Multicomponent Remote Sensing of Vehicle Exhaust by Dispersive

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Environ. Sci. Technol. 2001, 35, 3735-3741

Multicomponent Remote Sensing of Vehicle Exhaust by Dispersive Absorption Spectroscopy. 2. Direct On-Road Ammonia Measurements MARC M. BAUM,* EILEEN S. KIYOMIYA, SASI KUMAR, AND ANASTASIOS M. LAPPAS Department of Chemistry, Oak Crest Institute of Science, 2275 East Foothill Boulevard, Pasadena, California 91107 VADYM A. KAPINUS Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125 HARRY C. LORD III Air Instruments & Measurements, Inc., 13300 Brooks Dr., Suite A, Baldwin Park, California 91706

Remote sensing was employed for the first time to measure NH3 levels in the exhaust of on-road light duty motor vehicles. The sensor also measured the concentration of CO2, CO, hydrocarbons, and NO, among other pollutants, in the emitted exhaust. Field measurements were conducted at a Los Angeles freeway on-ramp; vehicles traveled at cruise speeds between 20 and 25 m s-1 (4555 mi h-1). Mean fleet NH3 levels of 44.7 ( 4.1 ppm were observed. These emissions exhibited a highly skewed distribution: 50.1% of the emitted NH3 was contributed by 10% of the sampled fleet. The pollutant distribution among high NH3 emitters is analyzed to identify the conditions that lead to three-way catalyst malfunction and, hence, NH3 formation. In contradiction with previous reports, we found that high NH3 emissions could not be attributed to vehicles running under rich air-fuel conditions. We estimate a mean fleet NH3 mass emission rate of 667 ( 57 mg L-1 (Er ) 94 ( 8 mg km-1). These findings could have significant implications on air quality in the South Coast Air Basin (SoCAB) of California, since they support the hypothesis that emissions from motor vehicles constitute a dominant regional source of NH3, between 20 and 27% of total daily emissions. As NH3 is the predominant atmospheric base, tropospheric levels play a key role in the buffering capacity of the atmosphere and, hence, the formation of fine aerosol. Our results could explain the ubiquitous distribution of ammonium fine particles observed during fall stagnation conditions in the SoCAB.

Introduction Atmospheric ammonia (NH3) emissions from anthropogenic sources are increasingly coming under scrutiny as associated environmental impacts are becoming better understood (1). Ammonia, the primary atmospheric base, plays a crucial role * Corresponding author phone: (626) 817-0883; fax: (626) 8170884; e-mail: [email protected]. 10.1021/es002046y CCC: $20.00 Published on Web 08/09/2001

 2001 American Chemical Society

in determining the acid-neutralizing capacity of tropospheric air masses (2, 3). Airborne sulfuric and nitric acid, produced by atmospheric oxidation of sulfur dioxide (SO2) and nitrogen dioxide (NO2), respectively (4), react with gaseous NH3 to afford ammonium bisulfate (NH4HSO4), ammonium sulfate [(NH4)2SO4], and ammonium nitrate (NH4NO3) fine particles (aerosol fraction with a mass median aerodynamic diameter of 2.5 µm or less, PM2.5) (5-9). Secondary air pollution particles are well-known to degrade visibility via efficient light scattering (10-22), leading to the dense haze common to many polluted urban atmospheres. As compared to free, gas-phase NH3, NH4+ aerosol has a higher chance for long-range transport as its removal rate from the atmosphere is 5-10 times slower (23). Fine aerosol is of special concern because smaller particles are able to penetrate more deeply into the lung and may lead to adverse health effects. Numerous epidemiological studies have examined air pollutant concentrations in relation to health statistics and have concluded that fine combustion-source pollution, common to many urban and industrial environments, is an important risk factor for cardiopulmonary disease and mortality (24). However, atmospheric NH3 also reduces ambient levels of acidic fine aerosol (pH < 4.3), which is suspected to be more deleterious to human health than neutral aerosol of the same size distribution (25-27). The quantitative ecological impacts resulting from anthropogenic NH3 emissions are still riddled with uncertainties, but evidence is mounting (28, 29) that dry and wet deposition of NH3 and its salts can adversely affect terrestrial (30-39) and aquatic (40-42) ecosystems. Deposited NH3 disturbs soil nutrient balance (35) and can contribute toward soil acidification following nitrification (38). Atmospheric nitrogen deposition, thought to inhibit mechanisms used by needles of some conifers to protect themselves from frost injury (30), has been suggested (43) as one of the factors that may have triggered forest dieback in Europe. Atmospheric nitrogen inputs to aquatic ecosystems are a concern due to the potential for eutrophication (1, 41). Global inventories cite excreta from domestic and wild animals, the use of synthetic N-fertilizers, oceans, and biomass burning as the principal sources (in decreasing order) of the estimated 54 million tons N of NH3 emitted globally in 1990 (23, 44). However, Cass and Fraser reported (45) that NH3 emissions from light duty motor vehicles (LDMVs) equipped with three-way catalysts (TWCs) may compete with agricultural sources on a regional scale, such as the South Coast Air Basin (SoCAB) of California. High NH3 concentrations, frequently exceeding corresponding nitric oxide (NO) levels, emitted in the exhaust of modern LDMVs were first reported by Baum (46, 47) and later confirmed by remote sensing (48). The same remote sensing system was employed to determine NH3 levels, among other pollutants, in the exhaust of 2091 vehicles as they drove up a Southern California freeway on-ramp. For the first time, NH3 emissions from on-road vehicles were measured on a car-by-car basis. Preliminary data from this study suggest that NH3 emissions by vehicles in the SoCAB could be significantly higher than previously suspected (49). The purpose of this paper is to provide a full account of these results. Engine operating conditions and emission profiles of high NH3 emitters will be discussed in terms of TWC performance, as will the implications of our measurements on air pollution modeling and control in the SoCAB. VOL. 35, NO. 18, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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Experimental Details Remote Sensor. Measurements of motor vehicle exhaust emissions were carried out using the novel remote sensing instrument (RSI) described previously (48). The RSI employs dispersive UV-vis and IR absorption spectroscopy to quantify the concentration of over 20 pollutants in a vehicle’s exhaust plume. Only measurements on criteria pollutants and NH3 are presented here. Results on other noncriteria pollutants will be discussed elsewhere. Sampling periods were reduced as compared to the parking lot studies due to the high plume turbulence associated with on-road measurements. Once the vehicle emerged from the optical probe, 480 ms of measurement data were acquired and stored along with 160 ms of reference data, collected just prior to the vehicle entering the beams. After the spectral data are smoothed and the electronic noise is subtracted (vide infra), the BeerLambert expression (50) is applied to afford an absorbance spectrum of the vehicle exhaust plume. Thus, spectral contributions of background species (e.g., carbon dioxide, water vapor, methane, nitrous oxide) cancel out. The RSI’s ability to measure carbon dioxide (CO2) column densities between 1355 and 24 394 ppm-m under field conditions (i.e., optical depth of 70.4 m) has already been demonstrated in a prior report (Figure 3) (48). These spectra were collected with a background CO2 column density of ca. 25 000 ppmm, demonstrating that weak CO2 signals can be measured on top of a strong background signal. Field Measurements. Field measurements were made at the on-ramp of the northbound 605 freeway, Los Angeles St., Baldwin Park, CA, between April 25 and 30, 1999. The site is located in an industrial zone, with the nearest residential area outside a 3-km radius. This ensured that all sampled vehicles were operating under “hot” conditions. It is assumed that all LDMVs are running on California phase II reformulated gasoline. The RSI was set up facing NE, with an 8.8 m spacing between the field and objective mirrors of the multiple reflection system affording a probed air column of 70.4 m. Beam centers were located 31 cm (12 in.) above the road surface. The instrument measured exhaust emissions from vehicles typically travelling between 20 and 25 m s-1 (45-55 mi h-1) as they accelerated onto the freeway. The on-ramp is slightly uphill, and traffic flux along this single lane was in the northwesterly direction. Valid data on 2091 LDMVs were collected between April 26 and April 29; measurements on April 30 were cut short due to rain. Meteorological conditions (wind speed and direction, ambient temperature, relative humidity, barometric pressure, and solar radiation) were acquired using a wireless weather station (Rainwise WS-2000). During the field campaign, weather conditions varied between hot and clear, to rainy and windy. Ambient temperature cycled between 5 and 28 °C, and the barometric pressure was between 98.1 and 99.4 kPa (736 and 746 Torr). Moderate winds, typically 3.1 m s-1 (6.9 mi h-1), peaking at 8.1 m s-1 (18 mi h-1) from a south to east-northeasterly direction prevailed throughout much of the measurement period. Safety. All toxic cylinder gases were handled in fume hoods using standard safety protocols and were destroyed with appropriate chemical scrubbers prior to release to the environment. Remote sensing of vehicle exhaust did not expose the instrument operator to significant levels of emissions. Freeway testing was carried out in close cooperation with CalTrans, under permit no. 799-6SV-0965, and the California Highway Patrol.

Results and Discussion Analytical Approach. The instrumental procedures employed for calibration, signal processing, and data validation have 3736

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FIGURE 1. MIR spectrum of vehicle exhaust calculated using internal “dark” compensation and multi-point baselining, along with the corresponding fit result (11 800 ppm-m CO2). been described previously (48). The high turbulence of exhaust plumes emitted by vehicles travelling at relatively high velocities under demanding meteorological conditions required additional refinements to the computation of recorded transmission spectra, especially in the mid-infrared region (MIR, 5000-2000 cm-1). These improvements will be described in detail elsewhere and only a summary is presented here. Because of the depth of the optically sampled air column, 12CO absorption features in the 2395-2280 cm-1 region 2 (fundamental CdO asymmetric stretch) are completely saturated (i.e., opaque to IR radiation). Carbon dioxide therefore is measured (48) as a function of the 13CO2 absorption band (2320-2240 cm-1), overlapping the edge of the 12CO2 P branch. The rapid scan rate (> 3 cm-1 µs-1) of the IR spectrometer appears to induce “dark” (electronic) noise cross talk from the saturated 12CO2 (no signal) band to the 13CO2 sideband (weak signal, typically 450 digital counts out of a possible 4096). A method was devised to facilitate dynamic subtraction of “dark” values from sample (I) and reference (I0) spectra when calculating absorbance spectra using the BeerLambert expression. This approach relied on predetermined wavelengths in the UV-vis and MIR regions where it is known with certainty that no light was incident on the detectors. In the UV-vis, smoothed signals covering a narrow band of pixels (typically 10-15) at the edges of the array provided a suitable measure of the electronic noise offset. In the IR, three windows of zero transmission, 5345 cm-1 (saturated water, H2O, band), 3680 cm-1 (saturated H2O and 12CO2 bands), and 2350 cm-1 (saturated 12CO2 band), are present when probing an optical depth of 70.4 m. The signals within these spectral windows were used to generate a linear function describing electronic noise across the complete wavelength measurement range of the IR spectrometer. Thus, “dark” correction was achieved internally for each measurement, rather than subtracting a single library “dark” spectrum collected twice daily. A spectrum of vehicle exhaust, processed according to this new approach, is shown in Figure 1. Our refined spectral processing led to improved signal-to-noise ratios in vehicle exhaust absorbance spectra, as well as significant enhancement of the spectral structure in areas of low light levels. The method used to baseline the spectral window in the 2420-2220 cm-1 range, where CO2 is measured, was also improved. Figure 1 shows an example of the fit by a CO2 reference signal on a measured signal. Only samples with CO2 column densities exceeding 4000 ppm-m are reported here. A cutoff filter based on CO2 column densities is commonly used in remote sensing measurements of vehicle

TABLE 1. Gas-Phase Emissions Data on Criteria Pollutants Measured between April 25 and 30, 1999 mean (% V) s.d. (% V) max (% V) Em (g L-1) Er (g km-1)a a

CO2

CO

14.48 1.18 15.05 2100 296

0.79 1.65 11.50 69 9.7

THC (as C3H8) 0.0145 0.0455 1.37 1.9 0.27

NO 0.0665 0.0813 0.623 9.9 1.4

Based on a mean fleet fuel efficiency of 7.1 km L-1.

exhaust emissions (51, 52), since valid measurements are derived from a strong overlap between the gas plume emitted by the vehicle and the remote sensor’s optical probe (48). A measured column density of 4000 ppm-m corresponds to a plume overlap of less than 10%, indicating that no skewing of the data is expected to result from our choice of cutoff filter. Accurate CO2 measurements are essential in evaluating the concentration of pollutants in undiluted vehicle exhaust (53). Criteria Pollutants. In 2000, the U. S. Environmental Protection Agency (EPA) estimated that, for 1998, U.S. onroad vehicles contributed 57, 31, and 29% of all carbon monoxide (CO), nitrogen oxide (NOx), and volatile organic compound emissions, respectively (54). Remote sensing has been used for over a decade as an effective means of identifying high polluting vehicles, especially in terms of CO (55) and total hydrocarbon (THC) (56) measurements. Large databases, containing remote sensing emissions data on hundreds of thousands of vehicles (57), have been compiled in a time- and cost-efficient manner. These data can be useful for atmospheric modeling and computing emission inventories. Remote sensing measurements of criteria pollutants from the present study are presented in Table 1. The advantages of our RSI over other technologies, especially with respect to hydrocarbon measurements, have already been discussed in the literature (48, 58). Analyte concentrations and mass emission rates (Em) were calculated according to published methods (53). Emission rates (Er), in g km-1, are a function of fuel efficiency and require a knowledge of vehicle year, make, and model, which were not recorded in our study. Using the U.S. average fuel economy of 7.1 km L-1 (20 mi gal-1) estimated by the U.S. Department of Energy for 1999, mean mass emissions can be converted conveniently to mean emission rates. However, this approximation may introduce uncertainties in the Er estimates, as mean fuel efficiencies at the measurement point may not equal the national average. Mean observed CO levels (0.79%) were slightly lower than those measured by Stephens (0.82%) in the SoCAB using remote sensing in 1994 (59). Our measured mean total hydrocarbon (THC, as propane) concentrations were significantly lower than the 370 parts per million (ppm, 1 ppm ) 1 part in 106 by volume or moles) reported by Stephens in the same study. Over the five years, reformulated gasoline was introduced, TWC technology was improved, and a larger portion of the on-road fleet was equipped with emissions control systems. These changes may explain the observed reduction in LDMV pollutant emissions. Remote sensing measurements of NO emissions from onroad LDMVs show considerable variation. Zhang et al. reported mean levels of 500 ppm (standard deviation 800 ppm) obtained during a 1994 study in Denver, Colorado. In 1996, Jime´nez et al. measured NO levels (mean, 321 ppm, standard deviation, 525 ppm) in exhaust emissions from vehicles travelling at average velocities of 13.9 m s-1 on a Los Angeles surface street (60). Popp et al. reported mean NO levels of 400 ppm during a 1997 remote sensing study in the Chicago area (61). Our higher observed mean NO concen-

TABLE 2. Gas-Phase Fleet NH3 Emissions Data Measured between April 25 and 30, 1999 mean concentration (ppm V) standard deviation (ppm V) maximum concentration (ppm V) mean NH3/CO2 ratio (ppm V/ppm V) Em (mg L-1) Er (g km-1)a a

44.7 83 2024 31.9 × 10-5 667 94

Based on a mean fleet fuel efficiency of 7.1 km L-1.

trations (665 ppm) can be explained in terms of vehicle driving conditions at the measurement point. Nitric oxide is formed primarily in the postflame gases during combustion in the engine cylinder (62). The kinetics of this reaction are highly dependent on gas temperature, with elevated temperatures leading to high NO formation rates. Nitric oxide emissions are also increased with the engine operating under load and at air-fuel ratios (A/Fs) slightly lean of stoichiometric. Thus, NO emissions are highly dependent on driving conditions. The vehicles in our study were travelling under load, due to the moderate incline of the on-ramp, and at high velocities, explaining the relatively high NO concentrations in the vehicle exhaust plumes. Mean mass emissions were calculated as 69 g L-1 (260 g gal-1) and 1.9 g L-1 (7.3 g gal-1) for CO and THC. These levels are significantly lower than Em estimates of 130 g L-1 (20.8 g km-1) and 9.1 g L-1 (1.5 g km-1) for CO and THC, respectively, reported by Fraser and Cass based on 1993 measurements in the Van Nuys Tunnel (45). The observed differences also can be attributed to the gradual reduction in LDMV fleet emissions during the 1990s. As expected (63), the pollutant emission distributions for all three pollutants were highly skewed; 10% of the measured vehicle fleet contributed over 50% of the total emissions, except in the case of NO (38% of total emissions generated by the 10% dirtiest vehicles). NH3 Emissions. For the first time, remote sensing was used to measure gas-phase NH3 directly in the exhaust plume emitted by on-road vehicles. The mean NH3 emission of the fleet was 44.7 ( 4.1 ppm, mean NH3/CO2 ratio of (31.9 ( 2.8) × 10-5, with a standard deviation of 83 ppm (see Table 2); the maximum observed NH3 concentration was 2024 ppm. A histogram of the distribution of NH3 emissions is presented in Figure 2. The negative readings primarily result from measurement noise at low emissions (vide infra) and are retained to avoid biasing of the average. We found that 21 vehicles emitted NH3 levels below -30 ppm (highest negative emission: -165 ppm), probably resulting from a low emitter following in the wake of a high emitter. These data were not used in the calculation of the mean to avoid biasing. The instrument confidence factor was evaluated from the distribution of the negative instrument readings (Figure 2) in an analogous manner to that reported by Jime´nez et al. (60, 64). This approach has the advantage of quantifying instrument uncertainty in an unbiased, systematic fashion, since small negative emissions generally can be assumed to have no other physical meaning. There are numerous factors contributing to potential biases of on-road vehicular remote sensing measurements. Instrument noise will primarily depend on fluctuations in radiation levels emitted by the optical sources and on electronics noise inherent to the spectrometers. Optical alignment, environmental conditions (e.g., wind speed), as well as the dynamics and pollutant concentration in the emitted plume, will contribute further to the errors associated with diluted exhaust measurements (i.e., uncorrected pollutant concentrations in the probed air column). The errors are then amplified by correcting for dilution using CO2, CO, and THC measurements; uncertainties from all these measurements are introduced into the undiluted pollutant concentration. Further discussion of the VOL. 35, NO. 18, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 2. Frequency of NH3 emission readings between -50 and 300 ppm (full range -170 to 2030 ppm).

FIGURE 3. Statistical distribution of NH3 emissions. factors limiting remote sensor accuracy is provided in the literature (52). Our estimation of NH3 measurement uncertainty takes these error sources into account by using a large data set collected under the real-world conditions of the field campaign. Ammonia emissions were found to follow a γ-distribution function: 10% of the sampled fleet was responsible for 50.1% of the total emissions. This important observation is illustrated by the decile plot presented in Figure 3; the first decile represents the fraction of the total analyte produced by the 10% dirtiest fraction of the measured vehicle fleet, and so on. Vehicular NH3 exhaust concentrations can be converted into an estimated Er using eq 1:

Er ) {[NH3]/[CO2]}Em(CO2)/7.1

(1)

where [NH3]/[CO2] is a mean ratio of “diluted” measurements (i.e., remote sensor readings prior to correction for plume dilution and overlap between the optical probe and the diffusing exhaust plume); the mean CO2 mass emission rate, Em(CO2), is calculated as 2100 g L-1 (7950 g gal-1) according to published methods (53). Using the above expression, a mass emission NH3 emission rate of 667 ( 57 mg L-1 (Er ) 94 ( 8 mg km-1) is calculated based our remote sensing measurements. Gas-phase NH3 in the Van Nuys Tunnel study (vide supra) was collected onto open-faced filter systems impregnated 3738

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with oxalic acid (45). Ammonium levels were determined colorimetrically in aqueous extracts of the filters. Estimated NH3 emission rates of 72 mg km-1 (ca. 480 mg L-1) were calculated for a fleet consisting exclusively of vehicles equipped with TWCs, or TWCs plus oxidizing catalysts. In the summer of 1999, Kean et al. conducted NH3 tunnel measurements in the San Francisco Bay area using an analogous approach to that described by Fraser & Cass (65). Ammonia sampling was performed using glass annular denuders coated with a solution of citric acid and glycerin in methanol; the denuders were washed with deionized water and the aqueous extracts were analyzed by ion chromatography to determine NH4+ concentrations. Kean et al. reported NH3 mass emission rates of 475 ( 29 mg L-1, statistically equivalent to those estimated by Fraser and Cass for a modern vehicle fleet. In contrast, our calculated NH3 mass emission rates of 667 ( 57 mg L-1 are 28% higher than those previous estimates. The magnitude of vehicular NH3 emission is likely to be dependent on driving conditions and, hence, the location of the RSI. The 2091 vehicles measured at the freeway on-ramp were typically travelling at, or close to, cruise speeds of 24 m s-1 (55 mi h-1). The gradual incline of the ramp prevented vehicles from idling through the measurement point. Therefore, driving conditions should have been representative of freeway travel. The technique used in the tunnel NH3 measurements is known to suffer from sampling artifacts that tend to give low NH3 readings; sampling losses up to 13% have been reported (65). Ammonia losses in the tunnel due to wall deposition also are not treated specifically. On the basis of these arguments, our NH3 emission rates appear realistic for the SoCAB. However, more comprehensive remote sensing studies at a variety of sites representative of driving patterns in the SoCAB, along with vehicle identification as well as speed and acceleration measurements, are required for NH3 inventory models. Mechanism of Heterogeneous Transition Metal-catalyzed NH3 Formation. The dominant reaction for NO conversion to dinitrogen (N2) in TWCs is either by reaction with dihydrogen (H2), eq 2, or CO, eq 3 (66); NO can also react with H2 to yield NH3, eq 4. All three processes are

2NO + 2H2 f N2 + 2H2O

∆H -665 kJ mol-1

2NO + 2CO f N2 + 2CO2

∆H -747 kJ mol-1 (3)

2NO + 5H2 f 2NH3 + 2H2O

∆H -273 kJ mol-1

(2)

(4)

thermodynamically favored, with the formation of NH3 being the least exothermic. Virtually all the NH3 emitted by in-use vehicles is assumed to form in the TWC. The reduction of NO, formally N(II), to N2, formally N(0), is a four-electron process, with another six electrons required to reduce N2 further, yielding two molecules NH3, formally N(-III). In nature, the molybdoenzyme nitrogenase is wellknown to afford NH3, the kinetic product, from N2 (67). The same metalloenzyme also catalyzes the two-electron reduction of nitrous oxide (N2O) to N2 (68). The mechanism of NO reduction in synthetic systems employing TWCs is unclear (69), but the reaction’s selectivity appears to be governed by the relative amounts of N, NO, and H adsorbed to the catalyst surface. A series of reaction steps have been postulated in the literature (66, 69-79). The complexity of these interrelated processes suggests that engine running conditions alone may not offer a satisfactory explanation for elevated vehicular NH3 emissions. In 1980, two parallel laboratory studies investigated NH3 emissions from five (80) and 17 (81) test LDMVs equipped with a variety of emission control systems. Cadle and Mulawa found elevated NH3 emissions (327.1 ppm) in the exhaust of

TABLE 3. Emissions Data of the 10% Highest NH3 Emitters (209 vehicles) Measured between April 25 and 30, 1999 mean concentration (ppm V) standard deviation (ppm V) mean A/F standard deviation mean [NH3]/[CO] ratio (ppm V/ppm V) mean [NH3]/[HC] ratio (ppm V/ppm V) mean [NH3]/[NO] ratio (ppm V/ppm V)

220 156 14.3 0.6 130 1.15 0.40

only one vehicle, which was running under highly fuel-rich (air/fuel ratio < 13.5) conditions (81). Urban and Garbe also found the highest NH3 emissions (57 mg km-1) when the vehicles were running fuel-rich, with the air pump disabled to simulate malfunctioning conditions (80). However, it is unlikely that these isolated observations explain the distribution of high NH3 emitters in a modern, on-road fleet. Gasoline formulations and emission control technologies have evolved significantly over the past 20 years. The potential impact of lowering fuel sulfur levels on NH3 emissions, for instance, has been discussed previously (48). The above laboratory studies also examined a very small set of vehicles, probably not representative of a modern on-road fleet. Nevertheless, these inconclusive results are commonly used to speculate on the cause of elevated NH3 emission in the exhaust of modern LDMVs. Multicomponent remote sensing allows the emission characteristics from a large set of high NH3 emitters to be examined noninvasively for the first time under real-world driving conditions. The observed γ-distribution signifies that “dirty” vehicles are intrinsically different from “clean” vehicles. The emission characteristics of the 10% of the highest NH3 emitters, 209 LDMVs, are shown in Table 3. These vehicles emitted a mean NH3 concentration of 220 ppm, and there appeared to be no direct correlation between the NH3 levels and CO, HC, and NO concentrations. This lack of correlation is not surprising when the mechanism for catalytic NH3 formation is considered. Fuel-rich conditions are required to afford H2 and adsorbed H-atoms, and adsorbed CO species, whereas stoichiometric, or excess air, conditions are needed to yield adsorbed NO and N species. The selectivity of subsequent reduction reactions on the catalyst yielding NH3 in lieu of N2, N2O, and nitrous acid (HONO) will depend on numerous factors, including absolute and relative surface area, as well as gas-phase, concentrations of these species. There was also no apparent correlation between NH3 levels and instantaneous A/F (by mass), which were calculated in terms of a carbon balance (53). Interestingly, the mean A/F for high NH3 emitters was 14.3, near stoichiometric, not highly fuel-rich (i.e., A/F < 13.5) as predicted by the 1980 reports. Our results are supported by recent laboratory studies, which showed that isocyanic acid (HNCO), which hydrolyzes to NH3 on the catalyst support (82), can form in the presence of O2 (83). Cant et al. also showed that NH3 may be generated during warm-up under lightly lean conditions (84). Our A/F calculations are expected to suffer from a low bias, since the approach based on carbon balance (i.e., using CO2, CO, and THC emissions data) only is applicable to vehicles running in fuel-rich or stoichiometric regimes. Only 19 out of the 209 high NH3 emitters were operating at an instantaneous A/F below 13.5. These important observations clearly indicate that engine running conditions alone, especially low A/F, do not explain the high NH3 emissions generated by a small portion of the on-road fleet. The cause for malfunctioning emission control systems, and the resulting high NH3 emissions, may be linked to the TWC technology, both the type of catalyst system and its condition, and to the driving conditions. In a previous remote sensing study on

the emission characteristics of 20 test vehicles, we measured the highest NH3 levels in the exhaust of six LDMVs manufactured between 1993 and 1998 (48), indicating that older vehicles equipped with early TWC technology are not necessarily high NH3 generators. Further large-scale remote sensing studies, in conjunction with identification of vehicle make, model, year, and catalyst type as well as speed and acceleration measurements, are required to shed further light on this complex phenomenon. Implications of Vehicular NH3 Emissions on Regional Air Quality. In 2000, the EPA attributed 86% of the total national NH3 emissions for 1998 to livestock agriculture and fertilizer application (54). On-road and nonroad engines and vehicles for the same year were said to make up only 5% of the total NH3 emission budget on a national scale. Between 1990 and 1998, vehicular NH3 emissions are believed to have increased from 198 to 260 thousand short tons (54), probably due to a reduction of the noncatalyst, oxidation catalyst, and dual-bed catalyst vehicle portion of the on-road fleet. The environmental and ecological implications of increased NH3 emissions have already been discussed above. Results from recent tunnel studies in California (45, 65), together with the on-road remote sensing measurements presented here strongly suggest that vehicular NH3 emissions may be more significant than previously suspected. Traffic in the SoCAB amounts to ca. 471 × 106 km day-1 (45), leading to an estimated 44 t day-1 of vehicular, gas-phase NH3 emissions in this region, based on our calculated NH3 emission rates of 94 mg km-1. Ammonia release from livestock waste decomposition at dairies in the same geographical area is between 27 and 30 t day-1, out of an inventory of about 165-218 t day-1 indicating that emissions from vehicles could be the dominant source of NH3 (i.e., between 20 and 27% of total emissions). Ammonia emissions from vehicles on a regional scale therefore could be up to five times greater than the national average. The spatial and temporal distribution of atmospheric ammonium aerosol in the SoCAB has been widely studied over the past two decades (5-8, 85-90). A common observation is the uniform concentration of NH4+ fine aerosol throughout the Basin in the summer months. Persistent onshore winds sweep across the Basin to the north and east with concentrations effectively doubling at the Rubidoux sampling site, situated in the eastern portion of the SoCAB downwind of the Los Angeles metropolitan area. Rubidoux is also located just east of the Chino dairy area where livestock waste decomposition and other agricultural activities form a concentrated localized NH3 source, which contributes to the observed enhanced production of NH4+ aerosol. In a particle-monitoring program spanning January 1995 to February 1996, Kim et al. characterized temporal variations of PM2.5 in the SoCAB (90). The highest concentrations (monthly averages typically 60 µg m-3, with 24 h averages exceeding 100 µg m-3) of fine particles were measured during fall (October-December) stagnation conditionssweak desert high-pressure systems counteract onshore breeze thereby minimizing air flow through the Basinsand cool temperatures. This observation is consistent with other recent reports (87, 88), but Kim et al. found that NH4+ levels during stagnant conditions are ubiquitous throughout the entire SoCAB fine particle-monitoring network (90) consisting of five stations. During these episodes, secondary ionic species were found to make up the bulk (77%) of the PM2.5 mass. These observations can readily be explained in terms of an important NH3 source delocalized throughout the Basin, such as mobile sources. Our results, along with those from tunnel studies, provide compelling evidence for this hypothesis. Currently, the U.S. Department of Agriculture and U.S. EPA are refining their NH3 inventory for all source categories (54). Such NH3 inventories are important to study the VOL. 35, NO. 18, 2001 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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formation of secondary particles in the atmosphere using transport and transformation models. The present U.S. EPA NH3 model employs average fleet emission rates of 63.2 mg km-1 for vehicles equipped with TWCs, derived from a collection of dynamometer studies carried out prior to 1984 (91) and could be underestimating on-road NH3 emissions from a modern vehicle fleet by 33%. Nitrous oxide is another important nitrogen-containing product of three-way catalysis. Emission of N2O and NH3 has been reported to occur at similar catalyst temperatures (250-300 °C) during the warm-up period (84). A number of studies have recently attempted to quantify on-road vehicular emission rates of N2O, a potent greenhouse gas, via tunnel (92-94) and remote sensing (64) measurements. Results from these measurements have been discussed in detail (64). The range of mean emission rates calculated in these studies varied between 5 and 11 and 25 mg km-1, with a compounded average for four tunnel studies and on-road tunable infrared laser measurements of 13 ( 7 mg km-1. The U.S. EPA estimates that mobile sources accounted for 17.5% of U.S. N2O emissions in 1997 (54). Ammonia and N2O are the principal forms of reduced nitrogen, other than N2, produced in LDMV catalytic emissions control systems (66), and onroad vehicular NH3 emissions appear to be around seven times greater. One benefit possibly arising from vehicular NH3 emissions is the suppression of any potential HONO release, as illustrated by eq 5, although HONO levels in vehicle exhaust are generally very low (95).

(14) (15) (16) (17)

NH3 + HONO f N2 + 2H2O

(33)

(5)

(18) (19) (20) (21) (22) (23) (24) (25) (26) (27) (28) (29) (30) (31) (32)

(34)

Acknowledgments This research was carried out under the sponsorship of the Mobile Source Air Pollution Reduction Review Committee (MSRC) (contract no. AB2766/96028). We gratefully acknowledge the valuable assistance provided by this program. We would like to acknowledge the support of CalTrans for issuing a permit in haste. We also thank Prof. M. R. Hoffmann of Caltech for valuable discussions. The statements and conclusions in this paper are those of the authors and not necessarily those of the MSRC or the South Coast Air Quality Management District (SCAQMD). The mention of commercial products, their sources or their uses in connection with material reported herein is not to be construed as either an actual or implied endorsement of such products.

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Received for review December 29, 2000. Accepted June 25, 200120012001. ES002046Y

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