Automated Chemical Mass Balance Receptor Modeling

Abstract

A nontrivial portion of heavy-duty vehicle emissions of NO_x and particulate matter (PM) occurs during idling. Regulators and the environmental community are interested in curtailing truck idling emissions, but current emissions models do not characterize them accurately, and little quantitative data exist to evaluate the relative effectiveness of various policies. The objectives of this study were to quantify the effect of accessory loading and engine speed on idling emissions from a properly functioning, modern, heavy-duty diesel truck and to compare these results with data from earlier model year vehicles. It was found that emissions during idling varied greatly as a function of engine model year, engine speed, and accessory load conditions. For the 1999 model year Class 8 truck tested, raising the engine speed from 600 to 1050 rpm and turning on the air conditioning resulted in a 2.5-fold increase in NO_x emissions in grams per hour, a 2-fold increase in CO₂ emissions, and a 5-fold increase in CO emissions while idling. On a grams per gallon fuel basis, NO_x emissions while idling were approximately twice as high as those at 55 mph. The CO₂ emissions at the two conditions were closer. The NO_x emissions from the 1999 truck while idling with air conditioning running were slightly more than those of two 1990 model year trucks under equivalent conditions, and the hydrocarbon (HC) and CO emissions were significantly lower. It was found that the NO_x emissions used in the California Air Resources Board’s (CARB) EMFAC2000 and the U.S. Environmental Protection Agency’s (EPA) MOBILE5b emissions inventory models were lower than those measured in all of the idling conditions tested on the 1999 truck.     

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.     

Idle emissions from heavy-duty diesel vehicles: review and recent data

Heavy-duty diesel vehicle idling consumes fuel and reduces atmospheric quality, but its restriction cannot simply be proscribed, because cab heat or air-conditioning provides essential driver comfort. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from the West Virginia University transient engine test cell, the E-55/59 Study and the Gasoline/Diesel PM Split Study. It covered 75 heavy-duty diesel engines and trucks, which were divided into two groups: vehicles with mechanical fuel injection (MFI) and vehicles with electronic fuel injection (EFI). Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NOx), particulate matter (PM), and carbon dioxide (CO2) have been reported. Idle CO2 emissions allowed the projection of fuel consumption during idling. Test-to-test variations were observed for repeat idle tests on the same vehicle because of measurement variation, accessory loads, and ambient conditions. Vehicles fitted with EFI, on average, emitted approximately 20 g/hr of CO, 6 g/hr of HC, 86 g/hr of NOx, 1 g/hr of PM, and 4636 g/hr of CO2 during idle. MFI equipped vehicles emitted approximately 35 g/hr of CO, 23 g/hr of HC, 48 g/hr of NOx, 4 g/hr of PM, and 4484 g/hr of CO2, on average, during idle. Vehicles with EFI emitted less idle CO, HC, and PM, which could be attributed to the efficient combustion and superior fuel atomization in EFI systems. Idle NOx, however, increased with EFI, which corresponds with the advancing of timing to improve idle combustion. Fuel injection management did not have any effect on CO2 and, hence, fuel consumption. Use of air conditioning without increasing engine speed increased idle CO2, NOx, PM, HC, and fuel consumption by 25% on average. When the engine speed was elevated from 600 to 1100 revolutions per minute, CO2 and NOx emissions and fuel consumption increased by >150%, whereas PM and HC emissions increased by approximately 100% and 70%, respectively. Six Detroit Diesel Corp. (DDC) Series 60 engines in engine test cell were found to emit less CO, NOx, and PM emissions and consumed fuel at only 75% of the level found in the chassis dynamometer data. This is because fan and compressor loads were absent in the engine test cell.     

Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.     

Idle Emissions from Heavy-Duty Diesel Vehicles: Review and Recent Data

Abstract

Heavy-duty diesel vehicle idling consumes fuel and reduces atmospheric quality, but its restriction cannot simply be proscribed, because cab heat or air-conditioning provides essential driver comfort. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from the West Virginia University transient engine test cell, the E-55/59 Study and the Gasoline/Diesel PM Split Study. It covered 75 heavy-duty diesel engines and trucks, which were divided into two groups: vehicles with mechanical fuel injection (MFI) and vehicles with electronic fuel injection (EFI). Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NO_x), particulate matter (PM), and carbon dioxide (CO₂) have been reported. Idle CO₂ emissions allowed the projection of fuel consumption during idling. Test-to-test variations were observed for repeat idle tests on the same vehicle because of measurement variation, accessory loads, and ambient conditions. Vehicles fitted with EFI, on average, emitted [~20 g/hr of CO, 6 g/hr of HC, 86 g/hr of NO_x, 1 g/hr of PM, and 4636 g/hr of CO₂ during idle. MFI equipped vehicles emitted ~35 g/hr of CO, 23 g/hr of HC, 48 g/hr of NO_x, 4 g/hr of PM, and 4484 g/hr of CO₂, on average, during idle. Vehicles with EFI emitted less idleCO, HC, and PM, which could be attributed to the efficient combustion and superior fuel atomization in EFI systems. Idle NO_x, however, increased with EFI, which corresponds with the advancing of timing to improve idle combustion. Fuel injection management did not have any effect on CO₂ and, hence, fuel consumption. Use of air conditioning without increasing engine speed increased idle CO₂, NO_x, PM, HC, and fuel consumption by 25% on average. When the engine speed was elevated from 600 to 1100 revolutions per minute, CO₂ and NO_x emissions and fuel consumption increased by >150%, whereas PM and HC emissions increased by ~100% and 70%, respectively. Six Detroit Diesel Corp. (DDC) Series 60 engines in engine test cell were found to emit less CO, NO_x, and PM emissions and consumed fuel at only 75%of the level found in the chassis dynamometer data. This is because fan and compressor loads were absent in the engine test cell.     

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.     

Idle Emissions from Heavy-Duty Diesel and Natural Gas Vehicles at High Altitude

ABSTRACT

Idle emissions of total hydrocarbon (THC), CO, NO_x, 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 NO_x, and 0.030 g/min PM. Diesel buses averaged 0.137 g/min THC, 1.326 g/min CO, 2.015 g/min NO_x, 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 NO_x emissions were significantly higher (30-100%) than model predictions. For the pre-1999 (pre-consent decree) truck engines examined in this study, idle NO_x emissions increased with Health and Environment; June 30, 1999 (available from the authors).     

Idle Emissions from Medium Heavy-Duty Diesel and Gasoline Trucks

Abstract

Idle emissions data from 19 medium heavy-duty diesel and gasoline trucks are presented in this paper. Emissions from these trucks were characterized using full-flow exhaust dilution as part of the Coordinating Research Council (CRC) Project E-55/59. Idle emissions data were not available from dedicated measurements, but were extracted from the continuous emissions data on the low-speed transient mode of the medium heavy-duty truck (MHDTLO) cycle. The four gasoline trucks produced very low oxides of nitrogen (NO_x) and negligible particulate matter (PM) during idle. However, carbon monoxide (CO) and hydrocarbons (HCs) from these four trucks were approximately 285 and 153 g/hr on average, respectively. The gasoline trucks consumed substantially more fuel at an hourly rate (0.84 gal/hr) than their diesel counterparts (0.44 gal/hr) during idling. The diesel trucks, on the other hand, emitted higher NO_x (79 g/hr) and comparatively higher PM (4.1 g/hr), on average, than the gasoline trucks (3.8 g/hr of NO_x and 0.9 g/hr of PM, on average). Idle NO_x emissions from diesel trucks were high for post-1992 model year engines, but no trends were observed for fuel consumption. Idle emissions and fuel consumption from the medium heavy-duty diesel trucks (MHDDTs) were marginally lower than those from the heavy heavy-duty diesel trucks (HHDDTs), previously reported in the literature.     

Further Validation of Artificial Neural Network-Based Emissions Simulation Models for Conventional and Hybrid Electric Vehicles

Abstract

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO₂] and oxides of nitrogen [NO_x]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO₂ and NO_x in the case of a class-8 truck but were more accurate as the truck weight increased.     

Temperature effects on particulate emissions from DPF-equipped diesel trucks operating on conventional and biodiesel fuels

Emissions tests were conducted on two medium heavy-duty diesel trucks equipped with a particulate filter (DPF), with one vehicle using a NOx absorber and the other a selective catalytic reduction (SCR) system for control of nitrogen oxides (NOx). Both vehicles were tested with two different fuels (ultra-low-sulfur diesel [ULSD] and biodiesel [B20]) and ambient temperatures (70ºF and 20ºF), while the truck with the NOx absorber was also operated at two loads (a heavy weight and a light weight). The test procedure included three driving cycles, a cold start with low transients (CSLT), the federal heavy-duty urban dynamometer driving schedule (UDDS), and a warm start with low transients (WSLT). Particulate matter (PM) emissions were measured second-by-second using an Aethalometer for black carbon (BC) concentrations and an engine exhaust particle sizer (EEPS) for particle count measurements between 5.6 and 560 nm. The DPF/NOx absorber vehicle experienced increased BC and particle number concentrations during cold starts under cold ambient conditions, with concentrations two to three times higher than under warm starts at higher ambient temperatures. The average particle count for the UDDS showed an opposite trend, with an approximately 27% decrease when ambient temperatures decreased from 70ºF to 20ºF. This vehicle experienced decreased emissions when going from ULSD to B20. The DPF/SCR vehicle tested had much lower emissions, with many of the BC and particle number measurements below detectable limits. However, both vehicles did experience elevated emissions caused by DPF regeneration. All regeneration events occurred during the UDDS cycle. Slight increases in emissions were measured during the WSLT cycles after the regeneration. However, the day after a regeneration occurred, both vehicles showed significant increases in particle number and BC for the CSLT drive cycle, with increases from 93 to 1380% for PM number emissions compared with tests following a day with no regeneration.

Implications:?The use of diesel particulate filters (DPFs) on trucks is becoming more common throughout the world. Understanding how DPFs affect air pollution emissions under varying operating conditions will be critical in implementing effective air quality standards. This study evaluated particulate matter (PM) and black carbon (BC) emissions with two DPF-equipped heavy-duty diesel trucks operating on conventional fuel and a biodiesel fuel blend at varying ambient temperatures, loads, and drive cycles.     

On-road motor vehicle emissions and fuel consumption in urban driving conditions

This paper reports on the analysis of on-road vehicle speed, emission, and fuel consumption data collected by four instrumented vehicles. Time-, distance-, and fuel-based average fuel consumption, as well as CO, HC, NOx, and soot emission factors, were derived. The influences of instantaneous vehicle speed on emissions and fuel consumption were studied. It was found that the fuel-based emission factors varied much less than the time- and distance-based emission factors as instantaneous speed changed. The trends are similar to the results obtained from laboratory tests. The low driving speed contributed to a significant portion of the total emissions over a trip. Furthermore, the on-road data were analyzed using the modal approach. The four standard driving modes are acceleration, cruising, deceleration, and idling. It was found that the transient driving modes (i.e., acceleration and deceleration) were more polluting than the steady-speed driving modes (i.e., cruising and idling) in terms of g/km and g/sec. These results indicated that the on-road emission measurement is feasible in deriving vehicle emissions and fuel consumption factors in urban driving conditions.     

Heavy Duty Diesel Particulate Emission Factors

For the past several years, EPA has been measuring particulate emissions from a variety of heavy-duty diesel engines through contracts with Southwest Research Institute. Particulate emissions samples have been collected using an exhaust splitter to divert a fraction of the engine exhaust into a standard dilution tunnel. A small fraction of the diluted exhaust from the tunnel is pulled through a filter from which particulate mass and, in some cases, organic content of the particulate is determined. This paper discusses the sampling system and gives particulate emission factors that have been computed from truck and bus fuel consumption data as well as average truck and bus speed data from New York and Los Angeles (freeway and nonfreeway usage). Average particulate emission test results (steady state tests) for 2-stroke engines were 4.74 g/kg fuel and for 4-stroke engines were 2.64 g/kg fuel. Using average particulate emissions results, a particulate emission factor range of 0.8 to 1.3 g/km was computed. Nationwide diesel particulate emissions were calculated to be 88,000 metric tons per year.     

On-road emission characteristics of heavy-duty diesel vehicles in Shanghai

On-road vehicle tests of nine heavy-duty diesel trucks were conducted using SEMTECH-D, an emissions measuring instrument provided by Sensors, Inc. The total length of roads for the tests was 186 km. Data were obtained for 37,255 effective driving cycles, including 17,216 on arterial roads, 15,444 on residential roads, and 4595 on highways. The impacts of speed and acceleration on fuel consumption and emissions were analyzed. Results show that trucks spend an average of 16.5% of the time in idling mode, 25.5% in acceleration mode, 27.9% in deceleration mode, and only 30.0% at cruise speed. The average emission factors of CO, total hydrocarbons (THC), and NO_x for the selected vehicles are (4.96±2.90), (1.88±1.03) and (6.54±1.90) g km⁻¹, respectively. The vehicle emission rates vary significantly with factors like speed and acceleration. The test results reflect the actual traffic situation and the current emission status of diesel trucks in Shanghai. The measurements show that low-speed conditions with frequent acceleration and deceleration, particularly in congestion conditions, are the main factors that aggravate vehicle emissions and cause high emissions of CO and THC. Alleviating congestion would significantly improve vehicle fuel economy and reduce CO and THC emissions.     

Remote Sensing Data and a Potential Model of Vehicle Exhaust Emissions

In June 1991, General Motors Research and Development Center (GMR&D) participated in a remote sensing study conducted by the California Air Resources Board and the U. S. Environmental Protection Agency. During this study, the GMR&D remote sensor was used to measure the carbon monoxide (CO) and hydrocarbon (HC) emissions from approximately 15,000 vehicles. The vehicle type (passenger car, light-duty truck, or medium/heavy-duty truck), manufacturer, and model year were identified for each vehicle by acquiring registration data from the state of California. Analyses were performed separately for each vehicle type and for passenger cars by separate model years. The data indicate that the passenger cars with the highest 10% of CO emissions generated approximately 58% of the total CO from all cars. Similarly, the 10% highest HC-emitting cars generated 65% of the total HC from cars. It was found that for each model year of vehicle, the distribution of emission concentrations followed a logarithmic relationship. The logarithmic functions that describe these relationships can be used to estimate the fraction of vehicles that emitted at or above any given concentration of CO or HC. However, these logarithmic functions only describe measured distributions for vehicles emitting more than 1% CO and 0.015% HC.     

Effects of a zeolite-selective catalytic reduction system on comprehensive emissions from a heavy-duty diesel engine

The effects of a zeolite urea-selective catalytic reduction (SCR) aftertreatment system on a comprehensive spectrum of chemical species from diesel engine emissions were investigated in this study. Representative samples were collected with a newly developed source dilution sampling system after an aging process designed to simulate atmospheric dilution and cooling conditions. Samples were analyzed with established procedures and compared between the measurements taken from a baseline heavy-duty diesel engine and also from the same engine equipped with the exhaust aftertreatment system. The results have shown significant reductions for nitrogen oxides (NOx), carbon monoxide, total hydrocarbons, polycyclic aromatic hydrocarbons (PAHs), and organic carbon (OC) emissions. Additionally, less significant yet notable reductions were observed for particulate matter mass and metals emissions. Furthermore, the production of new species was not observed with the addition of the zeolite urea-SCR system joined with a downstream oxidation catalyst.     

Field Measurements of Particulate Matter Emissions,Carbon Monoxide,and Exhaust Opacity from Heavy-Duty Diesel Vehicles

ABSTRACT

Diesel particulate matter (PM) is a significant contributor to ambient air PM₁₀ and PM_2.5 particulate levels. In addition, recent literature argues that submicron diesel PM is a pulmonary health hazard. There is difficulty in attributing PM emissions to specific operating modes of a diesel engine, although it is acknowledged that PM production rises dramatically with load and that high PM emissions occur during rapid load increases on turbocharged engines. Snap-acceleration tests generally identify PM associated with rapid transient operating conditions, but not with high load. To quantify the origin of PM during transient engine operation, continuous opacity measurements have been made using a Wager 650CP full flow exhaust opacity meter. Opacity measurements were taken while the vehicles were operated over transient driving cycles on a chassis dynamometer using the West Virginia University (WVU) Transportable Heavy Duty Vehicle Emissions Testing Laboratories. Data were gathered from Detroit Diesel, Cummins, Caterpillar, and Navistar heavy-duty (HD) diesel engines. Driving cycles used were the Central Business District (CBD) cycle, the WVU 5-Peak Truck cycle, the WVU 5-Mile route, and the New York City Bus (NYCB) cycle. Continuous opacity measurements, integrated over the entire driving cycle, were compared to total integrated PM mass. In addition, the truck was subjected to repeat snap-acceleration tests, and PM was collected for a composite of these snap-acceleration tests. Additional data were obtained from a fleet of 1996 New Flyer buses in Flint, MI, equipped with electronically controlled Detroit Diesel Series 50 engines. Again, continuous opacity, regulated gaseous emissions, and PM were measured. The relationship between continuous carbon monoxide (CO) emissions and continuous opacity was noted. In identifying the level of PM emissions in transient diesel engine operation, it is suggested that CO emissions may prove to be a useful indicator and may be used to apportion total PM on a continuous basis over a transient cycle. The projected continuous PM data will prove valuable in future mobile source inventory prediction.     

A Chassis Test Procedure to Mimic the Heavy-Duty Engine Transient Emissions Certification Test

ABSTRACT

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     

The relationship between atmospheric pollutant emissions and fuel qualities of inland vessels in Jiangsu Province,China

Air pollution caused by ship exhaust emission is receiving more and more attention. The physical and chemical properties of fuels, such as sulfur content and PAHs content, potentially had a significant influence on air pollutant emissions from inland vessels. In order to investigate the effects of fuel qualities on atmospheric pollutant emissions systematically, a series of experiments was conducted based on the method of actual ship testing. As a result, SO2, PM and NOx emission rates all increased with the increase of main engine rotating speed under cruise mode, while PM and NOx emission factors were inversely proportional to the main engine rotating speed. Moreover, SO2 emission factor changed little with the increase of the main engine rotating speed. In summary, the fuel-dependent specific emission of SO2 was a direct reflection of the sulfur content in fuel. The PM emission increased with the increase of sulfur content and PAHs content in fuel. However, fuel qualities impacted little on NOx emissions from inland vessels because of NOx formation mechanisms and conditions.

Implications: Ship activity is considered to be the third largest source of air pollution in China. In particular, air pollutants emitted from ships in river ports and waterways have a direct impact on regional air quality and pose threat on the health of local residents owing to high pollutants concentration and poor air diffusion. The study on the relationship between air pollutant emissions and fuel quality of inland vessels can provide foundational data for local authority to formulate reasonable and appropriate policies for reducing atmospheric pollution due to inland vessels.     

Comparison of on-road emissions for B-0, B-10, and B-20 in transit buses

Biodiesels are often marketed as being cleaner than regular diesel for emissions. Emission test results depend on the biodiesel blend, but laboratory tests suggest that biodiesels decrease particulate matter, carbon monoxide, hydrocarbons, and air toxins when compared to regular diesel. Results for the amount of oxides of nitrogen (NOx) have been less conclusive. Tests have also not evaluated the commonly available ranges of biodiesel blends in the laboratory. Additionally, little information is available from on-road studies, so the effectiveness of using biodiesels to reduce actual emissions is unknown. A more complex relationship exists between engine operation and the rate of emission production than is typically evaluated using engine or chassis dynamometer tests. On-road emissions can vary dramatically because emissions are correlated to engine mode. Additionally, activity such as idling, acceleration, deceleration, and operation against a grade can produce higher emissions than more stable engine operating modes. Because these modes are not well captured in a laboratory environment, understanding on-road relationships is critical in evaluating the emissions reductions that may be possible with biodiesels. More tests and quantifications of the effects of different blends on engine and vehicle performance are required to promote widespread use of biodiesel. The objective of this research was to conduct on-road tests to compare the emission impacts of different blends of biodiesel to regular diesel fuel under different operating conditions. The team conducted on-road tests that utilized a portable emissions monitoring system that was used to instrument transit buses. Regular diesel and different blends of biodiesel were evaluated during on-road engine operation by instrumenting three in-use transit buses, from the CyRide system of Ames, Iowa, along an existing transit route.     

A Fuel-Based Motor Vehicle Emission Inventory

Abstract

A fuel-based methodology for calculating motor vehicle emission inventories is presented. In the fuel-based method, emission factors are normalized to fuel consumption and expressed as grams of pollutant emitted per gallon of gasoline burned. Fleet-average emission factors are calculated from the measured on-road emissions of a large, random sample of vehicles. Gasoline use is known at the state level from sales tax data, and may be disaggregated to individual air basins. A fuel-based motor vehicle CO inventory was calculated for the South Coast Air Basin in California for summer 1991. Emission factors were calculated from remote sensing measurements of more than 70,000 in-use vehicles. Stabilized exhaust emissions of CO were estimated to be 4400 tons/day for cars and 1500 tons/day for light-duty and medium- duty trucks, with an estimated uncertainty of ±20% for cars and ±30% for trucks. Total motor vehicle CO emissions, including incremental start emissions and emissions from heavy-duty vehicles were estimated to be 7900 tons/day. Fuelbased inventory estimates were greater than those of California's MVEI 7F model by factors of 2.2 for cars and 2.6 for trucks. A draft version of California's MVEI 7G model, which includes increased contributions from high-emitting vehicles and off-cycle emissions, predicted CO emissions which closely matched the fuel-based inventory. An analysis of CO mass emissions as a function of vehicle age revealed that cars and trucks which were ten or more years old were responsible for 58% of stabilized exhaust CO emissions from all cars and trucks.