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Project Level Analyses

Chapter 6. Emission Control Strategy Analysis at Sample Port Using VSP Profiles

This chapter describes a sample analysis of some emission reduction strategy options for the port terminals operated by the Port Authority of New York and New Jersey. This analysis was performed primarily using a recent origin-destination study which was performed during 2004 and 2005. Some relevant statistics from the Port Authority of New York and New Jersey Container Terminal Truck O-D survey are provided below, which may be useful for comparing with another port of interest.

Since some of the inputs required to perform the MOVES runs described in this section used data from the Port Authority of New York and New Jersey, it is important that users compare the data provided in Tables VI-1 and VI-2 below, to those of their port of interest in order to develop appropriate MOVES inputs.

Table VI-1 below summarizes key data from the Port Authority of New York and New Jersey for 2009. This data was taken from the Port Authority 2009 Annual Report¹².

Table VI-2 shows the daily gate movements in and out of all container terminals surveyed. Based on findings from the two-day surveys taken during December 2004 in New York and one-day surveys taken during May 2005 in New Jersey, approximately 9,600 trucks enter and exit the marine container terminals on a typical day. Truck volumes to and from the Port Newark and Elizabeth Port Authority Marine Terminal were approximately 78 percent of the regional total, with approximately 7,490 trucks entering and exiting. Truck volumes to and from the marine container terminals are dependent upon the shipping line schedules and, therefore, daily volumes of trucks are variable.

For the Port Authority of New York and New Jersey port terminals, the general practice is to open the gates at 6:00 a.m. and close at 4:00 p.m.

Overall, 74 percent of the survey respondents said that they typically spend about 2 hours or less at the seven container terminals surveyed which included queuing and processing time at the gates and the time spent inside the terminal for drop off or pick-up.

A. OVERVIEW OF ANALYSIS AND CONTROL STRATEGIES ANALYZED

Using the basic information shown above for the Port Authority of New York and New Jersey ports, several emission control strategies that could be used to reduce emissions at ports were analyzed. The strategies evaluated included idling reduction, diesel retrofits, truck replacements, and freight diversion to rail. These are not intended to be an all-inclusive list of control strategies for reducing emissions at ports, but rather to demonstrate how such analyses can be conducted at the project level using the VSP profiles developed as discussed in Chapter II. The primary reductions from the freight diversion to rail strategy come from significant reductions in truck VMT. Thus, this strategy was not evaluated at the project level, but was an evaluation comparing the reduced truck emissions to the corresponding increase in rail emissions.

B. METHODOLOGY BY CONTROL STRATEGY

This section provides an overview of methodologies presented in Chapter VI.

1. Idling Reduction

Several states have laws that affect ports and marine terminals. They prohibit the idling of heavy-duty diesel trucks at marine terminals for more than 30 minutes (California, Illinois, Massachusetts, New Jersey, Texas, and Washington)¹³. A wide variety of idling reduction technologies exist; most of these are designed to provide services (e.g., heat, air conditioning, and/or electricity) to a vehicle that would otherwise require the operation of the main drive engine while the vehicle is temporarily parked or remains stationary. The following truck idling reduction technologies are verified by EPA¹⁴:

• Electrified Parking Spaces: an Electrified Parking Spaces system operates independently of the truck's engine and allows the truck engine to be turned off as the system supplies heating, cooling, and electrical power (provides off-board electrical power).
• Auxiliary Power Units and Generator Sets: these devices supply cooling, heating, and electrical power to Class 8 trucks and other applications.
• Fuel Operated Heaters: a Fuel Operated Heater provides heat (only) by combusting fuel drawn from the main engine or other fuel system.
• Battery Air Conditioning Systems: a Battery Air Conditioning System uses batteries to power an independent electric cooling system. Typically, these systems integrate a Fuel Operated Heater to supply heating.
• Thermal Storage Systems: a Thermal Storage System stores energy in cold storage as the truck is driven, and then provides air conditioning when the truck is turned off.
• Automatic Shut-down/ Start-Up Systems: automatic engine shut-down/start-up systems not only turn off the engine while idling but can re-start the engine when necessary¹⁵.

The impact of an idling reduction control strategy can be modeled in MOVES by adjusting the off-network link. As described in the MOVES user guide,¹⁶ the off-network provides information about vehicles which are not driving on the project links, but still contribute to the project emissions (while idling or starting for instance). For each vehicle type, the off-network input includes:

• The ‘vehicle population': average number of "off network" vehicles during the hour being modeled.
• The ‘start fraction': a number which specifies the fraction of this population which has a "start" operation in the given hour.
• The ‘extended idle fraction': a number which specifies the fraction of the population which has had an ‘extended idle' operation in the given hour.
• The ‘parked vehicle fraction': a number which specifies the fraction of the ‘vehicle population' which have been parked in the given hour.

In order to model an idling reduction control strategy, the fraction of trucks idling (while waiting at the gate) was reduced; this fraction of trucks for which idling was reduced was added to the fraction of parked trucks and to the start fraction. For demonstration purposes, the case of an automatic shut-down system was selected; it was assumed that such a system does not have associated emissions. It is important to note that (when modeling other idling reduction technologies) emissions associated with the idling reduction control strategy need to be taken into account. Indeed, although overall emissions may decrease, emissions from the idling reduction technology itself need to be taken into account. The following section explains how the original off network link was created and how it was modified to model the idling reduction control strategy.

Original off-network link (no idling reduction):

• The total population of trucks for the hour modeled was assumed to be 625¹⁷.
• The fraction of trucks that were originally idling while at the gate was assumed to be 0.35¹⁸.
• The fraction of trucks that were originally parked while at the gate was assumed to be 0.64 (it was assumed that most trucks were either idling or parked while at the gate; a small fraction of 0.01 was left based on the "On-Port property" link trucks volume¹⁹).
• The fraction of trucks that start during the modeled hour was assumed to be 0.64. It was assumed that all the activity in the port occurs evenly during all (working) hours of the day; therefore, all the trucks that are parked must start. This is a simplification since during the early hours of the day, more trucks would be idling and stopped (very few would actually start); in the late hours of the day, more trucks would be starting and less would be parked. To obtain more accurate results, this needs to be modified by users with port-specific data when modeling a particular hour.
• The average idling time for a truck that does idle was assumed to be 2 hours²⁰.

Modified off-network link (with idling reduction):

As mentioned above, the case of an automatic shut-down system was selected. Engines were modeled to turn-off after 30 minutes of idling. This threshold was selected based on the state laws affecting ports described earlier. The fraction of trucks idling (while waiting at the gate) was reduced; this fraction of trucks for which idling was reduced was added to the fraction of parked trucks and to the start fraction.

• The total population of trucks for the hour modeled is still 625.
• The new fraction of trucks idling while at the gate is now 0.0875 (only a quarter of the original fraction, since trucks now idle for 30 minutes instead of 2 hours).
• The new fraction of trucks parked while at the gate is now 0.9025 (the fraction of trucks that were idling and were switched off is now integrated into the parked fraction).
• The new fraction of trucks that start during the modeled hour is now 0.9025 (again, we assumed that all trucks that stopped will start and that those starts are evenly distributed throughout the day).

2. Diesel Retrofits

Various retrofit technologies are available and verified by EPA. A list of the diesel retrofit technologies that EPA has approved for use in engine retrofit programs can be found on EPA's website, along with each system's expected efficiency²¹.  The Continuously Regenerating Technology 3 (CRT3) Particulate Filter was selected in this example (it is one of the most efficient systems verified by EPA). The expected emissions reductions from the Diesel Particulate Filters (DPF) are listed in the table below:

MOVES has the capability to model on-road vehicle retrofit strategies for all exhaust pollutants for diesel trucks. A retrofit input file was created to model the impact of using the CRT3 Particulate Filter. This retrofit input file is provided in Appendix B. Some of the parameters in that input file include:

• Initial calendar year of retrofit implementation: first calendar year the retrofit program is administered. Due to an error in the MOVES model (both MOVES2010 and MOVES2010a versions), retrofit can only be modeled as if it happened entirely during the year modeled (rather than over a several year period before the modeled year). Therefore, all of the retrofits were applied in 2008.
• Final calendar year of the retrofit implementation: last calendar year during which the retrofit program is administered. This was 2008, as noted above.
• Initial model year that will be retrofitted: first model year of coverage for a particular vehicle class/pollutant combination. This year was selected based on EPA's guidelines for verified technologies. The CRT3 DPF is verified for truck model years 1994 to 2006. Thus, the selected initial model year was 1994.
• Final model year that will be retrofitted: last model year of coverage for a particular vehicle class/pollutant combination. This year was selected based on EPA's guidelines for verified technologies and on EPA heavy-duty truck regulations. The 2004 Federal regulation focused mostly on NOx, with no new limit on PM; therefore, PM emissions for model years 2004 were likely high. However, the 2006 Federal regulation imposed a stringent PM limit, which probably required a DPF to be installed in new vehicles by the manufacturer. Therefore, a retrofit is relevant for model years until 2006.
• Percentage of the fleet retrofit per year: represents the percentage of VMT of a particular fleet of a particular vehicle class, retrofit calendar year group, model year group, and pollutant combination that is to be rebuilt in a given calendar year. As described above, all of the retrofits were in 2008 with retrofits occurring for 100 percent of the trucks. This scenario allows a user to scale down the impact of the retrofit by pro-rating the emissions reduction (x percent of the emissions reduction would be achieved if only x percent of the trucks were retrofitted).
• Percentage effectiveness of the retrofit: percent emission reduction achieved by a retrofit. It is computed from a non-retrofit emission baseline. The excepted emissions reductions from the CRT3 Particulate Filter were used for running exhaust and extended idling. For start emissions, the efficiency of HC/CO conversion was set to zero ("cold start" phenomenon).

3. Truck Replacements

The impact of a truck replacement control strategy can be modeled in MOVES by adjusting the vehicle age distribution input. E.H. Pechan & Associates, Inc. used the New York and New Jersey Regional Truck Replacement Program guidelines to develop the MOVES inputs (replacement of trucks that have engines model year 1993 or older with newer trucks model year 2004 to 2008). The original age distribution input was created based on data in "The Port Authority of New York and New Jersey Drayage Truck Characterization Survey."  To model the truck replacement strategy, the fractions of trucks from 1993 and older were assumed to be zero and the original fractions were added to the newer truck fractions. The older trucks were modeled as being replaced with an even distribution of newer trucks that meet the New York and New Jersey Regional Truck Replacement Program criteria (20 percent of 2004, 20 percent of 2005, 20 percent of 2006, 20 percent of 2007, and 20 percent of 2008). With this method, it is possible to scale down the impact of the Truck Replacement Program by pro-rating the emissions reduction (x percent of the emissions reduction would be achieved if only x percent of the trucks were replaced with an even distribution of newer trucks). The table below shows the original age distribution and how it was modified to model the truck replacement.

Another option would be to replace an uneven distribution of trucks instead of replacing all trucks 1993 and older. For instance, another rule could be: the older the truck, the larger the proportion of trucks replaced. The table below shows how the age distribution can be modified to model such a program (it also lists the percentage of trucks replaced per model year). It was still assumed that trucks were replaced with 20 percent of 2004, 20 percent of 2005, 20 percent of 2006, 20 percent of 2007, and 20 percent of 2008. With this scenario, it is possible to scale down the impact of the program by pro-rating the emissions reduction (y percent of the emissions reduction would be achieved if instead of replacing 10 percent of 1993 trucks, 20 percent of 1992…, 100 percent of 1984, only (10*y) percent 1993, (20*y) percent of 1992…, (100*y) percent of 1984 trucks were replaced). Additional MOVES runs would be needed to evaluate the emission reduction, if the truck replacement followed a different pattern.

4. Freight Diversion to Rail

Another strategy that can be employed to reduce port-related emissions is to divert freight from trucks to rail. Diversion of freight is an alternative that is currently being considered for the Port Authority of New York and New Jersey ports.²²  Based on this current study, the diversion of long-haul truck trips (defined as trips of 500 miles or more) could reduce approximated 10 percent of the truck tonnage transported to or from these ports. When freight is diverted from trucks to rail over long distances, there is generally a significant emissions savings.

EPA has estimated the average emission factors for locomotives by calendar year, factoring in the emission standards applicable by model year and the populations of locomotives of each model year expected to be in place in a given calendar year.²³  EPA converted the emission factors in grams per brake horsepower-hour to grams per gallon by using a horsepower-hour per gallon conversion factor. These resulting emission factors in grams per gallon are shown in the table below. EPA has also noted that based on data collected by the Association of American Railroads, approximated one gallon of fuel is consumed when hauling 400 ton-miles of freight. Using this conversion factor, the table below shows the resulting emission factor by pollutant in grams per ton-mile of freight hauled by a large line-haul locomotive in 2008.

While there is no standard weight of a container moved by rail or freight truck, for this analysis, we have assumed a weight of 50,000 pounds or 25 tons. The resulting rail emissions for hauling one 25 ton container 500 miles by rail are shown in the table above. These emissions were then compared to the emissions from one combination long-haul truck driving the same distance.

To estimate comparable truck emissions, MOVES was used to estimate the emission rate in grams per mile of a combination long-haul truck traveling through the New York area. This run was made at the county level of MOVES, using county-level defaults. This was done because the emissions from the 500-mile trip will greatly outweigh the emissions in the port area, so the operating mode profiles developed under this project were not relevant to this strategy. The table below shows the resulting truck emissions and the percentage reduction in emissions from one trip diverted from truck travel to rail.

C. RESULTS USING NEW VSP PROFILES

Three of the VSP profiles that were developed by microsimulation were tested in MOVES:

• Port Gate 10 trucks per hour;
• Port Gate 60 trucks per hour; and
• In-Port Property.

For each one of these VSP profiles, emissions²⁴ were estimated for four control strategies:

• No control strategy (baseline; modeled in MOVES);
• Idling reduction (modeled in MOVES);
• Diesel retrofit (modeled in MOVES); and
• Truck replacement (modeled in MOVES).

Figures VI-1, VI-2, and VI-3 present the results of the MOVES runs for the scenarios described above (total emissions). Figures VI-4, VI-5, and VI-6 illustrate the emissions reduction obtained from the idling reduction, diesel retrofits, and truck replacement strategies, compared to the baseline. Those results are shown numerically in Tables VI-3, VI-4, and VI-5.

Figure VI-1. MOVES Emissions Output - Port Gate 10 Trucks per Hour Scenario

Figure VI-2. MOVES Emissions Output - Port Gate 60 Trucks per Hour Scenario

Figure VI-3. MOVES Emissions Output - In Port Property Scenario

Figure VI-4. MOVES Emissions Reductions - Port Gate 10 Trucks per Hour Scenario

Figure VI-5. MOVES Emissions Reductions - Port Gate 60 Trucks per Hour Scenario

Figure VI-6. MOVES Emissions Reductions - In Port Property Scenario

Before discussing the findings for the three control strategies modeled, it is interesting to note that the percent reductions for PM2.5 and PM10 in the above tables are the same. This stems from the fact that the MOVES PM10 emissions are a product of PM2.5 emissions (for each emissions process) and a PM10 emission ratio. This PM10 emission ratio is a unitless factor for the amount of PM10 created per unit of PM2.5 (this factor varies by the output pollutant, the source type, and the fuel type)²⁸.

The idling reduction strategy decreases CO, NOx, and PM emissions significantly. For instance, for the Port Gate 10 Trucks per Hour Scenario, emissions reductions are -56 percent, -58 percent, and -39 percent, respectively. It is important to note that in this particular example, idling emissions account for a large portion of the total baseline emissions (with no control strategy). This is due to the fact that driving distances are short (approach to gate only) and thus emissions from the "running" processes are comparatively low. Therefore, a drop in idling emissions translates into a drop in total emissions. VOC emissions are not affected by idling reduction because MOVES does not consider that any VOC emissions are generated during idling.

The retrofit control strategy has a significant impact on VOCs, CO, and PM. For the Port Gate 10 Trucks per Hour Scenario, the emissions reductions are -68 percent, -48 percent, and -56 percent, respectively. These reductions are directly correlated with the efficiency of the retrofit technology (in this case the CRT3 Particulate Filter); the chosen system does not have the capability of decreasing NOx, which is why those emissions remained constant.

Finally, the truck replacement strategy is the only one that leads to a change in the emissions of all pollutants. For the Port Gate 10 Trucks per Hour Scenario, those reductions were -19 percent for VOC, -19 percent for PM, -2 percent for NOx, and -4 percent for CO. The impact on emissions was not as significant as the one observed with other control strategies. The comment above about short driving distances (and thus low emissions from the "running" processes) is at the root of this phenomenon. If the emissions from the entire trip were to be taken into account, the drop in emissions would be more significant (the reductions in emissions from the "running" processes only range from -18 percent to -24 percent). One surprising result is the increase of NOx emissions with the truck replacement strategy for the In Port Property Scenario. Below is a possible explanation for this phenomenon:

• First, the distribution of heavy duty diesel/gasoline trucks in MOVES is as follows: 100 percent diesel after 1988 and 92-99 percent of diesel from 1978 to 1988 (1978 is the oldest model year in our analysis). Therefore, when a truck replacement strategy is modeled, an increase in the proportion of diesel trucks is applied.
• Then, according to EPA, NOx emissions from idling diesel trucks are about 5 times as high as NOx emissions from idling gasoline trucks²⁹. Therefore, when a truck replacement strategy is modeled, as the proportion of diesel trucks is increased, NOx idling emissions are also increased.
• One could also question why this phenomenon (global NOx emissions increase) is only observed for the in-port property scenario. It is likely that all driving scenarios follow the trend described above for idling emissions. However, the other driving scenarios have a larger number of trucks and longer links than the in-port property scenario. Therefore, running emissions are higher for other driving scenarios. Since running emissions significantly decrease with the truck replacement, this leads to a decrease of the global NOx emissions. For the in-port property, running emissions are small compared to idling emissions. Thus, the NOx idling emissions increase leads to an increase of the global NOx emissions.

D. RESULTS USING MOVES-GENERATED DEFAULT VSP PROFILES

In order to assess if the impact of control strategies varies depending on the driving conditions, a MOVES-generated "Default" VSP profile was modeled in MOVES ³⁰.  Emissions from this "Default" VSP profile were estimated for the same four control strategies:

• No control strategy (baseline; modeled in MOVES);
• Idling reduction (modeled in MOVES);
• Diesel retrofit (modeled in MOVES); and
• Truck replacement (modeled in MOVES).

Figure VI-7 presents the results of the MOVES run for the scenarios described above (total emissions). Figure VI-8 illustrates the emissions reduction obtained from the idling reduction, diesel retrofit, and truck replacement strategies, compared to the baseline. Those results are shown numerically in Table VI-6.

Figure VI-7. MOVES Emissions Output - "Default" VSP Profile

Figure VI-8. MOVES Emissions Reductions - "Default" VSP Profile

E. COMPARISON OF RESULTS

Table VI-7 summarized the results from the control strategy analyses when using the MOVES default operating mode profiles with the comparable results when using the operating mode profiles developed based on port conditions. This table shows that the results differ most significantly for the idling reduction strategy. For the retrofit control strategy, CO showed fairly significant differences in emission reduction percentages when the port-specific profiles were used compared to the MOVES defaults. However, for VOC and PM, the results were relatively similar. The truck replacement strategy showed only minor differences in emission reduction percentages for all pollutants when the default operating modes were used as opposed to the port-specific profiles.

Overall, the differences between default drive cycles and VSP profiles are rather small. One reason is that whether a VSP profile is provided or not, "extended" idling emissions are the same (because the off network input which is applied in both cases, does not change). However, as described earlier (in Chapter VI section C), idling emissions account for a large portion of the total baseline emissions in this particular example (because driving distances are short and thus emissions from the "running" processes are low comparing to idling emissions). Therefore, a significant portion of the baseline emissions are exactly the same for default drive cycles and input VSP profiles. This can explain limited differences among the scenarios, even if VSP profiles are different. If only running emissions were modeled (and/or if different off network inputs were developed), then larger differences between VSP profiles would likely be observed. Another possible reason is that while no operating mode was input for the default drive cycles, the links average speed was provided. This average speed was the same as the one used in the Port Gate 10 trucks per hour scenario.