Levels of transportation and emission modelling

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Levels of transportation and emission modelling
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Emission factor models for regional emissions

• MOBILE was developed for calculating regional
  emissions inventories using aggregated vehicle
  emissions data and estimates of vehicle activity
  in the form of VMT and average speed. Because of
  the inherent "averaging" that takes place in
  MOBILE, it is not suitable for evaluating traffic
  operational improvements that affect traffic and
  driving dynamics. For example, operational
  improvements that improve traffic flow (e.g.,
  ramp metering, signal coordination, and automated
  highway systems) cannot be evaluated accurately
  with an aggregated model such as MOBILE.

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Emission factor models for regional emissions

• The problem is that MOBILE uses average speed as
  the only variable for representing driving
  dynamics. Vehicle emissions are strongly coupled
  with driving dynamics, and average speed often
  does not properly characterize these dynamics. A
  large number of different driving patterns can
  have approximately the same average speed, but
  might have totally different driving dynamics and
  thus drastically different emissions responses.

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Modal Emission Models

• To better capture emissions effects associated
  with a wide range of driving dynamics,
  researchers have investigated at a more
  fundamental level the modal operation of a
  vehicle and related emissions directly to vehicle
  operating modes such as idle, steady-state
  cruise, and levels of acceleration and
  deceleration. Models that can predict emissions
  based on these vehicle-operating modes are often
  referred to as modal emissions models. The terms
  modal, instantaneous, and continuous are often
  used as synonyms when referring to this detailed
  microscale emissions modeling.

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Modal Emission Models

• MOBILE is based on emissions testing in which a
  single average emissions value is determined for
  a particular driving cycle. In contrast, modal or
  instantaneous emissions data collection consists
  of measuring emissions continuously during the
  chassis dynamometer tests and recording these
  data at a particular time interval, usually every
  second. Vehicle operational data are also
  recorded, such as the instantaneous vehicle speed
  and acceleration rate.

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Basic principles
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Basic ideas in a physically based modal emission
model
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CMEM Comprehensive Modal Emissions Model College
of Engineering-Center for Environmental Research
and Technology (CECERT) University of
California-Riverside, University of Michigan,
Lawrence Berkeley National Laboratory

• Objective to develop and verify a modal
  emissions model that accurately reflects
  Light-Duty Vehicle emissions produced as a
  function of the vehicles operating mode.
• Comprehensive
• able to predict emissions for a wide variety of
  LDVs in various states of condition (e.g.,
  properly functioning, deteriorated,
  malfunctioning).
• capable of predicting second-by-second tailpipe
  emissions and fuel consumption for a wide range
  of vehicle/technology categories.

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CMEM

• A modal emission model using a physical
  load-based approach.
• Collect second-by-second emissions data from a
  sample of vehicles to build a model that predicts
  emissions for the national fleet which is
  represented by 26 categories
• The choice of vehicles for this sample is
  crucial, since only a small sample (approximately
  340 vehicles) was used as the basis for the
  model.

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CMEM Model Structure

• The main purpose is to predict vehicle tailpipe
  emissions associated with different modes of
  vehicle operation, such as idle, cruise,
  acceleration, and deceleration.
• These modes may be very short (i.e., a few
  seconds) or may last for many seconds.
• Moreover, the model must deal with operating
  conditions like cold start, warm start
  moderate-power driving (i.e. FTP) off-cycle
  driving (enrichment and enleanment events).

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CMEM Model Structure

• FR Fuel use rate, g/s
• ( gemission/gfuel) engine out emission index
• CPF catalyst pass fraction

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CMEM Model Parameters

• Dynamic operating variables as input.
• second-by-second speed (from which acceleration
  can be derived acceleration can also be input as
  a separate input variable )
• grade
• accessory use (such as air conditioning).
• In many cases, grade and accessory use may be
  specified as static inputs or parameters.

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CMEM Model Parameters

• Static parameters
• 13 Readily Available Parameters
• 42 Calibrated Parameters.
• The Readily Available Parameters represent model
  input parameters which can be either obtained
  externally from public sources (e.g., sources of
  automotive statistics, datasets compiled by EPA,
  etc.), and are further divided into specific
  vehicle parameters and generic vehicle
  parameters. The generic vehicle parameters are
  ones that may not necessarily be specified on a
  vehicle-by-vehicle basis, but are rather
  specified generically for entire vehicle classes.

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CMEM Model Parameters

• The Calibrated Parameters cannot be directly
  obtained from publicly available sources rather
  they are deduced (i.e., calibrated) from the
  testing measurement data.
• The Calibration Parameters are determined using
  the measured emissions results for each test
• 1) directly from measurements
• 2) based on several regression equations or
• 3) based on an optimization process.

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parameters determined directly from the
dynamometer emission measurements

• maximum hot-stabilized catalyst efficiencies for
  CO, HC, and NOx emissions
• maximum fuel/air equivalence ratio
• maximum lean HC emission rate during long
  deceleration events
• maximum lean HC emission rate during transient
  events
• minimum fuel/air equivalence ratio during
  enleanment operation
• ratio of oxygen and engine-out HC emissions
  during enleanment operation and
• maximum cold-start fuel/air equivalence ratio

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CMEM -Vehicle Testing Issues

• Defining the 26 vehicle/technology categories
  that make up the modal emissions model.
• 2) Using the vehicle/technology categories for
  guidance, determining a vehicle recruitment
  strategy and
• 3) Developing a dynamometer test procedure for
  the measurement of modal emissions.

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Defining the 26 vehicle/technology categories

• vehicle/technology categories chosen based on a
  vehicles emissions contribution, as opposed to a
  vehicles actual population in the national
  fleet.
• more emphasis is put on high emitters than if
  based strictly on population numbers.
• these are NOT the same as the vehicle categories
  in MOBILE6 and are NOT IDENTICAL to the
  regulatory classification

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• Category Vehicle Technology Category
• Normal Emitting Cars
• 1 No Catalyst
• 2 2-way Catalyst
• 3 3-way Catalyst, Carbureted
• 4 3-way Catalyst, FI, gt50K miles, low
  power/weight
• 5 3-way Catalyst, FI, gt50K miles, high
  power/weight
• 6 3-way Catalyst, FI, lt50K miles, low
  power/weight
• 7 3-way Catalyst, FI, lt50K miles, high
  power/weight
• 8 Tier 1, gt50K miles, low power/weight
• 9 Tier 1, gt50K miles, high power/weight
• 10 Tier 1, lt50K miles, low power/weight
• 11 Tier 1, lt50K miles, high power/weight
• 24 Tier 1, gt100K miles

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Normal Emitting Trucks 12 Pre-1979 (lt8500
GVW) 13 1979 to 1983 (lt8500 GVW) 14 1984 to 1987
(lt8500 GVW) 15 1988 to 1993, lt3750 LVW 16 1988
to 1993, gt3750 LVW 17 Tier 1 LDT2/3 (3751-5750
LVW or Alt. LVW) 18 Tier 1 LDT4 (6001-8500 GVW,
gt5750 Alt. LVW) 25 Gasoline-powered, LDT (gt 8500
GVW) 40 Diesel-powered, LDT (gt 8500 GVW)
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High Emitting Vehicles 19 Runs lean 20 Runs
rich 21 Misfire 22 Bad catalyst 23 Runs very rich
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vehicle recruitment strategy

• 415 Vehicles were recruited throughout
  Californias South Coast Air Basin, with a small
  subset brought in from other states. 89 did not
  pass the
• initial safety inspection and were rejected.
• There are differences between California and
  49-state certification levels for many of the
  vehicle/technology groups. Approximately 12 of
  all vehicles tested (18 in categories where
  differences exist) were 49-state vehicles.
• To prevent bias and to ensure the broad
  applicability of the testing results, to the best
  extent possible, vehicles were sampled randomly
  within each vehicle/technology category

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CMEM -High-Emitter Vehicle Identification

• Remote Sensing
• Using a remote sensing van, a set of remote
  sensing measurements were made in the local area.
  Vehicles that had multiple high measurements were
  identified by license plate. The license plate
  data were then matched up with the DMV database
  in order to get the make and model of vehicle, as
  well as the address of the owner. Solicitation
  letters were then sent out to
• those targeted owners.

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CMEM -High-Emitter Vehicle Identification

• Local Car Dealers
• Several local car dealerships in the area were
  asked to inform customers who bring their
  vehicles in for emissions-related repairs about
  our study. Prior to having their vehicle fixed by
  the dealer, some vehicles were recruited for
  testing. It was hoped that this source would
  provide us with some newer model year vehicles
  with high emissions however only limited success
  was achieved.

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CMEM -High-Emitter Vehicle Identification

• Local Rental Agencies and Used Car Dealers
• Local car rental agencies and used car dealers
  were also contacted to identify high mileage
  vehicles. Candidate vehicles were brought to the
  testing site and driven past a remote sensing
  van. Vehicles that had multiple high remote
  sensing readings were selected for testing.

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CMEM -High-Emitter Vehicle Identification

• High Emitter List
• Using the Arizona I/M database of vehicle models
  with high average failure rates, a subset of the
  local DMV database of potential high emitting
  vehicle models was produced. Specific vehicles
  were then selected randomly from this list.
  Solicitation letters were sent out to the vehicle
  owners requesting their participation in the
  study. The owners would bring their vehicles to
  the testing site, where they were driven past the
  remote sensing van. If they had consistently high
  emissions, they were selected for testing.

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CMEM - dynamometer test procedure

• Second-by-second pre- and post-catalyst
  measurements of CO2, CO, HC, and NOx over three
  separate driving cycles
• 1) A complete 3-bag FTP test
• 2) A high speed cycle (US06)
• 3) A modal emission cycle (MEC01) developed by
  the research team.

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Speed fluctuation events
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Specific power and emissions

• Specific power (SP) is approximated as two times
  the product of velocity (v) and acceleration (a)
• SP 2 v a.
• v mph,
• a mph/s,
• SP (mph)2/s.
• five constant specific-power sub-cycles, (SP)
  150 - 400 (mph)2/s.

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MEC01 - Constant Power Section

• Specific power measures kinetic energy used
  during a driving episode.
• FTP maximum SP 192 (mph)2/s
• US06 maximum SP 480 (mph)2/s
• During high power episodes, the kinetic power
  required to overcome vehicle inertia typically
  dominates the total power requirements. Thus
  during high power operation, a constant specific
  power approximately represents constant total
  power.
• SP levels from 200 to 300 (mph)2/s represent
  moderately high power driving
• a level of 150 is within the power range of the
  FTP
• a level of 400 requires wide-open-throttle (WOT)
  operation in most vehicles.
• High values of SP cause fuel enrichment and
  increase of emissions, the power enrichment
  threshold, will be different for different
  vehicles and classes.

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Air Conditioning effects and repeatability

• The stoichiometric cruise section is repeated in
  the cycle, this time with the air conditioner on
  if the vehicle is so equipped.
• Air conditioning usage can have a drastic effect
  on emission rates this section of the cycle
  allows direct comparison with the initial
  steady-state cruise section.
• In order to determine emissions variance for each
  vehicle within a single test, the stoichiometric
  cruise section is again repeated, this time with
  the air conditioning turned off.
• This repeat hill allows comparison of the modal
  events within the hill or the composite emissions
  for both hills.

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Measured, g Modeled, g difference
mph
g/s
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VEHICLE COMPOSITING

• Each vehicle tested with sufficient and
  acceptable data can be modeled, using the
  calibration process.
• However, the primary modeling goal is to predict
  detailed emissions for each average, composite
  vehicle that represents the 26 vehicle/technology
  categories listed
• A compositing procedure has been developed to
  construct a composite vehicle to represent each
  of the 26 different vehicle/technology modeled
  categories.

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MOVES (Motor Vehicle Emissions Simulator)

• EPAs next generation motor vehicle emission
  model
• Based on modal emissions
• Attemps to unify emission modelling and analysis
  across multiple-scales (regional to local and
  instantaneous) and sectors (on-road, non-road)
• Uses VSP and speed bins to quantify modal
  emissions from particular source bins

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• Macroscale analyses are appropriate for
  developing large-scale (e.g. national)
  Inventories. The basic spatial unit for this
  scale would be the county. Consistent in concept
  with the current applications of MOBILE (with
  inventory generation capability) and NONROAD.
• Mesoscale analyses are geared towards generating
  local inventories at a finer level of spatial and
  temporal resolution. The basic spatial unit for
  this scale would be the roadway link and traffic
  analysis zone, consistent with output from
  standard travel demand models.
• Microscale analyses allow the estimation of
  emissions for specific corridors and/or
  intersections, which is appropriate for assessing
  the impact of transportation scenarios and
  performing project-level analyses.

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