Variations in Speciated Emissions From Spark-Ignition and Compression-Ignition Motor Vehicles in California’s South Coast Air Basin
By Fujita, Eric M Zielinska, Barbara; Campbell, David E; Arnott, W Patrick; Et al
ABSTRACT The U.S. Department of Energy Gasoline/Diesel PM Split Study examined the sources of uncertainties in using an organic compound-based chemical mass balance receptor model to quantify the contributions of spark-ignition (SI) and compression-ignition (CI) engine exhaust to ambient fine particulate matter (PM^sub 2.5^). This paper presents the chemical composition profiles of SI and CI engine exhaust from the vehicle-testing portion of the study. Chemical analysis of source samples consisted of gravimetric mass, elements, ions, organic carbon (OC), and elemental carbon (EC) by the Interagency Monitoring of Protected Visual Environments (IMPROVE) and Speciation Trends Network (STN) thermal/optical methods, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, alkanes, and polar organic compounds. More than half of the mass of carbonaceous particles emitted by heavy-duty diesel trucks was EC (IMPROVE) and emissions from SI vehicles contained predominantly OC. Although total carbon (TC) by the IMPROVE and STN protocols agreed well for all of the samples, the STN/IMPROVE ratios for EC from SI exhaust decreased with decreasing sample loading. SI vehicles, whether low or high emitters, emitted greater amounts of high- molecular-weight particulate PAHs (benzo[ghi]perylene, indeno[1,2,3- cd]pyrene, and coronene) than did CI vehicles. Diesel emissions contained higher abundances of two- to four-ring semivolatile PAHs. Diacids were emitted by CI vehicles but are also prevalent in secondary organic aerosols, so they cannot be considered unique tracers. Hopanes and steranes were present in lubricating oil with similar composition for both gasoline and diesel vehicles and were negligible in gasoline or diesel fuels. CI vehicles emitted greater total amounts of hopanes and steranes on a mass per mile basis, but abundances were comparable to SI exhaust normalized to TC emissions within measurement uncertainty. The combustion-produced high- molecular-weight PAHs were found in used gasoline motor oil but not in fresh oil and are negligible in used diesel engine oil. The contributions of lubrication oils to abundances of these PAHs in the exhaust were large in some cases and were variable with the age and consumption rate of the oil. These factors contributed to the observed variations in their abundances to total carbon or PM^sub 2.5^ among the SI composition profiles.
INTRODUCTION
Motor vehicle emissions are important sources of ambient air pollution and have been statistically associated with cancer and noncancer health effects.1,2 Vehicle exhaust is a complex mixture of particulate matter (PM), gaseous pollutants, and semivolatile organic compounds (SVOCs) that are in equilibrium with the particle phase. Several studies have been conducted recently to characterize the emission rates and organic speciation of PM from gasoline (or spark-ignition [SI]) and diesel (or compression-ignition [CI]) vehicles.3-12 The rate and chemical composition of gaseous and particulate emissions from diesel and gasoline vehicles depend on many factors, which include vehicle age and mileage, fuel, emission control technology, state of vehicle maintenance, type and condition of lubricating oil, vehicle operating mode (e.g., cold start or hot stabilized), engine load, and ambient temperature. Data from dynamometer exhaust emission tests of properly functioning light- duty gasoline vehicles show that modern, low-mileage vehicles have low CO, hydrocarbon, and PM emission rates during hot stabilized operation and during relatively nonaggressive driving conditions. 13,14 Emission rates are higher for properly functioning vehicles during cold starts, during intermittent high engine load conditions induced by hard acceleration and grade, and at low ambient temperatures.10,13,14 The distribution of emission rates among in- use vehicles is highly skewed with a relatively small fraction of high emitters accounting for a disproportionate fraction of total emissions.4,15,16
Receptor models have been widely used to estimate the contributions of various sources to measured airborne PM concentrations.3,5 The current understanding of the uncertainties associated with receptor modeling calculations is limited by data to sufficiently characterize the variations and representativeness of source composition profiles, especially for motor vehicles. The Gasoline/Diesel PM Split Study was conducted during the summer of 2001 to assess the sources of uncertainties in using the organic compound-based chemical mass balance (CMB) receptor model to quantify the relative contributions of emissions from SI and CI engines to the ambient concentrations of fine PM (PM2.5 ). The impetus for the study was the disparate conclusions obtained from studies in the Los Angeles, CA, area and the Northern Front Range of Colorado regarding the relative contributions of SI and CI vehicles to ambient concentrations of fine particles.3,5,6 Studies conducted in Denver, CO, indicated that gasoline combustion from mobile sources contributed more to ambient PM than diesel combustion. However, studies conducted in Los Angeles indicate that diesel combustion contributed more than gasoline combustion to ambient PM.
Key components of the design for the Gasoline/Diesel PM Split Study included characterization of the variations in exhaust composition within vehicle categories, the differences in determination of elemental carbon (EC) by two alternative methods, and comparability between multiple laboratories in the analysis of organic species. The study called for researchers from the Desert Research Institute (DRI) and the University of Wisconsin Madison (UWM) to work cooperatively on sample collection and quality assurance aspects of the study but to work independently, at least initially, on chemical analysis and data analysis. This current study did not necessarily seek to reconcile the results of the previous studies but was intended to examine the range of uncertainties that may be associated with the methods and procedures for sample collection, chemical analysis, and source apportionment. This paper presents the source composition profiles derived by the DRI. It examines variations in the relative abundances of organic carbon (OC), EC, and potential molecular markers in SI and CI exhaust relative to the factors that may be associated with the observed variations. The ambient source apportionment results obtained by DRI and associated uncertainties are described elsewhere.17,18
EXPERIMENTAL WORK
As part of this collaborative study, Bevilacqua-Knight, Inc. (BKI) with U.S. Environmental Protection Agency (EPA) and West Virginia University (WVU) conducted dynamometer tests of light-duty gasoline-powered vehicles and heavy-duty diesel-powered vehicles, respectively. The vehicle emission tests were conducted at the Ralphs Grocery distribution center in Riverside, CA, during the summer of 2001 (June 2-23 for light-duty vehicles and July 20 to September 19 for heavy-duty diesel vehicles). The vehicle selection and test protocols, vehicle characteristics, and dynamometer systems are described by EPA, BKI, and WVU.19,20 Details of the testing program that are pertinent to the development of exhaust composition profiles are summarized here.
Light-Duty Vehicle Testing
EPA and BKI conducted dynamometer tests on their transportable Clayton Model CTE-50-0 chassis dynamometer for 57 light-duty gasoline vehicles and 2 light-duty diesel vehicles in the 11 combined model-year and mileage categories shown in Table 1. Table S1, located in the supplemental information published at http:// www.awma.org/journal/pdfs/2007/6/10.3155-1047- 3289.57.6.705_supplmaterial.pdf, gives the make, model, model year, mileage, and PM2.5 emission rates for each vehicle.
Regulated emissions were determined with a constant volume sampling system (CVS) and continuous monitors for CO, carbon dioxide (CO2 ), total hydrocarbons (THCs), and oxides of nitrogen (NOx ). BKI tested each vehicle using a modified unified driving cycle (UDC) that consisted of a phase 1 plus phase 2 from a cold start, a 10- min soak, followed immediately by a repeat of the phase 1 (i.e., phase 3) plus phase 2 from a warm start. A pair of time-integrated samples was collected for each vehicle, one during phases 1 and 2 of the test cycle (“cold start” sample) and a second during the repeat of phases 1 and 2 after the 10-min soak (“warm start” sample). The warm start test was repeated for eight vehicles to investigate the reproducibility of the emissions. In two of the replicate tests, a set of parallel samples was collected from a smaller residence chamber with a volume equal to 20% of the main chamber (60 L) to investigate the extent of particle coagulation and condensation.
One composite sample was collected for each model year and mileage group in categories one through four by sampling all of the vehicles within each category through the same sampling media (“media composite”). Samples were collected on separate media for vehicles in all of the remaining vehicle categories and combined in the laboratory according to the scheme shown in Table S1. Selections of samples within the composites were based on a target minimum combined mass loading of 1 mg of OC, which was estimated by subtracting the photoacoustic black carbon (BC) from gravimetric mass. The analytical composites also combined samples with similar BC/PM^sub 2.5^ ratios. Other relevant chemical characterizations included lubricating oils from each vehicle and representative fuel samples from nearby service stations. The lubrication oil samples were analyzed by DRI for organic constituents and by Gregory Poole Laboratories for elements by inductively coupled plasma (ICP) analysis. Heavy-Duty Diesel Vehicle Testing
WVU tested heavy-duty diesel trucks and diesel buses on their transportable heavy-duty vehicle emissions testing laboratories. Thirty trucks were selected for testing in the 12 combined vehicle weight (light-heavy, medium-heavy, and heavy-heavy) and model year categories shown in Table 2. Fifteen trucks were newer model year, well-maintained fleet vehicles. The remaining 15 trucks were a mix of vehicles in typical service. Two transit buses were also tested with one transit bus representing older engine technology and one representing newer engine technology. All 30 trucks were operated over three duty cycles for purposes of developing composition profiles, the City Suburban Heavy Vehicle Route (CSHVR), the highway cycle (HW), and idle operation. The two buses were operated through the CSHVR, an idle period, and the Manhattan test cycle. WVU recorded continuous emissions levels of NOx , THC, CO, and CO2 . PM mass emissions were measured using two parallel filter-sampling trains. PM emissions were also continuously measured by WVU using a tapered element oscillating microbalance (TEOM). An oil sample was withdrawn from each engine tested and analyzed by DRI for organic constituents.
A set of time-integrated samples was collected in parallel by DRI and UWM for each test cycle run on each vehicle. When possible, the secondary dilution ratio was adjusted to compensate for variations in the emission rate of the vehicles. Table S2, in the supplemental information section, gives the make, model, model year, mileage, and PM^sub 2.5^ emission rates for each vehicle and shows which samples were combined into composite samples. Analytical results for the idle tests are not shown, because mass loadings were too low to yield useable data.
Sample Collection and Continuous Measurements
DRI provided a secondary dilution sampler that was capable of collecting diluted exhaust samples from the primary dilution tunnels of the EPA and WVU transportable dynamometers. The DRI dilution sampler was tested by Chang et al.21 and is based on a similar sampler originally designed by Hildemann et al.22 Emissions were withdrawn from the primary exhaust dilution tunnel through a heated Teflon line to the dilution sampler. In the sampler, the exhaust mixed with dilution air under turbulent flow conditions to cool and dilute the exhaust to near-ambient conditions. Ambient air filtered through a high-efficiency particulate air (HEPA) filter, and an activated carbon bed was used for dilution. The secondary dilution was adjusted to ratios between 20 and 50 for diesel testing. Several diesel trucks were also retested without secondary dilution as part of another project. Because of the large range of emission rates for different test cycles and vehicles, the optimal sampling rate could not always be achieved for all of the sampling media. For example, sample loading was excessive in some samples for thermal optical reflectance (TOR) carbon analysis but was optimal for organic speciation. In general, the range of PM emissions for diesel trucks was lower than expected, resulting in many diluted exhaust samples with near or below detection quantities for most organic species. For SI vehicles, the secondary dilution sampler was used without dilution (i.e., as a residence time chamber only) because of the low PM emission rates expected for most SI vehicles.
Sample air from the secondary dilution sampler was distributed to the various samplers from a conical aluminum plenum with 12 exit ports distributed radially around its base. From the residence chamber, the samples were drawn through cyclone separators with a cutoff diameter of 2.5 [mu]m, operating at 113 L/min, and collected using a DRI sequential filter sampler for inorganic species and the DRI sequential fine particulate/SVOC sampler for organic species.10 Samples were also collected by UWM in parallel with DRI from the same sampling plenum. Aerosol samples were collected by DRI on the following media: Gelman polymethylpentane ringed, 2-[mu]m pore size, 47-mm diameter polytetrafluoroethylene Teflon-membrane filters (RPJ047) for particle mass, elements, and water-soluble chloride, nitrate, sulfate, and ammonium; Pallflex 47-mm diameter prefired quartz-fiber filters (2500 QAT-UP) for OC and EC; and Pallflex T60A20 102-mm diameter Teflon-impregnated glass fiber (TIGF) filters followed by a cartridge of 20-60 mesh Amberlite XAD-4 (Aldrich Chemical Company, Inc.) sandwiched between two polyurethane foam (PUF) plugs for organic speciation. A 2,4-dinitrophenylhydrazine cartridge (Sep-Pak) sampler for carbonyl compounds, a Tenax sampler for hydrocarbons in the range of C^sub 8^-C^sub 20^, and a canister sampler for C^sub 2^-C^sub 12^ volatile organic compound speciation were added to the sample train during light-duty passenger vehicle testing as part of the California Regional PM^sub 10^/PM^sub 2.5^ Air Quality Study source characterization project.23
PM^sub 2.5^ mass was monitored during the dynamometer tests for all of the SI and CI vehicles using a TEOM, particle light scattering with a DustTrak nephelometer, and particle absorption using a photoacoustic instrument 24,25 to examine changes in emission rates and ratios of BC to PM2.5 with varying operating conditions.17 The continuous monitors also sampled from the same secondary dilution plenum connected to the primary dilution tunnel, both for gasoline and diesel vehicles. Continuous measurements of DustTrak light scattering provided immediate feedback about the nature of the emissions from vehicles and identified portions of the driving cycles where particulate emissions are greatest and least. They were also useful in determining whether the dilution tunnel had been adequately flushed between measurements. The continuous data were time averaged and accumulated (in real time) to provide total BC emissions and total particle emissions for use in comparison to the EC data from thermal/optical carbon analysis of the quartz filter and gravimetric mass analysis of the Teflon filters.
Periodic dynamic blank samples were collected during both phases of the vehicle testing program to characterize the dilution air used in the BKI constant volume dilution system and in the combined WVU primary dilution system and DRI secondary dilution sampler. The blanks also characterize any sampling artifacts that may have been introduced by components of the sampling system. The methods used to collect these blanks were identical to that used for the vehicle exhaust samples, except that no vehicle dynamometer test was run. The use of dynamic blanks for subtracting background contributions is not straightforward with regard to the development of source composition profiles that include OC and speciated organic compounds. Examination of the continuous light scattering and adsorption data for three of the SI dynamic blanks indicates that residual levels drop off rapidly and do not strongly influence the average concentration of the hour-long blank samples. Similar results were obtained for the CI dynamic blanks. We note that the primary dilution air was HEPA filtered to remove atmospheric background. Some of the OC in the blanks may be an artifact of SVOCs desorbing off the walls of the sampling system and adsorbing on the quartz filter. Desorption of SVOCs is favored in the equilibrium process of passing clean dilution air through the sampling system. Furthermore, subtracting the dynamic blank concentrations of polycyclic aromatic hydrocarbons (PAHs) essentially eliminates the heavier PAHs from the speciation profile for many of the low- emitting, late-model low-mileage SI vehicles and lower-emitting CI vehicles. In addition, many of the PAHs with positive values have large relative uncertainties. Based on these considerations, the profiles developed by DRI for study for subsequent receptor model calculations are reported here without dilution tunnel blank corrections. However, all of the samples were corrected for field/ transport blanks. Results for the dilution tunnel blanks are provided in the supplemental information section.
Analytical Methods
Before use, sampling media were precleaned as follows: quartz fiber filters were baked for several hours in a muffle furnace at 900 [degrees]C, and TIGF filters were cleaned by sonication for 10 min in dichloromethane (DCM; CH2 Cl2 ) twice, with the solvent replaced, drained, and son-icated for 10 min in methanol twice with the solvent replaced. New XAD-4 was washed with liquinox soap and rinsed with hot water, followed with deionized water and technical grade methanol (three to four times). The XAD-4 was then extracted using a Dionex accelerated solvent extractor (ASE) with DCM (CH2 Cl 2 ) at 1500 psi and 80 [degrees]C, followed by acetone. It was then dried in a vacuum oven at 50 [degrees]C and stored in clean 1-L glass jars that were placed in aluminum cans with activated charcoal. PUF plugs were cleaned by first washing with distilled water followed by Dionex ASE extraction for 15 min per cell with acetone at 1500 psi and 80 [degrees]C, followed by 10% diethyl ether in hexane under the same conditions. The extracted PUF plugs were dried in a vacuum oven at 50 [degrees]C for approximatted and stored in clean 1-L glass jars with Teflon-lined lids wrapped in aluminum foil. Each batch of precleaned XAD-4 resin and approximately 10% of precleaned TIGF filters and PUF plugs were checked for purity by solvent extraction and gas chromatography (GC)/mass spectrometry analysis of the extracts. The PUF plugs and XAD-4 resins were assembled into glass cartridges (10 g of XAD between two PUF plugs) and stored at room temperature before shipment to the field. All of the samples were shipped back to DRI in coolers at approximately 4 [degrees]C and stored in a freezer before extraction. Weighing was performed on a Cahn 31 electro microbalance with +-0.001 mg sensitivity. Unexposed and exposed Teflon-membrane filters were equilibrated at a temperature of 20 +- 5 [degrees]C and a relative humidity of 30% +- 5% for a minimum of 24 hr before weighing. The charge on each filter is neutralized by exposure to a polonium source for 30 sec before the filter is placed on the balance pan. X- ray fluorescence analysis was performed on Teflon-membrane filters for elemental analysis using a Kevex Corp. model 700/8000 energy dispersive X-ray fluorescence analyzer.26 Chloride, nitrate, and sulfate ions were measured with the Dionex 2020i ion chromatograph. The Dionex system contains a guard column (AG4a column; no. 37042) and an anion separator column (AS4a column; no. 37041) with a strong basic anion exchange resin and an anion micro membrane suppressor column (250′ 6-mm inside diameter) with a strong acid ion exchange resin. The anion eluent consists of sodium carbonate and sodium bicarbonate prepared in distilled, deionized water. A Technicon TRAACS 800 automated colorimetric system was used to measure ammonium concentrations by the indophenol method.
EC and OC were measured by the TOR method using the Interagency Monitoring of Protected Visual Environments (IMPROVE) temperature/ oxygen cycle (IMPROVE TOR).27,28 Samples were also analyzed according to the Speciation Trends Network (STN) protocol using a thermal/optical transmittance (TOT) instrument. 29 In both methods, samples are collected on quartz filters. A section of the filter sample is placed in the carbon analyzer oven such that the optical reflectance or transmittance of He-Ne laser light (632.8 nm) can be monitored during the analysis process. The filter is first heated under oxygen-free helium purge gas. The volatilized or pyrolyzed carbonaceous gases are carried by the purge gas to the oxidizer catalyst where all of the carbon compounds are converted to CO2 . The CO2 is then reduced to methane, which is quantified by a flame- ionization detector. The carbon evolved during the oxygen-free heating stage is defined as OC. The sample is then heated in the presence of helium gas containing 2% of oxygen, and the carbon evolved during this stage is defined as EC. Some organic compounds pyrolyze when heated during the oxygen-free stage of the analysis and produce additional EC, which is defined as pyrolyzed carbon (PC). The formation of PC is monitored during the analysis by the sample reflectance or transmittance. EC and OC are thus distinguished based on the refractory properties of EC using a thermal evolution carbon analyzer with optical (reflectance or transmittance) correction to compensate for the pyrolysis (charring) of OC. Carbon fractions in the IMPROVE method correspond with temperature steps of 120 [degrees]C (OC1), 250 [degrees]C (OC2), 450 [degrees]C (OC3), and 550 [degrees]C (OC4) in a nonoxidizing helium atmosphere and at 550 [degrees]C (EC1), 700 [degrees]C (EC2), and 850 [degrees]C (EC3) in an oxidizing atmosphere. The temperature steps in the STN thermal evolution protocol are 310 [degrees]C, 480 [degrees]C, 615 [degrees]C, and 900 [degrees]C in a nonoxidizing helium atmosphere and 600 [degrees]C, 675 [degrees]C, and 825 [degrees]C in an oxidizing atmosphere. The STN method uses fixed hold times of 45-120 sec at each heating stage, and IMPROVE method uses variable hold times of 150-580 sec so that carbon responses return to baseline values.
Thermal optical analysis of ambient samples by IMPROVE and STN protocols generally yields equivalent total carbon, but STN EC is often less than IMPROVE EC.30,31 Because EC and OC are operationally defined by the method, the specific instrument used, details of its operation, and choice of thermal evolution protocol can influence the split between EC and OC.32,33 Visual examination of filter darkening at different temperature stages has shown that substantial charring takes place within the filter, possibly because of adsorbed organic gases or diffusion of vaporized particles. The filter transmittance is more influenced by within-filter charring, whereas the filter reflectance is dominated by charring of the near-surface deposit. TOR and TOT corrections converge in the case of only a shallow surface deposit of EC or only a uniformly distributed pyrolyzed OC (POC) through the filter and diverge when EC and POC exist concurrently at the surface and are distributed throughout the filter, respectively, especially when the surface EC evolves before the POC. The difference between TOR and TOT partly depends on the POC/EC ratio in the sample.30 Thus, highly loaded source samples would yield similar EC values for TOR and TOT corrections, whereas lightly loaded source and ambient samples would typically yield different EC values. Although EC values for TOR may tend toward higher EC because of underestimation of the POC correction, higher absorption efficiency of POC within the filter may tend toward lower EC values for TOT.
For organic compound speciation, PUF/XAD/PUF cartridges and TIGF filters were extracted and analyzed together, except for CI blanks, idle cycle tests, and selected samples with low PM loadings, which were extracted and analyzed separately. Before extraction, the following deuter-ated internal standards were added to each filter and cartridge pair: naphthalene-d8 , acenaphthylene-d8 , phenanthrene d10 , anthracene-d10 , chrysene-d12 , pyrene-d10, benz(a)anthracene-d12 , benzo(a)pyrene-d12 , benzo(e) pyrene-d12 , benzo(k)fluoranthene-d-12, benzo(ghi) perylene-d12 , coronene-d12 , cholestane-d50 , and tetrocosane d50. Filters and XAD-4 were extracted with DCM, followed by acetone, using the Dionex ASE. Because PUF media degrade when extracted with DCM, the PUF plugs were extracted twice with acetone using the Dionex ASE. The extracts were then combined and concentrated by rotary evaporation at 20 [degrees]C under gentle vacuum to approximately 1 mL and filtered through 0.45 mm Acrodiscs (Gelman Scientific). The extract was concentrated to 1 mL and split into two fractions. The first fraction was precleaned by the solid-phase extraction technique using Superclean LC-SI SPE cartridges (Supelco) with sequential elution with hexane and hexane/benzene (1:1).34,35 The hexane fraction contained the nonpolar aliphatic hydrocarbons, hopanes, and steranes, and the hexane/benzene fraction contained the PAH. These two fractions were combined and concentrated to approximately 100 [mu]L and analyzed by GC/mass spectrometry technique for hydrocarbons, hopanes, steranes, PAH, and oxy-PAH. The second fraction was used for the polar compound analysis without precleaning. It was deri-vatized using a mixture of bis(trimethylsilyl)trifluoro-acetamide and pyridine to convert the polar compounds into their trimethylsilyl derivatives. The second fraction was evaporated to 100 [mu]L under moisture-filtered ultrahigh purity nitrogen and transferred to 300-[mu]L silanized glass inserts (National Scientific Co., Inc.). Samples were further evaporated to 50 [mu]L, and 25 [mu]L of pyridine (Pierce), 25 [mu]L of internal standard mixture (succinic acid d-4, myristic acid – d27, and 1,2,4-butanetriol), and 150 [mu]L of bis-trimethylsilyltri- fluoroacetamide with 1% N,O-bis (trimethylsilyl) trifluoroacetamide with bis-trimethylsi-lyltrifluoroacetamide (BSTFA) with 1% trimethylchlo-rosilane (Pierce) were added. The glass insert containing the sample was put into a 2-mL vial and sealed. The sample was then placed into a thermal plate (custom made) containing individual vial wells at 70 [degrees]C for 3 hr. The calibration solutions were freshly prepared and derivatized just before the analysis of each sample set, and then all of the samples were analyzed by GC/mass spectrometry within 18 hr to avoid degradation. Analysis of the polar organic compounds and the internal standards added are described elsewhere.36,37
Samples were analyzed by GC/mass spectrometry using Varian CP- 3800 GC equipped with a CP8400 autosampler and interfaced to a Varian Saturn 2000 ion trap operating in electron impact ionization mode (for PAH, oxy-PAH, ho-panes/steranes, and alkanes) or chemical ionization mode, using isobutene as an ionization gas (for polar compounds). Concentrations were quantified by comparing the response of the deuterated internal standards to the analyte of interest. 10 It should also be noted that, because of the lack of authentic standards, most of the hopanes/steranes are identified tentatively (with exception of hop19, hop23, and ster45, for which standards were available), based on the available literature data.34,35,38-40 Diesel fuel and gasoline and diesel lubrication oil samples were obtained from the vehicles immediately after emissions sampling and were analyzed for PAH and hopanes/steranes. The fuel and oils were cleaned and fractionated before analysis using the method described by Wang et al.34,35 and detailed elsewhere.
RESULTS
The 30 SI and 8 CI individual or analytical composite samples were further combined into six composite SI and 4 composite CI exhaust profiles as shown in Table 3. The SI composite profiles consist of low and high emitters for both “cold” (SI_LC and SI_HC, respectively) and “warm” (SI_LW and SI_HW) emission tests. Incremental cold-start profiles were obtained by subr of composite profiles was also derived for vehicles with higher proportions of EC (SI_BC and SI_BW). MDD is the composite of all available speciation data for light-heavy and medium-heavy trucks. HCS and HW are composites exhaust profiles for heavy-heavy trucks on the city suburban heavy vehicle route and highway driving cycles, respectively. Heavy-duty diesel (HDD) is the composite of the HCS and HW profiles. In several tests, secondary dilution of diesel exhaust resulted in insufficient amounts of sample for quantitative analysis of many organic species. These samples were excluded from the composite profiles. Samples collected for all idle tests were below detection. The composite profiles combine samples with similar PM^sub 2.5^ emission rates, EC/TC ratios, abundances of hopanes and steranes, and three of the high molecular weight PAHs, benzo (ghi)perylene, indeno(1,2,3-cd)pyrene, and coronene, that are potential markers for SI exhaust. The speciated emission rates are listed for the composite profiles in Table S3, located in the supplemental information section. These profiles were subsequently used in CMB receptor modeling to estimate the relative contributions of SI and CI exhaust to ambient carbonaceous particles in California’s South Coast Air Basin.18 Fine Particle Mass, Ions, and Metals
The average PM^sub 2.5^ emission rates for SI vehicles on the UDC were 27.2 mg/mi (251.9 maximum) for cold-start tests and 16.9 mg/mi (207.9 maximum) for warm-start tests. The distribution of PM^sub 2.5^ emissions for the 57 test SI vehicles is highly skewed, with 10% that were the highest emitters accounting for 62% and 69% of the cumulative emissions for cold and warm tests, respectively. Average PM^sub 2.5^ emission rates for heavy-duty trucks were 404 mg/mi (1125 maximum) on the hot city-suburban route cycle and 187 mg/mi (520 maximum) on the HW. The distribution of PM2.5 emissions for heavy-duty trucks is less skewed than light-duty SI vehicles, with 12% of the trucks accounting for 30% of the cumulative emissions for the hot CSHVR cycle.
The fractions of noncarbonaceous species to the total PM^sub 2.5^ in the composite profiles were negligible for both SI and diesel vehicles. Silicon and ammonium sulfate were dominant in the samples for light-duty vehicles in groups 1-4. Because these are major constituents of the ambient atmospheric PM, they are likely entrained through the vehicle’s air filter. Zinc, calcium, and phosphorus, which are the dominant elements in lubricating oil, were present in all of the samples. The emission rates of these elements for SI vehicles, shown in Figure 1a, are highly variable with a range spanning approximately 3 orders of magnitude (maximum of 11.8 mg/mi and minimum of 0.015 mg/mi). However, the relative proportions were constant, indicating that lubrication oil is likely the common source of these elements. The emissions distribution was highly skewed with most 1990 and newer SI vehicles emitting <0.1 mg/mi of the three elements and most pre-1990 SI vehicles showing higher emissions. The range of emission rates of these elements was not as large for CI exhaust (Figure 1b). The lower range was comparable to pre-1990 SI vehicles, and the upper end was comparable to the highest-emitting SI vehicles. The relative emissions of the three elements were more variable in CI exhaust with lower proportional amounts of phosphorus with increasing emissions. Although there is a general tendency toward higher PM2.5 emissions with greater emissions of zinc, calcium, and phosphorus, the correlations were weak.
Carbon Composition
More than half of the mass of carbonaceous particles emitted by heavy-duty diesel trucks is EC, as illustrated in Figure 2. The EC/ TC ratios for the combined light and medium heavy-duty diesel trucks (MDD) and the heavy heavy-duty diesel trucks (HDD) were both 0.62 (IMPROVE TOR method) with approximately two thirds of the EC in the EC2 fraction. By comparison, the EC/TC ratios among the SI composite profiles were lower and more variable. PM^sub 2.5^ emissions from SI vehicles with higher emission levels contain predominantly OC with EC/TC ratios of 0.17 and 0.12 for cold and warm start tests, respectively. The EC/TC ratios for lower emitters were 0.31 for both cold and warm start tests. SI vehicles emitted a larger fraction of EC as EC1 than CI vehicles. Table 3 shows that there were a few moderate- to high-emitting SI vehicles with EC/TC ratios that were comparable to heavy-duty diesel trucks (0.56 for cold-start test and 0.53 for warm-start test) with higher fractions of EC in the EC2 fraction.
EC and OC are operationally defined parameters and may vary with the specific instrument and protocol used. The scatterplots in Figure 3 for TC and EC show that measurements by the IMPROVE TOR and STN TOT protocols agree well for highly loaded samples. However, the STN TOT/IMPROVE TOR ratios for EC decrease with decreasing sample loadings. The divergence between the two methods occurs for lightly loaded SI samples. Figure 4 shows scatterplots of STN versus IMPROVE EC measurements for all of the CI (top left) and for SI (top right) samples. The same two plots are shown for lower exhaust concentrations in the bottom panels. Although the two methods agree for CI samples for the entire range of exhaust concentrations, IMPROVE TOR EC is higher relatively to STN TOT EC in SI samples at lower exhaust concentrations. The effect of variations in EC measurements by the two methods on the CMB source apportionments is discussed elsewhere.18
The continuous photoacoustic light absorption measurements showed that all of the vehicles tested, including late-model SI vehicles, had BC emissions.17 For SI vehicles, BC and PM2.5 emission rates can be two to eight times larger during the cold-start phase than during hot stabilized operation. Relatively clean SI vehicles have BC emissions that occur during the more aggressive portions of the driving cycle, with maximum emissions typical during cold start and a secondary peak during aggressive acceleration, which are both associated with fuel/air ratio enrichment. Figure 5 shows examples of the variations in light absorption during the test cycle for very clean, normal, and visibly smoking SI vehicles and for a light-duty diesel vehicle. The clean and normal vehicles had greatest emission concentrations in the first 5 min of phase 1 (cold start), and the similar driving cycle after 35 min in the phase 3 warm start produced much lower emissions. Virtually all of the PM emissions from “normal emitters” come from the first few minutes during a cold start and from hard accelerations with relatively higher amounts of BC produced during both cold starts and hard accelerations.
Distribution of Organic Compounds in Exhaust and Lubricating Oil
Figure 6 presents the emission rates (micrograms per mile) of higher-molecular-weight PAHs that are mostly particle associated in the composite diesel and gasoline exhaust. Gasoline vehicle exhaust contains higher proportions of the six-and seven-ring PAH, indeno(1,2,3-cd)pyrene, benzo(ghi)perylene, and coronene in comparison with diesel exhaust. This is consistent with the comparative composition of PAH emissions that have been reported in previous studies.10,41 In contrast, diesel emissions are enriched in two- to four-ring semivolatile PAHs, including primarily particle- associated chrysene and benz(a)anthracene. Benz(a)anthracene is a relatively reactive PAH; thus, it is not a suitable tracer for diesel emissions. However, chrysene is a stable PAH and is mostly particle associated at ambient conditions. Chrysene correlates well with IMPROVE TOR EC for the four composite diesel profiles (r^sup 2^ 0.97).
Although several six- and seven-ring PAHs are potential markers for gasoline exhaust, their relative abundances to TC emissions were variable. PAHs in lubricating oils may be one possible explanation of this variability. In a previous study, we reported that these PAHs are found in used gasoline motor oil but not in fresh oil and are negligible in used diesel engine oil.10 Combustion-produced PAH can escape from the combustion chamber past the piston rings with the blow-by gases that can absorb into the crankcase oil. We postulate that the concentration of PAH in the lubrication oil increases with mileage accumulation until the next oil change. Consequently, emissions of PAH may also depend on the rate of consumption and age of the lubrication oil, as well as the vehicle operating conditions that directly produce PAHs during combustion. Figure 7 shows the concentrations of the same eight higher- molecular-weight PAHs in diesel fuel and diesel and gasoline vehicle lubrication oils (in micrograms per gram). Gasoline lubrication oils contain higher concentrations of these PAHs in comparison with diesel fuels or oils. This is consistent with previous results.10 Note that whereas the absolute concentrations of PAHs vary in the gasoline vehicle lubricating oil, their proportions to each other are consistent.
Hopanes and steranes are compounds present in crude oil as a result of the decomposition of sterols and other biomass.39 These compounds are present in lubricating oils but not in the fuels.10 They have been used as molecular markers for vehicle emissions and are higher in vehicles that emit oil.10,38-40 Figure 8 shows the emission rates of individual hopanes and steranes for the composite diesel and gasoline vehicle profiles. Table S3 explains the mnemonics. CI composite exhaust profiles contain higher amounts of lower molecular weight hopanes and steranes, whereas the SI exhaust profiles have a more even distribution by molecular weight. This result is inconsistent with previous studies that have shown similar composition of hopanes and steranes in SI and CI exhaust.10 As noted earlier, the results for most CI vehicle samples have higher uncertainty because of the higher dilution ratios used in sample collection. Some CI samples have the expected patterns of hopanes and steranes but were not included in the composite profile because of invalid analytical results for other species (e.g., invalid carbon data because of overloaded quartz filter). Figure 9 shows the comparison of hopanes and ster-anes profiles in the lubricating oils and in the CI and SI vehicle exhaust. The composition of steranes and hopanes is similar in SI vehicle exhaust to that in lubrication oil, especially for steranes. Thus, we estimate lubricating oil emission rates for SI vehicles by assuming that all of the steranes present in emissions are from the lubrication oil and are not destroyed during the combustion process. The lubrication oil emission rates (Oil Em) were calculated from the following equation:
Oil Em (g/mi) = S^sub em^ ([mu]g/mi)/sec^sub oil^ ([mu]g/g) (1)
where S^sub em^ is total steranes emission rate from the SI vehicles, and S^sub oil^ is the total concentration of steranes in the lubrication oil of the corresponding vehicle. The emissions of PAHs that originate from the lubrication oil can be estimated from eq 2:
PAH emitted with oil ([mu]g/mi)=
PAH^sub oil^ ([mu]g/g) * Oil Em (g/mi) (2)
The ratio of PAHs originating from the oil to total PAHs in the exhaust gives the fraction of PAH in the emissions that is associated with oil. Table 4 shows the results calculated for the same eight and three (indeno[1,2,3-cd]pyrene, benzo [ghi]perylene and coronene) higher molecular weight PAHs for SI vehicles. The contribution of lubrication oil to emissions of PAHs ranges from 0.2% to 79% and from 0.1% to 55% for eight and three PAHs, respectively. This contribution depends on two key factors: the vehicle’s oil consumption rate and the time and mileage since the oil was last changed. For example, two SI vehicles from category 7 (SI_7C2 and SI_7C3) are not the highest lubrication oil emitters (67 and 96 mg/mi, respectively, as compared with >300 mg/mi for vehicle SI_10C3), but the PAH contributions from the lubrication oil are the highest among the SI group. This suggests that these two vehicles are excessive oil emitters. Indeed, the OC/TC ratio is also the highest for these two vehicles (91% and 93%, IMPROVE method). The highest lubrication oil emitter, vehicle SI_10C3 (358 mg/mi), has only moderate contribution of heavy PAH from the lubrication oil (5% for three PAHs), but its lubrication oil was only 8 days old, and the concentrations of these PAH in the oil were relatively low (see Figure 7). Vehicles from category 10 are high PM emitters, but the PAHs in the exhaust are formed mostly during the combustion process with a relatively minor contribution from the lubrication oil. It should be noted that the lubrication oil emissions calculated according to eq 1 are often higher than the PM^sub 2.5^ emissions. However, not all of the components of burned oil are in PM, because some may be too volatile to condense on the particles or may be destroyed during the combustion process.
Aliphatic and cyclic hydrocarbons were measured in vehicle emissions only. We quantified 15 n-alkanes (from C14 to C28); 5 branched alkanes: norfarnesane (2,6,10-trimethylundecane), farnesane (2,6,10-trimethyldodecane), norpristane (2,6,10- trimethylpentadecane), pristane (2,6,10,14-tetramethylpentadecane), phytane (2,6,10,14 tetramethylhexadecane); and 14 n- alkylcyclohexanes (from C7- to C20-cyclohexane). Table S3 lists the emission rates of these alkanes and, in addition, a sum of n- alkylcyclohexanes for composite CI and SI vehicles. It is clear from this table that the emission rates of these compounds are much higher for CI than SI vehicles. In fact, only high-emitting SI vehicles, especially in hot start mode, emit any significant amounts of branched and cyclic hydrocarbons. This is true for n-alkanes as well. For CI vehicle exhaust, n-alkanes, branched alkanes, and n- alkylcyclohexanes constitute approximately 60-80%, 6-20%, and 6- 30%, respectively, of total aliphatic and cyclic hydrocarbons. For SI vehicles, these percentages are more spread out, but for the higher emitting vehicles, they are in the same range. All five of the branched alkanes are present in the SI high-emitting cold and warm (SI[owen]HC and SI_HW) profiles as well; thus, they are not unique tracers for diesel vehicle exhaust.
Polar compounds were measured in the vehicle emissions only. Table S3 lists the emission rates of several polar compounds: tridecanoic acid (alkanoic acid), succinic and glutaric acid (alkanedioic acids), maleic acid (alkenedioic acid), and phthalic and isophthalic acid (aromatic diacid). The emission rates of these compounds are much higher for CI than SI vehicles. It is interesting to note that diacids that are often considered atmospheric transformation products are emitted by CI vehicles.42-48 Thus, these compounds are not unique tracers for either vehicle exhaust or secondary organic aerosols.
DISCUSSION
The results of this study are generally consistent with other recent vehicle exhaust emission characterization studies.4-7,10,11 PM emissions of most SI vehicles were relatively low compared with CI vehicles, especially in hot-stabilized mode. The PM^sub 2.5^ emissions of some SI high emitters were comparable to the emissions of most CI vehicles on the highway test cycle. OC and EC are the most abundant species in motor vehicle exhaust, accounting for more than 95% of the total PM^sub 2.5^ mass. EC is dominant in diesel exhaust, and its proportion to total carbon is generally less at lower engine load. More than half the mass of carbonaceous particles emitted by heavy-duty diesel trucks is EC measured by IMPROVE TOR with approximately two thirds in the EC2 fraction. PM^sub 2.5^ emissions from SI high emitters contain predominantly OC. However, BC and PM emission rates for SI vehicles can be two to eight times larger during the cold-start phase than during hot-stabilized operation, which confirm previous results from the Northern Front Range Air Quality Study (NFRAQS).5,6 Relatively clean SI vehicles can also produce BC emissions during the more aggressive portions of the driving cycle. Therefore, the emission profiles for clean SI vehicles from dynamometer tests may contain higher fractions of EC than would be produced in congested urban driving conditions. There are a few moderate-to-high emitting SI vehicles with EC/TC ratios that are comparable to heavy-duty diesel trucks with higher fractions of EC in the EC2 fraction.
Total carbon measurements by the IMPROVE-TOR and STN-TOT protocols agree well for diesel exhaust samples. EC emission rates measured by IMPROVE were also in good agreement with STN for CI exhaust. Although EC measurements for SI vehicles agreed between the two protocols at higher PM emission rates, the divergence increased with decreasing PM emissions. Using IMPROVE EC rather than STN EC in the CMB fit for the Gasoline/Diesel PM Split Study resulted in approximately 40% higher CI contributions to ambient particulate carbon but was not statistically significant within two overlapping standard errors.18 However, these results were attributed to greater differences between the two carbon analysis protocols for ambient samples.18
SI vehicles, whether low or high emitters, have higher emission rates than CI vehicles (per travel distance basis) of the high- molecular-weight particulate PAHs, benzo (ghi)perylene, indeno(1,2,3- cd)pyrene, and coronene. Diesel vehicles have higher emissions of two- to four-ring semivolatile PAHs. Hopanes and steranes are present in lubricating oil with similar composition for both gasoline and diesel vehicles and are negligible in gasoline or diesel fuels. CI vehicles emitted greater total amounts on a mass per mile basis, but abundances were comparable to SI exhaust normalized to total carbon emissions within a margin of error. Emission rates of hopanes and steranes are the highest for both gasoline and diesel high-emitting vehicles. Diacids were emitted by CI vehicles and cannot be considered unique tracers for either vehicle exhaust or secondary organic aerosols.
We also confirmed that the high-molecular-weight particulate PAHs, benzo(ghi)perylene, indeno(1,2,3-cd) pyrene, and coronene, are found in used gasoline motor oil but not in fresh oil and are negligible in used diesel engine oil.10 The contributions of lubrication oils to abundances of these PAHs in the exhaust were large in some cases and were variable with the age and consumption rate of the oil. These factors contributed to the observed variations in their abundances to total carbon or PM^sub 2.5^ among the SI composition profiles obtained in this study. As in the NFRAQS, we found in this study that the CMB apportionments of SI exhaust were sensitive to the abundance of high-molecular-weight PAHs in the profile and, to a lesser extent, to hopanes and steranes.18 Variations in abundances of these species in SI and CI exhaust profiles and differences in IMPROVE and STN EC measurements were two of the more important sources of uncertainty in the CMB analysis for this study.18
ACKNOWLEDGMENTS
This study was funded by the National Renewable Energy Laboratory through U.S. Department of Energy Office of FreedomCAR and Vehicle Technologies. The authors acknowledge the vehicle emissions tests performed by Bevilacqua Knight, Inc., and West Virginia University. They also acknowledge the following Desert Research Institute personnel for their assistance: Kelly Fitch for field sampling, Mark McDaniel and Anna Cunningham for the organic speciation analysis, and Steven Kohl, Barbara Hinsvark, and Dale Crow for analysis of inorganic species. They are grateful to Ralphs Grocery for providing a test site and test vehicles. Lastly, they also thank John Watson for his comments on the paper and for valuable scientific discussions.
IMPLICATIONS
We examined several factors that contribute to variations in chesition of PM2.5 emissions from in-use diesel and gasoline vehicles in California’s South Coast Air Basin. These factors included model year, mileage accumulation, vehicle test cycles, composition of lubrication oils, and variations in sampling and analytical methods. Distinctive differences were found in the abundances of specific chemical species in diesel and gasoline exhaust, but the variations among individual exhaust profiles were large. These variations should be considered when applying specific profiles in receptor modeling or emission inventory development and in estimating the uncertainties associated with the results. REFERENCES
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Eric M. Fujita, Barbara Zielinska, David E. Campbell, W. Patrick Arnott, John C. Sagebiel, Lynn Mazzoleni, and Judith C. Chow
Desert Research Institute, Division of Atmospheric Sciences, Reno, NV
Peter A. Gabele
Source Apportionment and Characterization Branch, National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC
William Crews and Richard Snow
Bevilacqua-Knight, Inc., Research Triangle Park, NC
Nigel N. Clark and W. Scott Wayne
Department of Mechanical and Aerospace Engineering, West Virginia University, Morgantown, WV
Douglas R. Lawson
National Renewable Energy Laboratory, Golden, CO
About the Authors
Eric Fujita and Barbara Zielinska are research professors, David Campbell is an assistant research scientist, John C. Sagebiel is an assistant research professor, and Judith Chow is a research professor in the Division of Atmospheric Sciences at the Desert Research Institute (Nevada System of Higher Education). William “Pat” Arnott is an associate professor in the Department of Physics at the University of Nevada, Reno, NV. Lynn Mazzoleni is a postdoctoral fellow in the Atmospheric Science Department/ Cooperative Institute for Research in the Atmosphere at Colorado State University, Ft. Collins, CO. Douglas R. Lawson is a principal scientist at the National Renewable Energy Laboratory. Nigel N. Clark is a professor and W. Scott Wayne is a research assistant professor of mechanical and aerospace engineering at West Virginia University. Peter A. Gabele is retired from U.S. Environmental Protection Agency. William Crews is currently a senior research leader with Southern Research Institute, Research Triangle Park, NC. Richard Snow is currently with Arcadis, Research Triangle Park, NC. Address correspondence to: Eric M. Fujita, Division of Atmospheric Sciences, Desert Research Institute, 2215 Rag-gio Parkway, Reno, NV, 89512; phone: +1-775-674-7084; fax: +1-775-674-7060; e-mail: Eric.Fujita@dri.edu.
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