SAN PEDRO BAY PORTS YARD TRACTOR LOAD FACTOR STUDY Addendum

SAN PEDRO BAY PORTS YARD TRACTOR LOAD FACTOR STUDY Addendum December 2008 Prepared by: Starcrest Consulting Group, LLC P.O. Box 434 Poulsbo, WA 98370

TABLE OF CONTENTS 1.0 EXECUTIVE SUMMARY...2 1.1 Background...2 1.2 Estimation of Emissions...5 2.0 LOAD FACTOR ANALYSIS...7 2.1 Sample Selection...7 2.2 Data Collection...7 2.3 Collected Data...9 2.4 Data Analysis... 14 3.0 CONCLUSIONS AND RECOMMENDATIONS... 16 ADDENDUM: CARB RESPONSE... 17 TABLE OF FIGURES Figure 1: Distribution of 2005 Port of Los Angeles Emissions by Source Category...2 Figure 2: Distribution of 2005 Port of Long Beach Emissions by Source Category...3 Figure 3: Yard Tractor...3 Figure 4: Percentage of Port of Los Angeles CHE Emissions by Equipment Type...4 Figure 5: Percentage of Port of Long Beach CHE Emissions by Equipment Type...4 Figure 7: Cummins INSITE Trip Information Screen View...8 Figure 8: Engine Load Histogram... 15 LIST OF TABLES Table 1: OFFROAD Model Inputs for Off-Highway Tractors...6 Table 2: Analysis of Variance of the Average Load Factor...9 Table 3: Vehicle Data...9 Table 4: Engine Data... 12 Table 5: Load Factor Descriptive Statistics... 14 Table 6: Idle Percentage Descriptive Statistics... 15 Starcrest Consulting Group, LLC 1 December 2008

1.0 EXECUTIVE SUMMARY Under contract to the Ports of Long Beach and Los Angeles, an analysis was performed of eighty five (85) yard tractors to determine if the average load factor of 65% used by the California Air Resources Board accurately reflects the use of this equipment in the San Pedro Bay Ports. The results suggest that the current load factor, and therefore the estimated emissions inventory attributed to yard tractors, may be overstated by more than forty percent. Based upon the results of this analysis, it is suggested that a load factor of thirty seven percent is appropriate for the San Pedro Bay Port yard tractor fleet. 1.1 Background Behind ocean going vessels and heavy duty diesel trucks, the emissions of cargo handling equipment (CHE) are the largest contributor to the inventory of Port related operations. The cargo handling equipment category comprises all of those vehicles used in loading and unloading cargo from ocean going vessels, trains and trucks, and includes tractors, top handlers, side picks, sweepers, dozers and cranes. Figures 1 and 2 illustrate the distribution of the emissions by source category at the Ports of Los Angeles and Long Beach, respectively. Figure 1: Distribution of 2005 Port of Los Angeles Emissions by Source Category PM10 PM2.5 DPM NOx SOx CO TOG 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% OGV HDV CHE Rail Harbor Craft Starcrest Consulting Group, LLC 2 December 2008

Figure 2: Distribution of 2005 Port of Long Beach Emissions by Source Category PM10 PM2.5 DPM NOx SOx CO TOG 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% OGV HDV Rail CHE Harbor Craft The largest contributors to the Ports CHE inventory are yard tractors. The Ports 1,500 yard tractors also referred to as yard hustlers and UTRs, are used within a terminal to move containers to and from vessels, trains, or dwelling spaces for subsequent pick up by heavy-duty diesel trucks. Figure 3 shows a typical yard tractor. Figure 3: Yard Tractor Starcrest Consulting Group, LLC 3 December 2008

Figures 4 and 5 illustrate the distribution of the cargo handling equipment emissions at the Ports of Los Angeles and Long Beach, respectively. Figures ES.4 and ES.5 show yard tractors contributed roughly 60% of the PM and NO x emissions for CHE at the Ports in 2005. Figure 4: Percentage of Port of Los Angeles CHE Emissions by Equipment Type PM10 PM2.5 DPM NOx SOx CO TOG 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Yard Tractor Top Handler, Side Pick Other Equipment RTG cranes, cranes Forklift Excavator Loader Sweeper Figure 5: Percentage of Port of Long Beach CHE Emissions by Equipment Type PM10 PM2.5 DPM NOx SOx CO TOG 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Yard Tractor Crane Top Handler, Side Pick Loader Forklift Sweeper Aerial Lift, Truck, Other Starcrest Consulting Group, LLC 4 December 2008

1.2 Estimation of Emissions The inventory of emissions attributable to yard tractors is estimated using the following equation: Emissions = EF (grams/bhp-hr) * HP * LF * Activity Where bhp-hr = brake horsepower-hour, EF = Emission Factor, HP = Maximum Rated Horsepower, LF = Load Factor, and Activity is expressed in hours per day or hours per year In the equation above, an estimate of emission in grams of pollutant per unit of work performed is coupled with an assumption of the amount of work done by each piece of equipment. The Load Factor (LF) is used in the equation to account for the fact that the equipment is not used at maximum power during typical operation. Emissions are assumed to increase linearly with increasing load. The Load Factors range from a maximum of 1 representing 100% load or full power, to a minimum of zero or no load where the emissions are also assumed to be zero. Because each of the factors in the equation is multiplicative, an overestimation or underestimation in any term would result in an overestimation or underestimation of equal magnitude in the result. The OFFROAD emissions inventory model was developed by the California Air Resources Board (CARB) and is used to estimate the emissions of various categories of off-highway vehicles and equipment. Although equipment specific to Port operations are not explicitly modeled in OFFROAD, the emissions of off-highway tractors are assumed to represent UTRs. OFFROAD carries an assumption of 65% load for off-highway tractors (regardless of their engine horsepower rating), an estimate derived by the Power Systems Research Company (PSR). PSR is a market research and consulting company specializing in engine, original equipment and components industries. A load factor of 65% represents the assumption that yard tractors are used at 65% of their maximum rated horsepower on average whenever the vehicles are in operation. Starcrest Consulting Group, LLC 5 December 2008

Table 1: OFFROAD Model Inputs for Off-Highway Tractors Activity (Annual Load hrs) 120 P 115 16 0.49 855 0.65 175 P 160 16 0.47 855 0.65 250 N 160 16 0.47 855 0.65 Category Type HP Group P/N Avg HP Life BSFC Construction Off Highway Tractors 750 N 697 16 0.42 855 0.65 999 N 999 16 0.42 855 0.65 From Appendix B CARB MSC# 99-32 In the Table 1, P/N refers to preempted or non-preempted status, Life is the Useful Life expressed in years, BSFC is the brake specific fuel consumption and Activity is expressed in hours per year. Starcrest Consulting Group, LLC 6 December 2008

2.0 LOAD FACTOR ANALYSIS In an effort to establish the validity of the 65% Load Factor used within the OFFROAD model, the engine control module (ECM) of an opportunity sample of 85 yard tractors, approximately 6% of the in-use fleet at the Ports, were queried to obtain engine operation information. A description of the vehicles and information gathered is included in Tables 5 and 6. 2.1 Sample Selection Although the project design originally called for the testing of a random sample of 60 vehicles (30 per Port), the procedure required to measure the average load on non-computer controlled engines in typical operation was thought to be too invasive. Therefore, data collection was limited to later model year vehicles with computer controlled engines. The eighty five tractors tested were randomly selected from newer model year truck in service at seven different terminals at the Ports of Long Beach and Los Angeles. The tractors ranged in age from model year 2000 to model year 2005 with an average model year of 2004. Table 3 lists all of the yard tractors which are mainly 2003 and 2004 model year. All tractors tested were equipped with Cummins engines, 68% of which were powered by diesel, with the remainder powered by propane. By way of comparison, 73% of the yard tractors in use at the Ports are model year 2000 or newer, 93% utilize Cummins engines and 98% are diesel powered. 2.2 Data Collection Engine parameter data were recorded to a laptop computer using Cummins INLINE communication interface hardware and Cummins INSITE software. Figure 6 demonstrates the special cables used to connect the INLINE device directly to the ECM of the yard tractors analyzed. Figure 6: Figure of Data Collection Device Starcrest Consulting Group, LLC 7 December 2008

Most of the desired data were stored in the ECM s Trip Information Table. This table includes summary information for all engine operation (cumulative) as well as data pertaining to engine parameters recorded since the system was last reset. In some instances, the average engine load was not available as a direct output from the ECM. In these cases, the average load was estimated by taking the ratio of the average engine speed and the maximum engine speed. A screenshot example of the ECM Trip Information Table is shown in Figure 7. Figure 7: Cummins INSITE Trip Information Screen View For purposes of this analysis, the cumulative trip information was used. In order to verify that this information faithfully reported the typical operating parameters of the vehicles, a subset of ten UTRs were tested twice. Load Factor and other operational information were initially gathered from each of the ten yard tractors which were subsequently retested after a week s worth of operation. Starcrest Consulting Group, LLC 8 December 2008

An analysis of variance (ANOVA) test on the initial (cumulative) and subsequent Load Factor data showed no statistically significant differences in the two results, suggesting that the cumulative engine parameter data appropriately reflects the average operation of the vehicles with respect to their Load Factor (See Table 2). Table 2: Analysis of Variance of the Average Load Factor Source of Variation SS df MS F P-value F crit Rows 0.037196 9 0.004133 6.756266 0.004457075 3.178893105 Columns 9.37E-05 1 9.37E-05 0.15325 0.704555855 5.117355008 Error 0.005505 9 0.000612 Total 0.042795 19 2.3 Collected Data Table 3 provides a description of each vehicle tested in the project and Table 4 includes the corresponding data. In addition to the average engine load, additional parameters were recorded including fuel consumption, mileage, time at idle and various other indicators of vehicle activity. Table 3: Vehicle Data ID YEAR MAKE ENGINE HP FUEL 4776 2003 Ottowa Cummins 215 Diesel 4779 2003 Ottowa Cummins 245 Diesel 4780 2003 Ottowa Cummins 245 Diesel 4781 2003 Ottowa Cummins 245 Diesel 4782 2003 Ottowa Cummins 245 Diesel 4783 2003 Ottowa Cummins 245 Diesel 4784 2003 Ottowa Cummins 245 Diesel 4786 2003 Ottowa Cummins 245 Diesel 4787 2003 Ottowa Cummins 245 Diesel 4789 2003 Ottowa Cummins 245 Diesel 4792 2003 Ottowa Cummins 245 Diesel 4793 2003 Ottowa Cummins 245 Diesel 4794 2003 Ottowa Cummins 245 Diesel 4795 2003 Ottowa Cummins 245 Diesel 4796 2003 Ottowa Cummins 245 Diesel 4797 2003 Ottowa Cummins 245 Diesel 4799 2003 Ottowa Cummins 245 Diesel Starcrest Consulting Group, LLC 9 December 2008

Table 3: Vehicle Data (Continued) ID YEAR MAKE ENGINE HP FUEL 4827 2004 Ottowa Cummins 245 Diesel 4828 2004 Ottowa Cummins 245 Diesel 4829 2004 Ottowa Cummins 245 Diesel 4831 2004 Ottowa Cummins 245 Diesel 4833 2004 Ottowa Cummins 245 Diesel 4835 2004 Ottowa Cummins 245 Diesel 4836 2004 Ottowa Cummins 245 Diesel 4837 2004 Ottowa Cummins 245 Diesel 4838 2004 Ottowa Cummins 245 Diesel 4839 2004 Ottowa Cummins 245 Diesel 4840 2004 Ottowa Cummins 245 Diesel 4841 2004 Ottowa Cummins 245 Diesel 4844 2004 Ottowa Cummins 245 Diesel 4845 2004 Ottowa Cummins 245 Diesel 4846 2004 Ottowa Cummins 245 Diesel 4848 2004 Ottowa Cummins 245 Diesel 4849 2004 Ottowa Cummins 245 Diesel 4850 2004 Ottowa Cummins 245 Diesel 4852 2004 Ottowa Cummins 245 Diesel 4860 2004 Ottowa Cummins 245 Diesel 4861 2004 Ottowa Cummins 245 Diesel 4865 2004 Ottowa Cummins 245 Diesel 4868 2004 Ottowa Cummins 245 Diesel 4869 2004 Ottowa Cummins 245 Diesel 4871 2004 Ottowa Cummins 245 Diesel 4873 2004 Ottowa Cummins 245 Diesel 4875 2004 Ottowa Cummins 245 Diesel 4880 2004 Ottowa Cummins 245 Diesel 4956 2005 Ottowa Cummins 245 Diesel 4883 2004 Ottowa Cummins 245 Diesel 5381 2004 Kalmar Cummins 195 Propane 5380 2004 Kalmar Cummins 195 Propane 5379 2004 Kalmar Cummins 195 Propane 5378 2004 Kalmar Cummins 195 Propane 5377 2004 Kalmar Cummins 195 Propane 5376 2004 Kalmar Cummins 195 Propane Starcrest Consulting Group, LLC 10 December 2008

Table 3: Vehicle Data (Continued) ID YEAR MAKE ENGINE HP FUEL 5375 2004 Kalmar Cummins 195 Propane 5368 2004 Kalmar Cummins 195 Propane 5364 2004 Kalmar Cummins 195 Propane 5363 2004 Kalmar Cummins 195 Propane 5361 2004 Kalmar Cummins 195 Propane 5357 2004 Kalmar Cummins 195 Propane 5352 2004 Kalmar Cummins 195 Propane 5351 2004 Kalmar Cummins 195 Propane 5350 2004 Kalmar Cummins 195 Propane 5348 2004 Kalmar Cummins 195 Propane 5347 2004 Kalmar Cummins 195 Propane 5345 2004 Kalmar Cummins 195 Propane 5344 2004 Kalmar Cummins 195 Propane 5342 2004 Kalmar Cummins 195 Propane 5340 2004 Kalmar Cummins 195 Propane 5338 2004 Kalmar Cummins 195 Propane 5337 2004 Kalmar Cummins 195 Propane 5335 2004 Kalmar Cummins 195 Propane 5334 2004 Kalmar Cummins 195 Propane 5331 2004 Kalmar Cummins 195 Propane 5330 2004 Kalmar Cummins 195 Propane T186 2004 Ottawa Cummins 173 Diesel T187 2004 Ottawa Cummins 173 Diesel T165 2004 Capacity Cummins 173 Diesel T198 2004 Ottawa Cummins 173 Diesel T154 2004 Capacity Cummins 173 Diesel T176 2004 Capacity Cummins 173 Diesel T192 2004 Ottawa Cummins 173 Diesel T151 2003 Ottawa Cummins 173 Diesel T147 2003 Ottawa Cummins 173 Diesel T143 2003 Ottawa Cummins 173 Diesel H191 2000 Capacity Cummins 173 Diesel Starcrest Consulting Group, LLC 11 December 2008

Table 4: Engine Data ID Load Miles On Hrs Idle Hrs % Idle Total Fuel Idle Fuel MPG MPH Gal/ Hr Idle Gal/hr 4776 41.6% 48384.3 9458.4 4570.2 48.32% 16242.8 2687.4 2.979 5.115 1.717 0.588 4779 40.4% 53394.7 10338.6 4940.0 47.78% 17900.9 2559.9 2.983 5.165 1.731 0.518 4780 40.3% 54111.5 10334.4 4895.8 47.37% 17784.1 2711.8 3.043 5.236 1.721 0.554 4781 40.2% 53523.5 10353.0 4962.1 47.93% 16820.9 2556.5 3.182 5.170 1.625 0.515 4782 40.1% 52481.4 10088.9 4779.2 47.37% 16863.4 2312.3 3.112 5.202 1.671 0.484 4783 40.0% 51967.2 10059.4 4803.7 47.75% 17133.0 2364.1 3.033 5.166 1.703 0.492 4784 40.0% 51929.6 10028.5 4773.1 47.60% 16987.4 2544.9 3.057 5.178 1.694 0.533 4786 39.4% 53632.1 10186.6 4799.8 47.12% 17191.6 2356.0 3.120 5.265 1.688 0.491 4787 33.6% 54345.1 9691.7 4606.8 47.53% 16784.9 2567.5 3.238 5.607 1.732 0.557 4789 40.0% 51196.1 9921.7 4775.9 48.14% 16924.3 2632.8 3.025 5.160 1.706 0.551 4792 45.4% 70213.7 10067.8 3334.8 33.12% 19369.0 1843.9 3.625 6.974 1.924 0.553 4793 38.5% 75135.9 10817.9 3496.8 32.32% 20378.0 18336 3.687 6.946 1.884 5.244 4794 44.1% 73492.5 10658.6 3513.2 32.96% 19412.8 1829.8 3.786 6.895 1.821 0.521 4795 43.9% 86740.5 12417.4 4050.7 32.62% 22555.1 2032.1 3.846 6.985 1.816 0.502 4796 44.3% 81412.9 11649.1 3819.4 32.79% 21363.3 1978.6 3.811 6.989 1.834 0.518 4797 44.1% 73444.6 10455.6 3443.8 32.94% 19547.3 1753.0 3.757 7.024 1.870 0.509 4799 40.4% 85338.4 12331.1 4149.5 33.65% 24702.4 2499.4 3.455 6.921 2.003 0.602 4827 34.3% 50949.7 9443.6 4501.8 47.67% 16895.3 2621.8 3.016 5.395 1.789 0.582 4828 34.1% 51630.7 9540.3 4407.6 46.20% 17349.3 2589.9 2.976 5.412 1.819 0.588 4829 33.8% 50003.0 9515.7 4569.5 48.02% 17049.5 3041.3 2.933 5.255 1.792 0.666 4831 34.5% 53066.6 9867.0 4606.0 46.68% 17379.9 2605.9 3.053 5.378 1.761 0.566 4833 33.1% 46211.3 8593.0 4018.2 46.76% 15014.8 2158.3 3.078 5.378 1.747 0.537 4835 41.7% 49318.8 9290.9 4427.0 47.65% 16632.3 2576.0 2.965 5.308 1.790 0.582 4836 41.4% 49589.5 9335.8 4395.9 47.09% 16439.5 2557.1 3.016 5.312 1.761 0.582 4837 33.8% 50117.5 9448.0 4529.1 47.94% 16393.0 2586.0 3.057 5.305 1.735 0.571 4838 41.6% 50886.2 9437.5 4495.3 47.63% 16804.4 2547.6 3.028 5.392 1.781 0.567 4839 33.1% 45788.7 8594.1 4080.5 47.48% 15064.8 2303.5 3.039 5.328 1.753 0.565 4840 40.1% 50822.1 9376.8 4429.3 47.24% 16774.5 2467.5 3.030 5.420 1.789 0.557 4841 33.5% 50200.5 9436.1 4412.5 46.76% 17255.8 2510.9 2.909 5.320 1.829 0.569 4844 34.4% 50871.7 9478.0 4471.1 47.17% 16642.5 2510.0 3.057 5.367 1.756 0.561 4845 34.6% 51512.3 9648.2 4528.1 46.93% 17248.3 2786.9 2.987 5.339 1.788 0.615 4846 36.9% 47795.2 8975.0 4212.4 46.93% 15925.4 2506.1 3.001 5.325 1.774 0.595 4848 38.4% 50999.2 9700.3 4673.2 48.18% 16851.1 2623.5 3.026 5.257 1.737 0.561 4849 42.2% 21742.7 3471.2 1568.1 45.17% 6264.3 905.8 3.471 6.264 1.805 0.578 4850 35.9% 49692.4 9309.3 4654.4 50.00% 16410.6 2412.9 3.028 5.338 1.763 0.518 4852 45.2% 71399.2 10035.6 3258.4 32.47% 19386.9 1823.3 3.683 7.115 1.932 0.560 Starcrest Consulting Group, LLC 12 December 2008

Table 4: Engine Data (Continued) ID Load Miles On Hrs Idle Hrs % Idle Total Fuel Idle Fuel MPG MPH Gal/ Hr Idle Gal/hr 4860 43.7% 71154.7 9916.5 3174.1 32.01% 18435.8 1696.1 3.860 7.175 1.859 0.534 4861 35.8% 74322.3 10767.7 3558.3 33.05% 20556.6 2077.3 3.615 6.902 1.909 0.584 4865 35.3% 47255.9 6118.4 2008.4 32.83% 10970.6 1015.9 4.308 7.724 1.793 0.506 4868 38.6% 77822.5 10312.2 3100.1 30.06% 19575.4 1709.1 3.976 7.547 1.898 0.551 4869 35.4% 74650.6 10938.7 3653.3 33.40% 20162.1 2063.5 3.703 6.824 1.843 0.565 4871 35.7% 70784.6 10182.2 3361.2 33.01% 19058.0 1902.5 3.714 6.952 1.872 0.566 4873 44.4% 73377.9 10245.6 3371.6 32.91% 18696.3 1793.5 3.925 7.162 1.825 0.532 4875 36.6% 70917.2 10194.4 3364.4 33.00% 19480.1 2037.3 3.640 6.956 1.911 0.606 4880 36.3% 67051.9 9477.1 3016.3 31.83% 17950.8 1750.0 3.735 7.075 1.894 0.580 4956 36.3% 41813.6 6127.5 2234.3 36.46% 11860.1 1099.3 3.526 6.824 1.936 0.492 4884 37.0% 52804.8 9767.7 4592.8 47.02% 17213.3 2572.9 3.068 5.406 1.762 0.560 5381 40.0% 32792.6 5633.6 2492.6 44.25% 11826.6 1977.0 2.773 5.821 2.099 0.793 5380 40.5% 28200.4 4964.5 2210.7 44.53% 10381.6 1826.9 2.716 5.680 2.091 0.826 5379 39.5% 33927.4 5974.5 2632.5 44.06% 12368.8 2090.2 2.743 5.679 2.070 0.794 5378 38.5% 33540.4 5853.7 2547.7 43.52% 12165.8 1907.5 2.757 5.730 2.078 0.749 5377 40.5% 33380.6 5802.3 2560.6 44.13% 12274.5 2037.2 2.719 5.753 2.115 0.796 5376 38.0% 27350.6 4974.2 2266.7 45.57% 9789.5 1716.1 2.794 5.498 1.968 0.757 5375 41.0% 31956.4 5620.3 2504.1 44.55% 11981.6 2039.6 2.667 5.686 2.132 0.815 5368 41.5% 34211.9 5863.3 2567.8 43.79% 12821.2 2128.7 2.668 5.835 2.187 0.829 5364 39.5% 33219.5 5687.9 2427.8 42.68% 11966.4 1911.7 2.776 5.840 2.104 0.787 5363 41.0% 30340.8 4945 2098.1 42.43% 10870.5 1714.8 2.791 6.136 2.198 0.817 5361 39.5% 31582.8 5439.1 2391.9 43.98% 11235.2 1887.7 2.811 5.807 2.066 0.789 5357 38.0% 28781.9 5070.7 2244.2 44.26% 9987.1 1721.9 2.882 5.676 1.970 0.767 5352 41.0% 33214.5 5642.3 2447 43.37% 12134.8 2019.4 2.737 5.887 2.151 0.825 5351 39.5% 32163.7 5739.8 2588 45.09% 11864.5 1991.8 2.711 5.604 2.067 0.770 5350 39.0% 26531.1 4969.3 2294.8 46.18% 10003.7 1807.5 2.652 5.339 2.013 0.788 5348 39.5% 32847 5777.9 2578.5 44.63% 12011.4 1991.2 2.735 5.685 2.079 0.772 5347 38.5% 26609.8 4848.5 2214 45.66% 9529.0 1685.7 2.792 5.488 1.965 0.761 5345 39.5% 30753.2 5457.7 2464.2 45.15% 11409.6 1916.6 2.695 5.635 2.091 0.778 5344 38.5% 29682.6 5384.9 2459.1 45.67% 10705.1 1867.2 2.773 5.512 1.988 0.759 5342 39.5% 31688.9 5527.3 2437.3 44.10% 11501.6 1916.2 2.755 5.733 2.081 0.786 5340 38.5% 30689.8 5488.9 2480.5 45.19% 11096.2 1885.5 2.766 5.591 2.022 0.760 5338 39.5% 27360.9 4744.3 2115.2 44.58% 9770.1 1691.9 2.800 5.767 2.059 0.800 5337 38.0% 29815.9 5342.7 2441.1 45.69% 10680.6 1829.5 2.792 5.581 1.999 0.749 5335 39.0% 35726.2 6082.2 2661.9 43.77% 12623.7 2027.9 2.830 5.874 2.076 0.762 5334 38.5% 31602.5 5643.1 2543 45.06% 11327.2 1955.4 2.790 5.600 2.007 0.769 5331 41.5% 24542.9 4513.4 2106.9 46.68% 9521.3 1805.6 2.578 5.438 2.110 0.857 Starcrest Consulting Group, LLC 13 December 2008

Table 4: Engine Data (Continued) ID Load Miles On Hrs Idle Hrs % Idle Total Fuel Idle Fuel MPG MPH Gal/ Hr Idle Gal/hr 5330 40.5% 28035.6 5222.5 2414.9 46.24% 10750.9 1984.6 2.608 5.368 2.059 0.822 T186 26.2% 7863 3246 41.28% 9835.5 1188.4 1.251 0.366 T187 27.1% 7421 2987 40.25% 9727.0 1123.0 1.311 0.376 T165 21.5% 7329 7328 99.99% 9205.9 9203.3 1.256 1.256 T198 26.0% 5004 2428 48.52% 8326.3 773.3 1.664 0.318 T154 17.5% 7177 7176 99.99% 9193.6 9191.9 1.281 1.281 T176 20.7% 7358 7357 99.99% 9804.3 9800.8 1.332 1.332 T192 34.6% 4635 1517 32.73% 7941.4 781.3 1.713 0.515 T151 26.8% 9154 3966 43.33% 10892.6 1316.8 1.190 0.332 T147 29.3% 9179 3950 43.03% 11324.4 1431.8 1.234 0.362 T143 26.8% 9258 4008 43.29% 11295.6 1422.8 1.220 0.355 H191 19.0% 68290.7 5195 2329.4 3.520 6.000 0.448 T186 26.2% 7863 3246 41.28% 9835.5 1188.4 1.251 0.366 2.4 Data Analysis The results of an analysis of the engine load data for all vehicles tested are presented in Table 5. Based upon these results, it can be concluded that the continued use of the current 65% Load Factor is not supported by the empirical data. Table 5: Load Factor Descriptive Statistics Sample Size Minimum Maximum Median Mean Std. Deviation 85 17.5% 45.4% 38.6% 37.1% 5.8% Starcrest Consulting Group, LLC 14 December 2008

Figure 8: Engine Load Histogram A lower estimate of average is also supported by analysis of the idle data. Given the fact that the average tractor sampled spent 43% of running time at idle (minimal engine load), an average load of 65% could not possibly be obtained even if the tractors operated at 100% load while in motion. However, if it is assumed that the average yard tractor idles 43% of the time, an average Load Factor of 37% would be derived if the tractors experienced 65% load while in motion. 43% Time x 0 LF (Idle) + 57% Time x 65% LF = 37% LF Therefore CARBs Load Factor may be more appropriate for characterizing the load of tractors when they are not idling. The idle statistics for the tested fleet are presented in Table 6. It should be noted that idle data was not available for one tractor and an additional three data points were excluded from this analysis as erroneous. Table 6: Idle Percentage Descriptive Statistics Sample Size Minimum Maximum Median Mean Std. Deviation 81 30.1% 50.0% 45.1% 42.8% 5.8% Starcrest Consulting Group, LLC 15 December 2008

3.0 CONCLUSIONS AND RECOMMENDATIONS Load Factor data collected from 85 yard tractors representing 6% of the San Pedro Bay Port UTR fleet were collected for purposes of this analysis. The cumulative data which summarized the typical operating parameters of these vehicles over 65,000 hours of operation suggest an average load factor of 37% is appropriate for this fleet. The use of a 37% Load Factor in place of the 65% estimate supplied by Power Systems Research and used by the California Air Resources Board would result in a 40% reduction in the emission inventory associated with these vehicles or approximately 1,000 tons per year of NO x and 30 tons per year of diesel particulate matter. Although this study was limited to newer vehicles (model year 2000 and newer), interviews with terminal operators suggest that these vehicles are not tasked by age and that the operation of the newer fleet should not be significantly different than the older vehicles in the fleet. In analyzing the hours of operation as a function of age for yard tractors, it was determined that older tractors may be used less than newer tractors but no evidence exists to suggest that they are used differently. An analysis of the idle data suggests that a typical yard tractor spends over 40% of running time at idle. Taking this fact into account, it appears that the 65% load factor is more appropriate for characterizing non-idle operation of UTRs rather than total engine-on time. Given the significant idle component of yard tractor operation, it may be more appropriate (accurate) to estimate the emissions of these vehicles in a bi-modal fashion much as methodology used for estimating the emissions of their on-road heavy-duty diesel counterparts while operating within terminals. It is suggested that idle emissions be estimated separately on a gram per hour basis and that the running component be estimated based on the current methodology or alternatively on a gram per mile basis using a non-linear speed correction factor rather than the traditional (limited) linear assumption of emissions increases as a function of load. Starcrest Consulting Group, LLC 16 December 2008

ADDENDUM: CARB RESPONSE The 2005 yard tractor emissions inventory for the Ports of Los Angeles and Long Beach was based on a load factor of 65%. This same load factor, which is based on the OFFROAD model, was used for the ARB Cargo Handling Equipment Regulation and the 2005 Rail Yard Health Risk Assessments. Since then the Ports have conducted an extensive load factor study of these vehicles. Load data was downloaded from the computers of 85 yard tractors (6% of the fleet), and more than a year s worth of fuel consumption data, idle hours, operational hours and other engine control module (ECM) parameters were collected. As mentioned in the report ( Draft San Pedro Bay Ports Yard Tractor Load Factor Study ) all yard tractors in the study were equipped with a Cummins engine, 68% were powered by diesel (32% powered by propane) and all were within the model year range of 2000-2005. Combined this sample is similar to the Ports fleet where 73% of the yard tractors are model year 2000 or newer, 98% are diesel powered, and 93% utilize Cummins engines. After review of the data and removal of the Long Beach tractors with 99% idle time (T154 & T176) ARB calculated a new activity weighted load factor of 39%. ARB supports the Ports of Los Angeles and Long Beach using this load factor for yard tractors in cargo handling equipment emissions inventory development and believes this represents the typical operating parameters at the Ports. Starcrest Consulting Group, LLC 17 December 2008