Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity

ARTICLE IN PRESS

JID: CNF

[m5G;March 17, 2016;9:0]

Combustion and Flame 0 0 0 (2016) 1–13

Contents lists available at ScienceDirect

Combustion and Flame journal homepage: www.elsevier.com/locate/combustflame

Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity Wolfgang Mühlbauer∗, Christian Zöllner, Sebastian Lehmann, Sebastian Lorenz, Dieter Brüggemann Department of Engineering Thermodynamics and Transport Processes (LTTT), Bayreuth Engine Research Center (BERC), University of Bayreuth, Universitätsstr. 30, D-95447 Bayreuth, Germany

a r t i c l e

i n f o

Article history: Received 15 November 2015 Revised 26 February 2016 Accepted 26 February 2016 Available online xxx Keywords: Diesel engine Particulate matter Soot Oxidation reactivity Physicochemical property

a b s t r a c t Plenty of publications have highlighted differences in individual physical or chemical properties of emitted diesel particulate matter (PM) and have correlated them to soot reactivity. An overview is given in the first part of the paper. Our study presented in the second part includes the determination of physical and of chemical properties of the emitted PM, which was generated at different boost and injection pressures on a modern light-duty diesel engine. The individual properties have been opposed to the reactivity of the PM. Afterwards, these correlations are discussed. The experiments show wide-ranging distinctions in soot reactivity (up to 162 °C). The determined differences in soot structures as well as in primary particle sizes are small and do not correlate clearly to soot reactivity. Hence, there has to be a further property which influences soot reactivity to a high extent. PM composition (oxygen, ash content) is identified as a further property impacting soot reactivity. The various ash contents show good correlations to the soot oxidation behavior. The distinctions in ash contents can be explained by the different sampling durations because of large changes in emitted particulate mass, due to the high differences in particle size and number emissions. The source of the ash (Ca, Zn, Al) is attributed to inorganic elements from fuel, lubricating oil and engine wear. In addition, the oxygen content in soot is a further chemical property impacting soot reactivity. © 2016 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

1. Introduction It is well-known that particulate matter (PM) emitted from diesel engines has a negative effect on human health and is associated with mortal diseases like cancer, Alzheimer and Parkinson [1–4]. Therefore, legislations from all over the world give limits for particulate matter emissions from diesel engines [5,6]. These strong regulations are mostly achieved by diesel particulate filters (DPF) which remove emitted particles very efficiently from the exhaust [6–8]. The trapped PM in the DPF builds up a particulate cake which causes an increasing backpressure with progressive operating time. The soot in the DPF has to be removed by active or passive regeneration to avoid disadvantages relating to engine efficiency [6,9]. By active regeneration, the soot is oxidized periodically via late post injection, where additional fuel has to be injected to reach a soot specific regeneration temperature range. By passive regeneration, the trapped PM in the DPF is oxidized continuously via exhaust containing molecular oxygen or nitrogen

∗

Corresponding author. Fax: +49 921 55 7165. E-mail address: [email protected] (W. Mühlbauer).

oxides. The knowledge of the oxidation behavior of the trapped soot in the DPF is a key factor for efficient DPF regeneration procedures [7,8,10]. Hence, many research groups have investigated the soot oxidation reactivity from diesel engines with different emission standards under diverse operating conditions. In current publications, different studies have asserted that the soot oxidation reactivity depends on engine operating parameters and on the diesel fuel which the combustion engine has been operated with. Therefore, an overview of current literature about this topic is given in the following chapter. Afterwards, different explanations for the variations in soot reactivity, presented in literature, are summarized by the authors. The integration and target of the study, which is presented subsequently in the paper, is explained and motivated by the review. 1.1. Differences in soot oxidation behavior By current literature, it has been affirmed that the reactivity of diesel soot is influenced by engine operating conditions (e.g. injection pressure and timing, exhaust gas recirculation, engine speed and load). Leidenberger et al. [11] studied the oxidation behavior of devolatilized PM generated from a four-cylinder Euro 4 light-duty

http://dx.doi.org/10.1016/j.combustflame.2016.02.029 0010-2180/© 2016 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF 2

ARTICLE IN PRESS

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

diesel engine by Thermogravimetric Analysis (TGA) in synthetic air. They determined that the oxidation temperature decreases with higher injection pressures. Xu et al. [12] also found out by TGA in air that devolatilized PM generated with higher injection pressures causes a higher soot reactivity. The variations in injection pressures have been conducted on a heavy-duty diesel engine under different load conditions which met the Chinese national stage III emission standards. The same observation has been made by Ye et al. [13] with soot from an eight-cylinder turbocharged diesel engine which was complied with EPA Tier 2 Bin 9 emission standards. The reactivity of the devolatilized soot samples was also analyzed by TGA. Yehliu et al. [14] have identified by experiments on a fourcylinder light-duty diesel engine that PM generated with higher engine speeds at constant engine torque is more reactive (TGA). In contrast, different engine torques at constant engine speed have no noticeable effects on the reactivity. Further researchers [15,16] pointed out that exhaust gas recirculation has a great impact on soot reactivity. Additionally, Liati et al. [17] showed by experiments with a modern four-cylinder diesel engine that diesel soot oxidation is dependent on the sampling position of PM along the exhaust line of the engine. 1.2. Potential explanations for the large differences in soot oxidation behavior Emitted particulate matter from diesel engines consists of different chemical components and differs strongly in its physical properties [18,19]. Hence, the considerable variation in oxidation reactivity of soot generated at various engine operating modes and by different types of diesel fuels are explained by diverse assumptions. Correlations between soot oxidation reactivity and their physical or chemical properties as found in current literature are summarized in the following section. 1.2.1. Correlation between soot oxidation reactivity and particle size Many studies pointed out that the aggregate diameter as well as the primary particle size change with engine operating parameters [11,20–24] and with the used fuel [25–28]. Hence, the large differences in PM reactivity have been explained by many authors with changes in the physical properties of the emitted particles. Leidenberger et al. [11] correlated the decreased soot oxidation temperature of PM, generated with standard diesel fuel at higher injection pressures on an Euro 4 light-duty engine, with the smaller sizes of primary particles and aggregates. The same was observed by Xu et al. [21] who explained that smaller particle sizes result in a larger active surface favoring the soot oxidation behavior. Lapuerta et al. [28] also figured out that biodiesel soot primary particles are significantly smaller and hence, have a higher specific surface area than those generated by conventional diesel fuel, which results in a higher oxidation reactivity. Lu et al. [29] also observed various soot oxidation rates in different size ranges. Nevertheless, other research groups revealed that ultra-fine soot particles generated by diesel fuel with higher biodiesel content are larger [13,30] but more reactive [13] than those generated by fossil diesel fuel. In conclusion, physical properties like aggregate and primary particle size are not the sole reason for differences in soot reactivity. 1.2.2. Correlation between soot oxidation reactivity and its nanostructure In many publications, distinctions in PM oxidation reactivity are associated with differences in soot particle nanostructures (e.g., [31–33]), which are caused by the in-cylinder combustion process [11,34–36], by pre-treatment or rather by thermal aging (e.g. in the exhaust line by residence time) of the emitted PM [17,37– 39]. Furthermore, many authors use model soot (e.g., [31,40]) as reactivity boundaries based on their nanostructure (less ordered

amorphous versus higher ordered graphitic structure). Thereby, spark-discharged (GfG) soot illustrates the most reactive soot because of its very defective and amorphous structure as well as due to the high surface area of the aggregates. Furnace soot or graphite powder represents the soot with the lowest reactivity based on their flat graphene layers with well-developed graphitic properties referring to less defective structures with higher order [40–42]. In literature, those changes in the soot (nano-) structure are mostly detected by High-Resolution Transmission Electron Microscopy (HRTEM), by Scanning Electron Microscopy (SEM), by Xray diffraction (XRD) or by Raman Spectroscopy (RS) (see Section 2.4.5) [40,43–45]. Knauer et al. [33] determined soot nanostructure (structural order of graphitic and amorphous carbon) and the reactivity from different model and heavy-duty engine soot. The measurements showed a correlation between changes in the more or less ordered nanostructure (amorphous versus graphitic carbon) observed by RS and the soot reactivity analyzed by TPO. In contrast, the experiments of Ye et al. [13] did not show any correlation between soot nanostructure and the reactivity determined by TGA. The nanostructure was analyzed by RS to determine the density of edge sites and the crystalline size distribution and also by XRD to identify the degree of disorder. They supposed that the differences in soot reactivity can be explained in larger length scales. Lapuerta et al. [28] revealed by RS that biodiesel soot has more ordered graphite-like structures and lower amorphous carbon concentrations. In addition, XRD exposed a higher degree of graphitization for biodiesel soot, although the authors measured a higher reactivity for the biodiesel soot by determining the pressure drop during DPF active regeneration. The higher reactivity was also interpreted by the authors due to different length scales (higher curvature of carbon fringes to thinner soot cake in the DPF channels). Liati et al. [45] summarized that distinctions in soot nanostructure (graphene sheet separation distance, degree of crystalline order, primary particle size) obtained by HRTEM and SEM correlates with differences in soot reactivity. Xu et al. [12] also claimed that primary particles generated at higher injection pressures, consist of flatter and shorter graphene layer segments, which is in line with the higher reactivity of emitted particles at advanced injection pressures. In the publication of Jaramillo et al. [46] model carbon blacks and a reference diesel soot with high differences in their nanostructure (onion- to fullerene-like structure) were oxidized isothermally in air by TGA. The experimental results showed that there is a relation between the oxidation behavior of the samples and their nanostructure (differences in lamellae length and tortuosity). The experiments of Al-Qurashi et al. [15] demonstrated that the primary particles of the diesel soot generated with an exhaust gas recirculation (EGR) rate of 20% has a core with a higher disordered fraction than the soot generated without EGR. This results in a slow external and a fast internal oxidation process at the same time for the former soot in contrast to the single burning mode of the soot generated without EGR. The authors explained that the supplemental internal oxidation mode results in a higher reactivity for the soot with 20% EGR. 1.2.3. Correlation between soot oxidation reactivity and chemical functional groups in the PM Adjacent to the correlations mentioned above, there are discussions in literature about the responsibility of chemical functional groups adsorbed on PM for distinctions in soot oxidation reactivity. Chong et al. [47] concluded that the impact of volatile components of the soluble organic fraction (SOF) on PM oxidation reactivity is weighing less. Yehliu et al. [48] asserted that the presence of surface oxygen is not responsible for different soot oxidation behaviors. In addition, in a publication of Liati et al. [45] it is mentioned that carbon-oxygen functional groups have a weak influence on soot oxidation rates. Bhardwaj et al. [25] showed by their

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF

ARTICLE IN PRESS

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

experiments that the generated soot from anoxic fuels contains different oxygen contents and differs significantly in their reactivity. Other research groups figured out that active oxygen species plays an important role in soot combustion [49–52]. In summary, current literature indicates that chemical functional groups (especially oxygen) can also have an impact on soot oxidation reactivity. 1.2.4. Correlation between soot oxidation reactivity and the ash content in the PM Ash particles in the accumulated PM of diesel engines have different sources. The major sources of ash emissions are from the lubricating oil and from the used diesel fuel, which can contain different contents of inorganic additives. These contents vary from oil to oil and from fuel to fuel. A smaller fraction of the accumulated ash originates from engine wear and from products caused by exhaust line corrosion [6,53,54]. The latter one differs from the former one in the way that the particles are larger. A further source of ash emitted by a diesel engine comes from the environment where the engine is operated. In laboratory experiments on engine test benches the last mentioned type origin is at its lowest. The catalytic impact of inorganic components in the emitted PM of diesel engines on soot oxidation reactivity is well-known [6,45,55,56]. Hence, many authors have illustrated the importance of ash on the soot oxidation behavior. Löpez Suárez et al. [57] revealed the higher soot reactivity of biodiesel by the higher content of Mg, Cu, Cr and K with a catalytic active property in the soot. The same has been asserted by Cordiner et al. [58]. Hansen et al. [55] also displayed that typical ash species (Na2 CO3 , K2 CO3 , K3 PO4 ) in PM samples decrease the soot oxidation temperatures. Liati et al. [45] found out that biofuel containing inorganic species (CaS and P-bearing components) contribute to ash engine emissions contiguous to particles from engine and exhaust line wear (Fe, Cr, Ni, Pt components). The influence of lubricating oil-containing ash elements on oxidation kinetics of PM emissions was also shown by Jung et al. [56]. Another study from Choi et al. [59] on a stoichiometrically operated gasoline direct injection (GDI) engine demonstrated that GDI soot reactivity is enhanced by the much higher ash fraction due to catalytic effects. An overview of catalyst materials for DPFs and their application relating to the control of diesel PM is given by Prasad et al. [60]. In summary, different research groups are in complete agreement that the ash fraction in soot affects the oxidation behavior of soot from different types of combustion engines. 1.3. Integration and objective of the present study The short review in the section above indicates that the reason for the differences in soot reactivity behavior does not occur from only one but from several properties of the emitted PM. Some papers [25,61,62] indicate this statement but there is still a knowledge gap relating to the correlation between the distinction of soot oxidation behavior and the individual physicochemical properties of PM emitted from modern diesel engines (primary particle and aggregate size, nanostructure, chemical composition of the emitted PM). Hence, in the first part of our study, presented in the next section of the paper, soot samples from a modern light-duty diesel engine (Euro 5) working with a European standard diesel fuel were extracted at different engine operating conditions (injection and boost pressure). The physical and chemical properties of the engine soot have been identified by several measurement techniques. Physical properties (primary particle size, aggregate size) were analyzed by a High-Resolution Transmission Electron Microscope (HRTEM) and by a Scanning Mobility Particle Sizer (SMPS). Emitted PM mass was determined gravimetrically. Changes in the soot nanostructure were examined by Raman Spectroscopy (RS). Ash as well as oxygen and carbon contents in the samples were diagnosed by Energy-Dispersive X-Ray Spectroscopy (EDX). An opti-

3

Table 1 Technical data of the production diesel engine [63]. Mercedes Benz OM 651 Bore Stroke Displacement Cylinder arrangement Number of valves per cylinder Rated torque Rated power Compression ratio Maximum peak pressure Injection system

Exhaust emission standard in base settings

99 mm 83 mm 2143 cm3 4, in line 4 500 N m at 1600–1800 rpm 150 kW at 4200 rpm 16.2:1 200 bar Common-rail system, four direct-acting piezo-injectors from Delphi Automotive PLC Euro 5

mized thermogravimetric method was used to analyze soot oxidation reactivity. At the end of the paper, correlations between soot reactivity and the individually determined physical and chemical properties are set up and discussed. 2. Experimental setups and methods 2.1. Test bench, diesel engine and fuel The experiments have been conducted on an engine test bench with a water-cooled, eddy-current brake. The peripheral devices of the test bed have been controlled and managed by the automation system CATSNT (Computer Aided Test System) from Siemens AG. A modern four-cylinder diesel engine from Daimler AG (model OM 651, Mercedes Benz, Germany), which is featured with a commonrail system and direct-acting piezoelectric injectors from Delphi Automotive PLC (United Kingdom) has been applied for our studies. The production engine in its base settings complies with the European exhaust emission standard Euro 5. The openly accessible engine control-unit (ECU) enables to adjust engine operating parameters like the boost and the injection pressure, the injected fuel mass and the exhaust gas recirculation (EGR) rate. The interface module ES593.1-Dfrom ETAS Group (Germany) is employed for communication and management between the Integrated Calibration and Application Tool (INCA) from ETAS Group (Germany) and the ECU. Additional modules (ES410.1, ES420.1, ES636.1) from ETAS Group (Germany) are included and linked to ES593.1-D to trace measured signals from different sensors (temperature, pressure, lambda, nitrogen oxides). A hot-film mass airflow sensor is installed (factory-provided) in the intake manifold of the engine. The air flow rate and the injected fuel mass flow have been readout by the interface module. The total exhaust mass flow could be calculated from these data. The prepared exhaust line of the turbo-charged engine contains thermocouples of type K 1.4841 from TC Mess- und Regeltechnik GmbH (Germany) to monitor exhaust temperatures as well as absolute pressure sensors of type PMP 131 from Endress+Hauser Messtechnik GmbH+Co. KG (Germany) to measure exhaust absolute pressures and pressure drops across the tissue filters (see Section 2.3). Oxygen contents (or rather air-fuel equivalence ratios) in the exhaust are detected by calibrated lambda sensors (LSU 4.9) from Robert Bosch GmbH (Germany). Nitrogen oxides in the exhaust are measured by calibrated smart NOx sensors from Continental AG (Germany). The exhaust line is equipped with a diesel oxidation catalyst (DOC) and with different sample positions for emission analysis. The installed DOC (5.66 in. in diameter and 4 in. in length) is made of 300 cells per square inch cordierite material. Technical data of the diesel engine are given in Table 1. Figure 1 shows an overview of the prepared exhaust line.

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

ARTICLE IN PRESS

JID: CNF 4

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

Fig. 1. Experimental setup on the engine test bench for PM loading of tissue quartz filters and copper grids as well as for analyzing particle size distributions.

Table 2 Properties of the diesel fuel according to DIN EN 590.

Fuel property Cetane number Density at 15 °C Kinematic viscosity at 40 °C Lower heating value Sulfur content Carbon content Hydrogen content Oxygen content Fatty acid methyl ester (FAME) content Oxidic ash content Distillation Distillation fuel volume recovered at 250 °C Distillation fuel volume recovered at 350 °C Distillation temperature at 95% by fuel volume recovered

Diesel fuel (DIN EN 590)

Standard test method

53 0.834 g/cm3 2.47 mm2 /s 42.18 MJ/kg 5.3 mg/kg 85.6 wt% 13.3 wt% 0.5 wt% 4.5 vol%

DIN EN 15195 DIN EN ISO 12185 DIN EN ISO 3104 DIN 51900-2 DIN EN ISO 20884 ASTM D 5291 ASTM D 5291 ASTM D 5291 DIN EN 14078

<0.005 wt%

DIN EN ISO 6245

41.5 vol%

DIN EN ISO 3405

94.4 vol%

DIN EN ISO 3405

353.8 °C

DIN EN ISO 3405

A standard diesel fuel according to DIN EN 590, which may contain up to 7% by volume of FAME, is employed for the tests. A 10 0 0 L storage tank for the diesel fuel ensures constant fuel quality (same batch) during the experiments. The diesel fuel had a FAME content of 4.5% by volume and therefore, a marginal oxygen concentration of 0.5% by weight. The fuel had also a broad distillation curve, which is typical for fossil diesel fuels. The main properties of the diesel fuel measured according to the analysis standards are shown in Table 2. The engine was filled with the lubricating oil eni i-Sint SAE 5W-30 from Eni Schmiertechnik GmbH (Germany). 2.2. Engine operating points and parameters As already mentioned in Section 1.1 the soot oxidation reactivity is influenced by engine operating parameters. Hence, a variation of injection (pi ) and boost (pb ) pressures has been examined in this study. The reference operating point with an engine speed of 10 0 0 rpm at constant accelerator position (25%) was chosen to provide a wide variation range of injection and boost pressures. In addition, this reference point with adjusted pi and pb offers particulate mass emissions as large as possible at concurrent low fuel

consumption to enable a higher number of PM samples in lower test bench operation time. The experiments were performed without exhaust gas recirculation to avoid cross-influences. The temporal position of pre-injections remained constant. The start of the main injection event was also kept constant at 6 crank angle degrees (°CA) after top dead center (ATDC). The total injected fuel masses mti per operation cycle and cylinder (for main and pilot injections) were controlled by the opening time of the injector nozzle. Hence, opening times of the injector nozzle were lower for higher injection pressures. The effective engine power Pe was measured by the eddy-current brake for each operating point. Chosen engine operating parameters and conditions are summarized in Table 3. 2.3. Sampling of particulate matter Two different filter types were applied for the different physicochemical analyses (see Section 2.4). Tissue quartz (TQ) filters (type tissuquartz 2500 QAT-UP) from Pall Corporation (USA) with a diameter of 47 mm were employed forTGA), for RS and for SEM-EDX. The TQ-filters were pretreated at 850 °C for four hours in a muffle furnace (model LH 30714) from Nabertherm GmbH (Germany). Afterwards, the filters were put into a modified in-line filter holder from Pall Corporation (USA). Before starting the sampling procedure, the filter holder with the TQ-filter was heated for half an hour at 200 °C in the muffle furnace (see above). It was ensured that the engine was running in the specified stationary operating point. Emitted particulate matter from the diesel engine was sampled after diesel oxidation catalyst (DOC). The TQ-filter loading procedure took place without dilution via a partial exhaust line. The filter holder as well as the partial exhaust line were also heated during sampling. Pressure sensors were installed before and after the filter holder to monitor the pressure drop across the filter. Hence, it was possible to recognize when the filter was loaded with its desired PM mass (∼3 mg). The exact mass was then determined by a precision balance (see Section 2.4.1). For the analysis of primary particles by HRTEM copper grids (lacey-carbon film coated, 3.05 mm diameter, 400 mesh) from Plano GmbH (Germany) are inserted in a self-designed grid-holder (see [11]). Before the sampling procedure, the holder equipment with grid was heated in the muffle furnace at 200 °C for half an hour. Afterwards, the holder with grid was held at a right angle to the (full) exhaust flow

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

ARTICLE IN PRESS

JID: CNF

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

5

Table 3 Engine operating parameters and conditions with standard deviations (engine speed (n), accelerator position (AP), boost pressure (pb ), injection pressure (pi ), start of main injection (SOMI), exhaust gas recirculation rate (EGR), total injected fuel mass per operation cycle and cylinder (mti ), injected fuel mass by pilot injections (mpi ), effective engine power (Pe ), air mass flow rate (m˙ air )). Operating Point OP [-]

n [rpm]

AP [%]

pb [bar]

pi [bar]

SOMI [°CA ATDC]

EGR [%]

mti [mg]

mpi [mg]

m˙ air [g/s]

OP1 OP2 OP3 OP4 OP5

10 0 0 10 0 0 10 0 0 10 0 0 10 0 0

25 25 25 25 25

1.33 1.33 1.33 1.10 1.45

620 300 10 0 0 620 620

6 6 6 6 6

0 0 0 0 0

35 35 35 35 35

2.5 2.5 2.5 2.5 2.5

23.1 23.1 23.1 19.1 25.0

to gather emitted soot particles onto the grid. The same sampling position was also employed to extract a defined exhaust flow by a conditioning system for the measurements of particle size distributions (see Section 2.4.2). The sampling procedure was also monitored by an in parallel installed Pegasor Particle Sensor (PPS) from Pegasor Oy Ltd (Finland). More details on the operation of the PPS are described in [64]. Figure 1 shows the experimental setup on the engine test bench. 2.4. Methods for characterization of particulate matter 2.4.1. Gravimetric determination of particulate mass For gravimetric determination of particulate mass emissions, the TQ-filters were weighed at hot conditions shortly before and immediately after the sampling procedure on the engine test bench. The particulate mass was then defined as the difference between both weighings. The gravimetric determination was carried out by a precision balance (model BP 210D) from Sartorius AG (Germany). The TQ-filters were loaded to a target mass of about 3 mg. The balance has a readability of 0.01 mg and a reproducibility of 0.02 mg (standard deviation). 2.4.2. Scanning Mobility Particle Sizer (SMPS) and exhaust conditioning system A calibrated SMPS has been deployed to determine the electrical mobility particle size distribution. The SMPS is composed of an Electrostatic Classifier (EC 3080, TSI), a Differential Mobility Analyzer (DMA 3081, TSI) and a Condensation Particle Counter (CPC 3022, TSI). At the inlet of the EC an impactor cuts off aerosols, which are larger than the measurement range of the SMPS. The aerosol flow is then guided through a krypton-85 source. Thereby, the particles achieve an equilibrium condition relating to their bipolar charge distribution. In the DMA, the particles in the aerosol flow are deflected according to the electrostatic principle. Thus, the impressed voltage selected a desired monodisperse particle size from the polydisperse aerosol flow. The monodisperse particle flow is fed to the CPC, where the particles are guided through a heated atmosphere saturated with butanol. By cooling the aerosol flow, the butanol vapor condenses on the particles. As a consequence, the particles grow strongly in size which is important for the detection and counting procedure by the optics of the CPC [65,66]. In this way, the particle size distribution of engine-out soot emissions can be analyzed by the method described above. For the measurements of emitted solid particles from diesel engines, the exhaust gas has to be conditioned and diluted before feeding it to a particle measuring instrument, like a SMPS [18,19]. Therefore, a combined system of a Rotating Disc Thermodiluter (model 379020A, TSI) and a Thermal Conditioner Air Supply (model 379030, TSI) is employed to analyze the particle size distribution according to the particle measurement program (PMP) regulations [67,68]. The exhaust from the diesel engine was directly extracted by a partial flow with a heated hose and fed to the con-

Pe [kW] ± ± ± ± ±

0.3 0.4 0.3 0.4 0.4

18.6 17.9 18.3 16.6 18.9

± ± ± ± ±

0.1 0.2 0.1 0.1 0.2

ditioning system (see Fig. 1). The position in the exhaust line for SMPS measurements was the same as for HRTEM sampling. 2.4.3. High-Resolution Transmission Electron Microscopy (HRTEM) Emitted particles from diesel engines are more or less branched-chain aggregates, which consist of spherical primary particles. The diameter of primary particles was analyzed in the study by a HRTEM. For these measurements, the device Libra 200 FE from Carl Zeiss AG (Germany) with a maximum magnification of up to 106 and an image resolution of 0.2 nm was employed. The diameters of the primary particles were analyzed from the HRTEMimages by the Java-based software program ImageJ (written and maintained by Wayne Rasband of National Institutes of Health, USA), which is available as freeware for download [69]. 2.4.4. Scanning Electron Microscopy (SEM) with Energy-Dispersive X-Ray Spectroscopy (EDX) Scanning Electron Microscopy (SEM) combined with EnergyDispersive X-Ray Spectroscopy (EDX) has often been employed in literature [70–72] to analyze the chemical composition of particulate matter. Compared to other methods like Inductively Coupled Plasma Mass Spectrometry (ICP-MS) SEM-EDX has two advantages. On the one hand the method works nondestructively, which is important for examining soot samples from modern diesel engines with less soot emissions because the samples could be used for further physicochemical analysis. On the other hand it does not need any special sample preparation. In addition, it is possible to determine the carbon as well as the oxygen content in the PM simultaneously. Hence, in our study a scanning electron microscope (type SM840A) from Jeol Ltd. (Japan) was deployed to analyze the chemical composition (carbon, oxygen and ash) of the particulate samples. 2.4.5. Raman Spectroscopy (RS) The PM samples on the mentioned tissue quartz filters were also analyzed via Raman Spectroscopy (RS). Raman spectra were obtained with an appropriate setup (see Fig. 2) using a frequency doubled Nd:YVO4 -Laser (Coherent Inc., Verdi V-5) with 532 nm wavelength as excitation source. The laser beam was focused on the sample surface through a focusing lens (HALO f = 90) from Linos AG (Germany). The Raman-light was collected in a backscattering configuration with two lenses and subsequently focused on the entrance of the spectrometer. A long-pass filter (OG-550) from Schott AG (Germany) between the lenses (KBX157 f = 125, KBX151 f = 88.3) from Newport Corporation (United States) was applied to block scattering light in the area of shorter wavelengths as well as Rayleigh-scattering. The incident light is analyzed by a spectrometer (Kaiser Optical Systems, Holospec f/1.8i) and detected by a Peltier-cooled ICCD camera (1024 pixel × 256 pixel, Princeton Instruments, PI-Max 2). The system was calibrated using an Hg(Ar) lamp. Ten accumulations with an integration time of 8 seconds were taken for a good signal-to-noise ratio. The incident laser power was reduced to ∼0.02 W in order to avoid degradation of

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF 6

ARTICLE IN PRESS

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

Fig. 2. Experimental setup for the Raman Spectroscopy (left) and 5-bands regression according to Sadezky et al. [73] (right).

the soot samples. Thereby, no visual or spectral changes were observed in the soot sample during the measurement procedure. From each sample, five Raman spectra were recorded at different positions on each tissue quartz filter to confirm homogeneity of the sampled soot. The software OriginPro 9.1 was used for the spectral analysis. First order Raman spectra were processed in the 80 0–20 0 0 cm−1 range. Curve fitting for the determination of the spectral parameters was performed after linear baseline correction and normalization to the peak at ∼1590 cm−1 . The 5-bands regression, referring to Sadezky et al. [73] (Fig. 2), which is a widely established method for quantitative spectral analysis, was deployed to evaluate the Raman spectra of carbonaceous compounds. According to Sadezky et al., spectra were curve fitted by 4 Lorentzian-shaped bands (G, D1, D2 and D4 at ∼1590, ∼1350, ∼1620 and ∼1200 cm−1 ) and one Gaussian-shaped band (D3 at ∼1500 cm−1 ). 2.4.6. Thermogravimetric Analysis (TGA) Thermogravimetry is a powerful method to determine changes in the sampled particulate mass as a function of increasing temperature with a constant heating rate. In our study, we used a thermogravimetric analyzer (type STA 449 C Jupiter) from NetzschGerätebau GmbH (Germany). The controlling of the TGA and the readout of the mass loss curve and their first derivation (mass loss rate) were executed by the software Proteus Version 4.8 from Netzsch-Gerätebau GmbH (Germany). The sampled PM on TQfilters were not extracted from the filters because this method has a negative impact on the oxidation behavior by changing packing density of the PM sample as mentioned by Bhardwej et al. [74]. Instead, filter samples of 5 mm in diameter were stamped out from the loaded TQ-filters and inserted into the Aluminum oxide crucible for TGA in such a manner that the same initial PM mass was analyzed at every TGA experiment. An optimized thermogravimetric program according to Rodríguez-Fernández et al. [75] was applied with the following steps: The sample was heated up to 400 °C in an inert gas atmosphere (nitrogen, N2 ) with a heating rate of 5 °C/min to remove volatiles. Afterwards, the sample was cooled down to 200 °C under N2 conditions. Subsequently, the composition of the flow was changed to an oxygencontaining atmosphere (5% oxygen (O2 ), 95% N2 , typical engine exhaust conditions). After a short phase of adjustment (10 min) the samples were heated up to 780 °C with a ramp of 5 C/min under the adjusted oxygen atmosphere. The gas flow rate was always set to 70 mL/min according to the recommendation of the manufacturer [76]. In addition to the samples produced by the engine, also model soot (graphite, less reactive and spark discharge soot (GfG), reactive) was analyzed by the TGA for comparison. The yielded mass loss rate curves (dm/dt)oxid from TGA experiments were used to determine a characteristic temperature of the

Fig. 3. Brake specific PM emissions (BSPM) and sampling durations for the different engine operating conditions with standard deviations obtained from the repeated loading procedure (dashed line only to guide the reader‘s eyes).

oxidation process (Tmax ). Tmax is defined as the temperature where maximum mass loss rate (dm/dt)max,oxid occurs (see Fig. 10). 3. Experimental results and discussion 3.1. Emitted particulate mass In engine studies particulate matter emissions are usually normalized to the total exhaust mass flow and to the effective engine power Pe . Hence, the particulate mass flow rate in the exhaust manifold of the engine was calculated from the concentration of particulate matter in the partial flow. The ratio of particulate mass flow in the exhaust line to the effective engine power is defined as brake specific particulate matter emissions (BSPM). For the determination of particulate mass, the loading procedure was repeated three times. Figure 3 shows the average value with standard deviations of brake specific particulate matter emissions (BSPM) and the sampling duration for every operating point (injection and boost pressure variation). BSPM for the lower injection (OP2) and boost pressures (OP4) are much higher than for the reference operating point (OP1). With further increase of pi (OP3) or of pb (OP5) the BSPM decreases again. The reason for this behavior is attributed to a better preparation of the in-cylinder air-fuel mixture, which improves combustion. For details see e.g., [11,20]. In view of the differences in BSPM, the sampling duration (to get the same target mass (∼3 mg) on the TQ-filters independent of engine operating condition) was shortest for the low boost pressure followed by the low injection pressure (see Fig. 3). The sampling of PM took place with heated filter holders, pipes and filters at hot

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF

ARTICLE IN PRESS

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

Fig. 4. Electrical mobility particle size distributions, and calculated geometric mean diameters (GMD) of the emitted particles and total particle number concentrations (TPNC) at different injection and boost pressures.

conditions (∼200 °C) and after the diesel oxidation catalyst (DOC), which provides sufficiently high temperatures (especially at the chosen engine operating points) to oxidize most of the volatile hydrocarbons. Thus, the condensation of volatile hydrocarbons could be eliminated. Subsequently, it could be assumed that particulate matter on the filter consisted mostly of solid particles (soot and ash which can contain hydrogen and / or oxygen) without volatiles (e.g. condensed water or volatile hydrocarbons). In addition, the TGA experiments (see Section 3.5) showed no mass losses under inert gas conditions at high temperatures (up to 400 °C). 3.2. Electrical mobility aggregate and primary particle size distribution The electrical mobility particle diameter of the emitted aggregates at different injection and boost pressures has been measured by a SMPS with a conditioned gas flow as described in Section 2.4.2. Figure 4 displays the average value of normalized number concentration for every dp with standard deviation of five repeated measurements. The figure also shows the average value of the geometric mean diameter (GMD) and the total particle number concentration (TPNC) with standard deviations calculated from the repeated measurements. The analysis indicates that the particle number concentration as well as the geometric mean diameter decreases with increasing injection pressures(OP1 to OP3). Enhancing the boost pressure from 1.10 bar (OP4) to 1.33 bar (OP1) the particle number emissions as well as the GMD decreases significantly. With further increase of pb (OP5), particle number emissions are fewer but the GMD is a little higher than at 1.33 bar (OP1). The changes in particle number emissions and in their sizes explain the differences in the emitted particulate mass (see Section 2.4.1). Low injection and boost pressures cause significantly higher

7

particle number emissions and the emitted particles are considerably larger than those at high injection and boost pressures resulting in higher BSPM (Fig. 3). According to this, OP4 shows higher particle number emissions with significantly larger particles than OP2 followed by OP1 and OP3, which causes higher BSPM for the low boost and injection pressure. Emitted aggregates consist of spherule primary particles (Fig. 5). The size of these primary particles at different injection and boost pressures has been analyzed by HRTEM as described in Section 2.4.3. Figure 6 shows the size distribution and the average primary particle diameter (APPD) with its standard deviation at different injection and boost pressures. The number of evaluated primary particles (nPP ) is also given in the figure for every operating point. Increasing the injection pressure from 300 bar (OP2) to 620 bar (OP1) primary particles tend to become smaller due to the narrower size distribution with a lower APPD. A further increase of pi (OP3) results in a further, slight reduction of the APPD based on the further narrowing of the size distribution and the lower APPD of OP3. Enhancing the boost pressure from 1.10 bar (OP4) to 1.33 bar (OP1) also tends to result in smaller primary particle diameters because of the lower APPD with a similar width of the size distribution and with roughly the same nPP . Whether the differences in APPD are very small in contrast to the width of the distribution, the evaluation suggests the trend described above. Nevertheless, the sizes of primary particles are very similar for the different injection and boost pressures. The experiments relating to the injection pressure variation are consistent with other studies (e.g., [11,12,20,21]). In literature, smaller particles and lower particle number concentrations at higher injection and boost pressures are attributed to a better preparation of the in-cylinder air-fuel mixture and to an increase of air entrainment, which results in lower soot formation but high soot oxidation during in-cylinder combustion. More details in this regard can be found in e.g., [11,20,77,78]. OP5 is missing because the grid with the sample was destroyed at HRTEM imaging. 3.3. Chemical composition of particulate matter Current publications demonstrate that the composition of particulate matter, oxygen as well as catalytic active material (ash particles), influences the soot reactivity (see Sections 1.2.3 and 1.2.4). Hence, the PM of the different engine operating parameters has been analyzed by EDX (Fig. 7). Aluminum, zinc and calcium summarized as ash in the PM as well as the carbon and oxygen content could be detected. The analysis showed that PM samples at low boost (OP4) and low injection pressures (OP2) do not contain any ash elements, whereas samples generated at the reference operating point (OP1) and at high injection (OP3) and boost pressures (OP5) comprise ash contents of different values as elemental composition. PM of OP1 (reference operating point) only contains aluminum, whereas PM of OP5 (high boost pressure) includes zinc. PM generated at high injection pressures comprises the highest value of ash (zinc and calcium). The higher ash contents in the soot samples can be explained by the longer sampling duration

Fig. 5. Examples of TEM images for the different injection and boost pressures.

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF 8

ARTICLE IN PRESS

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

Fig. 6. Primary particle size distribution and average primary particle diameter (APPD) with standard deviation (SD) and the number of measured primary particles (nPP ).

PM mass) becomes higher with increasing sampling duration. The catalytic activity of the detected elements has already been shown in literature. Different research groups observed in their experiments that calcium [79–81] and zinc [79,82–84] are moderately active catalysts, whereas aluminum is a less active catalyst concerning the soot oxidation behavior [85,86]. The oxygen content in the PM samples generated at different injection and boost pressures has also been detected simultaneously by EDX (Fig. 7). One can observe that the oxygen contents in the samples differ strongly. The lowest oxygen content can be found in the sample at low boost pressures (OP4) followed by the reference operation point (OP1) and the operating point with higher injection pressures (OP3). The highest oxygen content could be detected at low injection (OP2) and high boost pressures (OP5). The dissimilar amounts of oxygen in the PM samples can be explained by differences in the in-cylinder combustion process, especially in the pre-reaction phase during ignition as described in literature [25,87]. Fig. 7. Detected elemental composition (carbon C, oxygen O, aluminum Al, zinc Zn, calcium Ca) of the PM samples with standard deviations calculated from EDXAnalysis at six different positions on the filters.

(see Fig. 3) due to lower soot raw emissions at higher injection and boost pressures as a result of better in-cylinder mixture preparation causing lower in-cylinder soot formation [11,20]. Thereby, the ash content of the PM sample from lubricating oil, from inorganic elements in the fuel and from engine wear (at the same loaded

3.4. Particle nanostructure First-order Raman spectra of disordered carbonaceous materials exhibit two broad overlapping bands with peaks at ∼1350 cm−1 (referred to as amorphous band or D-band) and ∼1590 cm−1 (referred to as graphitic band or G-band). The presence of the DPeak occurs from the in-plane vibrational mode at the surface of the sp2 domains and is characteristic for amorphous carbons. The G-Peak originates from the stretching modes of the sp2 site. As

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF

ARTICLE IN PRESS

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

Fig. 8. Average values of D1-FWHM and ID1/IG with standard deviation obtained from five Raman spectra for soot samples from different engine operating parameters.

already mentioned above (Section 2.4.5), the five-peak curve-fitting was used in this study for the determination of the spectral parameters. The D1-full width at half maximum (D1-FWHM) and the integrated intensity ratio of the D1 and G bands (ID1 /IG ) are useful Raman parameters to interpret the nanostructure and the degree of graphitization of the soot. The width of the D-Peak depends on the distribution of clusters with different orders and dimensions. Hence, the D1-FWHM reflects the distribution of the crystallite sizes. In literature, the integrated intensity ratio of the D- and G-Peak is commonly adopted for the estimation of the degree of graphitization or rather for decreasing soot reactivity [15,88–90]. Figure 8 shows the evaluated D1-FWHM and the integrated intensity ratio ID1 /IG of the retrieved soot samples, collected under different engine operating conditions and deactivated EGR by varying the boost and injection pressure. OP1, OP3 and OP4 exhibit lower D1-FWHM than OP2 and OP5. The smaller values for the D1-FWHM imply a higher order of the investigated soot nanostructure. On the other hand soot samples from OP2 and OP5 seem to have a more disordered nanostructure. The integrated intensity ratio of the D1- and the G-peak shows only small differences for the soot samples from different engine operating conditions. Only OP3 (pb = 1.33 bar, pi = 10 0 0 bar) exhibits a significantly lower intensity ratio compared to the other operating points. The small discrepancies of the other soot samples lie immediately within the standard deviation. In conclusion, nanostructures of the soot samples are very similar for the different injection and boost pressures. 3.5. Soot reactivity Figure 9 displays the mass loss rate curve during the inert gas phase (dm/dt)inert normalized to the respective maximum of the mass loss rate curve (dm/dt)max,oxid during the oxidation phase for the PM samples emitted by the diesel engine at different injection and boost pressures. The figure points out that no mass losses can be observed during the inert gas phase for all analyzed PM samples from the diesel engine. This indicates that the PM on the TQfilters is dry (no volatiles) and consists of soot, ash and chemical functional groups like oxygen. Figure 10 shows the mass loss rate curve (dm/dt)oxid normalized to the respective maximum of the curve (dm/dt)max,oxid during the oxidation phase (5% oxygen, 95% nitrogen) for the model soot, graphite and GfG, as well as for the soot samples from the diesel engine. The characteristic temperature Tmax determined from the

9

Fig. 9. Mass loss rates during the inert gas phase normalized to the respective maximum of the mass loss rate curve during oxidation phase for the PM samples from the diesel engine.

Fig. 10. Normalized mass loss rates for the different engine operating parameters and for the model soot (GfG and graphite) under oxygenic atmosphere.

normalized curve of mass loss rates during the oxidation experiment, as described in Section 2.4.6, was deployed for the degree of soot reactivity. The lower Tmax , the higher the reactivity of the soot, and the higher Tmax , the lower the soot reactivity. The uncertainty in determining Tmax was found to be ±3 °C. Graphite shows the lowest reactivity of the studied samples followed by the PM generated at the low boost (OP4) and at the low injection pressure (OP2). Highest reactivity can be observed at the high injection pressure (OP3) followed by the operation point with the high boost pressure (OP5). The reactivity of PM from the engine operating point with an injection pressure and a boost pressure between the maximum values lies in-between the mentioned reactivities. Tmax of GfG can be located next to those of OP5 and OP3. Increasing the injection pressure from 300 bar to 10 0 0 bar results in an absolute reduction of Tmax of 151 °C. The increase of the boost pressure from 1.10 bar to 1.45 bar lowers Tmax of about 162 °C. This observed behavior will be discussed in the following section by correlating PM reactivity to the physicochemical properties of the emitted PM samples.

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF 10

ARTICLE IN PRESS

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

Fig. 11. Correlations between soot reactivity and (a) geometric mean diameter (GMD) of the emitted particles, total particle number concentration (TPNC) with standard deviations from SMPS measurements and average primary particle diameter (APPD) from HRTEM, (b) particle structure from Raman Spectroscopy with standard deviations, (c) PM composition from REM-EDX analysis, and (d) average value of the sampling duration with standard deviation of the soot onto TQ-filters (dashed lines only to guide the reader’s eyes).

3.6. Correlation between reactivity and physicochemical properties of emitted particulate matter In Fig. 11, the reactivity of emitted PM at varying operating conditions is opposed separately to the individual physicochemical properties to find correlations in between. Figure 11a displays that the soot generated at operating points causing smaller aggregates (lower geometric mean diameter (GMD)) and lower total particle number concentrations exhibit higher reactivity. However, as already mentioned in Section 3.2 the differences in primary particle sizes are not that high for the variation of injection and boost pressures. In addition, the correlation between reactivity and primary particle size (APPD) is not consistent in all cases. The reactivity at the low injection pressure (OP2) is slightly higher than for the low boost pressure (OP4) but the APPD tend to be a bit higher for OP2 than for OP4. In addition, it has to be mentioned that the differences in primary particle sizes between the operating points are significantly smaller in contrast to the differences in aggregate sizes and number concentrations. Consequently, the influence of the aggregate size and of number concentration on soot reactivity might be higher than that of the primary particle size. However, it should be mentioned that at low levels of injection pressure (300– 620 bar) and of boost pressure variations (1.10–1.33 bar), the differences in the aggregate sizes and number concentrations are significantly higher than at higher injection (620–10 0 0 bar) and boost pressure levels (1.33–1.45 bar), although the change in soot reactivity is still high at these high levels. Hence, the question arises, what the reason for the high influence of particle size distribution on soot reactivity is. Moreover, there has to be a further property which influences soot reactivity in a high extent as well. As mentioned in Section 2.4.5, the soot nanostructure of the different operating points studied by Raman Spectroscopy does not

show significant variances (Fig. 11b). The small deviations in the integrated intensity ratios of the D1- and the G-peak as well as the D1-full width at half maximum do not clearly emphasize the large differences in soot reactivity. In addition, a correlation between soot reactivity and structure cannot be examined consentaneously. Similar inconsistent conclusions have already been reported in prior work from different research groups [15,62,91]. Figure 11c represents total ash and oxygen concentrations of the soot samples from different injection and boost pressures detected by EDX (see Sections 1.2.3 and 1.2.4). It is obvious that soot reactivity from OP4 to OP2 increases. This observation can be explained by the significantly higher oxygen content in the PM sample at OP2 (Fig. 11a). Although the oxygen content from OP2 to OP1 decreases slightly, the soot reactivity increases. The reason for this observation is that the PM at OP1 contains some ash species in contrast to OP2 and OP4 which do not have any ash contents. From OP3 to OP5, soot reactivity slightly decreases, which can be attributed to the lower ash content of OP5 with a little higher oxygen content. The higher reactivity of OP5 in contrast to OP1 is caused by the slightly higher ash and also by the higher oxygen content. The high distinctions of ash contents in the PM samples can be attributed to the high differences in sampling duration (tsampling ) of the PM to get the same PM mass onto the TQ-filters due to the high changes in emitted soot raw emissions (see Fig. 11d). The high distinctions in emitted particulate mass are explained by the high variations of the GMD and of TPNC (see Fig. 11a). Low discrepancies in soot reactivity (OP4 to OP2 and OP3 to OP5) correlate with low differences in sampling duration, and high discrepancies in soot reactivity (OP4 to OP1, OP2 to OP1, OP1 to OP3, OP1 to OP5) correlate with significantly high differences of the sampling duration. The higher ash content with increasing sampling duration is caused by oil- and fuel-containing inorganic elements as well as

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF

ARTICLE IN PRESS W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

[m5G;March 17, 2016;9:0] 11

by the increasing content of particles from engine wear. In view of new diesel engine technologies with higher injection and boost pressures due to downsizing concepts and low soot raw emission strategies (enhancement of in-cylinder combustion), the impact of catalytic effects of different ash elements in the PM on the soot reactivity will increase in the future.

Furthermore, the authors would like to thank Ingrid Otto (University of Bayreuth, Chair of Materials Processing) for supporting the TGA and the REM-EDX measurements, as well as Dr. Christian Hochmuth (University of Bayreuth, Metals and Alloys) for supporting the HRTEM imaging.

4. Summary and conclusions

References

In the present paper physical and chemical properties of the emitted diesel particulate matter (PM) generated at different boost and injection pressures on a modern light-duty diesel engine were examined by several measurement techniques. The individually determined properties have been opposed to the reactivity of the emitted PM. Afterwards, the found correlations have been discussed. The experiments show clear distinctions in soot reactivity of about 151 °C by varying injection pressures from 300 bar to 10 0 0 bar and of about 162 °C by varying the boost pressure from 1.1 bar to 1.45 bar. The determined differences in the soot structure as well as in the primary particle size are low and do not correlate clearly to soot reactivity. Hence, there has to be a further property which influences soot reactivity to a high extent. PM composition (oxygen, ash content) is identified as another property impacting soot reactivity. The various ash contents in the samples show good correlations to the soot oxidation behavior. The differences in ash contents can be explained by the different sampling durations (to get the same mass onto the TQ-filters) caused by high distinctions in emitted particulate mass. The reasons for that are attributed to high changes in in-cylinder soot production (differences in the soot formation and oxidation processes) by varying engine operating parameters impacting the sizes and number concentrations of emitted particles. The source of the ash (Ca, Zn, Al) is attributed to inorganic elements from lubricating oil, fuel and engine wear. In addition to ash species, the oxygen content in soot is a further chemical property having a great impact on soot reactivity. In the future, by the world-wide trend of enhancing boost and injection pressures (downsizing technology, improving in-cylinder combustion with lower soot raw emissions), the effect of catalytic active species (fuel-containing and oil-containing ash elements) and of soot containing oxygen will play a more and more important role in soot reactivity and hence in efficient DPF regeneration. In further work, the experiments should be conducted with different biofuels and at operating points in common driving cycles (New European Driving Cycle, Worldwide harmonized Light vehicles Test Procedures). Furthermore, the reason for the differences of oxygen in soot has to be clarified in the future and also the role of individual ash elements as well as their dispersion in the PM have to be investigated relating to the soot oxidation behavior.

[1] D.T. Silverman, C.M. Samanic, J.H. Lubin, A.E. Blair, P.A. Stewart, R. Vermeulen, J.B. Coble, N. Rothman, P.L. Schleiff, W.D. Travis, R.G. Ziegler, S. Wacholder, M.D. Attfield, The diesel exhaust in miners study: a nested case–control study of lung cancer and diesel exhaust, J. Natl. Cancer Inst. 104 (2012) 855–868. [2] M.D. Attfield, P.L. Schleiff, J.H. Lubin, A. Blair, P.A. Stewart, R. Vermeulen, J.B. Coble, D.T. Silverman, The diesel exhaust in miners study: a cohort mortality study with emphasis on lung cancer, J. Natl. Cancer Inst. 104 (2012) 869–883. [3] International Agency for Research on Cancer (IARC), Diesel engine exhaust carcinogenic, 2012. [4] A.M. Hartz, B. Bauer, M.L. Block, J.-S. Hong, D.S. Miller, Diesel exhaust particles induce oxidative stress, proinflammatory signaling, and P-glycoprotein up-regulation at the blood-brain barrier, FASEB J. 22 (2008) 2723–2733. [5] European Union, Commission regulation (EU) No 136/2014 of 11 February 2014 amending directive 2007/46/EC of the European parliament and of the council, Commission regulation (EC) No 692/2008 as regards emissions from light passenger and commercial vehicles (Euro 5 and Euro 6) and commission regulation (EU) No 582/2011 as regards emissions from heavy duty vehicles (Euro VI), 2014. [6] T.V. Johnson, Review of vehicular emissions trends, SAE Int. J. Engines 8 (2015) 1152–1167. [7] T.V. Johnson, Diesel emissions in review, SAE Int. J. Engines 4 (2011) 143–157. [8] T.V. Johnson, Diesel emission control in review, SAE Int. J. Fuels Lubr. 2 (2009) 1–12. [9] V. Bermudez, J.R. Serrano, P. Piqueras, Ó. García-Afonso, Influence of dpf soot loading on engine performance with a pre-turbo aftertreatment exhaust line. SAE Technical Paper 2012-01-0362, 2012. [10] K. Ogyu, T. Oya, T. Kasuga, K. Ohno, Study on filter substrate structure for lower backpressure and higher regeneration performance. SAE Technical Paper 200601-1526, 2006. [11] U. Leidenberger, W. Mühlbauer, S. Lorenz, S. Lehmann, D. Brüggemann, Experimental studies on the influence of diesel engine operating parameters on properties of emitted soot particles, Combust. Sci. Technol. 184 (2012) 1–15. [12] Z. Xu, X. Li, C. Guan, Z. Huang, Effects of injection pressure on diesel engine particle physico-chemical properties, Aerosol Sci. Technol. 48 (2014) 128–138. [13] P. Ye, C. Sun, M. Lapuerta, J. Agudelo, R. Vander Wal, A.L. Boehman, T.J. Toops, S. Daw, Impact of rail pressure and biodiesel fueling on the particulate morphology and soot nanostructures from a common-rail turbocharged direct injection diesel engine, Int. J. Engine Res. 17 (2) (2016) 193–208. [14] K. Yehliu, O. Armas, V. Wal, L. Randy, A.L. Boehman, Impact of engine operating modes and combustion phasing on the reactivity of diesel soot, Combust. Flame 160 (2013) 682–691. [15] K. Al-Qurashi, A.L. Boehman, Impact of exhaust gas recirculation (EGR) on the oxidative reactivity of diesel engine soot, Combust. Flame 155 (2008) 675–695. [16] X. Li, Z. Xu, C. Guan, Z. Huang, Impact of exhaust gas recirculation (EGR) on soot reactivity from a diesel engine operating at high load, Appl. Thermal Eng. 68 (2014) 100–106. [17] A. Liati, P. Dimopoulos Eggenschwiler, D. Schreiber, V. Zelenay, M. Ammann, Variations in diesel soot reactivity along the exhaust after-treatment system, based on the morphology and nanostructure of primary soot particles, Combust. Flame 160 (2013) 671–681. [18] M. Matti Maricq, Chemical characterization of particulate emissions from diesel engines: a review, J. Aerosol Sci. 38 (2007) 1079–1118. [19] H. Burtscher, Physical characterization of particulate emissions from diesel engines: a review, J. Aerosol Sci. 36 (2005) 896–932. [20] W. Mühlbauer, U. Leidenberger, S. Lorenz, D. Brüggemann, Optical studies about the influence of diesel engine operating parameters on the physicochemical properties of emitted soot particles, SAE Int. J. Engines 6 (2013) 1866–1876. [21] Z. Xu, X. Li, C. Guan, Z. Huang, Effects of injection timing on exhaust particle size and nanostructure on a diesel engine at different loads, J. Aerosol Sci. 76 (2014) 28–38. [22] D.K. Srivastava, Effect of engine load on size and number distribution of particulate matter emitted from a direct injection compression ignition engine, Aerosol Air Qual. Res. 11 (2011) 915–920. [23] U. Mathis, M. Mohr, R. Kaegi, A. Bertola, K. Boulouchos, Influence of diesel engine combustion parameters on primary soot particle diameter, Environ. Sci. Technol. 39 (2005) 1887–1892. [24] M. Lapuerta, F.J. Martos, J.M. Herreros, Effect of engine operating conditions on the size of primary particles composing diesel soot agglomerates, J. Aerosol Sci. 38 (2007) 455–466. [25] O.P. Bhardwaj, B. Lüers, B. Holderbaum, T. Koerfer, S. Pischinger, M. Honkanen, Utilization of HVO fuel properties in a high efficiency combustion system: part 2: relationship of soot characteristics with its oxidation behavior in DPF, SAE Int. J. Fuels Lubr. 7 (2014) 979–994.

Acknowledgments The research project was funded by the German Ministry of Food, Agriculture and Consumer Protection (Bundesministerium für Ernährung, Landwirtschaft und Verbraucherschutz – BMELV) through its agency for Renewable Resources (Fachagentur Nachwachsende Rohstoffe e. V. – FNR) as well as by the Research Association for Combustion Engines e. V. (Forschungsvereinigung Verbrennungskraftmaschinen e.V. – FVV). Financial support granted by FVV (Project code: 1106) and FNR (Project code: 22041211) as well as Dr. Dieter Rothe (MAN Truck & Bus AG) as chairman of the accompanying project for technical assistance, expertise and coordination are gratefully acknowledged. Thanks to Mr. Ronny Meißner (Daimler AG) for the supply of the diesel engine and to Mr. Thomas Hamacher (ms4 Analysetechnik) for the loan of the Pegasor Particle Sensor.

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF 12

ARTICLE IN PRESS

[m5G;March 17, 2016;9:0]

W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

[26] J. Wei, C. Song, G. Lv, J. Song, L. Wang, H. Pang, A comparative study of the physical properties of in-cylinder soot generated from the combustion of n-heptane and toluene/n-heptane in a diesel engine, Proc. Combust. Inst. 35 (2015) 1939–1946. [27] M. Lapuerta, O. Armas, J. Rodríguez-Fernández, Effect of biodiesel fuels on diesel engine emissions, Prog. Energy Combust. 34 (2008) 198–223. [28] M. Lapuerta, F. Oliva, J.R. Agudelo, A.L. Boehman, Effect of fuel on the soot nanostructure and consequences on loading and regeneration of diesel particulate filters, Combust. Flame 159 (2012) 844–853. [29] T. Lu, C.S. Cheung, Z. Huang, Size-resolved volatility, morphology, nanostructure, and oxidation characteristics of diesel particulate, Energy Fuels 26 (2012) 6168–6176. [30] Y.-C. Lin, C.-F. Lee, T. Fang, Characterization of particle size distribution from diesel engines fueled with palm-biodiesel blends and paraffinic fuel blends, Atmos. Environ. 42 (2008) 1133–1143. [31] J.-O. Müller, D.S. Su, R.E. Jentoft, J. Kröhnert, F.C. Jentoft, R. Schlögl, Morphology-controlled reactivity of carbonaceous materials towards oxidation, Catal. Today 102–103 (2005) 259–265. [32] A.L. Boehman, J. Song, M. Alam, Impact of biodiesel blending on diesel soot and the regeneration of particulate filters, Energy Fuels 19 (2005) 1857–1864. [33] M. Knauer, M. Carrara, D. Rothe, R. Niessner, N.P. Ivleva, Changes in structure and reactivity of soot during oxidation and gasification by oxygen, studied by micro-raman spectroscopy and temperature programmed oxidation, Aerosol Sci. Technol. 43 (2009) 1–8. [34] S. Kook, L.M. Pickett, Soot volume fraction and morphology of conventional, Fischer-Tropsch, coal-derived, and surrogate fuel at diesel conditions, SAE Int. J. Fuels Lubr. 5 (2012) 647–664. [35] B. Menkiel, A. Donkerbroek, R. Uitz, R. Cracknell, L. Ganippa, Measurement of in-cylinder soot particles and their distribution in an optical HSDI diesel engine using time resolved laser induced incandescence (TR-LII), Combust. Flame 159 (2012) 2985–2998. [36] R. Zhang, K. Szeto, S. Kook, Size distribution and structure of wall-deposited soot particles in an automotive-size diesel engine, SAE Int. J. Fuels Lubr. 6 (2013) 605–614. [37] D. Zarvalis, D. Pappas, S. Lorentzou, T. Akritidis, L. Chasapidis, A.G. Konstandopoulos, Experimental study of thermal aging on catalytic diesel particulate filter performance, SAE Int. J. Engines 6 (2013) 688–698. [38] H.L. Fang, M.J. Lance, Influence of soot surface changes on DPF regeneration, SAE Technical Paper 2004-01-3043, 2004. [39] M. Alfè, B. Apicella, R. Barbella, J.-N. Rouzaud, A. Tregrossi, A. Ciajolo, Structure–property relationship in nanostructures of young and mature soot in premixed flames, 32 (2009), pp. 697–704. [40] M. Knauer, M.E. Schuster, D. Su, R. Schlögl, R. Niessner, N.P. Ivleva, Soot structure and reactivity analysis by Raman microspectroscopy, temperature-programmed oxidation, and high-resolution transmission electron microscopy, J. Phys. Chem. A 113 (2009) 13871–13880. [41] V. Wal, L. Randy, A.J. Tomasek, Soot oxidation, Combust. Flame 134 (2003) 1–9. [42] V. Wal, L. Randy, A.J. Tomasek, Soot nanostructure: dependence upon synthesis conditions, Combust. Flame 136 (2004) 129–140. [43] S. Choi, C.L. Myung, S. Park, Review on characterization of nano-particle emissions and PM morphology from internal combustion engines: part 2, Int. J Autom. Technol. 15 (2014) 219–227. [44] K. Yehliu, V. Wal, L. Randy, A.L. Boehman, A comparison of soot nanostructure obtained using two high resolution transmission electron microscopy image analysis algorithms, Carbon 49 (2011) 4256–4268. [45] A. Liati, A. Spiteri, P. Dimopoulos Eggenschwiler, N. Vogel-Schäuble, Microscopic investigation of soot and ash particulate matter derived from biofuel and diesel: implications for the reactivity of soot, J. Nanopart. Res. 14 (2012) 1224. [46] I.C. Jaramillo, C.K. Gaddam, Vander Wal, L. Randy, J.S. Lighty, Effect of nanostructure, oxidative pressure and extent of oxidation on model carbon reactivity, Combust. Flame 162 (2015) 1848–1856. [47] H.S. Chong, S.K. Aggarwal, K.O. Lee, S.Y. Yang, H. Seong, Experimental investigation on the oxidation characteristics of diesel particulates relevant to dpf regeneration, Combust. Sci. Technol. 185 (2013) 95–121. [48] K. Yehliu, Vander Wal, L. Randy, O. Armas, A.L. Boehman, Impact of fuel formulation on the nanostructure and reactivity of diesel soot, Combust. Flame 159 (2012) 3597–3606. [49] A. Bueno - López, K. Krishna, M. Makkee, J.A. Moulijn, Active oxygen from CeO2 and its role in catalysed soot oxidation, Catal. Lett. 99 (2005) 203–205. [50] X. Wang, Y. Zhang, Q. Li, Z. Wang, Z. Zhang, Identification of active oxygen species for soot combustion on LaMnO3 perovskite, Catal. Sci. Technol. 2 (2012) 1822. [51] A. Setiabudi, J. Chen, G. Mul, M. Makkee, J.A. Moulijn, CeO2 catalysed soot oxidation, Appl. Catal. B: Environ. 51 (2004) 9–19. [52] T. Mendiara, M.U. Alzueta, A. Millera, R. Bilbao, Oxidation of acetylene soot: influence of oxygen concentration, Energy Fuels 21 (2007) 3208–3215. [53] I. Dimou, A. Sappok, V. Wong, S. Fujii, H. Sakamoto, K. Yuuki, C.D. Vogt, Influence of material properties and pore design parameters on non-catalyzed diesel particulate filter performance with ash accumulation, SAE Technical Paper 2012-01-1728, 2012. [54] A. Sappok, C. Kamp, V. Wong, Sensitivity analysis of ash packing and distribution in diesel particulate filters to transient changes in exhaust conditions, SAE Int. J. Fuels Lubr. 5 (2012) 733–750. [55] B.B. Hansen, A.D. Jensen, P.A. Jensen, Performance of diesel particulate filter catalysts in the presence of biodiesel ash species, Fuel 106 (2013) 234–240.

[56] H. Jung, D.B. Kittelson, M.R. Zachariah, The influence of engine lubricating oil on diesel nanoparticle emissions and kinetics of oxidation, SAE Technical Paper 20 03-01-3179, 20 03. [57] F.-E. Löpez Suárez, A. Bueno-López, M.-J. Illán-Gómez, B. Ura, J. Trawczynski, Study of the uncatalyzed and catalyzed combustion of diesel and biodiesel soot, Catal. Today 176 (2011) 182–186. [58] S. Cordiner, V. Mulone, M. Nobile, V. Rocco, Diesel engine biofuelling: effects of ash on the behavior of the diesel particulate filter, SAE Technical Paper 201324-0165, 2013. [59] S. Choi, H. Seong, Oxidation characteristics of gasoline direct-injection (GDI) engine soot: catalytic effects of ash and modified kinetic correlation, Combust. Flame 162 (2015) 2371–2389. [60] R. Prasad, V.R. Bella, A review on diesel soot emission, its effect and control, Bull. Chem. React. Eng. Catal. 5 (2011) 69–86. [61] O.P. Bhardwaj, B. Lüers, A.F. Kolbeck, T. Koerfer, F. Kremer, S. Pischinger, A. von Berg, G. Roth, ASME 2013 Internal Combustion Engine Division Fall Technical Conference (2013) V0 02T02A0 07. [62] M.N. Ess, H. Bladt, W. Mühlbauer, S.I. Seher, C. Zöllner, S. Lorenz, D. Brüggemann, U. Nieken, N.P. Ivleva, R. Niessner, Reactivity and structure of soot generated at varying biofuel content and engine operating parameters, Combust. Flame 163 (2016) 157–169. [63] J. Schommers, J. Leweux, T. Betz, J. Huter, B. Jutz, P. Knauel, G. Renner, H. Sass, Der neue Vierzylinder-Dieselmotor für Pkw von Mercedes-Benz, MTZ – Motortechnische Zeitschrift 69 (20 08) 10 0 0–10 09. [64] L. Ntziachristos, S. Amanatidis, Z. Samaras, K. Janka, J. Tikkanen, Application of the pegasor particle sensor for the measurement of mass and particle number emissions, SAE Int. J. Fuels Lubr. 6 (2013) 521–531. [65] P. Kulkarni, P.A. Baron, K. Willeke, Aerosol measurement: principles, techniques, and applications, 3rd ed., Wiley, Hoboken, N.J., 2011. [66] W.C. Hinds, Aerosol technology: properties, behavior, and measurement of airborne particles, 2nd ed., Wiley, New York, 1999. [67] B. Giechaskiel, P. Dilara, J. Andersson, Particle Measurement Programme (PMP) light-duty inter-laboratory exercise: repeatability and reproducibility of the particle number method, Aerosol Sci. Technol. 42 (2008) 528–543. [68] B. Giechaskiel, A. Mamakos, J. Andersson, P. Dilara, G. Martini, W. Schindler, A. Bergmann, Measurement of automotive nonvolatile particle number emissions within the european legislative framework: a review, Aerosol Sci. Technol. 46 (2012) 719–749. [69] W. Rasband, ImageJ: image processing and analysis in Java, http://rsb.info.nih. gov/ij/ (accessed 29.06.15). [70] A. Liati, P. Dimopoulos Eggenschwiler, J. Czerwinski, P. Bonsack, S. Hermle, Comparative studies of particles deposited in diesel particulate filters operating with biofuel, diesel fuel and fuel blends, SAE Technical Paper 2011-240102, 2011. [71] M. Patel, A. Ricardo, C. Leonor, P. Scardi, P.B. Aswath, Morphology, structure and chemistry of extracted diesel soot—part I: transmission electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy and synchrotron X-ray diffraction study, Tribol. Int. 52 (2012) 29–39. [72] O.B. Popovicheva, Microstructure and chemical composition of diesel and biodiesel particle exhaust, Aerosol Air Qual. Res. 14 (2014) 1392–1401. [73] A. Sadezky, H. Muckenhuber, H. Grothe, R. Niessner, U. Pöschl, Raman microspectroscopy of soot and related carbonaceous materials: spectral analysis and structural information, Carbon 43 (2005) 1731–1742. [74] O.P. Bhardwaj, F. Kremer, S. Pischinger, B. Lüers, A.F. Kolbeck, T. Koerfer, Impact of biomass-derived fuels on soot oxidation and DPF regeneration behavior, SAE Int. J. Fuels Lubr. 6 (2013) 505–520. [75] J. Rodríguez-Fernández, F. Oliva, R.A. Vázquez, Characterization of the diesel soot oxidation process through an optimized thermogravimetric method, Energy Fuels 25 (2011) 2039–2048. [76] E. Füglein, J. Hanss, P. Konkret, Untersuchungen zum einfluss der tiegelgeometrie auf die verbrennung verschiedener ruße, Netzsch OnSet 11 (2013) 12–14. [77] L.G. Dodge, S. Simescu, G.D. Neely, M.J. Maymar, D.W. Dickey, C.L. Savonen, Effect of small holes and high injection pressures on diesel engine combustion, SAE Technical Paper 2002-01-0494, 2002. [78] D.R. Tree, K.I. Svensson, Soot processes in compression ignition engines, Prog. Energy Combust. Sci. 33 (2007) 272–309. [79] J. Moldanová, E. Fridell, H. Winnes, S. Holmin-Fridell, J. Boman, A. Jedynska, V. Tishkova, B. Demirdjian, S. Joulie, H. Bladt, N.P. Ivleva, R. Niessner, Physical and chemical characterisation of PM emissions from two ships operating in European emission control areas, Atmos. Meas. Tech. 6 (2013) 3577–3596. [80] J.P. Neeft, M. Makkee, J.A. Moulijn, Metal oxides as catalysts for the oxidation of soot, Chem. Eng. J. Biochem. Eng. J. 64 (1996) 295–302. [81] G. Mul, F. Kapteijn, J.A. Moulijn, Catalytic oxidation of model soot by metal chlorides, Appl. Catal. B: Environ. 12 (1997) 33–47. [82] D.W. McKee, Metal oxides as catalysts for the oxidation of graphite, Carbon 8 (1970) 623–635. [83] E. Heintz, W. Parker, Catalytic effect of major impurities on graphite oxidation, Carbon 4 (1966) 473–482. [84] C. Moreno-Castilla, J. Rivera-Utrilla, A. López-Peinado, I. Fernández-Morales, F.J. López-Garzón, Gasification reaction of a lignite char catalysed by Cr, Mn, Fe, Co, Ni, Cu and Zn in dry and wet air, Fuel 64 (1985) 1220–1223. [85] H. Amariglio, X. Duval, Etude de la combustion catalytique du graphite, Carbon 4 (1966) 323–332. [86] F.E. López-Suárez, A. Bueno-López, M.J. Illán-Gómez, Cu/Al2 O3 catalysts for soot oxidation: copper loading effect, Appl. Catal. B: Environ. 84 (2008) 651–658.

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029

JID: CNF

ARTICLE IN PRESS W. Mühlbauer et al. / Combustion and Flame 000 (2016) 1–13

[87] C.K. Westbrook, W.J. Pitz, O. Herbinet, H.J. Curran, E.J. Silke, A comprehensive detailed chemical kinetic reaction mechanism for combustion of n-alkane hydrocarbons from n-octane to n-hexadecane, Combust. Flame 156 (2009) 181–199. [88] A.C. Ferrari, J. Robertson, Interpretation of Raman spectra of disordered and amorphous carbon, Phys. Rev. B 61 (20 0 0) 14095–14107. [89] T. Jawhari, A. Roid, J. Casado, Raman spectroscopic characterization of some commercially available carbon black materials, Carbon 33 (1995) 1561–1565.

[m5G;March 17, 2016;9:0] 13

[90] A. Williams, R.L. McCormick, R.R. Hayes, J. Ireland, H.L. Fang, Effect of biodiesel blends on diesel particulate filter performance, SAE Technical Paper 2006-013280, 2006. [91] J. Song, M. Alam, A. Boehman, U. Kim, Examination of the oxidation behavior of biodiesel soot, Combust. Flame 146 (2006) 589–604.

Please cite this article as: W. Mühlbauer et al., Correlations between physicochemical properties of emitted diesel particulate matter and its reactivity, Combustion and Flame (2016), http://dx.doi.org/10.1016/j.combustflame.2016.02.029