Quantification of natural gas and other hydrocarbons from production sites in northern West Virginia using tracer flux ratio methodology.

Tracer flux ratio (TFR) methodology performed downwind of 15 active oil and natural gas production sites in Ohio County, West Virginia sought to quantify air pollutant emissions over two weeks in April 2018. In coordination with a production company, sites were randomly selected depending on wind forecasts and nearby road access. Methane (CH4), ethane (C2H6), and tracer gas compounds (acetylene and nitrous oxide) were measured via tunable infrared direct absorption spectroscopy. Ion signals attributed to benzene (C6H6) and other volatile gases (e.g., C7 - C9 aromatics) were measured via proton-transfer reaction time-of-flight mass spectrometry. Short-term whole facility emission rates for 12 sites are reported. Results from TFR were systematically higher than the sum of concurrent on-site full flow sampler measurements, though not all sources were assessed on-site in most cases. In downwind plumes, the mode of the C2H6:CH4 molar ratio distribution for all sites was 0.2, which agreed with spot sample analysis from the site operator. Distribution of C6H6:CH4 ratios was skew but values between 1 and 5 pptv ppbv-1 were common. Additionally, the aromatic profile has been attributed to condensate storage tank emissions. Average ratios of C7 - C9 to C6H6 were similar to other literature values reported for natural gas wells.

Evaluating Natural Gas Emissions from Pneumatic Controllers from Upstream Oil and Gas Facilities in West Virginia.

In April of 2018, an optical gas imaging (OGI) and full flow sampler (FFS) emissions measurement study of pneumatic controllers (PCs) was conducted at 15 oil and natural gas production sites in West Virginia. The objective of the study was to identify and characterize PC systems with excessive emissions caused by maintenance issues or nonoptimized process conditions. A total of 391 PC systems were found on the sites and all were classified by the operator as snap-acting (on/off) intermittent venting PCs (IPCs) that should exhibit little gas release while the PC is closed between actuation events. The population was comprised of two groups, 259 infrequently actuating, lower emitting (LE) IPCs and 132 gas processing unit (GPU) liquid level IPCs and associated dump valve actuators that vent more frequently and have larger emission volumes. Using a PC-specific OGI inspection protocol with an assumed whole gas OGI detection threshold of 2.0 scfh, only 2 out of 259 LE-IPCs exhibited OGI detectable emissions indicating good inspection and maintenance practices for this category. Due to combined (ganged) GPU exhaust vents, the OGI inspection of the GPU liquid level IPCs was comparatively less informative and determination of single component IPC emissions by the FFS was more difficult. The time resolved FFS measurements of GPU IPCs defined three categories of operation: one that indicated proper function and two associated with higher emissions that may result from an IPC maintenance or process issues. The overall GPU IPC emission distribution was heavy tailed, with a median value of 12.8 scfh, similar to the 13.5 scfh whole gas IPC emission factor (EF). Total emissions were dominated by non-optimal temporal profile high-emitter IPC cases with the top 20% of IPC systems accounting for between 51.3% and 70.7% of GPU liquid level IPC emissions by volume. The uncertainty in the estimate was due to the ganged nature of the GPU exhaust vents. The highest GPU IPC emission came from a single malfunctioning unit with a measured whole gas value of 157 scfh. Up to six IPCs exceeded 100 scfh. An analysis of FFS emission measurements compared to liquids production per IPC unit employed indicated that production sites operating at a high level of liquids production test the limits of the site engineering, likely resulting in higher IPC emissions. Overall, this study found that the LE-IPCs with OGI-verified low closed bleed rates may emit well below the IPC EF while GPU liquid level IPC systems are likely well represented by the current IPC EF. IPCs that are experiencing a maintenance or process issue or that are operating at sites with a very high product throughput per IPC employed can emit at rates exceeding ten times IPC EF.

Methane emissions from oil and gas production sites and their storage tanks in West Virginia.

A measurement campaign characterized methane and other emissions from 15 natural gas production sites. Sites were surveyed using optical gas imaging (OGI) cameras to identify fugitive and vented emissions, with the methane mass emission rate quantified using a full flow sampler. We present storage tank emissions in context of all site emissions, followed by a detailed account of the former. In total, 224 well pad emission sources at 15 sites were quantified yielding a total emission rate of 57.5 ± 2.89 kg/hr for all sites. Site specific emissions ranged from 0.4 to 10.5 kg/hr with arithmetic and geometric means of 3.8 and 2.2 kg/hr, respectively. The two largest categories of emissions by mass were pneumatic devices (35 kg/hr or ~61% of total) and tanks (14.3 kg/hr or ~25% of total). Produced water and condensate tanks at all sites employed emissions control devices. Nevertheless, tanks may still lose gas via component leaks as observed in this study. The total number of tanks at all sites was 153. One site experienced a major malfunction and direct tank measurements were not conducted due to safety concerns and may have represented a super-emitter as found in other studies. The remaining sites had 143 tanks, which accounted for 42 emissions sources. Leaks on controlled tanks were associated with ERVs, PRVs, and thief hatches. Since measurements represented snapshots-in-time and could only be compared with modeled tank emission data, it was difficult to assess real capture efficiencies accurately. Our estimates suggest that capture efficiency ranged from 63 to 92% for controlled tanks.

Comprehensive US database and model for ethanol blend effects on regulated tailpipe emissions.

Particulate matter (PM), oxides of nitrogen (NOx), carbon monoxide (CO), and total hydrocarbons (THC) in gasoline exhaust affect atmospheric quality, and hence human health. Ethanol produced from corn grain is a renewable resource with favorable anti-knock properties for gasoline blending. Refiners alter petroleum composition to produce a finished blend that meets specifications. Ethanol blending affects emissions from market fuels both directly and indirectly since aromatics are typically removed from the BOB as ethanol is added to reach a constant octane rating. Numerous studies have been conducted to assess the effect of ethanol blending on light duty vehicle emissions. However, few studies have examined market fuel blends directly and small studies yield insufficient information to be generally applicable. If blending of fuels for a study does not yield gasoline that adequately resembles the composition of a market blend, the generalizability of study results may be impacted by nonlinear blending effects. Most vehicle-based fuel effect studies employed fuel formulations that either facilitate examination of several fuel variables or blend ethanol into a baseline gasoline (splash blending). Such study results do not support direct quantification of emissions inventory effects. To examine real world blending implications on regulated emissions [PM, NOx, CO, THC], we compiled a comprehensive database of US emission studies, developed regression models based on fuel and vehicle properties, and used those models to estimate differences in emissions from expected market fuel compositions. We addressed nonlinear responses to ethanol composition by modeling both low (up to 10% ethanol by volume) and mid blends (split models). We used the Federal Test Procedure (FTP) and Unified Cycle (LA92) driving schedule data, with the cold-start eliciting the highest emissions. PM cold-start emissions were lower with higher ethanol content, and more so at higher blend levels but hot-running emissions showed no differences with respect to ethanol level. For all emissions, the effects differed between port fuel injection (PFI) and gasoline direct injection (GDI) powered vehicles and for NOx, CO and THC there were differences between comphrehensive and split models. NOx results varied over blend levels and THC results were scattered for the higher blends. CO emissions were lower with higher ethanol content in nearly all cases for PFI but only the hot-running GDI. Results did not differ between summer regular and premium fuels. To the extent that PFI and GDI models differ, an emissions inventory calculation should treat them separately. There is uncertainty directly associated with the regression process, and with model inputs since study methods vary and compositions are reported differently between laboratories and test methods. Small changes in modeled emissions should be considered in this light.

Quantification of gasoline-ethanol blend emissions effects.

Emissions levels from current gasoline spark-ignited engines are low, and emissions changes associated with the blending of ethanol into gasoline are small and difficult to quantify. Addition of ethanol, with a high blending octane number, allows a reduction in aromatics in market gasoline. Blending behavior of ethanol is nonlinear, altering the distillation curve, including the 50% temperature point, T50. Increase in gasoline direct injection (GDI) engine technology in the fleet challenges ability of older models based on port fuel injection (PFI) results to predict the overall air quality impact of ethanol blending. Five different models derived from data collected through U.S. Environmental Protection Agency Energy Policy Act (EPAct) programs were used to predict LA92 Phase 1 particulate matter (PM) emissions for summer regular (SR) E0 (gasoline with 0% ethanol by volume), E10 (gasoline with 10% ethanol) and E15 (gasoline with 15% ethanol). Substantial reductions of PM for E10 and E15 relative to E0 were predicted when aromatics were displaced by ethanol to maintain octane rating. SR E0 and E10 were also matched to linear combinations of EPAct fuels and results showed a 35% PM reduction for SR E10 relative to SR E0. For GDI vehicles the Coordinating Research Council (CRC) E-94-3 study found that E10 had 23% or 29% PM increase. However, CRC E-129 found an E10 PM reduction of 10% when one E0 fuel and its splash blended (SB) E10 were compared. Both CRC project E-129 SB data and fuel triplets selected from the EPAct study showed variation for E15 emissions, although E-129 suggests that E15 in GDI offers about a 25% reduction of PM with respect to E0. Overall, data suggest that ethanol blending offers a modest to a substantial reduction of cold-start PM mass if aromatic levels of the finished products are reduced in response to ethanol addition. Implications: Studies of exhaust emissions effects of ethanol blending with gasoline vary in conclusions. Blending properties are nonlinear. Modeling of real-world emissions effects must consider all fuel composition adjustments and property changes associated with ethanol addition. Aromatics are reduced in E10 or E15, compared with E0, and distillation changes. PFI-derived models show reductions in cold-start PM for expected average E10 versus E0 pump fuel, due to reduced aromatic content. Relative emissions effects from older technology (PFI) engines do not predict newer engine (GDI) results reliably, but recent GDI data show reduced cold-start PM when ethanol displaces aromatics.

The (in)visible health risks of climate change.

This paper scrutinizes the assertion that knowledge gaps concerning health risks from climate change are unjust, and must be addressed, because they hinder evidence-led interventions to protect vulnerable populations. First, we construct a taxonomy of six inter-related forms of invisibility (social marginalization, forced invisibility by migrants, spatial marginalization, neglected diseases, mental health, uneven climatic monitoring and forecasting) which underlie systematic biases in current understanding of these risks in Latin America, and advocate an approach to climate-health research that draws on intersectionality theory to address these inter-relations. We propose that these invisibilities should be understood as outcomes of structural imbalances in power and resources rather than as haphazard blindspots in scientific and state knowledge. Our thesis, drawing on theories of governmentality, is that context-dependent tensions condition whether or not benefits of making vulnerable populations legible to the state outweigh costs. To be seen is to be politically counted and eligible for rights, yet evidence demonstrates the perils of visibility to disempowered people. For example, flood-relief efforts in remote Amazonia expose marginalized urban river-dwellers to the traumatic prospect of forced relocation and social and economic upheaval. Finally, drawing on research on citizenship in post-colonial settings, we conceptualize climate change as an 'open moment' of political rupture, and propose strategies of social accountability, empowerment and trans-disciplinary research which encourage the marginalized to reach out for greater power. These achievements could reduce drawbacks of state legibility and facilitate socially-just governmental action on climate change adaptation that promotes health for all.

Future methane emissions from the heavy-duty natural gas transportation sector for stasis, high, medium, and low scenarios in 2035.

Today's heavy-duty natural gas-fueled fleet is estimated to represent less than 2% of the total fleet. However, over the next couple of decades, predictions are that the percentage could grow to represent as much as 50%. Although fueling switching to natural gas could provide a climate benefit relative to diesel fuel, the potential for emissions of methane (a potent greenhouse gas) from natural gas-fueled vehicles has been identified as a concern. Since today's heavy-duty natural gas-fueled fleet penetration is low, today's total fleet-wide emissions will be also be low regardless of per vehicle emissions. However, predicted growth could result in a significant quantity of methane emissions. To evaluate this potential and identify effective options for minimizing emissions, future growth scenarios of heavy-duty natural gas-fueled vehicles, and compressed natural gas and liquefied natural gas fueling stations that serve them, have been developed for 2035, when the populations could be significant. The scenarios rely on the most recent measurement campaign of the latest manufactured technology, equipment, and vehicles reported in a companion paper as well as projections of technology and practice advances. These "pump-to-wheels"(PTW) projections do not include methane emissions outside of the bounds of the vehicles and fuel stations themselves and should not be confused with a complete wells-to-wheels analysis. Stasis, high, medium, and low scenario PTW emissions projections for 2035 were 1.32%, 0.67%, 0.33%, and 0.15% of the fuel used. The scenarios highlight that a large emissions reductions could be realized with closed crankcase operation, improved best practices, and implementation of vent mitigation technologies. Recognition of the potential pathways for emissions reductions could further enhance the heavy-duty transportation sectors ability to reduce carbon emissions. IMPLICATIONS: Newly collected pump-to-wheels methane emissions data for current natural gas technologies were combined with future market growth scenarios, estimated technology advancements, and best practices to examine the climate benefit of future fuel switching. The analysis indicates the necessary targets of efficiency, methane emissions, market penetration, and best practices necessary to enable a pathway for natural gas to reduce the carbon intensity of the heavy-duty transportation sector.

Pump-to-Wheels Methane Emissions from the Heavy-Duty Transportation Sector.

Pump-to-wheels (PTW) methane emissions from the heavy-duty (HD) transportation sector, which have climate change implications, are poorly documented. In this study, methane emissions from HD natural gas fueled vehicles and the compressed natural gas (CNG) and liquefied natural gas (LNG) fueling stations that serve them were characterized. A novel measurement system was developed to quantify methane leaks and losses. Engine related emissions were characterized from twenty-two natural gas fueled transit buses, refuse trucks, and over-the-road (OTR) tractors. Losses from six LNG and eight CNG stations were characterized during compression, fuel delivery, storage, and from leaks. Cryogenic boil-off pressure rise and pressure control venting from LNG storage tanks were characterized using theoretical and empirical modeling. Field and laboratory observations of LNG storage tanks were used for model development and evaluation. PTW emissions were combined with a specific scenario to view emissions as a percent of throughput. Vehicle tailpipe and crankcase emissions were the highest sources of methane. Data from this research are being applied by the authors to develop models to forecast methane emissions from the future HD transportation sector.

Design and Use of a Full Flow Sampling System (FFS) for the Quantification of Methane Emissions.

The use of natural gas continues to grow with increased discovery and production of unconventional shale resources. At the same time, the natural gas industry faces continued scrutiny for methane emissions from across the supply chain, due to methane's relatively high global warming potential (25-84x that of carbon dioxide, according to the Energy Information Administration). Currently, a variety of techniques of varied uncertainties exists to measure or estimate methane emissions from components or facilities. Currently, only one commercial system is available for quantification of component level emissions and recent reports have highlighted its weaknesses. In order to improve accuracy and increase measurement flexibility, we have designed, developed, and implemented a novel full flow sampling system (FFS) for quantification of methane emissions and greenhouse gases based on transportation emissions measurement principles. The FFS is a modular system that consists of an explosive-proof blower(s), mass airflow sensor(s) (MAF), thermocouple, sample probe, constant volume sampling pump, laser based greenhouse gas sensor, data acquisition device, and analysis software. Dependent upon the blower and hose configuration employed, the current FFS is able to achieve a flow rate ranging from 40 to 1,500 standard cubic feet per minute (SCFM). Utilization of laser-based sensors mitigates interference from higher hydrocarbons (C2+). Co-measurement of water vapor allows for humidity correction. The system is portable, with multiple configurations for a variety of applications ranging from being carried by a person to being mounted in a hand drawn cart, on-road vehicle bed, or from the bed of utility terrain vehicles (UTVs). The FFS is able to quantify methane emission rates with a relative uncertainty of ± 4.4%. The FFS has proven, real world operation for the quantification of methane emissions occurring in conventional and remote facilities.

Methane Emissions from Leak and Loss Audits of Natural Gas Compressor Stations and Storage Facilities.

As part of the Environmental Defense Fund's Barnett Coordinated Campaign, researchers completed leak and loss audits for methane emissions at three natural gas compressor stations and two natural gas storage facilities. Researchers employed microdilution high-volume sampling systems in conjunction with in situ methane analyzers, bag samples, and Fourier transform infrared analyzers for emissions rate quantification. All sites had a combined total methane emissions rate of 94.2 kg/h, yet only 12% of the emissions total resulted from leaks. Methane slip from exhausts represented 44% of the total emissions. Remaining methane emissions were attributed to losses from pneumatic actuators and controls, engine crankcases, compressor packing vents, wet seal vents, and slop tanks. Measured values were compared with those reported in literature. Exhaust methane emissions were lower than emissions factor estimates for engine exhausts, but when combined with crankcase emissions, measured values were 11.4% lower than predicted by AP-42 as applicable to emissions factors for four-stroke, lean-burn engines. Average measured wet seal emissions were 3.5 times higher than GRI values but 14 times lower than those reported by Allen et al. Reciprocating compressor packing vent emissions were 39 times higher than values reported by GRI, but about half of values reported by Allen et al. Though the data set was small, researchers have suggested a method to estimate site-wide emissions factors for those powered by four-stroke, lean-burn engines based on fuel consumption and site throughput.

Near-Field Characterization of Methane Emission Variability from a Compressor Station Using a Model Aircraft.

A model aircraft equipped with a custom laser-based, open-path methane sensor was deployed around a natural gas compressor station to quantify the methane leak rate and its variability at a compressor station in the Barnett Shale. The open-path, laser-based sensor provides fast (10 Hz) and precise (0.1 ppmv) measurements of methane in a compact package while the remote control aircraft provides nimble and safe operation around a local source. Emission rates were measured from 22 flights over a one-week period. Mean emission rates of 14 ± 8 g CH4 s(-1) (7.4 ± 4.2 g CH4 s(-1) median) from the station were observed or approximately 0.02% of the station throughput. Significant variability in emission rates (0.3-73 g CH4 s(-1) range) was observed on time scales of hours to days, and plumes showed high spatial variability in the horizontal and vertical dimensions. Given the high spatiotemporal variability of emissions, individual measurements taken over short durations and from ground-based platforms should be used with caution when examining compressor station emissions. More generally, our results demonstrate the unique advantages and challenges of platforms like small unmanned aerial vehicles for quantifying local emission sources to the atmosphere.

Modeling transit bus fuel consumption on the basis of cycle properties.

A method exists to predict heavy-duty vehicle fuel economy and emissions over an "unseen" cycle or during unseen on-road activity on the basis of fuel consumption and emissions data from measured chassis dynamometer test cycles and properties (statistical parameters) of those cycles. No regression is required for the method, which relies solely on the linear association of vehicle performance with cycle properties. This method has been advanced and examined using previously published heavy-duty truck data gathered using the West Virginia University heavy-duty chassis dynamometer with the trucks exercised over limited test cycles. In this study, data were available from a Washington Metropolitan Area Transit Authority emission testing program conducted in 2006. Chassis dynamometer data from two conventional diesel buses, two compressed natural gas buses, and one hybrid diesel bus were evaluated using an expanded driving cycle set of 16 or 17 different driving cycles. Cycle properties and vehicle fuel consumption measurements from three baseline cycles were selected to generate a linear model and then to predict unseen fuel consumption over the remaining 13 or 14 cycles. Average velocity, average positive acceleration, and number of stops per distance were found to be the desired cycle properties for use in the model. The methodology allowed for the prediction of fuel consumption with an average error of 8.5% from vehicles operating on a diverse set of chassis dynamometer cycles on the basis of relatively few experimental measurements. It was found that the data used for prediction should be acquired from a set that must include an idle cycle along with a relatively slow transient cycle and a relatively high speed cycle. The method was also applied to oxides of nitrogen prediction and was found to have less predictive capability than for fuel consumption with an average error of 20.4%.

Expressing cycles and their emissions on the basis of properties and results from other cycles.

A method is proposed to predict vehicle emissions over a driving cycle on the basis of the vehicle's emissions measured over other driving cycles and the properties of these cycles. These properties include average velocity, average inertial power, and average acceleration. This technique was demonstrated and verified using data from the Coordinating Research Council (CRC) E-55/59 emissions inventory program using the statistical properties of the cycles used for measurement in E-55/59. These cycles were Idle mode, Creep mode, Cruise mode, and Transient mode of the 5-Mode CARB H-HDDT, and their intensive properties were average velocity, average acceleration, and average inertial power. The predicted emissions were from the vehicle driven over the U.S. heavy-duty urban dynamometer driving schedule (UDDS). The emissions data were collected from 56 heavy-duty trucks operating at a test weight of 56000 lbs. The predicted emissions data for the UDDS can be expressed as a linear combination of emissions from Idle, Transient, and Cruise modes, and the weighting factors for the linear combination can be determined without prior knowledge of the UDDS emissions themselves. Different combinations of cycles were employed to predict UDDS emissions, and the combination of Idle, Transient, and Cruise modes was found to be the most suitable. For the 56 heavy-duty trucks, the coefficient of determination (R2) in predicting carbon dioxide (CO2) was 0.80, oxides of nitrogen (NOx) was 0.89, and total particulate matter (PM) was 0.71. The average errors between the predicted and measured cycle emissions were 4.2%, 7.8%, and 46.8%, respectively. As with most emissions modeling tools, CO2 and NOx were better predicted than PM. The generic use of the technique was further demonstrated by predicting the emissions expected to arise from operation over the European Transient Cycle (ETC).

Regression-based oxides of nitrogen predictors for three diesel engine technologies.

Models of diesel engine emissions such as oxides of nitrogen (NO(x)) are valuable when they can predict instantaneous values because they can be incorporated into whole vehicle models, support inventory predictions, and assist in developing superior engine and aftertreatment control strategies. Recent model-year diesel engines using multiple injection strategies, exhaust gas recirculation, and variable geometry turbocharging may have more transient sensitivity and demand more sophisticated modeling than for legacy engines. Emissions data from 1992, 1999, and 2004 model-year U.S. truck engines were modeled separately using a linear approach (with transient terms) and multivariate adaptive regression splines (MARS), an adaptive piece-wise regression approach that has limited prior use for emissions prediction. Six input variables based on torque, speed, power, and their derivatives were used for MARS. Emissions time delay was considered for both models. Manifold air temperature (MAT) and manifold air pressure (MAP) were further used in NO(x) modeling to build a plug-in model. The predictive performance for instantaneous NO(x) on part of the certification transient test procedure (Federal Test Procedure [FTP]) of the 2004 engine MARS was lower (R2 = 0.949) than the performance for the 1992 (R2 = 0.981) and 1999 (R2 = 0.988) engines. Linear regression performed similarly for the 1992 and 1999 engines but performed poorly (R2 = 0.896) for the 2004 engine. The MARS performance varied substantially when data from different cycles were used. Overall, the MAP and MAT plug-in model trained by MARS was the best, but the performance differences between LR and MARS were not substantial.

Development of a heavy heavy-duty diesel engine schedule for representative measurement of emissions.

The Advanced Collaborative Emissions Study (ACES) has the objective of characterizing the emissions and assessing the possible health impacts of the 2007-2010 heavy-duty diesel engines and their control systems. The program seeks to examine emissions from engines operated in a realistic duty cycle and requires the development of an engine test schedule described in this paper. Field data on engine operation were available from Engine Control Unit (ECU) broadcasts from seven heavy heavy-duty trucks (HHDDT) tested during the Coordinating Research Council (CRC) E-55/59 study. These trucks were exercised at three weights (30,000 lb [13,610 kg], 56,000 lb [25,400 kg], and 66,000 lb [29,940 kg]) through four different active modes of a chassis test schedule that were developed from the data of in-use HHDDT operation in the state of California. The trucks were equipped with heavy-duty engines made by three major U.S. engine manufacturers with a range of model years from 1998 to 2003. This paper reports on the development of four engine test modes, termed creep, transient, cruise, and high-speed cruise (HHDDT_S), which correspond to the E-55/59 HHDDT chassis test modes. The creep and transient modes represent urban travel, and the cruise and HHDDT_S modes represent freeway operation. The test mode creation used the method of joining selected truck trips together while ensuring that they offered a reasonable statistical representation of the whole database by using a least-square errors method. Least-square errors between test modes and the database are less than 5%. The four test modes are presented in normalized engine

Testing of a heavy heavy-duty diesel engine schedule for representative measurement of emissions.

The Advanced Collaborative Emissions Study (ACES) program required the use of representative heavy-duty diesel engine activity. This need resulted in an engine test schedule creation program, and a schedule of engine modes representative of modern truck usage was developed based on data collected from engines in trucks operated through the heavy heavy-duty diesel truck (HHDDT) chassis schedule. The ACES test schedule included four active modes of truck operation including creep, transient, cruise, and high-speed cruise (HHDDT_S). This paper focuses on Phase 2 of the program, which was to validate and demonstrate the use of the ACES modes in a test cell. Preliminary testing was performed using a 1992 Detroit Diesel Corporation heavy heavy-duty diesel engine (HHDDE) on only the transient mode. On the basis of these results, each mode was modified slightly to suit implementation in a test cell. The locations of "closed throttle" points in the modes were determined through careful examination of the data. These closed throttle points were simulated during testing by adding negative set point torque values to the input file. After modification, all modes were tested during a final ACES modes demonstration period using a 2004 Cummins ISM HHDDE, obtaining three runs for each mode. During testing, carbon monoxide (CO), carbon dioxide (CO2), nitrogen oxides (NOx), particulate matter (PM), and hydrocarbon (HC) emissions were measured, and engine control unit (ECU) data were recorded. The new ACES modes did not adopt the Federal Test Procedure (FTP) regression criteria. New regression criteria for acceptability of a run were determined for each mode using the data obtained during testing.

Design and testing of an independently controlled urea SCR retrofit system for the reduction of NOx emissions from marine diesels.

Diesel engine emissions for on-road, stationary and marine applications are regulated in the United States via standards set by the Environmental Protection Agency (EPA). A major component of diesel exhaust that is difficult to reduce is nitrogen oxides (NOx). Selective catalytic reduction (SCR) has been in use for many years for stationary applications, including external combustion boilers, and is promising for NOx abatement as a retrofit for mobile applications where diesel compression ignition engines are used. The research presented in this paper is the first phase of a program focused on the reduction of NOx by use of a stand-alone urea injection system, applicable to marine diesel engines typical of work boats (e.g., tugs). Most current urea SCR systems communicate with engine controls to predict NOx emissions based on signals such as torque and engine speed, however many marine engines in use still employ mechanical injection technology and lack electronic communication abilities. The system developed and discussed in this paper controls NOx emissions independentof engine operating parameters and measures NOx and exhaust flow using the following exhaust sensor inputs: absolute pressure, differential pressure, temperature, and NOx concentration. These sensor inputs were integrated into an independent controller and open loop architecture to estimate the necessary amount of urea needed, and the controller uses pulse width modulation (PWM) to power an automotive fuel injector for airless urea delivery. The system was tested in a transient test cell on a 350 hp engine certified at 4 g/bhp-hr of NOx, with a goal of reducing the engine out NOx levels by 50%. NOx reduction capabilities of 41-67% were shown on the non road transient cycle (NRTC) and ICOMIA E5 steady state cycles with system optimization during testing to minimize the dilute ammonia slip to cycle averages of 5-7 ppm. The goal of 50% reduction of NOx can be achieved dependent upon cycle. Further research with control optimization, urea distribution and possible use of oxidation catalysts is recommended to improve the NOx reduction capabilities while minimizing ammonia slip.

Investigation into pedestrian exposure to near-vehicle exhaust emissions.

BACKGROUND: Inhalation of diesel particulate matter (DPM) is known to have a negative impact on human health. Consequently, there are regulations and standards that limit the maximum concentrations to which persons may be exposed and the maximum concentrations allowed in the ambient air. However, these standards consider steady exposure over large spatial and time scales. Due to the nature of many vehicle exhaust systems, pedestrians in close proximity to a vehicle's tailpipe may experience events where diesel particulate matter concentrations are high enough to cause acute health effects for brief periods of time. METHODS: In order to quantify these exposure events, instruments which measure specific exhaust constituent concentrations were placed near a roadway and connected to the mouth of a mannequin used as a pedestrian surrogate. By measuring concentrations at the mannequin's mouth during drive-by events with a late model diesel truck, a representative estimate of the exhaust constituent concentrations to which a pedestrian may be exposed was obtained. Typical breathing rates were then multiplied by the measured concentrations to determine the mass of pollutant inhaled. RESULTS: The average concentration of diesel particulate matter measured over the duration of a single drive-by test often exceeded the low concentrations used in human clinical studies which are known to cause acute health effects. It was also observed that higher concentrations of diesel particulate matter were measured at the height of a stroller than were measured at the mouth of a mannequin. CONCLUSION: Diesel particulate matter concentrations during drive-by incidents easily reach or exceed the low concentrations that can cause acute health effects for brief periods of time. For the case of a particularly well-tuned late-model year vehicle, the mass of particulate matter inhaled during a drive-by incident is small compared to the mass inhaled daily at ambient conditions. On a per breath basis, however, the mass of particulate matter inhaled is large compared to the mass inhaled at ambient conditions. Finally, it was determined that children, infants, or people breathing at heights similar to that of a passing vehicle's tailpipe may be exposed to higher concentrations of particulate matter than those breathing at higher locations, such as adults standing up.