Field Measurements of Small Marine Craft Gaseous Emission Factors

Sep 28, 2009 - Exhaust emission factors were calculated for a number (n = 116) of small marine craft encountered during the 2004 New England Air Quali...
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Environ. Sci. Technol. 2009, 43, 8213–8219

Field Measurements of Small Marine Craft Gaseous Emission Factors during NEAQS 2004 and TexAQS 2006 BRIAN M. LERNER,* PAUL C. MURPHY, AND ERIC J. WILLIAMS Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado at Boulder, and NOAA Earth Systems Research Laboratory (ESRL), Chemical Sciences Division, Boulder, Colorado

Received April 21, 2009. Revised manuscript received August 24, 2009. Accepted September 1, 2009.

Exhaust emission factors were calculated for a number (n ) 116) of small marine craft encountered during the 2004 New England Air Quality Study-International Transport and Chemical Transformation and 2006 Texas Air Quality Study II field campaigns. Emission factors are reported for NOx, SO2, and CO in units of grams of pollutant per kilogram of fuel. These factors are compared to emission factors derived from the U.S. Environmental Protection Agency (EPA) NONROAD model, separated into spark-ignition and compression-ignition sources. NOx emission factors observed were significantly and substantially higher than predicted by the model by a factor of 2-10. CO emission factors were not significantly different than the model outputs. Because of the correlation between exhaust hydrocarbon and CO for marine craft, it is expected that EPA estimates of hydrocarbon exhaust emission factors are not significantly in error. Small commercial marine craft (e.g., inshore fishing trawlers) are not part of NONROAD, but their measured emission factors were comparable to those of large diesel recreational marine craft in the model.

Introduction Exhaust emissions from small marine craft are an important consideration for air quality. Small craft emissions of carbon monoxide (CO), hydrocarbons (HC), and the sum of nitric oxide and nitrogen dioxide (NO + NO2 ) NOx) can contribute to local and regional air quality degradation and are typically accounted for in national ambient air quality standards (NAAQS) attainment state implementation plans (SIPs) to comply with Clean Air Act regulations (1). In 1996, the U.S. Environmental Protection Agency (EPA) identified a number of ozone nonattainment areas, including New York City, San Diego, Miami, and Milwaukee, where recreational marine craft contributed >3% of the total anthropogenic HC burden during summer. The Regional Air Quality Planning Committee for the Houston-Galveston area also identified marine gasoline spark-ignition (SI) and diesel compression-ignition (CI) vessels as a significant contributor to that region’s total anthropogenic HC burden (2). The EPA has recently adopted new exhaust emission standards for SI stern-drive and inboard marine engines that will limit HC and NOx emissions in 2010-2011 for new * Corresponding author e-mail: [email protected]. 10.1021/es901191p CCC: $40.75

Published on Web 09/28/2009

 2009 American Chemical Society

engines on the basis of power, with the intention of reducing total summed NOx + HC emissions by 70% and CO emissions by 50% (3). Regulations with similar intent are being phased in between 2006-2009 (4) for new diesel recreational marine engines greater than 37 kW (50 hp), depending upon engine displacement, and for new and remanufactured marine diesel engines greater than 600 kW (800 hp) but with displacement less than 30 L per cylinder, typically used by commercial fishing and tug boats (5). Previously published investigations of exhaust gas emissions from marine craft engines have been conducted in laboratory settings by using direct sampling of the raw exhaust (6-8), a constant volume sampling dilution system of dry exhaust (9), and constant volume sampling after bubbling exhaust gas through either fresh or saltwater (9-12). These studies report CO, NOx, and HC emission rates, in grams per horsepower per hour, at various power loads. Carbon dioxide emission rates are either measured directly or can be calculated from the brake-specific fuel consumption rate, less HC and CO output. To the authors’ best knowledge, only one other study of field-measured emission factors or ratios for small marine craft engines has been published to date (13). The current nonroad mobile emissions modeling tool available from the EPA, NONROAD 2005a, provides both mass emission rates and emission factors for a number of source categories, including recreational marine craft (14). There are two large sources of uncertainty in the small craft inventory available from the EPA NONROAD model: (1) allocation of boat use and fuel consumption to specific counties within the study region and (2) conversion of fuel consumption to mass emission rates across a wide class of engine sizes and types. During the summer of 2004, the NOAA R/V Ronald H. Brown (RHB) participated in the New England Air Quality Study-Intercontinental Transport and Chemical Transformation (NEAQS 2004) mission along the northeast U.S. coast, with considerable time spent inshore along New Hampshire and Massachusetts. During the summer of 2006, the RHB participated in the Texas Air Quality Study II (TexAQS 2006), sailing along the Texas coast between the Sabine River and Matagorda Bay and inside Galveston Bay in the Houston Ship Channel. One of the overriding goals of these field campaigns was to constrain emission inventories for a number of biogenic and anthropogenic sources important to the study region by means of ambient measurement. These air quality studies provided a unique opportunity to compare ambient gas-phase mixing ratios of compounds attributable to small marine craft exhaust against modeled emissions. Here, we evaluate modeled mass emission rates by comparison of emission factors (EFs) derived from the EPA NONROAD model outputs with those measured in situ from the RHB during these two field campaigns.

Experimental Section The RHB was equipped with a suite of gas- and aerosolphase chemical sensors for the NEAQS 2004 and TexAQS 2006 field campaigns (15, 16). The instrumental methods are briefly described below and uncertainties for the 1-Hz NOx, NOy, CO, CO2, and SO2 data used here are summarized in Table 1 (see Supporting Information for further instrumental details). A common sampling manifold of perfluoroalkoxy copolymer (PFA) provided tightly coupled sample delivery to the individual instruments, which reduced errors from simple timing mismatches. NOx and NOy (sum of all oxides VOL. 43, NO. 21, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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TABLE 1. Description of Gas-Phase Measurements Made on RHB and Used in This Work analyte CO CO2 SO2 NOx NOy

method

total uncertainty

instrument response

vacuum-UV resonance fluorescence nondispersive IR UV_fluorescence photolysis, followed by O3-induced chemiluminescence Au-tube conversion (325 °C, H2), followed by O3-induced chemiluminescence

((3% + 1.5 ppbv) (0.12 ppmv ((10% + 0.1 ppbv) ((5% + 0.1 ppbv) ((13% + 0.15 ppbv)

∼0.5 Hz ∼0.5 Hz >0.1 Hz ∼1 Hz ∼1 Hz

of nitrogen where nitrogen has at least a +2 oxidation state) were measured via ozone-induced chemiluminescence, with three channels measuring NO, NO plus a fraction of photolyzed NO2, and NO plus a fraction of thermally reduced higher oxides of nitrogen, respectively. Carbon monoxide is detected via vacuum-UV resonance fluorescence, carbon dioxide via nondispersive IR absorption, and sulfur dioxide by UV fluorescence. For the TexAQS 2006 data set, the NOx instrument displayed nonlinear behavior at high (>50 ppbv) mixing ratios due to faulty electronics. For this campaign, concurrent measurements of NOy, which consist of NOx and its oxidation products, are used in place of NOx, with the underlying assumption that all increases of measured NOy during small craft plumes are attributable to direct NOx emissions. Because these small craft plumes are sampled seconds to several minutes after emission, perturbation in the pollutant mixing ratio due to chemical transformation (e.g., NO2 oxidation to nitric acid via hydroxyl radical) or physical loss via deposition or scavenging is expected to be negligibly small (17). The reported data for TexAQS 2006 is referred to as NOx in the remainder of the text for simplicity. On Sunday, August 8, 2004, the RHB sailed into Boston Inner Harbor from the northeast (Figure 1a). On Wednesday, August 23, 2006, the RHB sailed into Matagorda Bay, TX, from the southeast. On Saturday, September 2, and Saturday, September 9, 2006, the RHB sailed near and in Galveston Bay, TX (Figure 1b). In each case, a number of small marine crafts passed near the ship, and their exhaust plumes were sampled. During the New England study, no attempt was made to identify specific engine types or to log encounters; a limited attempt to identify small craft encounters and engine type (inboard versus outboard) was performed during TexAQS. It is expected that the exhaust plumes from some small crafts were sampled more than a single time. Small craft plumes were identified in the data sets through inspection of the time series plots of the individual gas-phase species. Analysis was limited to the periods of interest described above; field notes were used to specify start and

stop times for these periods with many (>10) small craft encounters. Individual plumes are identified by brief, correlated increases in CO2, CO, and/or NOx mixing ratios (total plume width less than 60 s), while relative wind direction is forward of the ship’s beam. Emission plumes from larger (>100 gross metric tons) marine vessels (17, 18) were identified by an automated identification system and were removed from this data set.

Data and Calculations A typical plume encounter, from August 8, 2004, is shown in Figure 2a. By calculating the relative change of the target gas species mixing ratio with respect to the CO2 mixing ratio, an apparent molar emission ratio (MER) can be reported. Panels b-d of Figure 2 show NOx, CO, and SO2 plotted against CO2. Reduced major axis linear fits (19) indicate significant MERs for NOx and CO, while SO2 shows no relationship with CO2 (typical for a SI-derived plume, as discussed below). Certain caveats should be recognized. First, attempts to correlate SO2 mixing ratios with other gases in these plumes were problematic due to the slow time response of the instrument (17). To address this, we made an alternative calculation of MER by solving for the ratio of the integrated peak of the target pollutant and CO2. While CO and NOx MERs show good agreement between the two methods within calculated uncertainties, SO2 ratios are considerably scattered, although again most values are equivalent within uncertainties. Second, the correlations can be significantly perturbed if the composition of the background air into which they are mixed is not homogeneous. Because of the short time period required to sample these small craft plumes, typically less than 30 s, compared to the time scale of the variability in background air (minutes to hours), this effect was small. In instances when the background mixing ratios of the target gas-phase species was significantly perturbed (difference in baseline mixing ratio of the compared species before and after the plume >10% of maximum change in mixing ratio during the sampling time of a small craft plume), the plume was removed from the data set.

FIGURE 1. (a) Overview map and ship track for NEAQS 2004 during small craft encounters. (b) Overview map and ship track for TexAQS 2006 during small craft encounters. 8214

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The MERs described above were used to calculate mass emission factors (EFs), which report pollutant mass emitted per mass of carbon consumed (20). EF )

∆[P] mf ∆[CO] + ∆[CO2] C

(1)

Here, change in pollutant concentration (∆[P]) is change in mixing ratio × molecular weight, while change in CO and CO2 concentrations are change in mixing ratio × molecular weight × mass fraction C, and mfC is the mass fraction of carbon in fuel, assumed to be 860 g C per kg fuel. The resulting ratio is reported in grams of pollutant per kilogram of fuel. As the small craft emissions are measured remotely, no direct measurement of fuel consumption is available. Equation 1 may overstate pollutant EFs if HCs make up a significant portion of consumed carbon; estimates of this potential bias are considered below. For each pollutant, the general equation for mass EFs (eq 1) was rearranged to allow for solution by use of the molar emission ratios found from linear fits as described above, along with the additional MER of NOx:CO (not shown in Figure 2).

NOx EF )

[(

CO EF )

[(

1+

]

)

1 12 g C/mol × MERCO:CO2 28 g CO/mol

SO2 EF ) MERCO:CO2 + 1

[(

)

1 1 + × MERNOx:CO MERNOx:CO2 12 g C/mol -1 860 g C/kg fuel 46 g NOx /mol

MERSO2:CO2

)

×

12 g C/mol 64 g SO2 /mol

]

(2)

-1

]

860 g C/kg fuel

(3)

-1

860 g C/kg fuel

(4)

We use the usual assumption convention and report NOx as NO2 in eq 2. To state uncertainty for each calculation, all errors must be propagated through this analysis; errors include not just the uncertainty of the linear fits but also instrumental uncertainties and errors from assumptions made for eqns 1-4. Instrumental uncertainties are listed in Table 1 and described in detail in the Supporting Information. Four major

assumptions underlie the equations used to transform ambient measurements into emission factors: (1) Covariance of ambient measurements of CO2 and the target pollutant is due to a single source. (2) No chemical or physical transformations take place between emission and sampling. (3) The mass fraction of carbon in the fuel is constant. (4) CO and CO2 are the only significant exhaust products containing fuel C. The average gasoline and diesel fuel carbon mass fraction have previously been reported as 0.85 and 0.87 kg C/kg fuel, respectively, with 1% uncertainty (18, 21). The mean value of 0.86 kg C/kg fuel is therefore expected to conservatively contribute 2% uncertainty. Plumes are generally sampled within several minutes of emission, and chemical transformation of emitted NOx or SO2 is expected to be negligible. All uncertainties are propagated using standard methods, and individual EF uncertainties are shown for each plume in the figures presented below. The missing observation of HC emissions can positively bias our reported EFs as this will lead to an underestimation of total fuel C for each plume. For 4-stroke SI engines, this effect should be small (4%) and likely negligible for diesel engines (20) but can be a large systematic error in the characterization of 2-stroke SI engines (20-25%). As a result, the distribution of engine types for the sampled population will be a strong driver of any bias. For the data sets here, few exhaust plumes observed (6 of 116 over both field campaigns) had NOx and CO EFs characteristic of a 2-stroke SI engine. Therefore, we expect any bias in reported EFs to be 4% or less for nearly all of the plumes characterized here. A study that included ambient small craft HC emission factors at a freshwater lake (13) found gaseous HC emissions accounted for 8 ( 2% of fuel carbon. Derived mass emission factors can be calculated from NONROAD model outputs using eq 1 because individual mass emission rates for target pollutants (NOx, SO2, CO) and CO2 are reported as a function of equipment type and engine power. By calculating individual mass emission factors for each equipment type and engine power combination outputted by the model, we find upper and lower expected bounds for each engine type (diesel, 2-stroke, and 4-stroke). No error propagation is included with these calculations as no uncertainties are presented with the NONROAD outputs. The range of EFs for each engine type is used as a proxy for uncertainty. Because the NONROAD outputs are transformed using eq 1, any systematic biasing of the EFs from missing HC will be consistent.

FIGURE 2. Example of small craft plume measurement, encountered August 8, 2004: (a) ambient mixing ratios for target gas-phase species, with 1σ error, (b-d) scatter plots and reduced major axis fits for NOx versus CO2, CO versus CO2, and SO2 versus CO2, respectively. VOL. 43, NO. 21, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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FIGURE 3. Time series of calculated emission factors for small craft plumes encountered on (a) August 8, 2004, during the NEAQS 2004 field campaign and (b) three days [August 23, September 2, and September 9, 2006] during the TexAQS 2006 field campaign. Error bars on each plot indicate total uncertainty of the derived EF for each plume. Dashed lines indicate expected emission factors calculated from emission outputs from the EPA NONROAD 2005a model.

FIGURE 4. Histograms of calculated EFs for NEAQS 2004 and TEXAQS 2006.

Unlike CO and NOx emissions, sulfur compounds in exhaust plumes are entirely derived from the fuel sulfur content. If all fuel sulfur is assumed to be converted to SO2, the SO2 EF can be found from fuel sulfur content as (17) SO2[EF g SO2 /kg fuel] ) 20 × %S by mass

(5)

The likely fuel types for the small marine craft described here are gasoline, on-road diesel, and marine diesel; each has an EPA-stipulated maximum sulfur content of 15, 500, and 3000 ppm, respectively, which may be converted via eq 5 to EFs of 0.03, 1, and 6 g SO2/kg fuel, respectively. These values can serve as upper bounds for expected EFs for plumes encountered during the two field campaigns. On the basis of the maximum sulfur content for gasoline stated above, an increase in the CO2 mixing ratio of more than 16 ppmv would be required to characterize the SO2 EF of a gasoline-fueled small craft plume above stated uncertainties, and this mixing ratio is higher than for any plume described here.

Results NEAQS 2004. Thirty-four small craft plumes were observed during August 8, 2004 (Figure 3a). Upper and lower bounds calculated for each engine type in NONROAD are also included in Figure 3. SO2 mass emission ratios are directly based upon the sulfur content of the engine fuel and, therefore, can serve as an indicator of the engine type (SI versus diesel CI). Five of the thirty-three SO2 mass EFs measured were significantly greater than the gasoline-based emission factors used by NONROAD 2005a, although an additional six plumes have SO2 EFs with 1σ uncertainty ranges that include the putative diesel EF (5 g/kg fuel). More than half (20 of 33) measured NOx EFs were above the highest expected NOx EF for SI recreational marine engines, within stated uncertainties. CO EFs for sampled plumes have nearly the same proportion (19 of 33) below the lowest expected CO EF for SI recreational marine engines. It should be noted that the distribution of diesel and gasoline engine plumes encountered here may not be indicative of the entire local population 8216

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of small marine craft due to small sample size and lack of experimental method to gather a representative survey. TexAQS 2006. A total of 83 small craft plumes were measured on August 23, September 2, and September 9, 2006. Mass EFs for all three days are plotted on a single diurnal time period (Figure 3b), along with engine-based expected EF bounds. Many plumes were sampled during a short 20 min time period, 16:00-16:20, on September 9, when an apparent informal boat race passed nearby and directly upwind of the RHB. Nearly 30 individual plumes were extracted from this event alone, where the small craft population was dominated by high-performance stern-drive and inboard vessels operating at high load. This campaign produced substantially more resolved plumes (n ) 83) than NEAQS. This cohort included many plumes (24 of 75) with SO2 mass EFs (+1σ) at or above the expected level of diesel engines (eight sampled plumes were measured while the SO2 detector was off-line). These plumes were likely derived from encounters with small fishing trawlers operating in Galveston Bay or Matagorda Bay. NOx EFs showed the same trend as noted for NEAQS, where a majority of characterized plumes (69 of 83) were above the highest expected NOx EF for SI recreational marine engines and substantially more than can be attributed to CI engines, using the SO2 EF marker. Slightly more than half of the small craft plumes (44 of 83) also had CO EFs below the lowest expected CO EF for SI engines, again more than can be accounted for with plumes typical of CI engines.

Discussion Mass emission ratios or factors for small craft plumes encountered during NEAQS 2004 and TexAQS 2006 are summarized as histograms in Figure 4. There is large variability in the NOx emissions for each campaign (standard deviation greater than 50% of the mean), and the TexAQS population is not log-normally distributed. This is also the case with CO emission factors, and here, the populations for NEAQS 2004 and TexAQS 2006 are not log-normally dis-

TABLE 2. Model-Derived Emission Factors for Recreational Marine Craft during August 2004 for Boston Area and September 2006 for HGB area of Texas and Observed Emission Factors for Nominal SI- and CI-Powered Small Marine Craft Observed during NEAQS 2004 and TexAQS 2006a NONROAD

NEAQS

TexAQS

NOx (g/kg fuel) gasoline (SI), 2-stk

3.1-6.7

34 (9.2), 32, n ) 24

84 (18), 85, n ) 30

gasoline (SI), 4-stk diesel (CI)

13.4-19 33-45

-

65 (26), 51, n ) 22

CO (g/kg fuel) gasoline (SI), 2-stk

386-644

370 (100), 310, n ) 24

612 (86), 573, n ) 30

gasoline (SI), 4-stk diesel (CI)

419-475 5-27

-

44 (20), 31, n ) 22

a The NONROAD EFs are stated as a range spanning all power bin outputs of the model. The observed EFs are stated as mean ((95% C.I.), median, number of plumes nominally identified as either SI- or CI-derived. Only one EF is stated for all nominal SI-derived plumes. Only one plume was identified as CI-derived during NEAQS 2004, so no statistics are presented.

tributed. For the TexAQS campaign, the distribution of NOx EFs appears bimodal with a large population at values higher than any encountered during NEAQS 2004, while CO EFs have a significant mode at low values; both of these observations are likely due to CI engines. Emissions of SO2 have relatively higher variability, with the standard deviation larger than the mean in each campaign. The highest SO2 EFs are reported for TexAQS 2006, as the population of small craft plumes encountered then had a significant fraction of CI engines. To further interpret the calculated emission factors of encountered small marine craft, characterized plumes must be separated into bins on the basis of engine type. Two markers can be used to distinguish between CI and SI engine plumes: the NOx EF:CO EF ratio and the SO2 EF. Because of the combustion method, the exhaust of CI engines has a markedly higher NOx:CO ratio than that from SI engines. Using the emission factors for recreational marine craft in the current NONROAD model, the ratio of NOx:CO for SIengines, both outboard and stern-drive/inboard, ranges between 0.003-0.12 g NOx/g CO across all size and technology ranges, while the range for CI engines is 1.5-6.5 g NOx/g CO. The measured SO2 EF can provide a clear signature of fuel type because diesel fuel will have significantly higher

sulfur content than gasoline, and fuel sulfur content will determine the SO2 emissions in the exhaust plume. Unfortunately, because of the slow response time of the SO2 detector relative to the sampling period typical for a small marine craft exhaust plume, reported SO2 EFs have considerable uncertainty, often larger than the calculated EFs. Also, recent regulations promulgated by the federal government to greatly reduce the sulfur content in some diesel fuels from 500 to 15 ppm took effect during the summer and fall of 2006. TexAQS 2006 was the only field campaign that provided opportunities to sample exhaust plumes from a large number of CI craft. It is not known how the new diesel standard affected the fuel source of diesel craft encountered during the TexAQS study. The source-binned results for the NEAQS 2004 (SI craft only) and TexAQS 2006 study are summarized in Table 2 as mean and median EF for each subset of sampled exhaust plumes. For this analysis, data points are binned into SI source, CI source, or indeterminate by the following criteria: SI plumes (EFSO2 - σEFSO2 < 0.1 and EFNOx:EFCO < 0.8), CI plumes (EFSO2 - σEFSO2 > 1 and EFNOx:EFCO > 1). The sum of these two bins does not equal the total number of small craft plumes measured because some plumes did not match either bin’s criteria (Figure 5). In all cases, the large variability of the cohort is a larger contributor to the 95% confidence interval for the mean value of each bin than uncertainty of the calculated individual EFs. For NEAQS, only one plume met the criteria for CI source, and therefore, no discussion of diesel EFs for NEAQS will be presented. The NONROAD EFs used for recreational marine craft CI engines are adequate to describe the majority of nominal diesel vessel plumes measured during TEXAQS 2006. The EFs trend toward higher CO and lower NOx EFs than on average for the NONROAD outputs. The observed mean CO and NOx EFs for CI plumes are higher than those for the NONROAD model, but the median value in each case is lower than the mean as the distribution of the EFs within the subset is positively skewed; nonetheless, the means are not significantly higher than the NONROAD EF range. It should be noted that during TexAQS, a plurality of the diesel plumes measured were from small commercial trawling vessels; these vessels are not currently in the NONROAD database, which includes only recreational CI-powered craft. Nonetheless, the diesel emission factors used by NONROAD adequately describe these vessels, within stated uncertainties. Nominal SI plumes are not well-described by NONROAD. During NEAQS, NOx emissions were approximately double the NONROAD NOx EF range for 4-stroke SI engines. CO EFs were slightly lower than estimated by NONROAD, although this difference is statistically insignificant. For TexAQS, while the mean CO EF is higher than measured during NEAQS, it falls within the band predicted by NONROAD. For NOx EFs,

FIGURE 5. NOx EFs versus CO EFs for (a) NEAQS 2004 and (b) TexAQS 2006. Dashed lines indicate expected minimum and maximum ratios of EFs for each engine type on the basis of outputs from the EPA NONROAD 2005 model. VOL. 43, NO. 21, 2009 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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Literature Cited

FIGURE 6. Linear relationship between published hydrocarbon emission rates versus carbon monoxide emission rates for carbureted 2-stroke outboard and inboard/outboard 4-stroke marine engines. Fitted line and 95% confidence intervals are shown for each fit.

the mean and median values are approximately equal and an order of magnitude higher than the NONROAD EF range. Interestingly, the TexN model (Texas Commission on Environmental Quality NONROAD equivalent model) has annual emissions for NOx from SI-powered recreational marine craft about 80% higher than those from the equivalent model run by the EPA NONROAD model (22). The observations here indicate that NOx EFs are considerably higher than even the Texas model predicts, by nearly an order of magnitude, and that the EPA NONROAD model currently substantially underestimates NOx emissions from recreational marine craft. The exhausting of partially or completely uncombusted HCs from small marine craft engines is of primary concern for the emission inventories, but emissions factors for organic species could not be directly calculated from the ambient data. It is possible to estimate hydrocarbon emissions from HC/CO ratios calculated from published data. There are several studies of small SI marine engine emissions, surveying carbureted 2-stroke outboard engines (9-30 HP), carbureted 4-stroke outboards, and both carbureted and fuel-injected 4-stroke inboards (8-300 HP) (7-12, 23). The data from these studies is summarized in Figure 6, and for both engine classes the linear relationship between HC and CO emission rates is strongly significant with HC mass emissions from 2-stroke engines 9-fold higher than 4-stroke engines per gram CO emitted. The NONROAD model has several classes of marine engines; the HC/CO emission factors used in that model agree well with available literature data. The literature provides scant evidence of correlation between exhaust emission rates for NOx and HC. The small marine craft exhaust plumes characterized here are not significantly different in CO EF than the range of EFs used by the NONROAD model; therefore, the NONROAD model estimate of HC exhaust emissions from these vessels is not expected to be significantly in error.

Acknowledgments The authors thank the crew and fellow scientists on board NOAA R/V Brown during NEAQS-ITCT 2004 and TexAQS 2006. Funding was provided in part by NOAA, Air Quality, Climate Change, and Climate Research and Modeling Programs and by the Texas Commission on Environmental Quality (TCEQ).

Supporting Information Available Further descriptions of instrumental methods and uncertainty. This material is available free of charge via the Internet at http://pubs.acs.org. 8218

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