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CARB Freight Efficiency Program Although the primary goal of IFTA is to correctly distrib-
ute tax revenue, the reports collected by the association con-
In 2006, California enacted ambitious statewide greenhouse
tain a wealth of information about truck activity, geographic
gas reduction goals, aiming to reduce state GHG emissions to
distribution, and fuel consumption. Although these data are
1990 levels by 2020, and 80% below 1990 levels by 2050. In
only collected for trucks involved in freight movement across
response to these targets, CARB enacted a detailed scoping plan
the U.S.Canadian border, they could be extrapolated to rep-
that determined the share of GHG reductions by sector and
resent the entire trucking industry. However, the information
source, as well as mitigation programs to be used to reach each
stored by IFTA is currently unavailable to freight researchers
goal. To reduce freight emissions, CARB is implementing a
and practitioners.
Freight Transport Efficiency Measure to increase the fuel econ-
omy and decrease the carbon footprint of freight modes. The
goal of this measure is to reduce CO2 emissions by 3.5 million 4.3 Model Scope and Structure
metric tons (equivalent) by 2020. (191)
This section describes the scope and structure of a variety of
The CARB Freight Efficiency Program is patterned after
Conceptual Model components. The discussion starts with a
EPA's SmartWay Program, and is intended to reduce fuel
economy by introducing system and technology improvement description of the target audience, whose needs drive the
across modes. The program has identified several near-term development of five applications (global/national, freight cor-
opportunities for reducing fuel consumption, including vessel ridor, metropolitan, facility, and supply chain) and functional
speed reduction; on-road and nonroad anti-idling, transport areas. Business processes fulfill the requirements of the func-
refrigeration unit programs, and freight truck efficiency initia- tional areas, and the process flows describe information flows
tives. As of September 2009, CARB is working with industry between processes.
stakeholders to craft an implementation plan for the Freight
Efficiency Program. 4.3.1 Target Audience
The Conceptual Model targets four types of stakeholders,
NCFRP 12: Specifications for Freight Transportation each with different needs: the private industry (shippers, carri-
Data Architecture ers, and logistics providers), environmental regulatory agen-
The goal of NCFRP Project 12 (192) is to develop a structure cies, transportation agencies, and environmental organizations
for storing freight data from existing data sets and new data (Exhibit 4-3).
collections. Prior studies by TRB and the Cooperative Research
Programs have identified challenges in applying freight data Private Industry
stored in disparate forms by several agencies, and the opportu-
nities to improve freight analysis by uniting these data sources. The private freight transportation industry consists of man-
The desired outcome of NCFRP 12 is to create a unified data ufacturers, carriers, and logistics providers, as well as others
architecture and evaluate the costs and benefits of implement- responsible for the storage and distribution of parts and fin-
ing the structure in industry. The results of this project will ished products. The private industry's modus operandi has
complement the results of the NCFRP 12 report, and inform been to provide the right product at the right place at the right
decisions about optimal storage methods for data sources iden- time at the lowest possible cost. Typically, consideration of
tified here. environmental criteria has been related to compliance costs. In
recent years, however, many firms have started to address envi-
ronmental considerations to capture and keep new markets
International Fuel Tax Agreement
that are environmentally conscious, to fulfill the needs of cor-
The International Fuel Tax Agreement (IFTA) is an agree- porate social responsibility requirements, and to address con-
ment between the continental U.S. states and Canadian cerns of potential new regulations. Additionally, firms have
provinces to measure cross-border truck activity and appor- realized that GHG emission reductions are often associated
tion fuel tax revenues to the appropriate jurisdiction. Under with cost reductions (because of the direct correlation between
this agreement, implemented by the International Fuel Tax CO2 emissions and energy consumption), so they can develop
Association (also referred to as IFTA) truckers submit quar- leaner and more cost-effective supply chains while promoting
terly fuel tax reports, in which operators report the miles environmental stewardship.
driven and fuel consumed in each state and province. These Private firms will use the model to understand how choices
data are used to correctly apportion fuel tax revenue to each in terms of supply chain design, facility location, mode choice,
jurisdiction and to determine if operators are due a fuel tax route choice, inventory levels, packaging, and delivery patterns
surcharge or refund. affect the environmental performance of their supply chains.
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Exhibit 4-3. Stakeholders.
Private Industry Environmental Regulatory
(shippers/carriers) Agencies (EPA/ARB) & Air
Evaluate environmental performance of supply Quality Districts
chains
Evaluate environmental implications of
regulations/voluntary programs
Conceptual
Model
Environmental State/Local
Organizations Transportation Agencies
Evaluate health effects of freight system Evaluate environmental performance of
transportation corridors and facilities
They could also compare their operation's performance against of human exposure at various concentration thresholds, which
best-in-class performance through a benchmarking analysis. is combined with results from epidemiological studies in the
decision to modify the NAAQS.
EPA also compiles nationwide GHG emissions in the official
Environmental Regulatory Agencies
EPA GHG Inventory. (1) This national GHG inventory pro-
Public agencies responsible for environmental regulations vides a common and consistent mechanism for all nations to
include U.S. state and local environmental regulatory agen- estimate emissions and compare the relative contribution of
cies. Freight transportation emissions estimates can be pre- individual sources, gases, and nations to climate change. Com-
pared in response to federal or state regulations. These include plementary studies to the GHG inventory influence federal pro-
the National Environmental Policy Act (NEPA) and similar grams that, in turn, leverage programs targeting the freight
state laws, the Clean Air Act, and federal conformity regula- sector (e.g., EPA's SmartWay program).
tions. In other cases, freight emissions estimates are used in
non-mandatory studies that serve to educate stakeholders and
Transportation Agencies
guide government programs or policy. At the federal level,
EPA is responsible for setting criteria pollutant emission and Transportation agencies include metropolitan planning
ambient air quality standards. Most states follow these guide- organizations (MPOs), as well as state and federal DOTs. Trans-
lines, although others set their own standards (notably, Cali- portation agencies have a key role in influencing transportation
fornia via the California Air Resources Board). Air quality emissions. Transportation infrastructure investment can result
districts set local/regional policy to meet federal and state air in traffic flow improvements (that typically reduce emissions),
quality guidelines. In many applications, freight emissions are as well as in mode shifts due to capacity improvements in cer-
combined with emissions from other mobile and local sources tain modes. Transportation agencies also can enact finance
to identify the net impact on local populations and, in the case mechanisms such as taxes, fees, and tolls that can have a direct
of nonattainment areas, plan progress toward meeting air influence on freight transportation behavior through policies
quality standards. and transportation infrastructure investments.
Environmental regulatory agencies also sponsor studies of Transportation agencies will be interested in analyzing the
public health effects of air pollution, and many of these studies environmental performance of different transportation corri-
begin with estimates of emissions, including freight emissions. dors to inform infrastructure investment decisions. The Con-
For example, the National Air Toxics Assessment (NATA) pro- ceptual Model provides a framework to analyze freight activity
duces screening-level estimates of cancer and non-cancer health and emissions along potential goods movement corridors.
effects of air toxics by census tract for the entire United States.
Additionally, under the Clean Air Act, EPA is required to peri-
Environmental Organizations
odically review the National Ambient Air Quality Standards
(NAAQS) and, if warranted, modify them to protect public Environmental organizations include those groups inter-
health and welfare. This review typically includes an assessment ested in public health and environmental justice. These groups
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examine transportation decisions from a health impact per- natively, fuel consumption data can be used to estimate freight
spective and environmental justice framework. They tend to emissions of particular pollutants (especially GHGs) if there is
make sure existing environmental laws are upheld when a reasonable way to allocate them to freight sources. Outputs
new transportation investments are made so that public from this application include freight emissions associated with
health is not adversely impacted or toxic hot spots are not particular modes on a large geographic scale.
created. As such, these groups might use the model to deter- In instances where this application is intended to provide the
mine the incremental emissions impact of a new transporta- necessary inputs for air quality models, the spatial and tempo-
tion project. ral allocation of emissions also will be required to properly
characterize emissions released to the atmosphere.
4.3.2 Model Applications
Freight Corridor
Depending on the analysis objectives and available input
parameters, the Conceptual Model allows emissions estima- This application calculates freight emissions from a trans-
tion for five different categories of analysis. Four of these are portation corridor, which could fall within a single state or
geographic scales and one describes a business enterprise per- across multiple state boundaries. Objectives of this application
spective, as shown in Exhibit 4-4. include the following:
· Analyze current environmental performance of freight
Global/National
corridors;
The objective of this application is to calculate freight · Analyze how future capacity improvements could affect
emissions inventories associated with large geographic areas, environmental performance of a corridor (this could
typically at the state, national, or global level. Because this include environmental improvements from congestion
application considers all transportation facilities where freight relief, as well as from mode shift due to investments in a
moves or is transloaded, all freight modes are included. The given mode);
main users for this application will be government agencies · Identify corridors that are particularly energy efficient
aiming to estimate and track freight emissions over time, as (possibly for benchmarking purposes, or as candidates for
well as to compare the environmental performance of freight further investment) or inefficient (as candidates for future
systems in different geographic regions. improvements);
The model input will be generators of freight activity (i.e., · Compare environmental performance of different corridors
commodity flows) from which vehicle activity can be esti- in order to understand the correlations between corridor
mated, or direct vehicle or freight activity if statistics of capacity, commodity mix, mode share, and environmental
vehicle-miles traveled or freight ton-miles are available. Alter- performance;
Exhibit 4-4. Types of model applications.
Type of Analysis Objective Modes Audience
Global/National Calculate freight emissions All Environmental Regulatory
inventories associated with Agencies
large geographic areas.
Freight Corridor Calculate freight emissions Typically truck Transportation Agencies
associated with a specific and rail Private Industry
corridor.
State/Local Environmental
Agencies
Metropolitan Calculate freight emissions Typically truck Transportation Agencies
inventories within a only, but other Air Quality Districts
metropolitan area. modes can be
included
Facility Calculate emissions from Varies, Air Quality Districts
freight activity at a specific depending on Private Industry
facility (truck terminal, the facility
Environmental
railyard, port, and airport).
Organizations
Supply Chain Calculate freight emissions Varies, Private Industry
associated with the depending on
logistics of a product. the supply chain
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· Analyze how different freight modes compare in terms of environmental improvements from congestion relief, as
environmental performance on specific corridors; and well as from mode shift due to investments in a given
· Analyze environmental effects of mode shift on specific mode);
corridors. · Compare environmental performance of different metro-
politan regions, which would identify benchmarking regions,
Typically, a freight corridor application will evaluate land- as well as those that are particularly inefficient regarding
based modes, particularly truck and rail. However, other emissions from moving freight (this type of analysis also
modes also could be compared against truck and rail in some would examine the correlations between infrastructure
freight corridors, including inland waterways, short-sea ship- capacity, traffic volumes, mode share, fleet characteristics,
ping, and air freight. It is also possible to use this application and environmental performance);
for intercontinental sea routes. · Analyze the impact of freight emissions on local air quality
Potential users of this application include transportation and human health; and
agencies interested in investigating the environmental conse- · Compare freight emissions with emissions from other
quences of different types of infrastructure investments. The sectors.
private industry also could use this application to evaluate the
effects of specific route choices (e.g., Chicago to Los Angeles A metropolitan application will evaluate and geographically
via I-80 or I-40) on their environmental performance. Route situate all freight modes that are within metropolitan bound-
length, mode availability, terrain grade, and availability of aries, including all classes of heavy-duty trucks, rail, marine,
backhaul traffic could all affect the environmental perfor- and other intermodal facilities, as well as airports.
mance of a freight corridor. Potential users include local government agencies that will
The model input data sources used to calculate the amount find value in this type of application for planning purposes
of freight activity will depend on data availability. Ideally, esti- in order to identify how future improvements in transporta-
mates of vehicle activity and commodity flows are both avail- tion infrastructure and/or freight forecasts will influence
able; otherwise vehicle payload needs to be assumed. This can freight emissions, as well as to compare a local region with
be problematic since payload can vary widely, and it has a regions in the rest of the country. Air quality districts can use
strong effect on emissions. Other important input parameters this application to support air quality analyses and health
include fleet characteristics (e.g., model year, vehicle technol- risk assessments.
ogy, engine power, equipment capacity, emission controls), Input parameters to determine freight activity will differ
and network characteristics (e.g., link capacity, node capacity, by mode. Trucking activity likely will come from travel
congestion levels). demand models, and it is important to understand how
Outputs from this application include freight emissions such estimates are determined. As indicated in Chapter 3,
associated with particular modes under different scenarios that methods to estimate trucking activity in travel demand
can be characterized by commodity mix, mode share, traffic models can be somewhat inaccurate. Rail-related activity
capacity by mode, traffic volumes by mode, link characteristics can be obtained directly from local railroads, or estimated
(e.g., pavement quality, electrified railways), fleet characteris- from published statistics. Freight activity in terminals typi-
tics, and timeframe. cally needs to be calculated separately with facility-level
In instances where this application is intended to provide the analyses. Examples include truck terminals, warehouses,
necessary inputs for dispersion models, the spatial and tempo- railyards, ports, and airports. Because of the high uncer-
ral allocation of emissions also will be required to properly tainty in some of these input parameters, it is important that
characterize emissions released to the atmosphere. some indication of uncertainty levels be included in the cal-
culations, in order to identify which data elements warrant
further improvement to make the calculations of metropol-
Metropolitan
itan freight estimates more accurate.
This application calculates freight emissions inventories Outputs from this application include freight emissions
with temporal and spatial resolution within a metropolitan associated with different scenarios characterized by traffic vol-
region with the following goals: umes, infrastructure capacity, mode share, link characteristics,
node characteristics, fleet characteristics, and timeframe.
· Analyze current and future environmental performance of Because this application also is intended to provide the nec-
the freight system within a metropolitan region; essary inputs for dispersion models, the spatial and temporal
· Analyze how future expansion/improvements in trans- allocation of emissions is important. These allocations are nec-
portation infrastructure could affect the environmental essary to determine where and when emissions are released to
performance of a metropolitan region (this could include the atmosphere.
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Facility tic to expect a detailed evaluation of the fleet characteristics,
an indication of the general truck size, as well as fleet age, will
A facility-level application calculates freight emissions from
be necessary. For example, emissions can be quite different
freight facilities including truck terminals, railyards, marine
if the truck fleet is a long-distance fleet versus a drayage fleet.
and inland ports, and airports. The application has the follow-
If trucking activity on the surrounding roads is included,
ing objectives:
traffic levels also need to be estimated in order to provide
accurate emission estimates (because congestion can have a
· Develop current and future emissions inventories associated
strong effect on local emissions).
with a freight facility; · Railyards analysis typically can rely on detailed information
· Optimize facility environmental performance;
about locomotive activity, including fuel consumed by
· Analyze how future expansion/improvements in the facility
switch locomotives. More sophisticated analyses include
could affect its environmental performance (this could information about the share of time in each notch setting,
include environmental improvements from congestion which is an important determinant of average emission fac-
relief, as well as from mode shift due to investments in a tors. Cargo handling equipment information is necessary,
given mode); including number and type of equipment. In the case of
· Evaluate effects of different regulations/initiatives on the
intermodal rail terminals, there are drayage trucks accessing
emissions from a freight facility (e.g., extended idling restric- the railyard. In this case, the same input parameters described
tions, fleet renewal programs, chassis pools, and mode shift); for trucking terminals also apply.
· Compare environmental performance of (comparable) · Marine and inland port terminals' emission calculations rely
freight facilities, which could identify benchmarking on amount of cargo moved by cargo type. More sophisti-
regions, as well as those that are particularly inefficient cated analyses include information on individual ship and
regarding emissions from freight handling (this type of harbor craft movements, engine type, engine model year,
analysis would also examine the correlations between fuel used, and geographic port information to calculate
environmental performance and infrastructure capacity, emissions, as well as information on amount and type of
operational characteristics, traffic throughput, and fleet CHE, hours of use, and duty cycle. Truck and rail servicing
characteristics); and ports also need to be accounted for by determining the
· Analyze the impact of a freight facility on local air quality amount of cargo moved by each, as well as general truck and
and human health. rail characteristics. Similar information described for truck-
ing terminals and railyards apply to trucks and rail that
Different modes will be included depending on the facil- service ports.
ity. The analysis of trucking terminals will involve only · Airport operations analysis would use detailed information
trucks, but the evaluation of railyards can include rail, CHE, on the number of air cargo aircraft and the fraction of
and trucks, since most rail terminals are connected to the weight associated with cargo movement when aircraft oper-
rest of the freight system by roadways. Marine and inland ate in mixed modes. More sophisticated analysis would
terminals could include OGVs, harbor craft, CHE, trucks, include detailed information about each aircraft TIM
and possibly rail if on-dock or off-dock rail terminals exist. (approach, landing, taxi, takeoff, and climb out), along with
The evaluation of airports will include air freight and CHE specifics on the aircraft type (jet, turboprop, and piston)
as well as trucks. and engine type. Ground support equipment used to ser-
Users of this scale will include regulators involved in per- vice air cargo also needs to be accounted for--this would
mitting facilities, owners, and operators seeking permits or include information on the hours of use, duty cycle, and
improvement in operations, local air agencies considering fuel type.
facility contributions to local air emissions, and environmental
organizations concerned with public health and environ- Outputs from this application include freight emissions
mental justice. associated with different scenarios characterized by traffic
Input parameters for the following modes will depend on the throughput, operational characteristics (e.g., idling times),
facility and the level of resources available for data collection: infrastructure capacity, equipment characteristics, and
timeframe.
· Trucking terminals are likely to have records of the number Because this application also is intended to provide the nec-
of trucks entering and leaving the facility. Estimates of load- essary inputs for dispersion models, the spatial and temporal
ing and unloading times can provide an estimate of idling allocation of emissions is important. These allocations are
time, which needs to be evaluated in conjunction with necessary to determine where and when emissions are released
whether anti-idling programs exist. Although it is unrealis- to the atmosphere.
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Supply Chain 4.3.3 Functional Areas
This application calculates the emissions associated with a The Conceptual Model is divided into functional areas to
specific supply chain, including the supply of materials to fulfill the objectives of the five types of applications described
manufacturing/assembly facilities, and/or the distribution of in the previous section. These functional areas enable a user
intermediate or finished products to other facilities, storage to define the freight movement framework, calculate freight
locations, distribution centers, or consumers. As follows, this emissions, and evaluate freight emissions. Functional areas
application will: can be thought as general categories of modules in a system,
under which business processes run.
· Calculate the emissions associated with all freight trans- Exhibit 4-5 illustrates the six proposed functional areas. The
portation required to manufacture and distribute a product; first three functional areas--transportation network design,
· Optimize routing for best environmental performance; and planning of transportation services, and execution of trans-
· Evaluate the effects of mode, route, and equipment choice portation operations--are part of the system description.
on the environmental performance of the transportation These three functional areas allow the user to configure the
components of a supply chain (however, this application network and enter the necessary input parameters to describe
will not evaluate emissions embedded in materials or those commodity activity, vehicle activity, and equipment configu-
emissions associated with the actual manufacturing and ration. The following two functional areas--calculation of
assembly of products). freight emissions and allocation of freight emissions--use the
system setup information to calculate emissions and allocate
The modes included in this application will depend on the them to specific geographic areas and points in time. The last
specific supply chain, and can potentially include all modes of functional area--evaluation of freight emissions--enables the
transportation. This type of application will be most useful to comparison of different scenarios, as well as sensitivity and
shippers, carriers, or logistics providers interested in evaluat- uncertainty analyses, to improve freight emission estimates.
ing the environmental performance of their supply chains, These six functional areas are described in detail in the follow-
and in understanding the effects of mode, route, and equip- ing subsections.
ment choice on emissions. Input parameters will include sup-
ply chain design, facility location, mode choice, route choice,
Transportation Network Design
inventory levels, packaging, delivery patterns, and equipment
characteristics. This functional area consists of inputs describing the simu-
Outputs from this application include freight emissions lated transportation network. Freight transportation activity
associated with the transportation necessary to manufacture and associated emissions will be calculated on a transportation
and distribute a product under different scenarios. These sce- network, which will be based on a link-node system. Nodes
narios can be characterized by product type, supply chain con- will represent freight facilities, including trucking terminals,
figuration (location of suppliers, manufacturing/assembly railyards, marine/inland ports, and airports. Nodes also can be
facilities, storage locations, and consumers), mode choice, virtual points dividing two continuous links with different
route choice, fleet characteristics, and timeframe. characteristics. For example, two consecutive sections of the
Exhibit 4-5. Functional areas.
System
Calculations Evaluation
Setup
Transportation Calculation of Evaluation of
Network Freight Freight
Design Emissions Emissions
Planning of Allocation of
Transportation Freight
Services Emissions
Execution of
Transportation
Operations
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same roadway with different traffic volumes can be divided by Users will be able to create different scenarios to test the
a virtual node (e.g., freeway exit, interchange). Links will rep- effects of changes in freight demand, service levels, mode
resent transportation facilities where freight moves, including choice, and route choice on associated supply chain emissions.
roadways, railways, inland waterways, ocean routes, and air
routes. Freight activity and emissions will be allocated to either
Execution of Transportation Operations
a link or a node.
The Conceptual Model enables the creation of flexible net- This functional area takes the perspective of day-to-day
works with different levels of aggregation that can fit the transportation operations, and it collects inputs for three
objectives and accuracy requirements of an emission analysis. business processes. First, the equipment configuration deter-
Although virtual nodes can be created to divide one link into mines which type of equipment will handle the freight flows.
shorter links with different characteristics, the opposite is Required input parameters for equipment configuration
also possible in the case of more aggregate analysis. Compar- include model year, vehicle technology, engine power, emis-
ative analyses could also be made to evaluate the loss in accu- sion controls, equipment capacity, and fuel type. All of these
racy by increasing the level of aggregation when defining parameters are important for the determination of emission
links and nodes. factors associated with a specific equipment type.
Because the Conceptual Model will be setup to assist users in Second, loading patterns will be determined based on the
incorporating environmental criteria in the design of a trans- specified commodity and equipment configuration. Based on
portation network, the Conceptual Model enables the creation commodity density and packaging requirements, payload
of alternate nodes and links to test future potential transporta- will be determined. Loading patterns will also define require-
tion networks. Allowance for changes in node structure (e.g., ments for loading and unloading times, which will assist in
additional nodes to simulate the effects of a new (or modified) the estimation of idling or hotelling times.
distribution center) will enable the user to compare emissions Finally, vehicle activity will be determined based on com-
between scenarios. modity flows, mode choice, route choice, equipment config-
As described in the following section, there are three busi- uration, and loading patterns. Alternatively, vehicle activity
can be provided as a direct input parameter to the model.
ness processes that fall under this functional area--supply
chain design, link characterization, and node characterization.
The specific attributes of links and nodes are described under Calculation of Freight Emissions
link characterization and node characterization, respectively.
This functional area is responsible for calculating freight
emissions. Emission factors are determined based on equip-
Planning of Transportation Services ment characteristics and how the network is configured. Emis-
sions can either be determined from vehicle activity directly
This functional area configures the necessary input param-
by using emission factors in terms of freight activity (ton-mile,
eters for the determination of freight flows over a specified
hp-hr, hour), or from fuel consumption. In the latter case, fuel
transportation network, including the determination of com-
consumption either can be a direct input parameter to the
modity flows, service levels (i.e., requirements in terms of tran-
model, or it can be estimated from freight activity.
sit time, and transit time reliability), mode choice, and route The functional unit of the analysis determines how freight
choice. activity is measured. Typical functional units are VMT, ton-
For those applications that rely on commodity flows as mile, horsepower-hour (hp-hr), kilowatt-hour, and hour. For
input parameters, input data can be obtained from published example, truck activity is typically measured in terms of VMT,
sources, such as the Commodity Flow Survey, (193) or by but vessel activity is measured in kilowatt-hours.
internal sources of freight transportation demand in the case
of private firms. In the latter case, requirements for transit time
and transit time reliability also will assist in the selection of Allocation of Freight Emissions
mode. After mode selection, one or more routes will be chosen After freight emissions are calculated, they need to be allo-
for the analysis. cated to either a node or a link (i.e., spatial allocation). This
Other types of applications will not require the determina- functional area groups calculated emissions spatially and tem-
tion of commodity flows and, instead, transportation activity porally. Because links and nodes are associated with geographic
will be determined directly from measured (or estimated) regions, this will provide the necessary information for air
vehicle activity. For example, the analysis of freight emissions quality models and health risk assessments. Additionally, emis-
in a metropolitan area is to likely rely on travel demand mod- sions also need to be allocated to a specific time (i.e., temporal
els to estimate truck activity on a local transportation network. allocation) since this is also an important input parameter for
In this case, mode choice and route choice will already be air quality models. Emissions also can be allocated to a specific
determined. product or commodity.
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Evaluation of Freight Emissions fleet technology. Scenarios also can be modified based on spe-
cific input parameters, enabling sensitivity analyses. Thus,
This functional area allows comparisons between a variety
users can create different scenarios to test the effects of changes
of emission scenarios calculated by the Conceptual Model. The
in the level of network aggregation, freight demand, service lev-
model may be used to calculate emissions under a range of
els, mode choice, route choice, and equipment configuration.
scenario alternatives that may be compared against a baseline
or a benchmarking target, allowing alternatives to be differen-
tiated based on a variety of input parameters. This func- 4.3.4 Processes
tional area also allows the effects of emission reduction Each of the six functional areas described in the previous
strategies to be analyzed by the Conceptual Model, including section are essentially aggregations of related processes. Each of
the strategies affecting emission factors, freight activity, fuel these processes is responsible for specific activities required to
efficiency, and congestion. The ability to perform sensitivity fully describe a functional area and, eventually, for the calcula-
analysis of specific parameters is important for evaluating and tion and evaluation of freight emissions. Exhibit 4-6 summa-
improving the performance of supply chains and testing the rizes the processes included in each functional area.
effectiveness of transportation policies. For example, freight Some of these processes will apply only to some types of
emissions can be evaluated over time to examine emission applications. For example, for those analyses that rely on travel
changes based on economic forecasts (which drive commod- demand models to estimate truck activity over specific links,
ity flows), mode share forecasts, and advancements in vehicle all processes under the planning of transportation service
Exhibit 4-6. Processes.
FUNCTIONAL AREAS PROCESSES
1. Transportation · Supply chain design
· Link characterization
Network Design · Node characterization
2. Planning of · Determination of commodity flows
· Determination of service level
Transportation · Mode choice
Services · Route choice
3. Execution of · Equipment configuration
· Determination of loading patterns
Transportation · Determination of vehicle activity
Operations
4. Calculation of · Determination of emission factor
· Calculation of fuel consumption
Freight Emissions · Calculation of emissions
5. Allocation of · Spatial allocation of emissions
· Temporal allocation of emissions
Freight Emissions
6. Evaluation of · Analysis of alternative scenarios
· Sensitivity analysis of freight emissions based on changes in
Freight Emissions input parameters
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functional area will not be required. Processes also will need Exhibit 4-7 provides a list of some of the most important
to be adapted depending on the application because of differ- objects in the Conceptual Model.
ent analysis objectives, input parameters, calculation meth-
ods, and accuracy needs. For example, fuel consumption can
Supply Chain Design
be a direct input to the model (i.e., facility-level applications
where fuel consumed is available for participating carriers), it No objects are involved in this process.
can be calculated from vehicle activity based on equipment This process enables users to define the facilities included in
fuel efficiency, or it might be disregarded altogether if emis- a product supply chain, as well as the possible material flows
sion factors are not based on fuel consumed. between facilities. Facilities can be divided into the following
two types:
Objects
· Logistics facilities where products are processed and/or
All entities in the Conceptual Model are considered objects. stored, including suppliers' locations, manufacturing and
Objects may be either calculated from other objects or are assembly plants, warehouses, distribution centers, whole-
external input parameters. Higher-order objects are inputs to salers, retailers, and final consumers; and
lower-order objects. For example, emissions are a first-order · Transportation facilities, such as trucking terminals, rail-
object and are the product of two second-order objects: freight yards, intermodal facilities, ports, and airports.
activity and emission factors. Emission factors are produced
from third-order objects such as equipment model year, and The objective of this process is to determine the set of nodes
so on. The discussion of processes sometimes refers to objects involved in the analysis of freight emissions, as well as the flows
as input parameters; the terms are regarded as interchangeable that will move between these nodes. This process is conceptu-
in this report. ally simple, and it requires only the determination of possible
Exhibit 4-7. Main objects.
Variable Code Description
Activity ACT Freight activity is a measure of vehicle activity, cargo activity, or fuel consumption.
Activity Profile PRO Activity profiles represent driving cycles, duty cycles, or any other distribution of vehicle
activities that has an effect on emission factors.
Area ARE Combination of links and nodes.
Commodity COM In analyses in which vehicle (or freight) activity is not an external input parameter to the
model, commodity flows will determine vehicle activity. Each commodity group will be
assigned with ranges of possible densities for different types of equipment, so that a
commodity can be converted into number of vehicles.
Emission EF Determines the amount of a given pollutant emitted as a function of freight activity, which
Factor can be measured in vehicle-miles traveled, idling hours, ton-miles, energy, fuel, etc.
Emissions E Product of freight activity and emission factors.
Transportation EQP This includes the information necessary to characterize transportation equipment (or a
Equipment fleet), including vehicle type, weight class, engine technology, fuel type, power ratings,
model year, and emission control technologies.
Link LNK A link represents transportation facilities where freight moves, including roadways,
railways, inland waterways, ocean routes, and air routes.
Mode MOD Trucking, rail, water, cargo handling equipment, air.
Node NOD At the local/project level, nodes represent freight facilities, including trucking terminals,
railyards, marine/inland ports, and airports. Nodes can also be virtual points dividing two
continuous links with different characteristics. At the regional and national level, nodes
can represent cities or regions.
Payload PAY Payload represents the amount of cargo that can be loaded into transportation equipment.
Payload can be measured in terms of weight or volume.
Pollutant POL Emissions are reported separately by pollutant.
Route RTE A route is a series of links and nodes. Because links are mode-specific, a route is
responsible for linking multiple modes into a single supply chain.
Scenario SCE Scenarios can be differentiated by a variety of parameters, including year, equipment
type, route choices, commodity flows, payload, emission reduction strategies, etc.
Time Period TIM Time period represents the point in time at which emissions occur.
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facilities as well as flows between facilities. There also might be ferent characteristics. At the regional and national level, nodes
flows within the same facility, which can include the operations also can be cities or regions.
of drayage trucks within an intermodal terminal, switch loco- Nodes need to be characterized not only because they are
motives within railyards, waterborne vessels maneuvering at the source of freight-related emissions, but because they pro-
port terminal facilities, or aircraft taxiing on runways. vide the connectivity between links, thus influencing mode
There is a mutual dependency between supply chain design and route choice.
and other processes. Both mode choice and route choice Exhibit 4-8 presents the input parameters that will charac-
depend on an initial selection of logistics facilities, while terize a node, the transportation modes to which a parameter
the selection of transportation-related facilities depends on applies, and the purpose of a parameter (e.g., determination
mode and route selection. Required inputs for this process of emission factor).
include freight transportation demand. For outputs, this
process will determine the level of service required for a
Link Characterization
supply chain, given consumer preferences (e.g., fashion-related
products require fast deliveries), production requirements (e.g., The following object is involved in this process:
just-in-time systems require specific and reliable transit times),
and commodity characteristics (e.g., high-value commodities · Link (LNK).
require fast transit times because of inventory costs).
A link represents a transportation facility connecting two
nodes. Examples of links are roadways, railways, water routes,
Node Characterization
and air travel lanes. Links must be characterized based on a
The following object is involved in this process: series of parameters required to determine freight emissions
along a transportation link. Exhibit 4-9 includes the input
· Node (NOD). parameters that will characterize a link, the transportation
modes to which a parameter applies, and the purpose of the
Nodes represent freight facilities, including trucking termi- parameter (e.g., determination of emission factor).
nals, railyards, marine/inland ports, and airports. Nodes also Link characterization is dependent on mode choice,
can be virtual points dividing two continuous links with dif- since not all modes will be present between two nodes. The
Exhibit 4-8. Parameters for node characterization.
Parameter Description Mode Purpose
Type A node can be a freight facility (where transportation All N/A
operations occur), or a virtual node (that exists to connect two
links).
Link Determines which links are associated with a specific node. All Determine nodes associated
connectivity with a trip
Mode Determines which modes can be associated with a specific All Determine mode choice
availability node. For example, a marine terminal with road access but no
on-dock rail access will be associated with truck transportation
but not rail transportation. Consequently, node characterization
will have an influence on mode choice because nodes will only
be associated with certain modes.
Equipment Because there are freight transportation-related operations All Estimate freight activity at nodes
availability taking place at certain logistics and transportation facilities, and estimate emission factor
those can be associated with specific types of transportation
equipment. For example, marine terminals are specifically
associated with cargo handling equipment that does not leave
the terminal's premises. Similarly, switch locomotives can
operate strictly within a rail terminal, and ground support
equipment is confined to an airport. As a result, node
emissions will depend on the characteristics of these types of
equipment.
Geographic Associates a node with a geographic region, which can be All Allocate emissions to physical
area defined as a city, county, air basin, metropolitan region, state, locations
country, continent, or another region defined by the user.
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Exhibit 4-9. Parameters for link characterization.
Parameter Description Mode Purpose
Mode By definition, a link is mode-specific because link attributes are All N/A
also mode-specific.
Length Measured in miles. All Calculate freight activity
Initial node All Provide link with trip
End node All
Link capacity Generally measured in vehicles per hour. Truck Estimate congestion and
average speed
Number of Truck, Determine link capacity
lanes/tracks Rail
Facility type Can be the roadway classification (for trucks) or track class (for Truck,
rail). Rail
Traffic Generally measured in vehicles per hour. Truck Estimate congestion and
volume average speed
Average Measured in miles per hour, average speed either can be an Truck Estimate emission factor
speed input parameter as in the case of travel demand models, or it
can be estimated based on link capacity and traffic volumes.
Congestion Road level of service, varying from A to F. Truck Estimate emission factor
Equipment Determines any type of equipment restriction on a link, Truck,
restrictions including size and weight restrictions, and emission control Rail,
systems. OGV
Equipment If the typical fleet operating at a link has different Configure equipment
mix characteristics from the area's average, the user can
determine a customized equipment mix for a link.
Terrain grade Terrain grade is an important attribute of a link since it has a Estimate emission factor
strong influence on fuel consumption and emissions.
Geographic Associates a link with a geographic region, which can be All Allocate emissions to physical
area defined as a city, county, air basin, metropolitan region, state, locations
country, continent, or another region defined by the user.
characteristics of different links also will influence route choice. · Mode choice: O-D pairs will influence mode choice because
For example, a longer route with smoother grades might be not all modes are available for all O-D pairs;
preferable to a shorter (but steeper) route. · Determination of service level: commodity selection will
influence service level requirements because of commodity
value (e.g., high-value commodities will require faster tran-
Determination of Commodity Flows
sit times in order to minimize inventory levels in transit); and
The following object is involved in this process: · Activity: in the global/national and supply chain applica-
tions, commodity flows will determine freight activity.
· Commodity (COM).
Determination of Service Level
Commodity flows define the weight and volume of com-
modities between different origin-destination (O-D) pairs. No objects are involved in this process.
In global/national and supply chain applications, commodity Service level is generally described as a combination of travel
flows are the main drivers of freight activity and, consequently, time (e.g., 2-day delivery), travel time reliability (± 4 hours),
of emissions. In the freight corridor and facility applications, and delivery frequency. This process is only applicable for the
freight activity might be determined by either commodity supply chain application, in which users can determine the
flows or direct estimates of freight activity. This process is not required service level for a given supply chain. This process
applicable for the metropolitan application because vehicle depends on the supply chain design process, as well as on
activity is estimated directly from travel demand models. freight transportation demand (input parameter). Service lev-
Commodity flows will be determined by either the supply els affect the following three processes:
chain design process (in the case of the evaluation of specific
supply chains), or by economic activity forecasts (in the case · Mode choice: service levels will influence mode choice
of national/regional analyses). Commodity flows will influ- because certain modes can provide faster and/or more reli-
ence the following processes: able transit times;
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· Route choice: service levels will influence route choice A route is a series of links and nodes. Because links are
because some routes are shorter or faster; and mode-specific, a route is responsible for linking multiple
· Determination of loading patterns: load sizes are usually modes along a single supply chain. The selection of a route is
determined by the frequency of deliveries. important because a route is associated with travel distance,
and other characteristics specific to the links and nodes repre-
sented in a route (e.g., terrain grade, average speed, conges-
Mode Choice
tion). For a given O-D pair and mode, more than one route
The following object is involved in this process: might be available from origin to destination. In such cases, a
route will be determined based on travel distance, travel time,
· Mode (MOD). travel time reliability (which depends on congestion), and cost.
This process applies for three types of applications: national/
Based on a given O-D pair, mode choice will be determined global, freight corridor, and supply chain. The metropolitan
by mode availability, as well as other criteria (e.g., service level, application does not require this process because routes are
travel time, travel distance, cost, and emissions). The Concep- determined within a travel demand model. Because the facility
tual Model assumes that a user will evaluate these parameters application analyzes emissions at a node, route choice is not
outside of the model. necessary.
For the applications that can estimate vehicle activity from Initially, the Conceptual Model does not include an algo-
commodity flows--national/global, freight corridor, and sup- rithm to assist users in route choice based on selection criteria.
ply chain--more than one mode might be necessary for a given Instead, the user needs to consider all relevant criteria for route
flow. For example, a corridor analysis between Chicago and choice, and simply assign a route in the model.
Los Angeles could require the use of a double-stack train, plus Route choice will influence equipment configuration
a drayage truck movement on each end of the trip. because different equipment types might be associated with
Mode choice will determine the following processes: different regions.
· Equipment configuration: mode selection will determine
Equipment Configuration
the different types of vehicles involved in the analysis; and
· Route choice: mode choice also will have an influence in The following objects are involved in this process:
the selection of a route.
· Transportation Equipment (EQP), and
· Payload (PAY).
Route Choice
The following objects are involved in this process: This process is the determination of equipment charac-
teristics for a specific route or combination of routes (for
· Route (RTE), regional/national analyses). Exhibit 4-10 includes the parame-
· Link (LNK), and ters necessary for equipment configuration by mode. Some of
· Node (NOD). these parameters are necessary for the calculation of payload
Exhibit 4-10. Parameters for equipment configuration by mode.
Mode Parameter
Heavy-Duty Trucks Model year, mileage accumulation, truck weight class, payload, truck weight, fuel type,
engine power, vehicle technology, emission control technology, truck capacity (weight and
volume), commodity types
Rail Locomotive type, engine power, locomotive tier (emission control technology)
Ocean-Going Vessels Calls, ship type, engine type, engine model year, propulsion and auxiliary engine power,
ship size (DWT or TEUs), fuel type
Harbor Craft Population by engine type, number of engines per vessel, engine power by type,
deterioration factor, growth factor, engine age, median life, scrappage, use of retrofit
devices, fuel type
Cargo Handling Population, engine power, deterioration factor, growth factor, engine age, median life,
Equipment scrappage, use of retrofit devices, fuel type
Air Freight Engine type, fuel type, fraction of payload used for air cargo, aircraft type, fuel flow rates,
aircraft performance (throttle setting)
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(e.g., truck capacity), while others are used for the estimation supply chain and facility applications, and it is sometimes true
of appropriate emission factors (not all parameters listed are for the national/global and freight corridor applications. This
always necessary for the determination of emission factors). process is not required for the metropolitan application because
Equipment configuration depends on commodity type, vehicle activity for that application is determined directly by
mode choice, and sometimes on route choice because some travel demand models.
regions might have restrictions regarding which types of equip- Loading patterns will influence the equipment configura-
ment are permitted. Equipment configuration also is influ- tion process because it will determine the payload, and con-
enced by loading patterns, which will determine payload. sequently vehicle weight. Additionally, some supply chains
Equipment configuration will determine the following busi- prioritize delivery frequency over equipment capacity maxi-
ness processes: mization (e.g., just-in-time systems). In these cases, the normal
decision to optimize capacity might not be a good decision
· Determination of loading patterns: load capacity influ- given the specifics of supply chain requirements.
ences loading patterns;
· Determination of emission factor: emission factors are
dependent on equipment type, model year, engine charac- Determination of Freight Activity
teristics, and equipment weight; and
The following objects are involved in this process:
· Determination of vehicle activity: load capacity and equip-
ment utilization determine how many vehicles are neces-
· Activity (ACT),
sary to transport a given load.
· Scenario (SCE),
· Mode (MOD),
Determination of Loading Patterns · Transportation Equipment (EQP),
· Link (LNK), Node (NOD),
The following objects are involved in this process:
· Time (TIM), and
· Payload (PAY), and · Activity Profile (PRO).
· Commodity (COM).
This process consists of the determination of freight activ-
Loading patterns consist of how commodities are loaded ity, which can be measured in terms of vehicle activity (e.g.,
onto the transportation equipment. Loading patterns depend vehicle-miles traveled), product activity (e.g., ton-miles), or
on the service level--which will drive delivery frequencies-- fuel consumption (e.g., total gallons of fuel per functional
and equipment capacity. The determination of loading pat- unit). Vehicle activity either can be calculated from commod-
terns is important because it will influence vehicle activity and ity flows, or it can be an external input parameter from travel
payload, which in turn has an effect on emission factors. demand models. Fuel consumption either can be estimated
This process is required for the supply chain and facility from vehicle activity or provided to the model as an input
applications because vehicle activity might be determined from parameter. For example, the calculation of GHG emissions
commodity activity. The determination of loading patterns is and the analysis of rail emissions commonly rely on fuel con-
required for those applications in which vehicle activity is sumption. Exhibit 4-11 provides examples of activity metrics
determined from commodity activity. This is the case in the specific to each mode of transportation.
Exhibit 4-11. Vehicle and freight activity by mode.
Mode Activity Metrics Activity Profile Parameters
Heavy-Duty Trucks VMT, idling time, ton-miles Driving cycle, level of service,
average speed, bin allocation
Rail Train-miles, car miles, idling Duty cycle
time, ton-miles
Ocean-Going Vessels Calls, propulsion power Load factors, vessel speed
Harbor Craft Annual activity, fuel Load factors by engine type,
consumption duty cycle
Cargo Handling Equipment Load factor, activity Emission factor, duty cycle
Air Freight TIM (cruise, approach, Throttle setting (aircraft
taxi/idle, takeoff, climb out) performance),emission indices,
fuel flow rate
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Activity profiles characterize freight activity based on param- Since empty equipment activity will affect emissions, they
eters that affect energy consumption and/or emissions from an also will need to be included and allocated to the load in the
activity. Exhibit 4-11 also summarizes the parameters that case of the analysis of specific supply chains.
describe activity profiles.
This process will be handled differently depending on the Determination of Emission Factors
type of analysis. For those analyses that rely on commodity
activity to determine vehicle and freight activity, this process The following objects are involved in this process:
provides the necessary formulas to make the calculations.
Other types of analyses will rely on direct estimates of vehicle · Emission Factor (EF),
and freight activity as input parameters. An additional type of · Pollutant (POL),
analyses relies on direct fuel consumption estimates as input · Mode (MOD),
parameters, in which case estimates of vehicle or freight activ- · Transportation Equipment (EQP),
ity will not be necessary. · Activity Profile (PRO), and
In addition to emission factors, freight activity will be the · Link (LNK).
most important input in the calculation of emissions. Freight
activity will be calculated separately by scenario, mode, activ- Emission factors determine the amount of a given pol-
ity profile, transportation equipment, link/node, and time lutant emitted based on a given functional activity unit,
period. The specific formulas that will be used to calculate which can be related to vehicles (e.g., VMT, vehicle-hours,
freight activity will depend on the specific type of analysis energy), or related to freight (e.g., ton-miles). Emission fac-
and the exact input parameters. Equations 22 through 25 tors can account not only for fuel combustion, but also for
provide some examples of calculations of freight activity at the refining and distribution of fuel if a full fuel cycle analy-
the link level. sis is desired. Alongside vehicle/freight activity (or fuel con-
sumption), this process is the main input for emissions
Calculating vehicle activity from commodity activity (e.g.,
calculations.
vehicle-miles traveled) is performed as follows:
Emission factors will be determined separately by pollu-
COM SCE, MOD,PRO,EQP,LNK,TIM tant, mode, transportation equipment, activity profile, and
× Link _ LengthLNK link (in the case of emissions at a link). Depending on the
ACTSCE, MOD,PRO,EQP,LNK,TIM = mode, emission factors can be determined from emissions
PAYSCE, MOD,EQP
models or based on guidance documents, as summarized in
(Equ
uation 22) Exhibit 4-12. The Conceptual Model does not replace pre-
vious models that estimate emission factors or guidance
Calculating product activity from commodity activity (e.g.,
documents. Instead, it relies on emission factors from these
ton-miles) is performed as follows:
sources. Factors related to cleaner fuels or emission control
ACTSCE, MOD,PRO,EQP,LNK,TIM = COM SCE, MOD,PRO,EQP,LNK,TIM retrofits also should be used to adjust emission factors where
needed.
× Link _ LengthLNK (Equation 23)
Calculating fuel consumption from commodity activity
Exhibit 4-12. Source of emission factors
(e.g., gallons) is performed as follows:
by mode.
COM SCE, MOD,PRO,EQP,LNK,TIM
Source of Emission
× Link _ LengthLNK Mode
ACTSCE, MOD,PRO,EQP,LNK,TIM = Factors
PAYSCE, MOD,EQP
× Fuel _ Efficiency EQP,PRO,LNK Heavy-Duty Trucks MOVES, Mobile6
Rail EPA guidance
(Equation 24) Ocean-Going Vessels EPA guidance
Harbor Craft ARB NONROAD or EPA
Calculating fuel consumption from vehicle activity is per- OFFROAD models, other
formed as follows: EPA guidance, other studies
Cargo Handling Equipment ARB NONROAD or EPA
ACTSCE, MOD,PRO,EQP,LNK,TIM OFFROAD models, other
EPA guidance
Vehicle _ ActivitySCE, MOD,PRO,EQP,LNK,TIM Air Freight ICAO emissions certification
= (Equation 25) databank and fuel flow rates
Fuel _ Efficiency EQP,PRO,LNK
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Calculation of Emissions Spatial Allocation of Emissions
The following objects are involved in this process: The following objects are involved in this process:
· Emissions (E), · Area (ARE),
· Scenario (SCE), · Emissions (E),
· Mode (MOD), · Scenario (SCE),
· Link (LNK), · Link (LNK), and
· Node (NOD), · Node (NOD).
· Activity (ACT), and
· Emission Factor (EF). Freight emissions will always be associated with specific links
and nodes, which in turn are linked to geographic areas. As a
Although some methods and models are mode-specific, result, freight emissions can always be allocated spatially to
there are standard methods that can be applied to all modes. As specified geographic areas, thus supporting dispersion models
illustrated in the Equation 26, freight emissions are generally and health risk assessments. This process is only applicable for
the product of freight activity (e.g., fuel consumed, energy gen- the metropolitan and facility applications because of their nar-
erated, or vehicle miles traveled), and emission factors (in row geographic scope.
grams of pollutant per measure of freight activity). The user will be able to define different geographic areas,
which are defined as a combination of links and nodes. A GIS
Emissions = Freight Activity × Emission Factor (E
Equation 26) interface also can be created to provide a visual representation
of emissions. Emissions at an area are calculated as shown in
Depending on data availability and the complexity of ana- Equation 29.
lytical methods, emissions might be calculated separately by
vehicle type or other factors that affect emission factors (e.g., ESCE, ARE,POL = E SCE, POL, MOD, LNK ,TIM
average speed, road level of service), and added up to a total by LNK, MOD ,TIM
pollutant. With the exception of GHGs, which are summed by + E SCE, POL, MOD, NOD,TIM (Equatio
on 29)
multiplying their respective emissions by their global warming NOD, MOD ,TIM
potential, the emissions of other pollutants are always reported
separately.
The calculation of emissions will provide information for Temporal Allocation of Emissions
the following processes: The following objects are involved in this process:
· Spatial allocation of emissions: emissions will be allocated · Time (TIM),
to specific links, nodes, and geographic areas; and · Emissions (E),
· Temporal allocation of emissions: emissions can be allo- · Scenario (SCE),
cated to specific times during the day, days of the week, or · Link (LNK), and
months of the year. · Node (NOD).
Emissions will be calculated for each pollutant, scenario, Freight emissions can be allocated to specific times during
mode, link/node, and time period, as shown in Equations 27 the day, days of the week, or months of the year in order to
and 28. support dispersion models and health risk assessments.
Calculating mode emissions at a link is performed as follows: Because the dispersion of pollutants relies on variables that
are time-dependent (e.g., temperature, winds), the tempo-
ESCE,POL, MOD,LNK,TIM = ACTSCE,MOD,PRO,EQP,LNK,TIM ral allocation of emissions also is an input for dispersion
PRO, EQP
models and health risk assessments. This process is applica-
× EFMOD,PRO,EQP,LNK,POL (Equation
n 27) ble to any spatial scale for which air quality modeling might
be applied. Emissions at an area at a given time are calculated
Calculating mode emissions at a node is performed as as shown in Equation 30.
follows:
ESCE, ARE,TIM,POL = ESCE,POL, MOD,LNK,TIM
ESCE,POL, MOD,NOD,TIM = ACTSCE,MOD,PRO,EQP,NOD,TIM LNK , MOD
PRO, EQP
+ ESCE,POL, MOD,NOD,TIM (Equation 30
0)
× EFMOD,PRO,EQP,NOD,POL (Equation
n 28) NOD, MOD
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Model Calibration gates as freight activity is converted into emissions, which are
then used in air quality models and health risk assessments.
This process allows the calibration of the Conceptual
Uncertainty in the emissions calculations can generally be
Model based on results or input parameters from other studies
attributed to either process or parameter uncertainty. Process
or models. Invariably, there will be instances where surrogate
uncertainty is taken to be the degree to which algorithms used
input parameters will be used due to a lack of information
in the calculations represent the actual emissions processes.
about a given project, or a lack of resources to collect project-
These include uncertainties in the models themselves, as well
specific data. If input parameters from surrogate studies are
as uncertainties in choices made during parameterization,
available, they can be used directly in the Conceptual Model.
such as choice of models and geographic boundaries. Param-
If only final results are available, however, the Conceptual
eter uncertainty is the uncertainty in the individual elements
Model can be calibrated so that the final results can "match"
of the equations utilized. This includes uncertainties in emis-
the results from surrogate studies. The Model Calibration
sion factors, populations, activity, and other inputs.
process will let the users select one or more input parameters
In cases of both process and parameter uncertainty, any
that will need to be modified to enable the adjustment of
known biases should be corrected before calculations are
final results.
made; it is assumed here that any calculations will be made
with the best available information and methods. However,
Analysis of Scenarios unknown bias and uncertainty may still influence resulting
estimates. In some cases, this may only be estimated qualita-
This process allows the creation of alternative scenarios that
tively. In others, quantitative estimates of uncertainty may be
can be compared against a baseline or a benchmarking target.
made. Particularly, if the uncertainty (for example, the stan-
Scenarios can be differentiated based on any parameter in the
dard deviation, error, or other measure for various input
model. For example, freight emissions can be evaluated over
parameters) is known, then a quantitative estimate of the
time to examine emission changes based on economic fore-
resulting uncertainty can be made using standard error prop-
casts (which drive commodity flows), mode share forecasts,
agation methods.
and advancements in vehicle fleet technology. Scenarios also
A full discussion of error propagation methods is available
can be modified based on specific input parameters, which will
elsewhere. (194) Generally, overall uncertainty is derived from
enable sensitivity analyses. For example, users can create differ-
a Taylor's Series expansion of the controlling equation, such
ent scenarios to test the effects of changes in the level of network
that if emissions can be described by f(x1, x2, . . . xn), then the
aggregation, freight demand, service levels, mode choice, route
variance of emissions is as shown in Equation 33.
choice, and equipment configuration. The effects of emission
reduction strategies also are captured by the Conceptual Model, f 2
2
f 2
2
2emissions = x1 + x2 + . . .
including the strategies affecting emission factors, freight activ- x1 x 2
ity, fuel efficiency, and congestion. The ability to perform sen-
f f 2
sitivity analysis of specific parameters is important to evaluate + 2 x1 x 2 + . . .
x1 x 2
(Eq
quation 33)
and improve the performance of supply chains and to test the
effectiveness of transportation policies.
The emissions associated with a mode in one scenario are Where
calculated as shown in Equation 31. 2
i represents the variance on variable i and
2
ij represents the covariance between variables i and j.
ESCE,POL, MOD = ESCE,POL,MOD,LNK,TIM
LNK ,TIM In many cases, the fluctuations between two input variables
+ ESCE,POL,MOD,NOD,TIM (Equation 31) are uncorrelated, such that the cross-terms average to zero. In
NOD,TIM that case, the error equation is simplified, as shown in Equa-
tion 34. This equation may be used to approximate overall
Subsequently, total emissions associated with one scenario uncertainty in emissions from a quantified set of parameter
are calculated as shown in Equation 32. uncertainties.
ESCE,POL = ESCE,POL,MOD (Equation 32)
2 Emissions =
f 2
2
x1 +
f 2
2
x 2 + . . . (Equation 34)
MOD
x1 x 2
Another method to estimate parameter uncertainty is the
Sensitivity/Uncertainty Analysis
use of Monte Carlo simulation. By specifying probability
The evaluation of uncertainty associated with methods to distributions for selected input parameters, a Monte Carlo
estimate freight emissions needs to consider that error propa- analysis simulates real-world conditions in order to assess
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the uncertainty in emissions outputs. The biggest challenge sis. However, other processes do not apply to all applications.
remains in the selection of the most influential parameters Exhibit 4-13 summarizes how each process applies to the
and the determination of their probability distributions. Lit- five types of applications. Variations among the applications
erature research, data availability, and expert judgment can are described in the following subsections.
be used. It is important to emphasize that an uncertainty
assessment does not make emission outputs more accurate.
Global/National
However, probabilistic simulation models (e.g., Crystal Ball)
can determine the contribution of each parameter to the final This application calculates freight emission inventories
outcome. Based on that information, priority can be given to associated with geographic areas at the state, national, or
find more reliable sources of data for those parameters, and global level. Supply chain design is not relevant because the
suggest the use of ranges, instead of point estimates, for application does not intend to model a specific supply chain.
results. The level of link and node characterization will need to be
commensurate with the level of detail and accuracy required
by the analysis. Because freight activity will be determined
4.3.5 Process Flows
from commodity flows, the processes regarding commodity
Process flows, or the way data and calculations flow into flows, mode choice, and route choice are required. The deter-
and between analytical process steps, will vary depending on mination of service levels however, is not applicable because
the type of application. Some of these processes can apply to of the aggregate nature of the analysis (i.e., at an aggregate
all types of applications, including equipment configuration, level, it is not possible to determine requirements such as
determination of freight activity and emission factors, calcu- transit times and delivery frequencies). All of the subsequent
lation of emissions, scenario analysis, and uncertainty analy- processes are necessary, including equipment configuration,
Exhibit 4-13. Relationship between processes and applications.
Supply
Facility Type Global/National Corridor Metropolitan Facility
Chain
Supply Chain Design
Link Characterization
Node Characterization
Determination of Commodity
Flows
Determination of Service
Level
Mode Choice
Route Choice
Equipment Configuration
Determination of Loading
Patterns
Determination of Freight
Activity
Calculation of Fuel
Consumption
Determination of Emission
Factors
Calculation of Emissions
Spatial Allocation of
Emissions
Temporal Allocation of
Emissions
Analysis of Scenarios
Uncertainty Analysis
Mandatory Applicable Not Applicable
Key: indicates that a parameter is analyzed in the way denoted by the column: indicates that the parameter is
not discussed in the way denoted by the column.
