Quantification of Variability and Uncertainty in Lawn and Garden Equipment NOx and Total Hydrocarbon Emission Factors

Abstract

Variability refers to real differences in emissions among multiple emission sources at any given time or over time for any individual emission source. Variability in emissions can be attributed to variation in fuel or feedstock composition, ambient temperature, design, maintenance, or operation. Uncertainty refers to lack of knowledge regarding the true value of emissions. Sources of uncertainty include small sample sizes, bias or imprecision in measurements, nonrepresentativeness, or lack of data. Quantitative methods for characterizing both variability and uncertainty are demonstrated and applied to case studies of emission factors for lawn and garden (L&G) equipment engines. Variability was quantified using empirical and parametric distributions. Bootstrap simulation was used to characterize confidence intervals for the fitted distributions. The 95% confidence intervals for the mean grams per brake horsepower/hour (g/hp-hr) emission factors for two-stroke engine total hydrocarbon (THC) and NO_x emissions were from -30 to +41% and from -45 to +75%, respectively. The confidence intervals for four-stroke engines were from -33 to +46% for THCs and from -27 to +35% for NO_x. These quantitative measures of uncertainty convey information regarding the quality of the emission factors and serve as a basis for calculation of uncertainty in emission inventories (Els).     

Quantification of variability and uncertainty in air pollutant emission inventories: method and case study for utility NOx emissions

The quality of stationary source emission factors is typically described using data quality ratings, which provide no quantification of the precision of the emission factor for an average source, nor of the variability from one source to another within a category. Variability refers to actual differences caused by differences in feedstock composition, design, maintenance, and operation. Uncertainty refers to lack of knowledge regarding the true emissions. A general methodology for the quantification of variability and uncertainty in emission factors, activity factors, and emission inventories (EIs) is described, featuring the use of bootstrap simulation and related techniques. The methodology is demonstrated via a case study for a selected example of NOx emissions from coal-fired power plants. A prototype software tool was developed to implement the methodology. The range of interunit variability in selected activity and emission factors was shown to be as much as a factor of 4, and the range of uncertainty in mean emissions is shown to depend on the interunit variability and sample size. The uncertainty in the total inventory of -16 to +19% was attributed primarily to one technology group, suggesting priorities for collecting data and improving the inventory. The implications for decision-making are discussed.     

Sustainable Development by Design: Review of Life Cycle Design and Related Approaches

Abstract

The quality of stationary source emission factors is typically described using data quality ratings, which provide no quantification of the precision of the emission factor for an average source, nor of the variability from one source to another within a category. Variability refers to actual differences caused by differences in feedstock composition, design, maintenance, and operation. Uncertainty refers to lack of knowledge regarding the true emissions. A general methodology for the quantification of variability and uncertainty in emission factors, activity factors, and emission inventories (EIs) is described, featuring the use of bootstrap simulation and related techniques. The methodology is demonstrated via a case study for a selected example of NO_x emissions from coal-fired power plants. A prototype software tool was developed to implement the methodology. The range of interunit variability in selected activity and emission factors was shown to be as much as a factor of 4, and the range of uncertainty in mean emissions is shown to depend on the interunit variability and sample size. The uncertainty in the total inventory of ?16 to +19% was attributed primarily to one technology group, suggesting priorities for collecting data and improving the inventory. The implications for decision-making are discussed.     

Methods for Quantifying Variability and Uncertainty in AP-42 Emission Factors: Case Studies for Natural Gas-Fueled Engines

Abstract

Quantitative methods for characterizing variability and uncertainty were applied to case studies of oxides of nitrogen and total organic carbon emission factors for lean-burn natural gas-fueled internal combustion engines. Parametric probability distributions were fit to represent inter-engine variability in specific emission factors. Bootstrap simulation was used to quantify uncertainty in the fitted cumulative distribution function and in the mean emission factor. Some methodological challenges were encountered in analyzing the data. For example, in one instance, five data points were available, with each data point representing a different market share. Therefore, an approach was developed in which parametric distributions were fitted to population-weighted data. The uncertainty in mean emission factors ranges from as little as ~±10% to as much as -90 to 21+180%. The wide range of uncertainty in some emission factors emphasizes the importance of recognizing and accounting for uncertainty in emissions estimates. The skewness in some uncertainty estimates illustrates the importance of using numerical simulation approaches that do not impose restrictive symmetry assumptions on the confidence interval for the mean. In this paper, the quantitative method, the analysis results, and key findings are presented.     

Methods for quantifying variability and uncertainty in AP-42 emission factors: case studies for natural gas-fueled engines

Quantitative methods for characterizing variability and uncertainty were applied to case studies of oxides of nitrogen and total organic carbon emission factors for lean-burn natural gas-fueled internal combustion engines. Parametric probability distributions were fit to represent inter-engine variability in specific emission factors. Bootstrap simulation was used to quantify uncertainty in the fitted cumulative distribution function and in the mean emission factor. Some methodological challenges were encountered in analyzing the data. For example, in one instance, five data points were available, with each data point representing a different market share. Therefore, an approach was developed in which parametric distributions were fitted to population-weighted data. The uncertainty in mean emission factors ranges from as little as approximately +/-10% to as much as -90 to +180%. The wide range of uncertainty in some emission factors emphasizes the importance of recognizing and accounting for uncertainty in emissions estimates. The skewness in some uncertainty estimates illustrates the importance of using numerical simulation approaches that do not impose restrictive symmetry assumptions on the confidence interval for the mean. In this paper, the quantitative method, the analysis results, and key findings are presented.     

Effectiveness of emission control technologies for auxiliary engines on ocean-going vessels

Large auxiliary engines operated on ocean-going vessels in transit and at berth impact the air quality of populated areas near ports. This paper presents new information on the comparison of emission ranges from three similar engines and the effectiveness of three control technologies: switching to cleaner burning fuels, operating in the low oxides of nitrogen (NOx) mode, and selective catalytic reduction (SCR). In-use measurements of gaseous (NOx, carbon monoxide [CO], carbon dioxide [CO2]) and fine particulate matter (PM2.5; total and speciated) emissions were made on three auxiliary engines on post-PanaMax class container vessels following the International Organization for Standardization-8178-1 protocol. The in-use NOx emissions for the MAN B&W 7L32/40 engine family vary from 15 to 21.1 g/kW-hr for heavy fuel oil and 8.9 to 19.6 g/kW-hr for marine distillate oil. Use of cleaner burning fuels resulted in NOx reductions ranging from 7 to 41% across different engines and a PM2.5 reduction of up to 83%. The NOx reductions are a consequence of fuel nitrogen content and engine operation; the PM2.5 reduction is attributed to the large reductions in the hydrated sulfate and organic carbon (OC) fractions. As expected, operating in the low-NOx mode reduced NOx emissions by approximately 32% and nearly doubled elemental carbon (EC) emissions. However, PM2.5 emission factors were nearly unchanged because the EC emission factor is only approximately 5% of the total PM2.5 mass. SCR reduced the NOx emission factor to less than 2.4 g/kW-hr, but it increased the PM2.5 emissions by a factor of 1.5-3.8. This increase was a direct consequence of the conversion of sulfur dioxide to sulfate emissions on the SCR catalyst. The EC and OC fractions of PM2.5 reduced across the SCR unit.     

Quantification of emission factor uncertainty

Emissions factors are important for estimating and characterizing emissions from sources of air pollution. There is no quantitative indication of uncertainty for these emission factors, most factors do not have an adequate data set to compute uncertainty, and it is very difficult to locate the data for those that do. The objectives are to compare the current emission factors of Electric Generating Unit NOx sources with currently available continuous emission monitoring data, develop quantitative uncertainty indicators for the Environmental Protection Agency (EPA) data quality rated emission factors, and determine the possible ranges of uncertainty associated with EPA's data quality rating of emission factors. EPA's data letter rating represents a general indication of the robustness of the emission factor and is assigned based on the estimated reliability of the tests used to develop the factor and on the quantity and representativeness of the data. Different sources and pollutants that have the same robustness in the measured emission factor and in the representativeness of the measured values are assumed to have a similar quantifiable uncertainty. For the purposes of comparison, we assume that the emission factor estimates from source categories with the same letter rating have enough robustness and consistency that we can quantify the uncertainty of these common emission factors based on the qualitative indication of data quality which is known for almost all factors. The results showed that EPA's current emission factor values for NOx emissions from combustion sources were found to be reasonably representative for some sources; however AP-42 values should be updated for over half of the sources to reflect current data. The quantified uncertainty ranges were found to be 25-62% for A rated emission factors, 45-75% for B rated emission factors, 60-82% for C rated emission factors, and 69-86% for D rated emission factors, and 82-92% for E rated emission factors.     

A fuel-based assessment of off-road diesel engine emissions

The use of diesel engines in off-road applications is a significant source of nitrogen oxides (NOx) and particulate matter (PM10). Such off-road applications include railroad locomotives, marine vessels, and equipment used for agriculture, construction, logging, and mining. Emissions from these sources are only beginning to be controlled. Due to the large number of these engines and their wide range of applications, total activity and emissions from these sources are uncertain. A method for estimating the emissions from off-road diesel engines based on the quantity of diesel fuel consumed is presented. Emission factors are normalized by fuel consumption, and total activity is estimated by the total fuel consumed. Total exhaust emissions from off-road diesel equipment (excluding locomotives and marine vessels) in the United States during 1996 have been estimated to be 1.2 x 10(9) kg NOx and 1.2 x 10(8) kg PM10. Emissions estimates published by the U.S. Environmental Protection Agency are 2.3 times higher for both NOx and exhaust PM10 emissions than estimates based directly on fuel consumption. These emissions estimates disagree mainly due to differences in activity estimates, rather than to differences in the emission factors. All current emission inventories for off-road engines are uncertain because of the limited in-use emissions testing that has been performed on these engines. Regional- and state-level breakdowns in diesel fuel consumption by off-road mobile sources are also presented. Taken together with on-road measurements of diesel engine emissions, results of this study suggest that in 1996, off-road diesel equipment (including agriculture, construction, logging, and mining equipment, but not locomotives or marine vessels) was responsible for 10% of mobile source NOx emissions nationally, whereas on-road diesel vehicles contributed 33%.     

Idle emissions from heavy-duty diesel and natural gas vehicles at high altitude

Idle emissions of total hydrocarbon (THC), CO, NOx, and particulate matter (PM) were measured from 24 heavy-duty diesel-fueled (12 trucks and 12 buses) and 4 heavy-duty compressed natural gas (CNG)-fueled vehicles. The volatile organic fraction (VOF) of PM and aldehyde emissions were also measured for many of the diesel vehicles. Experiments were conducted at 1609 m above sea level using a full exhaust flow dilution tunnel method identical to that used for heavy-duty engine Federal Test Procedure (FTP) testing. Diesel trucks averaged 0.170 g/min THC, 1.183 g/min CO, 1.416 g/min NOx, and 0.030 g/min PM. Diesel buses averaged 0.137 g/min THC, 1.326 g/min CO, 2.015 g/min NOx, and 0.048 g/min PM. Results are compared to idle emission factors from the MOBILE5 and PART5 inventory models. The models significantly (45-75%) overestimate emissions of THC and CO in comparison with results measured from the fleet of vehicles examined in this study. Measured NOx emissions were significantly higher (30-100%) than model predictions. For the pre-1999 (pre-consent decree) truck engines examined in this study, idle NOx emissions increased with model year with a linear fit (r2 = 0.6). PART5 nationwide fleet average emissions are within 1 order of magnitude of emissions for the group of vehicles tested in this study. Aldehyde emissions for bus idling averaged 6 mg/min. The VOF averaged 19% of total PM for buses and 49% for trucks. CNG vehicle idle emissions averaged 1.435 g/min for THC, 1.119 g/min for CO, 0.267 g/min for NOx, and 0.003 g/min for PM. The g/min PM emissions are only a small fraction of g/min PM emissions during vehicle driving. However, idle emissions of NOx, CO, and THC are significant in comparison with driving emissions.     

Modelling the spatial distribution of SO2 and NOx emissions in Ireland

The spatial distributions of sulphur dioxide (SO2) and nitrogen oxides (NOx) emissions are essential inputs to models of atmospheric transport and deposition. Information of this type is required for international negotiations on emission reduction through the critical load approach. High-resolution emission maps for the Republic of Ireland have been created using emission totals and a geographical information system, supported by surrogate statistics and landcover information. Data have been subsequently allocated to the EMEP 50 x 50-km grid, used in long-range transport models for the investigation of transboundary air pollution. Approximately two-thirds of SO2 emissions in Ireland emanate from two grid-squares. Over 50% of total SO2 emissions originate from one grid-square in the west of Ireland, where the largest point sources of SO2 are located. Approximately 15% of the total SO2 emissions originate from the grid-square containing Dublin. SO2 emission densities for the remaining areas are very low, < 1 t km-2 year-1 for most grid-squares. NOx emissions show a very similar distribution pattern. However, NOx emissions are more evenly spread over the country, as about 40% of total NOx emissions originate from road transport.     

Interinstrument comparison of remote-sensing devices and a new method for calculating on-road nitrogen oxides emissions and validation of vehicle-specific power

Emissions of nitrogen oxides (NOx) by vehicles in real driving environments are only partially understood. This has been brought to the attention of the world with recent revelations of the cheating of the type of approval tests exposed in the dieselgate scandal. Remote-sensing devices offer investigators an opportunity to directly measure in situ real driving emissions of tens of thousands of vehicles. Remote-sensing NO₂ measurements are not as widely available as would be desirable. The aim of this study is to improve the ability of investigators to estimate the NO₂ emissions and to improve the confidence of the total NOx results calculated from standard remote-sensing device (RSD) measurements. The accuracy of the RSD speed and acceleration module was also validated using state-of-the-art onboard global positioning system (GPS) tracking. Two RSDs used in roadside vehicle emissions surveys were tested side by side under off-carriageway conditions away from transient pollution sources to ascertain the consistency of their measurements. The speed correlation was consistent across the range of measurements at 95% confidence and the acceleration correlation was consistent at 95% confidence intervals for all but the most extreme acceleration cases. VSP was consistent at 95% confidence across all measurements except for those at VSP ≥ 15 kW t^?1, which show a small underestimate. The controlled distribution gas nitric oxide measurements follow a normal distribution with 2σ equal to 18.9% of the mean, compared to 15% observed during factory calibration indicative of additional error introduced into the system. Systematic errors of +84 ppm were observed but within the tolerance of the control gas. Interinstrument correlation was performed, with the relationship between the FEAT and the RSD4600 being linear with a gradient of 0.93 and an R² of 0.85, indicating good correlation. A new method to calculate NOx emissions using fractional NO₂ combined with NO measurements made by the RSD4600 was constructed, validated, and shown to be more accurate than previous methods.

Implications: Synchronized remote-sensing measurements of NO were taken using two different remote-sensing devices in an off-road study. It was found that the measurements taken by both instruments were well correlated. Fractional NO₂ measurements from a prior study, measurable on only one device, were used to create new NO_x emission factors for the device that could not be measured by the second device. These estimates were validated against direct measurement of total NO_x emission factors and shown to be an improvement on previous methodologies. Validation of vehicle-specific power was performed with good correlation observed.     

Effects of improved spatial and temporal modeling of on-road vehicle emissions

Numerous emission and air quality modeling studies have suggested the need to accurately characterize the spatial and temporal variations in on-road vehicle emissions. The purpose of this study was to quantify the impact that using detailed traffic activity data has on emission estimates used to model air quality impacts. The on-road vehicle emissions are estimated by multiplying the vehicle miles traveled (VMT) by the fleet-average emission factors determined by road link and hour of day. Changes in the fraction of VMT from heavy-duty diesel vehicles (HDDVs) can have a significant impact on estimated fleet-average emissions because the emission factors for HDDV nitrogen oxides (NOx) and particulate matter (PM) are much higher than those for light-duty gas vehicles (LDGVs). Through detailed road link-level on-road vehicle emission modeling, this work investigated two scenarios for better characterizing mobile source emissions: (1) improved spatial and temporal variation of vehicle type fractions, and (2) use of Motor Vehicle Emission Simulator (MOVES2010) instead of MOBILE6 exhaust emission factors. Emissions were estimated for the Detroit and Atlanta metropolitan areas for summer and winter episodes. The VMT mix scenario demonstrated the importance of better characterizing HDDV activity by time of day, day of week, and road type. More HDDV activity occurs on restricted access road types on weekdays and at nonpeak times, compared to light-duty vehicles, resulting in 5-15% higher NOx and PM emission rates during the weekdays and 15-40% lower rates on weekend days. Use of MOVES2010 exhaust emission factors resulted in increases of more than 50% in NOx and PM for both HDDVs and LDGVs, relative to MOBILE6. Because LDGV PM emissions have been shown to increase with lower temperatures, the most dramatic increase from MOBILE6 to MOVES2010 emission rates occurred for PM2.5 from LDGVs that increased 500% during colder wintertime conditions found in Detroit, the northernmost city modeled.     

Regulated and unregulated emissions from highway heavy-duty diesel engines complying with U.S. Environmental Protection Agency 2007 emissions standards

As part of the Advanced Collaborative Emissions Study (ACES), regulated and unregulated exhaust emissions from four different 2007 model year U.S. Environmental Protection Agency (EPA)-compliant heavy-duty highway diesel engines were measured on an engine dynamometer. The engines were equipped with exhaust high-efficiency catalyzed diesel particle filters (C-DPFs) that are actively regenerated or cleaned using the engine control module. Regulated emissions of carbon monoxide, nonmethane hydrocarbons, and particulate matter (PM) were on average 97, 89, and 86% lower than the 2007 EPA standard, respectively, and oxides of nitrogen (NOx) were on average 9% lower. Unregulated exhaust emissions of nitrogen dioxide (NO2) emissions were on, average 1.3 and 2.8 times higher than the NO, emissions reported in previous work using 1998- and 2004-technology engines, respectively. However, compared with other work performed on 1994- to 2004-technology engines, average emission reductions in the range of 71-99% were observed for a very comprehensive list of unregulated engine exhaust pollutants and air toxic contaminants that included metals and other elements, elemental carbon (EC), inorganic ions, and gas- and particle-phase volatile and semi-volatile organic carbon (OC) compounds. The low PM mass emitted from the 2007 technology ACES engines was composed mainly of sulfate (53%) and OC (30%), with a small fraction of EC (13%) and metals and other elements (4%). The fraction of EC is expected to remain small, regardless of engine operation, because of the presence of the high-efficiency C-DPF in the exhaust. This is different from typical PM composition of pre-2007 engines with EC in the range of 10-90%, depending on engine operation. Most of the particles emitted from the 2007 engines were mainly volatile nuclei mode in the sub-30-nm size range. An increase in volatile nanoparticles was observed during C-DPF active regeneration, during which the observed particle number was similar to that observed in emissions of pre-2007 engines. However, on average, when combining engine operation with and without active regeneration events, particle number emissions with the 2007 engines were 90% lower than the particle number emitted from a 2004-technology engine tested in an earlier program.     

A chassis test procedure to mimic the heavy-duty engine transient emissions certification test

In-use emissions from vehicles using heavy-duty diesel engines can be significantly higher than the levels obtained during engine certification. These higher levels may be caused by a combination of degradation of engine components, poor engine maintenance, degradation or failure of emissions after-treatment devices, and engine and emissions system tampering. A direct comparison of in-use vehicle emissions with engine certification levels, however, is not possible without removing an engine from the vehicle in order to perform engine dynamometer emissions testing. The goal of this research was to develop a chassis test procedure that mimics the engine performance, and as such the expected emissions levels, from the engine certification emissions test prescribed in the U.S. Code of Federal Regulations. Emissions measurements were taken from two engines during testing on an engine dynamometer using the transient heavy-duty Federal Test Procedure (FTP). Additionally, each engine was installed in an appropriate vehicle, and emissions measurements were taken using a chassis dynamometer while employing a vehicle driving schedule intended to match closely the instantaneous torque and speed schedule of the engine FTP. Engine and chassis testing was performed with the engines in stock (unmodified) condition as well as in several modes to simulate either tampered or poorly maintained conditions. The use of a chassis test as a predictive tool for determining whether an engine in a vehicle would pass the engine certification test has proven to be worthwhile. Analysis of the data shows that identification of chassis-mounted engines with NOx emissions above certification levels is possible by employing engine-specific correction factors. In the case of PM emissions, significant data scatter allowed only the identification of gross PM emitters. Engine tampering and poor maintenance can raise PM and NOx emissions, and these increases can be correctly identified by a chassis test. Analysis of chassis and engine CO and HC emissions did not reveal a strong enough correlation to warrant the use of the chassis test for emissions screening of these two pollutants.     

Temporal,spatial characteristics and uncertainty of biogenic VOC emissions in the Pearl River Delta region,China

Using the Global Biosphere Emissions and Interactions System model (GloBEIS), 3 × 3 km gridded and hourly biogenic volatile organic compound (BVOC) emissions in the Pearl River Delta (PRD) were estimated for the year 2006. The study used newly available land cover database, observed meteorological data, and recent measurements of emission rates for tree species in China. The results show that the total BVOC emission in the PRD region in 2006 was 296 kt (2.2 × 10¹¹ gC), of which isoprene contributes about 25% (73 kt, 6.4 × 10¹⁰ gC), monoterpenes about 34% (102 kt, 8.9 × 10¹⁰ gC), and other VOCs (OVOC) about 41% (121 kt, 6.8 × 10¹⁰ gC). BVOC emissions in the PRD region exhibit a marked seasonal pattern with the peak emission in July and the lowest emission in January, and are mainly distributed over the outlying areas of the PRD region, where the economy and land use are less developed. The uncertainties in BVOC emission estimates were quantified using Monte Carlo simulation; the results indicate high uncertainties in isoprene emission estimates, with a relative error of ?82 to +177%, ranging from 12.4 to 186.4 kt; ?41 to +58% uncertainty for monoterpenes emissions, ranging from 67.7 to 181.9 kt; and ?26 to +30% uncertainty in OVOC emissions, ranging from 88.8 to 156.2 kt on the 95% confidence intervals. The key uncertainty sources include emission factors and the model empirical coefficients α, C_T1, C_L, and E_opt for estimating isoprene emission, and emission factors and foliar density for estimating monoterpenes and OVOC emissions. This implies that determining these empirical coefficient values properly and conducting more field measurements of emission rates of tree species are key approaches for reducing uncertainties in BVOC emission estimates. Improving future BVOC emission inventory work in the PRD region requires giving priority to research on shrub land, coniferous forests, and irrigated cropland and pasture.     

Estimates of emissions of SO2, NOx, HCl and NH3 from a densely populated region of the UK

Estimates of emissions of SO2, NOx, HCl and NH3 have been made for a densely populated region of the UK, the North-West of England, using data on power generation, incinerator plant capacity, fuel usage and animal and human population statistics. The spatial distributions of SO2 and NOx emissions are quite different, reflecting their different source strengths. The emissions from motor vehicles make up 52% of the NOx emissions from the North-West of England, whilst those from fossil-fuel-fired power stations make up 20%. The emissions of fossil-fuel-fired power stations make up 58% of SO2 emissions from the North-West. A large fossil-fuel-fired power station is the largest known point source for emissions of SO2, NOx and HCl. The largest contribution to NH3 emissions in the North-West is from cattle. Humans may contribute some NH3 to overall emissions but there is considerable uncertainty as to how much is emitted and what fraction of this is deposited within buildings. The uncertainties in the methodologies used are high-lighted and, where possible, recommendations are made as to how future emissions estimates might be improved. Potential reductions in emissions of SO2, NOx and HCl are discussed under basic scenarios of planned power station closures in the area and the compliance of the electricity generation industry with the European Community Directive on Large Combustion Plants.     

Regulated and unregulated emissions from modern 2010 emissions-compliant heavy-duty on-highway diesel engines

The U.S. Environmental Protection Agency (EPA) established strict regulations for highway diesel engine exhaust emissions of particulate matter (PM) and nitrogen oxides (NO_x) to aid in meeting the National Ambient Air Quality Standards. The emission standards were phased in with stringent standards for 2007 model year (MY) heavy-duty engines (HDEs), and even more stringent NO_X standards for 2010 and later model years. The Health Effects Institute, in cooperation with the Coordinating Research Council, funded by government and the private sector, designed and conducted a research program, the Advanced Collaborative Emission Study (ACES), with multiple objectives, including detailed characterization of the emissions from both 2007- and 2010-compliant engines. The results from emission testing of 2007-compliant engines have already been reported in a previous publication. This paper reports the emissions testing results for three heavy-duty 2010-compliant engines intended for on-highway use. These engines were equipped with an exhaust diesel oxidation catalyst (DOC), high-efficiency catalyzed diesel particle filter (DPF), urea-based selective catalytic reduction catalyst (SCR), and ammonia slip catalyst (AMOX), and were fueled with ultra-low-sulfur diesel fuel (~6.5 ppm sulfur). Average regulated and unregulated emissions of more than 780 chemical species were characterized in engine exhaust under transient engine operation using the Federal Test Procedure cycle and a 16-hr duty cycle representing a wide dynamic range of real-world engine operation. The 2010 engines’ regulated emissions of PM, NO_X, nonmethane hydrocarbons, and carbon monoxide were all well below the EPA 2010 emission standards. Moreover, the unregulated emissions of polycyclic aromatic hydrocarbons (PAHs), nitroPAHs, hopanes and steranes, alcohols and organic acids, alkanes, carbonyls, dioxins and furans, inorganic ions, metals and elements, elemental carbon, and particle number were substantially (90 to >99%) lower than pre-2007-technology engine emissions, and also substantially (46 to >99%) lower than the 2007-technology engine emissions characterized in the previous study.

Implications:?Heavy-duty on-highway diesel engines equipped with DOC/DPF/SCR/AMOX and fueled with ultra-low-sulfur diesel fuel produced lower emissions than the stringent 2010 emission standards established by the U.S. Environmental Protection Agency. They also resulted in significant reductions in a wide range of unregulated toxic emission compounds relative to older technology engines. The increased use of newer technology (2010+) diesel engines in the on-highway sector and the adaptation of such technology by other sectors such as nonroad, displacing older, higher emissions engines, will have a positive impact on ambient levels of PM, NOx, and volatile organic compounds, in addition to many other toxic compounds.     

Hazardous air pollutant emissions from gas-fired combustion sources: emissions and the effects of design and fuel type

Air emissions from gas-fired combustion devices such as boilers, process heaters, gas turbines and stationary reciprocating engines contain hazardous air pollutants (HAPs) subjected to consideration under the federal clean air act (CAA). This work presents a recently completed major research project to develop an understanding of HAP emissions from gas-fired boilers and process heaters and new HAP emission factors based on field emission tests of gas-fired external combustion devices used in the petroleum industry. The effect of combustion system design and operating parameters on HAP emissions determined by both field and research tests are discussed. Data from field tests of gas-fired petroleum industry boilers and heaters generally show very low emission levels of organic HAPs. A comparison of the emission data for boilers and process heaters, including units with and without various forms of NOx emission controls, showed no significant difference in organic HAP emission characteristics due to process or burner design. This conclusion is also supported by the results of research tests with different burner designs. Based on field tests of units fired with natural gas and various petroleum industry process gases and research tests in which gas composition was intentionally varied, organic HAP emissions were not determined to be significantly affected by the gas composition. Research data indicate that elevated organic HAP emission levels are found only under extreme operating conditions (starved air or high excess air combustion) associated with poor combustion.     

Development of probabilistic emission inventories of air toxics for Jacksonville, Florida, USA

Probabilistic emission inventories were developed for 1,3-butadiene, mercury (Hg), arsenic (As), benzene, formaldehyde, and lead for Jacksonville, FL. To quantify inter-unit variability in empirical emission factor data, the Maximum Likelihood Estimation (MLE) method or the Method of Matching Moments was used to fit parametric distributions. For data sets that contain nondetected measurements, a method based upon MLE was used for parameter estimation. To quantify the uncertainty in urban air toxic emission factors, parametric bootstrap simulation and empirical bootstrap simulation were applied to uncensored and censored data, respectively. The probabilistic emission inventories were developed based on the product of the uncertainties in the emission factors and in the activity factors. The uncertainties in the urban air toxics emission inventories range from as small as -25 to +30% for Hg to as large as -83 to +243% for As. The key sources of uncertainty in the emission inventory for each toxic are identified based upon sensitivity analysis. Typically, uncertainty in the inventory of a given pollutant can be attributed primarily to a small number of source categories. Priorities for improving the inventories and for refining the probabilistic analysis are discussed.     

Modeling and direct sensitivity analysis of biogenic emissions impacts on regional ozone formation in the Mexico-U.S. border area

A spatially and temporally resolved biogenic hydrocarbon and nitrogen oxides (NOx) emissions inventory has been developed for a region along the Mexico-U.S. border area. Average daily biogenic non-methane organic gases (NMOG) emissions for the 1700 x 1000 km2 domain were estimated at 23,800 metric tons/day (62% from Mexico and 38% from the United States), and biogenic NOx was estimated at 1230 metric tons/day (54% from Mexico and 46% from the United States) for the July 18-20, 1993, ozone episode. The biogenic NMOG represented 74% of the total NMOG emissions, and biogenic NOx was 14% of the total NOx. The CIT photochemical airshed model was used to assess how biogenic emissions impact air quality. Predicted ground-level ozone increased by 5-10 ppb in most rural areas, 10-20 ppb near urban centers, and 20-30 ppb immediately downwind of the urban centers compared to simulations in which only anthropogenic emissions were used. A sensitivity analysis of predicted ozone concentration to emissions was performed using the decoupled direct method for three dimensional air quality models (DDM-3D). The highest positive sensitivity of ground-level ozone concentration to biogenic volatile organic compound (VOC) emissions (i.e., increasing biogenic VOC emissions results in increasing ozone concentrations) was predicted to be in locations with high NOx levels, (i.e., the urban areas). One urban center--Houston--was predicted to have a slight negative sensitivity to biogenic NO emissions (i.e., increasing biogenic NO emissions results in decreasing local ozone concentrations). The highest sensitivities of ozone concentrations to on-road mobile source VOC emissions, all positive, were mainly in the urban areas. The highest sensitivities of ozone concentrations to on-road mobile source NOx emissions were predicted in both urban (either positive or negative sensitivities) and rural (positive sensitivities) locations.