeast Asia, such as India and Nepal, two wheeler vehicles are also responsible for a serious and continuing deterioration of air qual-ity due to their high market share, which account for ~70% of the total vehicle fleet [4-5]. To curb motor-cycle emissions, strategies including phase-in the im-plementation of stricter vehicle emission standards, regular testing, promotion for clean alternative fuels, eliminating old vehicles and two-stroke engine motor-cycles and advocating the use of low-pollution motor-cycles, have been carried out by Environmental Pro-tection Agency in Taiwan. Beyond these measures, catalytic converters were enforced to be assembled on

motorcycles produced later than 1998 to reduce emis-sions of harmful air pollutants [6,7].

However, during the used periods, catalytic con-verters become deactivated, which is attributed to op-eration conditions of high temperature and impurities [8]. Deactivation, which is the loss of catalytic activity and/or selectivity over time, can be divided into five mechanisms: (1) thermal degradation, (2) fouling, (3) crushing, (4) poisoning, and (5) solid-state transfor-mation. Among these, thermal degradation and poi-soning are the most prominent causes for the deactiva-tion of modern catalytic converters. Thermal degrada-tion, the loss of active surface via structural modifica-tion caused by high temperature, can be classified into two types: sintering and solid-solid reaction. Poison-ing is the loss of activity due to the strong chemisorp-tion of impurities on active sites. The uses of fuels containing sulfur and lubricants containing phospho-rus, zinc or calcium would result in the poisoning of catalytic converters [9-12].

According to the results of motorcycle exhaust testing data, pollutant emissions exhibit a trend of in-creasing with the age and mileage of motorcycles. The trend is the most obvious for motorcycles used longer than 3 years or more than 10,000 km. The increasing

38 Sustain. Environ. Res., 21(1), 37-43 (2011)

trend of pollutant emissions resulted from the deacti-vation-induced changes of catalytic properties during the used periods [2]. Moreover, the study by Chiang et al. [13] reported that tune-ups fail to reduce emissions of high emitters because of deterioration of the three-way catalyst over time. In the case of automobile cata-lysts, their durability is better. There was no signifi-cant impact of aging on catalytic performance for CO, HC, and NOx until 120,000 km [14].

The useful life and warranty period were set to be 3 years or 15,000 km in the Phase 5 Motorcycle Air Pollutant Emission Standards in Taiwan. However, there are not any existing regulations enforcing own-ers to replace old catalytic converters with new ones. The study by Jia et al. [8] described 5-30% deteriora-tion of the catalytic conversion as the accumulated mileage exceeded 10,000 km. Moreover, most motor-cycle owners do not replace the old pipes voluntarily owing to the high prices of original equipment manu-facturer’s exhaust pipes containing catalytic convert-ers. Consequently, motorcycles equipped with those deactivated catalytic converters or without catalytic converters cause severe impact on the environment.

In order to investigate the effects of used time on catalytic properties, the primary focus of this study is to probe the aging-induced changes in properties of motorcycle catalytic converters. Catalysts used for dif-ferent ages and mileages were collected and disas-sembled from exhaust pipes, and then characterized. Statistical models were constructed on the basis of data in order to analyze the effects of age and mileage on specific surface areas of catalytic converters and predict their specific surface areas for different ages or mileages.

MATERIALS AND METHODS

In this study, catalysts used for different ages

and mileages were disassembled from exhaust pipes and characterized. Table 1 displays the basic informa-tion on the collected catalysts. Different measure-ments of the fresh and used catalysts were performed to compare catalysts’ properties. Specific surface ar-eas, surface structures and elemental components of catalysts were analyzed by a Brunauer-Emmett-Teller (BET) specific surface area analyzer; X-ray powder diffraction (XRD) and inductively coupled plasma-mass spectrometer (ICP-MS), to provide information for investigating deactivation phenomena of motorcy-cle catalytic converters.

1. Activity Measurements

The tubular reactor with the dimension of diame-

ter 10 cm and length 100 cm was used for the activity measurements. The catalysts were put inside the reac-tor made of aluminum oxide. The total flow rate dur-ing the activity measurements was 20 L min-1 corre-

Table 1. Basic information on the collected catalysts

Serial number Displacement

(mL) Age (yr)

Mileage (km)

1 100 0 0 2 125 0 0 3 125 0 0 4 101 0 0 5 100 3 16350 6 100 6 30201 7 125 4 32045 8 125 5 40136 9 125 6 24867 10 125 7 20641 11 150 5 50480 12 125 3 31302 13 125 6 40813 14 101 5 27847 15 101 6 27399 16 101 4 15910 17 101 4 28044 18 101 4 36477

sponding gas hourly space velocity of approximately 24000 h-1. The concentrations of propylene (C3H6) were then measured by the exhaust analyzer after air had passed through the catalytic reactor to calculate conversions (X) of the pollutant.

%1000

0 ×−

=C

CCX (1)

where: C0 = the concentration of the pollutant in the fed stream; C = the concentration of the pollutant in the reactor outlet. Subsequently, the performances of the fresh and aged catalysts were evaluated by com-paring their performance.

2. Specific Surface Area

In this study, physisorption measurements were

carried out to characterize the used catalysts. Specific surface areas and pore volumes were measured ac-cording to the standard BET method by using a sur-face area analyzer (Micromeritics TriStar 3000). Cata-lysts were outgassed by the pressure of 3 ×10-3 mm-Hg at 200 °C overnight before the measurements. Data of specific surface area, pore size distribution and pore volume were obtained from N2 adsorption isotherms at 77 K by assuming the cylindrical shape of pores.

3. XRD

A PANalytical X' Pert PRO X-ray diffractometer

with monochromatic Cu Kα radiation was used to de-tect the bulk phases in the sample, and to determine the ageing-induced solid-solid phase transformations. The measurements were taken from 10 to 90° with a

Chen et al.: Aging of Motorcycle Catalytic Converter 39

scanning speed of 3° min-1. X-rays are energetic enough to penetrate into the material and their wave-lengths are of the same order of magnitude as intera-tomic distances in solids. Therefore, a collimated beam of X-rays is diffracted by the crystalline phases in the sample according to Bragg’s Law.

4. Elemental Analysis

A Perkin Elmer SCIEX ELAN 5000 ICP-MS

was used for elemental measurements qualitatively and quantitatively. Initially, the solid sample was dis-solved and converted into very small droplets by a nebulizer. The aerosols were carried through a spray chamber, the torch and then into the plasma. The sam-ple was then atomized and ionized. Ions produced in the ICP then passed through the interface to the MS and were measured by the ion detector.

5. Statistical Analysis

After the catalysts used for different ages and

mileages had been characterized, the effects of deacti-vation on catalytic properties were investigated. The effects of age and mileage on catalytic properties were determined by the analysis of Pearson product-moment correlation. The age and mileage were set as the independent variables as they stand for how long the catalyst had been used. Specific surface area, which is an important factor in a catalytic reaction, was set as the dependent variable in the statistical re-gression. Empirical models were then constructed on the basis of physisorption measurements.

The variables including specific surface area of the fresh catalysts D0, the average age A and the av-erage mileage M of the collected motorcycles were chosen as the characteristic scales to nondimensional-ize the dependent and independent variables. The de-pendent variable D was nondimensionalized to be D* = D/D0. The independent variables A and M were nondimensionalized to be A* = AA / and M* =

MM / respectively. Where D = specific surface area, m2 g-1, A = age

of the catalytic converter, year and M = mileage of the catalytic converter, km.

5.1. Linear regression model

D* = aA* + mM* + bA* M* + ε (2) Where D* = dimensionless specific surface area, A* = dimensionless age of the catalytic converter, M* = dimensionless mileage of the catalytic converter, a, m, b = regression coefficients, and ε = intercept.

5.2. Power model

D* = ε (A*)a (M*)m (3)

⇒ *** loglogloglog MmAaD ++= ε (4)

5.3. Exponential model Take into consideration that the deactivation rate

slows down as the used time increases [15], a variable Deq was involved to construct an exponential model.

ln (D* - Deq*) = ε + aA* + mM* (5)

Where Deq = the limiting surface area at infinite time, m2 g-1, and Deq

* = Deq / D0 = dimensionless limiting surface area at infinite time

RESULTS AND DISCUSSION

1. Characterization of Motorcycle Catalytic

Converters

1.1. Activity and specific surface area According to the data, the difference of activities

between the fresh and used catalysts was only ob-served under the low temperature zone. Take catalysts No. 2 (fresh) and No. 12 (used) for example, the per-formance of the fresh catalyst is slightly lower than the used catalyst within the temperature range under 400 °C (Fig. 1). As the temperature exceeding 500 °C, both fresh and used catalysts can perform as high con-version as 100%. The reason is that under the high temperature range, enough energy was provided for the pollutant to react. Therefore, there was no signifi-cant difference in light-off temperature (T50, the tem-perature at which the conversion of pollutant achieves 50%) between the fresh and used catalysts. The differ-ence of conversions between fresh and used catalysts under the low temperature zone was inferred to be at-tributed to the loss of specific surface area (Fig. 2).

1.2. Elemental analysis and phase transitions of catalysts Poisoning of P and Ca was identified by means

Fig. 1. C3H6 conversion of the collected catalysts.

40 Sustain. Environ. Res., 21(1), 37-43 (2011)

Fig. 2. Specific surface area of the fresh and used

catalysts.

Fig. 3. XRD diffractograms of the fresh and used

catalysts. of XRD and ICP-MS. The presence of cerium oxides (CeO2), Ce- and Zr-rich mixed oxides (CexZr1-xO2) and zirconium oxides (ZrO2) was observed in the XRD dif-fractogram of all fresh catalysts. Catalyst No. 2 was taken as the representative of fresh catalysts shown in Fig. 3. As regards the used catalysts, catalysts No. 9 and 13 were taken for example because all used cata-lysts exhibited similar patterns. The formation of CeAlO3 was observed attributed to the reactions of γ-alumina with the pure cerium oxide in the catalyst’s washcoat. Besides, phosphorus contamination was de-tected in the used catalysts as cerium phosphate (CePO4) which was formed by the reaction of phosphorus com-pounds with the washcoat components. Phosphate-containing overlayer was observed in some aged cata-lysts as well as the presence of calcium phosphate (Ca3(PO4)2). Phosphate overlayer is one of the major phosphorus contamination poisoning catalytic convert-ers. The other form is aluminum or cerium phosphate within the washcoat caused by the reaction of phospho-rus with washcoat material [16-19].

1.3. Pore size distribution of catalysts Pore size distributions were compared in the case

of catalysts from the same vehicle model. Take No. 1 (fresh catalyst) and No. 5 (used catalyst) for example,

the growth in the pore diameter and the loss of pores was observed in Fig. 4. The change in pore size distri-bution was attributed to the poisoning and thermal de-activation phenomena. The aging-induced changes in structure of catalysts consequently led to the decrease in the total pore volume and specific surface area.

2. Correlation Analyses of Catalytic Properties

To compare properties of the fresh and used

catalysts, Table 2 describes the characteristic data of the catalysts, including specific surfaces areas, aver-age pore diameters, pore volumes, T50, and content of Pt, Pd, Rh and P. The average P content depositing on the used catalyst equals to 7.6%. Table 3 displays the results of correlation analyses between properties of the fresh and used catalysts. The differences in cata-lytic properties between the fresh and used catalysts were observed to be statistically significant. P con-tents depositing on the surface increased with the used time. The specific surface area and pore volume were highly negatively correlated to the age, mileage and P contents of the catalysts. The increasing trend of the deactivation potential with the accumulation of age or mileage is one of the reasons why the amount of pol-lutant emissions of the in-use motorcycles was ob-served to be 5 to 15 times higher than that of the new ones [8,20].

3. Construction of Prediction Model

Specific surface area is one major variable re-

flecting catalytic performance. It was observed to be highly negatively correlated to the age and mileage of the catalysts due to the deactivation mechanisms. To determine the effects of the used time on the specific surface area, empirical models were constructed based on the isothermal measurement data to predict specific surface areas of catalysts with different ages and mile-ages.

Fig. 4. Pore size distribution of the collected catalysts.

Fresh catalyst Used catalyst

Spec

ific

surf

ace

area

, D (m

2 g-1

)

Pore diameter (Å)

Ads

orpt

ion

volu

me

(x10

-4 c

m3 g

-1)

12

10

8

6

4

2

0

Chen et al.: Aging of Motorcycle Catalytic Converter 41

Table 2. Description statistics of catalytic properties Catalyst property Fresh (N = 4) Used (N = 14) Specific surface area, D (m2 g-1) 66 ± 9 24 ± 12 Average pore diameter (Å) 164 ± 7 193 ± 42 Pore volume (cm3 g-1) (0.3 ± 2.7) x 10-2 (0.1 ± 4.6) × 10-2 Light-off temperature, T50 (°C) 461 ± 4 450 ± 18 Pt content (%) (0.5 ± 3.6) × 10-2 0.6 ± 0.4 Pd content (%) (0.5 ± 4.1) × 10-2 0.3 ± 0.2 Rh content (%) (2.0 ± 1.4) × 10-3 (5.5 ± 9.0) × 10-2 P content (%) – 7.6 ± 4.4

Table 3. Correlation analyses for catalysts used for

different mileages Variable 1 Variable 2

Specific surface area

Pore volume P content

Age – (*) – (*) + (*) Mileage – (*) – (*) + (*) P content – (*) – (*)

“+” means variable 1 is positively correlated to variable 2.

“–” means variable 1 is negatively correlated to variable 2.

“*” means variable 1 is highly correlated to variable 2 with the p-value < 0.05.

3.1. Linear model The model was constructed on the basis of phy-

sisorption measurements by the linear regression. The regression result described the highly statistical sig-nificance of the constructed model, as shown below:

D* = 1.004 - 0.638 (A*) - 0.408 (M*) + 0.4 (A*) (M*) (6)

(R2 = 0.772, p-value = 0.000)

The correlation between the specific surface area measured by BET method and predicted by the con-structed models was examined to evaluate the appli-cability of the models. According to the high determi-nation coefficients (R2 = 0.772) and the low p-value (= 0.000) of the correlation between specific surface areas measured and predicted by the linear model, the constructed model can predict the change of specific surface areas reasonably.

2-** 10515.3999.0 ×+= predictedmeasured DD (7)

Where 0* / DDD measuredmeasured = = dimensionless spe-

cific surface area measured by BET method; and 0

* / DDD predictedpredicted = = dimensionless specific sur-face area predicted by the constructed models

3.2. Power model Log(A) and Log(M) were set as the independent

variables and Log(D) was set as the dependent vari-able to construct the power model by the linear regres-sion. The data of the fresh catalysts with the age and mileage equal to 0 were not considered in the regres-sion. The model is described below:

log D* = 0.54 - 0.309 log10 (A*)

+ 0.135 log10 (M*) (8)

(R2 = 0.021, p-value = 0.888)

135.0*309.0** )()(2884.0 MAD −=⇒ (9)

As regards the power model, it is not statistically sig-nificant because of the low determination coefficients (0.016) and the high p-value ( = 0.671).

431.4919.0 ** += predictedmeasured DD (10)

3.3. Exponential model The decreasing rate of specific surface area was

reported to reduce with the increase of the used period [6,7,9,12]. Accordingly, the exponential model was constructed on the basis of the isothermal measure-ment data to study the effect of motorcycle’s age and mileage on catalytic specific surface area.

ln (D* - Deq*) = -0.303 - 1.186 (A*)

+ 0.109 (M*) (11)

(R2 = 0.341, p-value = 0.044)

)109.0186.1-303.0-(exp **** MADD eq ++=⇒ = 0.1 + exp (-0.303 - 1.186A* + 0.109M*) (12)

The high determination coefficients (R2 = 0.711) and the low p-value (= 0.000) of the correlation indicated that the constructed exponential model can predict the change of specific surface areas reasonably. Besides, the exponential model can best reflect the actual deac-tivation conditions.

842.0162.1 ** += predictedmeasured DD (13)

CONCLUSIONS

Catalytic converters have been used to reduce

pollutant emissions from motorcycle exhaust since 1990s in Taiwan. During the used periods, their prop-erties would be affected attributed to different types of deactivation mechanisms, including thermal degrada-tion, poisoning, fouling and so on. In this study, cata-

42 Sustain. Environ. Res., 21(1), 37-43 (2011)

lysts with different ages and mileages were collected and characterized to probe the differences in catalytic properties between the fresh and the used catalysts.

According to the results, the differences in cata-lytic properties between the fresh and used catalysts were statistically significant. The aging induced phase transitions, loss in specific surface areas and pore vol-ume, and the growth in the pore size verified that the changes were ascribed to the thermal deactivation and poisoning. ICP-MS data interpreted that P is the major poison of the used catalysts. The specific surface area was observed to be highly negatively correlated to the age, mileage and P contents of the catalysts. Conse-quently, the accumulation of the used time stands for the increase in the deactivation potential.

To explain the effects of the used time on spe-cific surface area, linear, power and exponential mod-els were constructed to predict specific surface areas of catalysts with different ages and mileages. The re-sults of applicability evaluation described that the lin-ear and exponential models can predict the specific surface areas of the catalysts well. The exponential model can best reflect the real deactivation conditions as it took Deq and the decreasing trend of deactivation rate into consideration. The empirical models can be used as the reference index to evaluate the necessity of replacing the used catalysts.

ACKNOWLEDGMENTS

The authors would like to thank National Sci-

ence Council R.O.C. for the financial support (Project number: NSC 96-EPA-Z-002-003-). Thanks are also due to Taiwan Power Research Institute, National Taiwan University Center for Nano Science and Technology, and National Tsing Hua University In-strument Center for their technical and analytical as-sistance.

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Discussions of this paper may appear in the discus-sion section of a future issue. All discussions should be submitted to the Editor-in-Chief within six months of publication.

Manuscript Received: May 19, 2010Revision Received: June 13, 2010

and Accepted: June 17, 2010