Emissions Measurement
A report for the
National ITS Implementation Center
Authors:
Hesham Rakha
Charles Via Jr. Department of Civil and Environmental Engineering, Virginia Tech
3500 Transportation Research Plaza (0536)
Blacksburg, VA 24061
Phone: (540)
231-1505
Fax: (540)
231-1555
E-mail: hrakha@vt.edu
Sangjun Park
Charles Via Jr. Department of Civil and Environmental Engineering, Virginia Tech
3500 Transportation Research Plaza (0536)
Blacksburg, VA 24061
Phone: (540)
231-1505
Fax: (540)
231-1555
E-mail: sangjun@vt.edu
Linsey C. Marr
Charles Via Jr. Department of Civil and Environmental
Engineering, Virginia Tech
411 Durham Hall
Blacksburg, VA 24061
Phone: (540) 231-6071
E-mail: lmarr@vt.edu
Richard Olin
Virginia Department of
Environmental Quality, Richmond, VA 23240
Phone: (804) 698-4425
E-mail: rdolin@deq.virginia.gov
summary
Remote Sensing Devices (RSDs) are used as supplementary tools to identify high emitting vehicles (HEVs) in order to help achieve the U.S. National Ambient Air Quality Standards (NAAQS). Accordingly, we conduct two studies to enhance the procedures of HEVs detection using RSDs.
First, the
conversion of volumetric concentration to mass emissions is studied. Tailpipe emissions in grams cannot be directly measured using remote
sensing (RS) systems because they utilize a concentration-based technique. Consequently,
converting emission measurements from concentration to mass emissions is
needed. The study combines the carbon balance equation with fuel consumption estimates
to make this conversion. In estimating vehicle fuel consumption rates, the
VT-Micro model and a Vehicle Specific Power (VSP)-based model (the PERE model)
are considered and compared. The results of the comparison demonstrate that
both of the VT-Micro and PERE models provide reliable fuel consumption estimates
(R2 of 90% and higher for a 1993 Honda Accord with a 2.4L engine). The study clearly demonstrates
that the proposed procedure works well in converting concentration measurements
to mass emissions and can be applicable in the screening of HEVs and normal
emitting vehicles for several vehicle types such as sedans, station
wagons, full-size vans, mini vans, pickup trucks, and SUVs.
Second, remote sensing cut points that are sensitive to engine load conditions is proposed to enhance the HEV screening procedures using RSDs. Emission compliance is determined by comparing the concentration of pollutants measured by an RSD to on-road remote sensing (RS) emission standards. The literature shows that the current RS emission standards are insensitive to vehicle speed and acceleration levels even though vehicle emissions are highly affected by the engine load. Consequently, the study firstly demonstrates variability of vehicle exhaust emissions to motivate this study and proposes a procedure for constructing on-road remote sensing emission standards that are sensitive to vehicle speed and acceleration levels. Given the proposed remote sensing cut points, a comparison to the existing cut points is presented as well as sample tests using the proposed cut points. The results of the sample tests demonstrate that the approach is effective for HE (high-emitting) 3 and 4 vehicles of the VT-Micro emission models and require further enhancements for HE1 and 2 vehicles.
This report consists of two separate papers which follow.
SOLUTIONS FOR ENHANCING REMOTE SENSING HIGH
EMITTER VEHICLE SCREENING PROCEDURES
INTRODUCTION
To reduce air pollutant emissions to meet the National Ambient Air Quality Standards (NAAQS), many state environmental agencies are focusing their efforts on identifying high emitting vehicles (HEVs). HEVs are vehicles whose emissions of hydrocarbons (HCs), nitrogen oxides (NOx) are two and/or carbon monoxide (CO) are three times higher than the certification emissions level for the vehicle (EPA, 1999). Although HEVs comprise only a small fraction of the vehicle fleet, they contribute to a large fraction of total emissions. For example, one study found that 7.8 percent of the fleet is responsible for 50 percent of the total emissions based on a gram of CO per gallon of fuel burned (Lawson et al. 1990). Another study found that 5 percent of the vehicles emitted 80 percent of the emissions (Wolf et al. 1998).
Many of the states in the U.S. operate their own Inspection and Maintenance (I/M) Program, in order to identify and repair HEVs. In addition, other supplementary devices, such as RSDs (remote sensing devices), are used to identify HEVs. Several states are now using RSDs because they can collect on-road emission data from the in-use vehicle fleet. In contrast to some I/M tests that quantify emissions on a mass per time basis over a driving cycle that can last up to four minutes, RSDs report mole fractions, or concentrations, of pollutants in exhaust at a single point in time. The advantage of RSDs is that they are able to capture site-specific measurements under real-world conditions as vehicles are driven on-road. However, several issues remain in screening HEVs and normal emitting vehicles using RSDs, including converting from concentrations to mass emission rates and setting RSD-based standards to identify HEVs.
The objectives of this paper are to validate the use of RSD measurements to predict mass emission rates, to compare and contrast different methods for estimating fuel consumption rates, and to evaluate the accuracy with which RSDs can be used to screen HEVs using the proposed methods.
In terms of the paper layout, the paper first presents the validation of the procedure developed to estimate mass emissions. Secondly, the Physical Emission Rate Estimator (PERE) model that is based on vehicle specific power (VSP) and the VT-Micro model are compared, because these models can be used to estimate fuel consumption rates. The following section presents the mass emission estimations and a comparison of the emission estimates against field measurements. Finally, the conclusions of the study and recommendations for further research are presented.
VALIDATION
OF MASS EMISSION PROCEDURE
Conversion of Concentration
Measurements to Mass Emissions
Measurements of vehicle exhaust emissions are very important because they are used in many air-quality improvement activities such as I/M programs and the development of emission models and inventories. In practice, two test methods are widely used in quantifying vehicle exhaust emissions: mass emission tests and concentration tests. Mass emission tests directly measure the mass of several pollutants emitted from a vehicle running a simulated driving cycle. In these tests, exhaust emissions are measured in units of grams per unit time or grams per unit distance. A group of tests that are named based on the underlying drive cycle fall into this category. The Federal Test Procedure (FTP) is used to certify new vehicle emissions. Other tests used by state I/M programs include the IM240, BAR31, IM93 (CT93), and IM147 (NRC 2001).
Concentration tests measure the pollutants in vehicle exhaust emissions and report results in units of percentage or parts per million (PPM) of total exhaust volume. Idle and ASM tests fall into this category and are used in I/M programs in several states. Additionally, RSDs measure the concentrations of emissions from on-road vehicles. RSDs are considered a supplemental tool for I/M programs, due to their ability to capture on-road emissions. Consequently, several states in the U.S. are trying to improve their I/M programs using RSDs. However, in order to estimate the mass emissions per unit of time, a relationship between concentrations and mass emission rates needs to be developed.
The literature describes two approaches for developing conversion equations. The first approach is based on regression models. One thing should be addressed is that the regression models require to use of both concentration and mass emission measurements of a sample of vehicles to develop coefficients. For instance, Austin et al. (1989) proposed a new emission test procedure, the Acceleration Simulation Mode (ASM) test, that can correctly and economically identify 90% of vehicles that emit excessive nitrogen oxide (NOx) emissions for I/M programs. In the study, they concluded that the ASM 5015 test is best for identifying high NOX emitting vehicles and the 2500 rpm test could most correctly identify high CO and/or HC emitting vehicles. In addition, formulae were developed for the estimation of carbon monoxide (CO), hydrocarbon (HC), and nitrogen dioxide (NO2) emissions using regression methods. In estimating CO and HC mass emissions, the concentration of CO and HC emissions are measured from the 2500 rpm test based on the engine size and used as the regressors for CO and HC mass emissions. Engine displacement is also used as a regressor for CO and HC mass emissions. On the other hand, the NOX mass emissions are regressed from the concentration of NOX emissions measured by the ASM 5015 test and the emission test weight (vehicle weight plus 300 lbs for light duty vehicles) rather than the engine size.
DeFries et al. (2002) constructed models for simulating
Virginia IM240 emissions from concentration measurements taken from ASM 5015
and ASM 2525 test procedures, because Virginia must report emission reductions
in terms of mass emissions to the EPA. In this study, a dataset of 1702 paired
ASM and IM240 emissions were utilized for the modeling purpose. The models for the conversion
were constructed by utilizing full ASM tests, not “fast pass” ASM tests. First,
raw emission concentration measurements are corrected for dilution and humidity
effects. Using the corrected measurements, the intermediate predictor
variables, HC, CO, and NOX terms, are computed for the input
variables. Finally, the IM240 mass emissions are regressed from HC, CO, and NOX
terms, vehicle engine displacement, vehicle age, vehicle type, and a carbureted-or-fuel
injected flag. Specifically, the HC term, NOX term, engine
displacement, and vehicle age are used as regressors for IM240 HC emissions.
The model for IM240 CO emissions includes the CO term, engine displacement, and
vehicle age as the input variables. Lastly, the model for IM240 NOX
emissions utilizes the HC term, CO term, NOX term, engine
displacement, vehicle age, vehicle type, and carbureted-or-fuel injected engine.
The second approach for developing conversion equations is to use carbon balance for converting concentrations to mass emission rates per unit of fuel burned (NRC 2001). For example, Stedman, developer of the FEAT system (an RSD for on-road vehicle emissions), and his colleagues derived the equations for the conversions. Initially, they developed only one equation for CO emissions. This equation was then extended to HC and NOx emissions when the RSD system was updated to measure these pollutants (Bishop et al. 2003). In addition, Singer and Harley (1996) proposed a fuel-based methodology for computing motor vehicle emission inventories. In this study, the inventory was estimated as the product of mass-based emission factors with fuel consumption rates. In the process of calculating emission factors, the concentrations of on-road vehicle emissions are converted into mass emissions in units of grams of emissions per fuel consumed. Since the equation that they used is also based on carbon balance, it has the same structure as the equations that Stedman used. Specifically, mass emissions per fuel burned are computed by multiplying the number of moles of HC, CO, NOX emissions per fuel burned and the molecular weight of HC, CO, and NOX. In order to compute the number of moles for pollutant, the ratio of pollutant to the sum of CO2, CO, and HC is multiplied by the number of moles of carbon per fuel burned.
Data Description
The study utilizes a dataset of second-by-second IM240 emission measurements that were taken by TESTCOM since a comparison between measured emission rates and estimated emission rates can be done easily for validating a proposed procedure and for testing its effectiveness. The measurements were taken between September 2001 and April 2002. The vehicle model years ranged from 1981 to 2001, and body types included sedans, station wagons, full size vans, mini vans, pickup trucks, and sport utility vehicles.
A second-by-second IM240 emission test reports the vehicle’s
speed profile, HC, CO, and NOx emission rates as a function of time,
as illustrated in Figure 1.
The tested vehicle in Figure 1
is a 1993 Honda Accord with a 2.4L engine.
Validation Procedure
The mass emission equations that are presented in the literature were validated by first applying them to calculate pollutant concentrations from mass emission rates measured during a sample IM240 test run. The calculated concentrations were then used together with fuel properties and the rate of fuel consumption to predict mass emission rates. The fuel consumption rate was computed using the carbon balance equation, and exhaust concentrations were estimated from the mass emissions using the combustion equation. Finally, predicted mass emission rates were compared to the original mass emission rates.
All the carbon enters the engine as fuel leaves in the form of HC (g/s), CO (g/s), CO2 (g/s), and a typically negligible amount of particulate matter that will be ignored here. Given that the molecular weight of carbon and oxygen are 12 and 16 g/mole, respectively, the molecular weight of CO2 can be calculated to be 44 g/mole (12+16x2). Therefore, CO2 contains 27.3 percent (12/44) carbon. Similarly, the molecular weight of CO is 28 g/mole (12+16) yielding 42.9 percent carbon in CO. Also, according to the Code of Federal Regulations Title 40 Part 86 (40 CFR 86), HC emissions from a gasoline powered vehicle contain 86.6 percent carbon by weight. Consequently, the instantaneous carbon emission rate in units of g/s can computed as
.
Recognizing that average gasoline sold in the US contains 86.4 percent of carbon, and has a density of 738.8 g/L (or 2800 g/gallon), there are 638.31 (0.864×738.8) grams of carbon in a liter of gasoline. Consequently, the fuel consumption rate (L/s) can be computed as
.
Using the mass emissions of HC, CO, NOx, and CO2 available from IM240 test runs, the emission concentrations were computed by first estimating the mass emissions of N2 through the use of the combustion equation, which can be cast as
,
where CH1.9 represents gasoline; O2 + 3.76 N2 represents air composed of 21% O2 and 79% N2 (with argon and other non-oxygen components lumped with N2); combustion is assumed to be complete with an equivalence ratio of one; and formation of minor species such as NO and CO can be neglected relative to the amount of major species such as N2 and CO2 emitted in the exhaust.
Consequently, the mass ratio of N2 to CO2 can be computed as
.
The N2 emissions in g/s are then computed as
.
The volumetric concentrations of HC, CO, NOx, and CO2 can be computed as
,
,
, and
.